CN114764681A - P2P transaction mode-based interconnected comprehensive energy network scheduling method and device - Google Patents

P2P transaction mode-based interconnected comprehensive energy network scheduling method and device Download PDF

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CN114764681A
CN114764681A CN202210152840.4A CN202210152840A CN114764681A CN 114764681 A CN114764681 A CN 114764681A CN 202210152840 A CN202210152840 A CN 202210152840A CN 114764681 A CN114764681 A CN 114764681A
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梅生伟
魏韡
曹阳
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Abstract

The invention provides a P2P transaction mode-based interconnected comprehensive energy network scheduling method and device, wherein the method is applied to an interconnected comprehensive energy network system, the interconnected comprehensive energy network system comprises a plurality of sub electric heating networks, and the method comprises the following steps: establishing an operation model of the interconnected comprehensive energy network system based on the P2P transaction mode; and carrying out distributed solving on the operation model to obtain a first electric energy quantity related to the purchase electric energy cost of a superior electric power network, active power output by the distributed generator set related to the operation cost of the distributed generator set, natural gas power input by the cogeneration set related to the operation cost of the cogeneration set, and a second electric energy quantity related to the purchase electric energy cost of the same-level electric heating networks, so that the operation cost of each sub-electric heating network and the operation cost of the interconnected comprehensive energy network system are the lowest. The invention realizes the maximization of the overall benefit of the interconnected comprehensive energy network system.

Description

P2P transaction mode-based interconnected comprehensive energy network scheduling method and device
Technical Field
The invention relates to the technical field of interconnected comprehensive energy networks, in particular to a P2P transaction mode-based interconnected comprehensive energy network scheduling method and device.
Background
Energy crisis and environmental pollution are two major problems in modern society. In order to deal with these crises, renewable energy sources mainly including wind power and photovoltaic have been rapidly developed in recent years. In order to promote the consumption of new energy, a series of researches are carried out inside the power system, such as the application of a series of energy storage technologies, such as battery energy storage, flywheel energy storage and compressed air energy storage, and the application of demand side response. However, these techniques still only exploit the flexibility potential of the power system, and still have significant limitations and deficiencies in the face of large-scale new energy consumption problems.
Electrical energy is a form of ready-to-use, instantaneously balanced energy that is transmitted at a very fast rate but is difficult to store. On the contrary, the heat energy as a delayed energy form has the characteristics of easy storage and difficult transmission, and has natural complementary characteristics with the characteristics of difficult storage and easy transmission of the electric energy, so that the thermodynamic system is a huge inertial system relative to the electric power system, and can provide huge energy storage potential for a power grid. Therefore, the electric heating coupling system (also called an interconnection comprehensive energy network) can greatly improve the flexibility of the system and promote the large-scale consumption of new energy. Currently, it is a hot spot of current research to find a way to reduce the operation cost of the interconnected integrated energy network system to the maximum extent.
Disclosure of Invention
The invention provides a P2P transaction mode-based interconnected comprehensive energy network scheduling method and device, which can realize maximization of the overall benefits of an interconnected comprehensive energy network system on the basis of ensuring the benefits of each electric heating main body.
The invention provides an interconnected comprehensive energy network scheduling method based on a P2P transaction mode, which is applied to an interconnected comprehensive energy network system, wherein the interconnected comprehensive energy network system comprises a plurality of sub electric heating networks, each sub electric heating network at least comprises a power network, a heating power network, a distributed generator set, a wind turbine set, a cogeneration set, a heat pump, an electricity storage device and a heat storage device, the sub electric heating networks are connected through a soft switch and perform transactions in a P2P transaction mode, and the method comprises the following steps: establishing an operation model about the interconnected comprehensive energy network system based on the P2P transaction mode, wherein the operation model comprises operation costs of each sub electric heating network, and the operation costs comprise purchase electric energy costs of a superior electric power network, operation costs of a distributed generator set, operation costs of a cogeneration set and purchase electric energy costs of a peer electric heating network; and carrying out distributed solving on the operation model to obtain a first electric energy quantity related to the purchase electric energy cost of the superior electric power network, active power output by the distributed generator set related to the operation cost of the distributed generator set, natural gas power input by the cogeneration set related to the operation cost of the cogeneration set, and a second electric energy quantity related to the purchase electric energy cost of the same-level electric heating network, so that the operation cost of each sub-electric heating network and the operation cost of the interconnected comprehensive energy network system are the lowest.
According to the interconnected comprehensive energy network scheduling method based on the P2P transaction mode, the operation model of the interconnected comprehensive energy network system comprises the sum of the operation cost of each sub electric heating network, and the operation cost is determined by adopting the following formula:
Figure BDA0003511272270000021
wherein,
Figure BDA0003511272270000022
the cost of the operation is expressed in terms of,
Figure BDA0003511272270000023
represents a purchase power cost of the upper power network,
Figure BDA0003511272270000024
represents a cost of operation of the distributed generator set,
Figure BDA0003511272270000025
represents the operating cost of the cogeneration unit,
Figure BDA0003511272270000026
and representing the purchase electric energy cost of the peer electric heating network.
According to the interconnected comprehensive energy network scheduling method based on the P2P transaction mode, the purchase electric energy cost of the upper-level power network is determined by adopting the following formula:
Figure BDA0003511272270000031
wherein,
Figure BDA0003511272270000032
representing the unit price of purchasing electric energy from an upper power network,
Figure BDA0003511272270000033
a first amount of electrical energy representing a cost of purchasing electrical energy in relation to the upper level electrical power network, the electrical power network having a model of:
Figure BDA0003511272270000034
Figure BDA0003511272270000035
Vj,t＝Vi,t-(rijPij,t+xijQij,t)/V0
wherein p isj,tRepresenting the total active power injected at node j in the power network, including a first amount of power with respect to the cost of purchasing power from the superior power network
Figure BDA0003511272270000036
A second amount of electrical energy related to a cost of purchasing electrical energy from the peer electrical heating network
Figure BDA0003511272270000037
Active output of the distributed generator set
Figure BDA0003511272270000038
Active power output of the cogeneration unit
Figure BDA0003511272270000039
Active power output of the wind turbine generator
Figure BDA00035112722700000310
Charging power of the electricity storage device
Figure BDA00035112722700000311
And discharge power
Figure BDA00035112722700000312
Figure BDA00035112722700000313
Representing the total active load at node j in the power network, including the base electrical load and the active power consumed by the heat pump
Figure BDA00035112722700000314
qj,tRepresenting the total reactive power injected at node j in the power network, including the reactive power from the superior power network
Figure BDA00035112722700000315
And reactive power output of the distributed generator set
Figure BDA00035112722700000316
Figure BDA00035112722700000317
Representing a reactive load at node j in the electrical power network; pij,tAnd Qij,tRespectively representing the active power and the reactive power of a line from a node i to a node j in the power network; r isijAnd xijRepresenting line resistance and line from node i to node j in the power network, respectivelyA path reactance; vi,tRepresenting a voltage magnitude of a node i in the power network; v0Represents a reference voltage;
Figure BDA0003511272270000041
representing a set of downstream nodes for node j.
According to the interconnected comprehensive energy network scheduling method based on the P2P transaction mode, the operation cost of the distributed generator set is determined by adopting the following formula:
Figure BDA0003511272270000042
wherein,
Figure BDA0003511272270000043
representing the active power output by the distributed generator set,
Figure BDA0003511272270000044
the first constant coefficient is represented by a first constant coefficient,
Figure BDA0003511272270000045
a second constant coefficient is represented by a second constant coefficient,
Figure BDA0003511272270000046
and expressing a third constant coefficient, wherein the distributed generator set has the following model:
Figure BDA0003511272270000047
Figure BDA0003511272270000048
wherein,
Figure BDA0003511272270000049
representing reactive power output by the distributed generator set;
Figure BDA00035112722700000410
and
Figure BDA00035112722700000411
respectively representing an upper limit and a lower limit of active power of the distributed generator set;
Figure BDA00035112722700000412
and
Figure BDA00035112722700000413
respectively representing an upper limit and a lower limit of reactive power of the distributed generator set.
According to the interconnected comprehensive energy network scheduling method based on the P2P trading mode, the operation cost of the cogeneration unit is determined by adopting the following formula:
Figure BDA00035112722700000414
wherein,
Figure BDA00035112722700000415
which represents the unit price of the natural gas,
Figure BDA00035112722700000416
representing a natural gas power input by the cogeneration unit, wherein the cogeneration unit has a model as follows:
Figure BDA00035112722700000417
Figure BDA00035112722700000418
Figure BDA00035112722700000419
wherein,
Figure BDA00035112722700000420
and
Figure BDA00035112722700000421
respectively representing the electric power and the thermal power output by the cogeneration unit;
Figure BDA00035112722700000422
and
Figure BDA00035112722700000423
respectively representing the gas-to-electricity efficiency and the gas-to-heat efficiency of the cogeneration unit;
Figure BDA0003511272270000051
and
Figure BDA0003511272270000052
respectively representing the upper limit and the lower limit of the input natural gas power of the cogeneration unit.
According to the interconnected comprehensive energy network scheduling method based on the P2P transaction mode, the purchase electric energy cost of the peer electric heating network is determined by adopting the following formula:
Figure BDA0003511272270000053
wherein,
Figure BDA0003511272270000054
representing the unit price of electric energy purchased by peer electric heating networks based on P2P transaction mode,
Figure BDA0003511272270000055
a second amount of electrical energy representing a cost of purchasing electrical energy for a peer electrical heating network between a sub-electrical heating network m and a sub-electrical heating network n, wherein the soft switch connecting the sub-electrical heating network m and the sub-electrical heating network nThe model has the following:
Figure BDA0003511272270000056
Figure BDA0003511272270000057
wherein,
Figure BDA0003511272270000058
representing active power loss in the soft switch;
Figure BDA0003511272270000059
representing a power loss coefficient of the soft switch; m is a group ofnRepresents a set of sub-electric heating networks connected to the sub-electric heating network n.
According to the interconnected comprehensive energy network scheduling method based on the P2P transaction mode, the distributed solving of the operation model comprises the following steps: acquiring a target auxiliary variable, wherein the target auxiliary variable is an auxiliary variable of a second electric energy quantity related to the purchase electric energy cost of the peer electric heating network; based on the equality of demand and supply of the P2P transaction mode and the target auxiliary variable, hiding the cost of purchasing electric energy of the peer electric heating network in the operation model, and obtaining a simplified operation model; performing matrix conversion on the simplified operation model to obtain a matrix model related to the simplified operation model, and constructing an augmented Lagrangian function related to the matrix model; and based on the augmented Lagrange function, performing distributed solution on the operation model by using an alternative direction multiplier method.
According to the interconnected comprehensive energy network scheduling method based on the P2P transaction mode, the simplified operation model comprises a constraint function, the constraint function comprises a second electric energy quantity related to the purchase electric energy cost of the peer electric heating network, and a matrix model related to the simplified operation model has the following model:
Figure BDA0003511272270000061
Figure BDA0003511272270000062
Figure BDA0003511272270000063
Figure BDA0003511272270000064
wherein, ynRepresenting a remaining decision variable in the simplified operational model other than the second amount of electrical energy regarding the cost of purchasing electrical energy for the peer electrical heating network; z is a radical of formulanA second amount of electrical energy representing the constraint function in the simplified operating model for a cost of purchasing electrical energy for the peer electrical heating network;
Figure BDA0003511272270000065
representing the target auxiliary variable; f. ofn、dn、Cn、DnAnd EnAll represent constant coefficients.
According to the interconnected comprehensive energy network scheduling method based on the P2P transaction mode, the augmented Lagrangian function is determined by adopting the following formula:
Figure BDA0003511272270000066
wherein λ isnRepresenting functions with respect to constraints
Figure BDA0003511272270000067
The dual variable of (2) is used for representing the unit price of purchasing electric energy among peer electric heating networks based on the P2P transaction mode; rho tableAnd indicating a penalty parameter.
According to the interconnected comprehensive energy network scheduling method based on the P2P trading mode, the distributed solution is carried out on the operation model by using an alternating direction multiplier method based on the augmented Lagrangian function, and the method comprises the following steps:
s1: determining a convergence threshold epsilon, determining an initial price per unit for purchasing power among peer electrical heating networks based on a P2P transaction pattern
Figure BDA0003511272270000068
And setting the iteration times k to be 0, wherein the convergence threshold epsilon is more than 0;
s2: based on the independence of each sub electric heating network, the remaining decision variables y except the second electric energy quantity related to the electric energy purchase cost of the same electric heating network in the simplified operation model are updated in parallelnAnd a second quantity z of electrical energy of said constraint function in said simplified operating model relating to the cost of purchasing electrical energy by said peer electrical heating networknWherein
Figure BDA0003511272270000071
s.t.Cnyn+Dnzn≤fn
s3: updating the second amount of electrical energy z of the sub-gridn k+1Sharing other sub electric heating networks in the interconnected comprehensive energy network system and assisting variables for targets
Figure BDA0003511272270000072
The update is performed, wherein,
Figure BDA0003511272270000073
Figure BDA0003511272270000074
s4: updating unit price for purchasing electric energy among peer electric heating networks based on P2P transaction mode
Figure BDA0003511272270000075
Wherein,
Figure BDA0003511272270000076
s5: performing a convergence test if
Figure BDA0003511272270000077
The calculation is terminated and the final result is output
Figure BDA0003511272270000078
Otherwise, k ← k +1 is updated and returns to S2.
According to the interconnected comprehensive energy network scheduling method based on the P2P transaction mode, the thermodynamic network has the following model:
Figure BDA0003511272270000079
Figure BDA00035112722700000710
Figure BDA00035112722700000711
Figure BDA00035112722700000712
Figure BDA0003511272270000081
wherein,b represents a pipe of the thermodynamic network;
Figure BDA0003511272270000082
representing the total thermal power injected into said thermodynamic network by a heat source, including the thermal output of said cogeneration unit
Figure BDA0003511272270000083
Thermal output of the heat pump
Figure BDA0003511272270000084
The heat charging power of the heat storage device
Figure BDA0003511272270000085
And the heat-releasing power of the heat storage device
Figure BDA0003511272270000086
Figure BDA0003511272270000087
A heat dissipation power representing a heat load; c. CpRepresents the specific heat capacity of water;
Figure BDA0003511272270000088
representing the mass flow of circulating water injected into a water supply pipeline from a water return pipeline at a heat source;
Figure BDA0003511272270000089
representing the mass flow of circulating water from a water supply pipeline to a water return pipeline at a heat load;
Figure BDA00035112722700000810
and
Figure BDA00035112722700000811
respectively representing the water supply temperature and the water return temperature; m isb,tRepresenting the circulating water mass flow of the pipeline b;
Figure BDA00035112722700000812
and
Figure BDA00035112722700000813
respectively representing the inlet temperature and the outlet temperature of the pipeline b; gamma raybRepresents the temperature loss coefficient of the pipeline b; l is a radical of an alcoholbRepresents the length of the pipe b;
Figure BDA00035112722700000814
represents the ambient temperature;
Figure BDA00035112722700000815
indicating a fluid mixing temperature at the junction;
Figure BDA00035112722700000816
representing a pipeline set taking the node i as a terminal;
Figure BDA00035112722700000817
representing a set of pipes headed by node i.
According to the interconnected comprehensive energy network scheduling method based on the P2P transaction mode, the heat pump has the following models:
Figure BDA00035112722700000818
Figure BDA00035112722700000819
wherein,
Figure BDA00035112722700000820
and
Figure BDA00035112722700000821
respectively representing the electric power consumed and the thermal power output by the heat pump; COP (coefficient of Performance)iRepresenting an energy efficiency coefficient of the heat pump;
Figure BDA00035112722700000822
and
Figure BDA00035112722700000823
respectively representing the upper limit and the lower limit of the heat pump output heat power.
According to the interconnected comprehensive energy network scheduling method based on the P2P transaction mode, the heat storage device is provided with the following models:
Figure BDA0003511272270000091
Figure BDA0003511272270000092
Figure BDA0003511272270000093
wherein,
Figure BDA0003511272270000094
and
Figure BDA0003511272270000095
respectively representing the charging power and the discharging power of the heat storage device;
Figure BDA0003511272270000096
and
Figure BDA0003511272270000097
respectively representing the heat charging efficiency and the heat discharging efficiency of the heat storage device;
Figure BDA0003511272270000098
representing a rate of thermal energy loss of the heat storage device;
Figure BDA0003511272270000099
representing thermal energy stored in the thermal storage device;
Figure BDA00035112722700000910
and
Figure BDA00035112722700000911
respectively representing the upper limit and the lower limit of the charging power of the heat storage device;
Figure BDA00035112722700000912
and
Figure BDA00035112722700000913
respectively representing the upper limit and the lower limit of the heat release power of the heat storage device;
Figure BDA00035112722700000914
and
Figure BDA00035112722700000915
respectively representing the upper limit and the lower limit of the stored heat energy of the heat storage device; Δ t represents a scheduled time interval.
According to the interconnected comprehensive energy network dispatching method based on the P2P transaction mode, the power storage device has the following model:
Figure BDA00035112722700000916
Figure BDA00035112722700000917
Figure BDA00035112722700000918
wherein,
Figure BDA00035112722700000919
and
Figure BDA00035112722700000920
representing a charging power and a discharging power of the electric storage device, respectively;
Figure BDA00035112722700000921
and
Figure BDA00035112722700000922
respectively representing the charging efficiency and the discharging efficiency of the electric storage device;
Figure BDA00035112722700000923
representing a rate of power loss of the electric storage device;
Figure BDA00035112722700000924
representing electrical energy stored at the electrical storage device;
Figure BDA00035112722700000925
and
Figure BDA00035112722700000926
represents an upper limit and a lower limit of charging power of the electric storage device, respectively;
Figure BDA00035112722700000927
and
Figure BDA00035112722700000928
represents an upper limit and a lower limit of discharge power of the electric storage device, respectively;
Figure BDA0003511272270000101
and
Figure BDA0003511272270000102
represents an upper limit and a lower limit of stored electric energy of the electric storage device, respectively; Δ t represents a scheduled time interval.
The invention also provides an interconnected comprehensive energy network scheduling device based on the P2P transaction mode, which is applied to an interconnected comprehensive energy network system, wherein the interconnected comprehensive energy network system comprises a plurality of sub electric heating networks, each sub electric heating network at least comprises a power network, a heating power network, a distributed generator set, a wind turbine set, a cogeneration set, a heat pump, an electricity storage device and a heat storage device, the sub electric heating networks are connected through a soft switch and perform transaction by adopting the P2P transaction mode, and the device comprises: the establishing module is used for establishing an operation model of the interconnected comprehensive energy network system based on the P2P transaction mode, wherein the operation model comprises operation costs of each sub electric heating network, and the operation costs comprise a higher-level electric power network purchase electric energy cost, a distributed generator set operation cost, a cogeneration unit operation cost and a peer electric heating network purchase electric energy cost; and the processing module is used for carrying out distributed solving on the operation model to obtain a first electric energy quantity related to the purchase electric energy cost of the superior power network, active power output by the distributed generator set related to the operation cost of the distributed generator set, natural gas power input by the cogeneration set related to the operation cost of the cogeneration set and a second electric energy quantity related to the purchase electric energy cost of the same-level electric heating networks, so that the operation cost of each sub-electric heating network and the operation cost of the interconnected comprehensive energy network system are the lowest.
The invention also provides an electronic device, which comprises a memory, a processor and a computer program stored on the memory and capable of running on the processor, wherein the processor executes the program to realize the method for scheduling the interconnected comprehensive energy network based on the P2P transaction mode.
The present invention also provides a non-transitory computer readable storage medium, on which a computer program is stored, which when executed by a processor implements the method for scheduling an interconnected integrated energy network based on P2P transaction patterns as described in any one of the above.
The invention also provides a computer program product comprising a computer program, wherein the computer program is used for realizing the interconnected comprehensive energy network dispatching method based on the P2P transaction mode when being executed by a processor.
The P2P transaction mode-based interconnected comprehensive energy network scheduling method and device are applied to an interconnected comprehensive energy network system, wherein the interconnected comprehensive energy network system comprises a plurality of sub electric heating networks. The invention determines the transaction rules among the sub electric heating networks through the P2P transaction mode, so as to stimulate each sub electric heating network to participate in the P2P transaction and establish an operation model of the interconnected comprehensive energy network system based on the P2P transaction. And then, carrying out distributed solving on the operation model, and obtaining a first electric energy quantity of the purchase electric energy cost of a superior electric power network, the active power output by the distributed generator set, the natural gas power input by the cogeneration set and a second electric energy quantity of the purchase electric energy cost of the same level electric heating network on the premise of protecting the privacy data of each sub electric heating network, so that the operation cost of each sub electric heating network and the operation cost of the interconnected comprehensive energy network system are the lowest. According to the P2P transaction mode-based interconnected comprehensive energy network scheduling method, private data does not need to be shared by all sub electric heating networks, the incentive compatibility principle is met, the maximized overall benefits of the interconnected comprehensive energy network system are achieved when each sub electric heating network pursues the benefits of the sub electric heating network, and therefore the maximization of the overall benefits of the interconnected comprehensive energy network system is achieved on the basis of ensuring the benefits of each electric heating main body.
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In order to more clearly illustrate the technical solutions of the present invention or the prior art, the drawings needed for the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and those skilled in the art can also obtain other drawings according to the drawings without creative efforts.
Fig. 1 is a schematic flow chart of a P2P transaction mode-based interconnected integrated energy network scheduling method provided by the invention;
FIG. 2 is a schematic flow chart of distributed solution of the operation model provided by the present invention;
FIG. 3 is a schematic flow chart of a distributed solution of the operational model by using an alternative direction multiplier method based on an augmented Lagrange function according to the present invention;
fig. 4 is a schematic structural diagram of an interconnected integrated energy network dispatching device based on a P2P transaction mode, provided by the invention;
fig. 5 is a schematic structural diagram of an electronic device provided in the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention clearer, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings, and it is obvious that the described embodiments are some, but not all embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
With the development of distributed power generation resources, more and more sub-electric heating networks start to adopt an interconnection operation mode to improve the energy utilization efficiency of the whole system (corresponding to an interconnection comprehensive energy network system). For the interconnected comprehensive energy network system, each sub electric heating network in the interconnected comprehensive energy network system is an independent individual, the maximization of the benefit of the sub electric heating network is pursued, and the benefit of each main body can be well considered by adopting a P2P (peer-to-peer) trading mode, so that each sub electric heating network is stimulated to participate in the integral coordination operation. Therefore, it is highly desirable to design an interconnected integrated energy network dispatching method based on P2P trading mode to reduce the operation cost of the interconnected integrated energy network system to the maximum extent.
The interconnected comprehensive energy network scheduling method based on the P2P trading mode pursues maximization of the overall benefits of the interconnected electric heating system on the basis of guaranteeing the benefits of each electric heating main body.
The invention will be described with reference to fig. 1 for a process of a P2P transaction mode-based interconnected integrated energy network scheduling method.
Fig. 1 is a schematic flow chart of an interconnected integrated energy network scheduling method based on a P2P transaction mode according to the present invention.
In an exemplary embodiment of the invention, the interconnected integrated energy network dispatching method based on the P2P transaction mode can be applied to an interconnected integrated energy network system. The interconnected comprehensive energy network system can comprise a plurality of sub-electric heating networks, and for the sub-electric heating networks, the sub-electric heating networks are generally connected to a superior power grid through public connection points. Each sub-electric heating network at least comprises an electric power network, a heating power network, a distributed generator set, a wind turbine generator set, a cogeneration set, a heat pump, an electricity storage device and a heat storage device. The sub-electrothermal networks can be connected through a soft switch and trade by adopting a P2P trade mode.
The soft switch is a novel power electronic device, generally comprises two voltage source type inverters, can flexibly control power flow at two ends, and two ends of the soft switch can be respectively connected to a certain power grid node of two sub-electric heating networks, so that flexible and controllable power exchange between the two networks is realized, and a solid physical foundation is provided for the establishment of a subsequent P2P trading market.
Referring to fig. 1, the method for scheduling an interconnected integrated energy network based on P2P transaction mode may include steps 110 and 120, which are described below.
In step 110, based on the P2P transaction pattern, an operation model of the interconnected integrated energy network system is established, wherein the operation model includes operation costs of each sub-electric heating network, and the operation costs include purchase cost of electric energy of a superior electric power network, operation cost of a distributed generator set, operation cost of a cogeneration set, and purchase cost of electric energy of a peer electric heating network.
In the interconnected integrated energy network system, the goal of each sub-electric heating network is to seek the maximization of the self benefit or the minimization of the self operation cost. Therefore, the operation cost of all the sub electric heating networks can be added to obtain the total social operation cost (corresponding to the interconnected comprehensive energy network system). It can be seen that minimizing the total cost of social operations (maximizing social welfare) is a sought goal. In one example, the operational model for the interconnected integrated energy network system may include a sum of operational costs of each of the sub-electric heating networks.
In step 120, the operation model is solved in a distributed manner, so as to obtain a first electric energy quantity related to the purchase cost of the upper-level power network, active power output by the distributed generator sets related to the operation cost of the distributed generator sets, natural gas power input by the cogeneration sets related to the operation cost of the cogeneration sets, and a second electric energy quantity related to the purchase cost of the electric energy of the same-level electric heating networks, so that the operation cost of each sub-electric heating network and the operation cost of the interconnected comprehensive energy network system are the lowest.
Since the price of the trade between the purchase costs of electric energy in respect of the peer electric heating network is not a known quantity given in advance, the corresponding market equilibrium price can only be obtained after solving the problem. This introduces a paradox to the problem solution. Secondly, each sub-electric heating network is a different beneficial agent and is unwilling to share the private data of the sub-electric heating network, so that the traditional centralized solving algorithm cannot be applied. In an example, the operation model may be solved in a distributed manner, and a first electric energy quantity of the electric energy purchase cost of the upper-level electric power network, the active power output by the distributed generator set, the natural gas power input by the cogeneration set, and a second electric energy quantity of the electric energy purchase cost of the same-level electric heating network are obtained on the premise of protecting the privacy data of each sub electric heating network, so that the operation cost of each sub electric heating network and the operation cost of the interconnected comprehensive energy network system are minimized.
It should be noted that the first amount of electric energy related to the purchase cost of electric energy of the upper-level electric power network may be active power from the upper-level electric power grid. The second amount of electrical energy related to the cost of purchasing electrical energy from the peer electrical heating network may be the active power of the remaining sub-electrical heating networks obtained based on the P2P transaction.
The invention provides an interconnection comprehensive energy network scheduling method based on a P2P transaction mode, which is applied to an interconnection comprehensive energy network system, wherein the interconnection comprehensive energy network system comprises a plurality of sub electric heating networks. The invention determines the transaction rules among the sub electric heating networks through the P2P transaction mode, so as to stimulate each sub electric heating network to participate in the P2P transaction and establish an operation model of the interconnected comprehensive energy network system based on the P2P transaction. And then, carrying out distributed solving on the operation model, and obtaining a first electric energy quantity of the purchase electric energy cost of a superior electric power network, the active power output by the distributed generator set, the natural gas power input by the cogeneration set and a second electric energy quantity of the purchase electric energy cost of the same level electric heating network on the premise of protecting the privacy data of each sub electric heating network, so that the operation cost of each sub electric heating network and the operation cost of the interconnected comprehensive energy network system are the lowest. According to the P2P transaction mode-based interconnected comprehensive energy network scheduling method, private data does not need to be shared by all sub electric heating networks, the incentive compatibility principle is met, the maximized overall benefits of the interconnected comprehensive energy network system are achieved when each sub electric heating network pursues the benefits of the sub electric heating network, and therefore the maximization of the overall benefits of the interconnected comprehensive energy network system is achieved on the basis of ensuring the benefits of each electric heating main body.
For further description of the method for scheduling interconnected integrated energy networks based on P2P transaction patterns according to the present invention, the following embodiments will be described.
In one embodiment, a mathematical model of the interconnected integrated energy network system may be established. The sub electric heating network in the interconnected comprehensive energy network system at least comprises an electric power network, a heating power network, a distributed generator set, a wind turbine generator set, a cogeneration set, a heat pump, an electricity storage device and a heat storage device. For power networks, radial networks are common, and therefore can be described using a linearized branch power flow model.
In one embodiment, the power network may have the following model:
Figure BDA0003511272270000151
Figure BDA0003511272270000152
Vj,t＝Vi,t-(rijPij,t+xijQij,t)/V0 (3)
wherein p isj,tRepresenting the total active power injected at node j in the power network, including a first amount of power (also known as active power from the superior power network) for the cost of purchasing power from the superior power network
Figure BDA0003511272270000153
A second amount of electrical energy (also known as active power from the remaining sub-networks) related to the cost of purchasing electrical energy from the same electric heating network
Figure BDA0003511272270000154
Active power output of distributed generator set
Figure BDA0003511272270000155
Active power output of cogeneration unit
Figure BDA0003511272270000156
Active power output of wind turbine generator
Figure BDA0003511272270000157
Charging power of an electrical storage device
Figure BDA0003511272270000158
And discharge power
Figure BDA0003511272270000159
Figure BDA00035112722700001510
Representing the total active load at node j in the power network, including the base electrical load and the active power consumed by the heat pump
Figure BDA00035112722700001511
qj,tRepresenting the total reactive power injected at node j in the power network, including the reactive power from the superior power network
Figure BDA00035112722700001512
And reactive power output of distributed generator set
Figure BDA00035112722700001513
Figure BDA00035112722700001514
Representing a reactive load at node j in the power network; p isij,tAnd Qij,tRespectively representing the active power and the reactive power of a line from a node i to a node j in the power network; r is a radical of hydrogenijAnd xijRespectively representing the line resistance and line reactance from a node i to a node j in the power network; vi,tRepresenting the voltage amplitude of node i in the power network; v0Represents a reference voltage;
Figure BDA0003511272270000161
representing a set of downstream nodes for node j.
Wherein, the constraint (1) and the constraint (2) represent the balance condition of the active power and the reactive power at the node j; constraint (3) describes the relationship between the voltage drop from node i to node j and the active and reactive power flows on the line.
The heating power network can be composed of a water supply pipeline and a water return pipeline, and heat is transmitted and distributed by using circulating water. At the heat source node (typically configured as a cogeneration unit or heat pump), the heat source may inject energy into the thermal network through a heat exchanger. At the thermal load node, the heat exchanger may utilize the supply return water temperature difference to provide energy to the thermal load. Generally, the heat flow model of a thermal network can be described by a flow equation and a heat transfer equation, which is a highly non-convex mathematical model. In the embodiment, a scheduling mode of 'constant mass flow-variable temperature' commonly used in the operation of a thermodynamic network can be adopted, the circulating water mass flow described by the flow equation is given, and thus the heat flow model is described as a linear form only containing the heat transfer equation.
In one embodiment, the thermal network may have the following model:
Figure BDA0003511272270000162
Figure BDA0003511272270000163
Figure BDA0003511272270000164
Figure BDA0003511272270000165
Figure BDA0003511272270000166
wherein b represents a pipe of a thermodynamic network;
Figure BDA0003511272270000167
representing the total thermal power injected into the thermodynamic network by the heat source, including the thermal output of the cogeneration unit
Figure BDA0003511272270000168
Thermal output of heat pump
Figure BDA0003511272270000169
Charging power of heat storage device
Figure BDA0003511272270000171
And the heat-releasing power of the heat storage device
Figure BDA0003511272270000172
Figure BDA0003511272270000173
A heat dissipation power representing a heat load; c. CpRepresents the specific heat capacity of water;
Figure BDA0003511272270000174
indicating circulation of heat from return pipe into water supply pipeWater mass flow rate;
Figure BDA0003511272270000175
representing the mass flow of circulating water from a water supply pipeline to a water return pipeline at a heat load;
Figure BDA0003511272270000176
and
Figure BDA0003511272270000177
respectively representing the water supply temperature and the water return temperature; m isb,tRepresenting the circulating water mass flow of the pipeline b;
Figure BDA0003511272270000178
and
Figure BDA0003511272270000179
respectively representing the inlet temperature and the outlet temperature of the pipeline b; gamma raybRepresents the temperature loss coefficient of the pipeline b; l isbRepresents the length of the pipe b;
Figure BDA00035112722700001710
represents the ambient temperature;
Figure BDA00035112722700001711
indicating a fluid mixing temperature at the junction;
Figure BDA00035112722700001712
representing a pipeline set taking the node i as a terminal;
Figure BDA00035112722700001713
representing a set of pipes headed by node i.
Wherein constraints (4) and (5) represent energy exchange processes at heat source and heat load nodes, respectively; constraint (6) describes the drop in the head end temperature to the tail end temperature of the pipeline; constraint (7) represents the relationship of the temperature of the incoming water flow at the heat network junction i to the junction mix temperature; constraint (8) describes the temperature of the water stream exiting from the heat network junction i as a function of the junction mix temperature.
The sub-electric heating network may include local distributed power generation units (e.g., distributed gas turbine units) that may provide both active and reactive power to meet the energy supply requirements of the system. In one embodiment, the distributed generator set may have the following model:
Figure BDA00035112722700001714
Figure BDA00035112722700001715
wherein,
Figure BDA00035112722700001716
representing the active power output by the distributed generator set;
Figure BDA00035112722700001717
representing reactive power output by the distributed generator set;
Figure BDA00035112722700001718
and
Figure BDA00035112722700001719
respectively representing the upper limit and the lower limit of active power of the distributed generator set;
Figure BDA00035112722700001720
and
Figure BDA00035112722700001721
respectively representing the upper and lower limits of reactive power of the distributed generator set.
Wherein constraints (9) and (10) describe the range of active and reactive power output of the distributed generator set, respectively.
It should be noted that the wind turbine generator generally can only provide active power
Figure BDA00035112722700001722
And its available output can be affected by factors such as weather.
The cogeneration unit is a key coupling element in an electric heating system, and can provide electric energy and heat energy simultaneously to meet diversified energy supply requirements. In the electric heating network studied by the invention, the cogeneration units generally consume natural gas resources for energy supply.
In one embodiment, the cogeneration unit may have the following model:
Figure BDA0003511272270000181
Figure BDA0003511272270000182
Figure BDA0003511272270000183
wherein,
Figure BDA0003511272270000184
and
Figure BDA0003511272270000185
respectively representing the electric power and the thermal power output by the cogeneration unit;
Figure BDA0003511272270000186
representing the natural gas power input by the cogeneration unit;
Figure BDA0003511272270000187
and
Figure BDA0003511272270000188
respectively representing the gas-to-electricity efficiency and the gas-to-heat efficiency of the cogeneration unit;
Figure BDA0003511272270000189
and
Figure BDA00035112722700001810
respectively representing the upper limit and the lower limit of the natural gas input power of the cogeneration unit.
Wherein constraints (11) and (12) may represent a relationship between natural gas power input by the cogeneration unit and generated electric power and thermal power. In one example, the gas-to-electricity and gas-to-heat ratios of the cogeneration unit are a fixed constant; the constraint (13) describes the range of capacity of the cogeneration unit.
The heat pump is another key coupling element in the sub-electric heating network, and can force heat to flow from a low-temperature area to a high-temperature area in a reverse circulation mode by consuming electric energy, so that the high-efficiency supply of heat energy is realized. Generally speaking, the ratio of the thermal power of the heat pump to the electric power consumed by the heat pump can reach 3 to 4 times, and this ratio is also called the energy efficiency coefficient of the heat pump.
In one embodiment, the heat pump may have the following model:
Figure BDA00035112722700001811
Figure BDA00035112722700001812
wherein,
Figure BDA00035112722700001813
and
Figure BDA00035112722700001814
respectively representing the electric power consumed by the heat pump and the thermal power output; COP (coefficient of Performance)iRepresenting the energy efficiency coefficient of the heat pump;
Figure BDA00035112722700001815
and
Figure BDA00035112722700001816
respectively representing the upper limit and the lower limit of the heat pump output heat power.
Wherein the constraint (14) represents a relationship between thermal power output by the heat pump and electrical power consumed; the constraint (15) describes the thermal output range of the heat pump.
In the operation of the sub-electric heating network, the electricity storage device and the heat storage device play two key roles. Firstly, the effect of filling the millet is filled out in the peak clipping has been played, can exchange peak load and low ebb load according to energy price signal to promote the economic nature of the whole operation of system. And secondly, the function of flexibility adjustment is exerted, and a power gap caused by new energy fluctuation in the system is compensated, so that the flexibility and the reliability of the operation of the system are improved. The operating constraints of the electrical storage device and the thermal storage device can be described by the following equations.
Figure BDA0003511272270000191
Figure BDA0003511272270000192
Figure BDA0003511272270000193
Figure BDA0003511272270000194
Figure BDA0003511272270000195
Figure BDA0003511272270000196
Wherein,
Figure BDA0003511272270000197
and
Figure BDA0003511272270000198
respectively representing the charging power and the discharging power of the electric storage device;
Figure BDA0003511272270000199
and
Figure BDA00035112722700001910
respectively representing the charging efficiency and the discharging efficiency of the electric storage device;
Figure BDA00035112722700001911
representing a power loss rate of the electric storage device;
Figure BDA00035112722700001912
representing the electrical energy stored in the electrical storage device;
Figure BDA00035112722700001913
and
Figure BDA00035112722700001914
respectively representing an upper limit and a lower limit of charging power of the electric storage device;
Figure BDA00035112722700001915
and
Figure BDA00035112722700001916
respectively representing an upper limit and a lower limit of the discharge power of the electric storage device;
Figure BDA00035112722700001917
and
Figure BDA00035112722700001918
respectively representing an upper limit and a lower limit of stored electric energy of the electric storage device;
Figure BDA00035112722700001919
and
Figure BDA00035112722700001920
respectively representing the charging power and the discharging power of the heat storage device;
Figure BDA00035112722700001921
and
Figure BDA00035112722700001922
respectively representing the heat charging efficiency and the heat discharging efficiency of the heat storage device;
Figure BDA00035112722700001923
representing the rate of heat loss from the heat storage device;
Figure BDA00035112722700001924
representing the thermal energy stored in the heat storage device;
Figure BDA0003511272270000201
and
Figure BDA0003511272270000202
respectively representing the upper limit and the lower limit of the charging power of the heat storage device;
Figure BDA0003511272270000203
and
Figure BDA0003511272270000204
respectively representing the upper limit and the lower limit of heat release power of the heat storage device;
Figure BDA0003511272270000205
and
Figure BDA0003511272270000206
respectively representing the upper limit and the lower limit of the stored heat energy of the heat storage device; Δ t represents a scheduled time interval.
Wherein, the constraints (16) and (17) respectively describe the charging and discharging (heat) processes of the electric storage device and the heat storage device, and the relation between the stored energy and the charging and discharging power is disclosed. Constraints (18) - (21) describe the upper and lower bound ranges of charge-discharge (thermal) power and stored energy, respectively.
The soft switch is a power electronic device composed of a double-end voltage source type inverter, and can flexibly and freely control active power exchange between sub electric heating networks connected through the soft switch. For the sub electric heating network m and the sub electric heating network n connected by the soft switch, the power balance constraint at the connection is as follows.
Figure BDA0003511272270000207
Figure BDA0003511272270000208
Wherein,
Figure BDA0003511272270000209
active power flowing from the sub electric heating network m to the sub electric heating network n (also referred to as a second electric energy amount regarding a cost of purchasing electric energy by a peer electric heating network between the sub electric heating network m and the sub electric heating network n);
Figure BDA00035112722700002010
representing active power loss in the soft switch;
Figure BDA00035112722700002011
representing the power loss coefficient of the soft switch; mnRepresents a sub electric heating network set connected with the sub electric heating network n.
Wherein the constraint (22) represents an active power balance condition in the soft switch; the constraint (23) describes the relation between power loss and transmission power in the softswitch. Typically, the power loss in the soft switch is much less than its transmission power (which may be 0.02, for example). Therefore, the power loss is ignored in this embodiment, so that the power balance condition (22) is described in a simpler form as follows:
Figure BDA00035112722700002012
in the invention, a basis can be laid for establishing the interconnected comprehensive energy network scheduling method based on the P2P transaction mode by establishing the mathematical model of the interconnected comprehensive energy network system. In the application process, an operation model of the combined comprehensive energy network system can be established based on the constructed mathematical model.
In one embodiment, the operational model for the interconnected integrated energy network system may include a sum of operational costs of each of the sub-electric heating networks. For any sub electric heating network n, the operation cost is divided into four parts:
Figure BDA0003511272270000211
wherein,
Figure BDA0003511272270000212
which represents the cost of the operation of the device,
Figure BDA0003511272270000213
indicating the purchase cost of electric energy in the upper electric network (also called sub-electric heating network n with price)
Figure BDA0003511272270000214
The cost of purchasing power from an upper-level grid),
Figure BDA0003511272270000215
represents the cost of operating the distributed generator set,
Figure BDA0003511272270000216
represents the running cost of the cogeneration unit,
Figure BDA0003511272270000217
represents the cost of purchasing electric energy by the peer electric heating network (also called the cost of purchasing electric energy from other sub electric heating networks in P2P trading market by the sub electric heating network n).
In one embodiment, the upper level power network purchase power cost may be determined using the following formula:
Figure BDA0003511272270000218
wherein,
Figure BDA0003511272270000219
representing the unit price of purchasing electric energy from an upper power network,
Figure BDA00035112722700002110
a first amount of electrical energy representing a cost of purchasing electrical energy with respect to an upper level electrical power network.
In one embodiment, the distributed generator set operating cost may be determined using the following equation:
Figure BDA00035112722700002111
as can be appreciated, the operating costs of the distributed generator set
Figure BDA00035112722700002112
Is a convex quadratic function which can be converted into a piecewise linear function by a piecewise linear approximation method. Wherein,
Figure BDA00035112722700002113
representing the active power output by the distributed generator set,
Figure BDA00035112722700002114
a first constant coefficient is represented by a first coefficient,
Figure BDA00035112722700002115
the second constant coefficient is represented by a second constant coefficient,
Figure BDA00035112722700002116
representing the third constant coefficient.
In one embodiment, the co-generator set operating cost may be determined using the following equation:
Figure BDA0003511272270000221
wherein,
Figure BDA0003511272270000222
which represents the unit price of the natural gas,
Figure BDA0003511272270000223
representing the natural gas power input by the cogeneration unit.
In one embodiment, the purchase cost of the electric energy of the peer electric heating network can be determined by adopting the following formula:
Figure BDA0003511272270000224
cost of purchasing electric energy in peer electric heating network
Figure BDA0003511272270000225
Which may also be referred to as the sub electric heating network n, purchases the cost of electric energy from the remaining sub electric heating networks in the P2P trading market, or sells the profit of electric energy to the remaining electric heating networks. Wherein,
Figure BDA0003511272270000226
the unit price of electric energy purchased among peer electric heating networks based on the P2P transaction mode is represented;
Figure BDA0003511272270000227
a second amount of electric energy representing a cost of purchasing electric energy with respect to the peer electric heating networks between the sub electric heating network m and the sub electric heating network n. It will be appreciated that the above-described,
Figure BDA0003511272270000228
the value of (d) may be positive or negative depending on the direction of transmission of the exchanged power. This feature indicates that the transaction is at P2PIn the market, part of the sub-electric heating network plays the role of a producer, and part of the sub-electric heating network plays the role of a consumer, so that the bidirectional transaction of the market is realized. Note that P2P trades prices
Figure BDA0003511272270000229
Rather than a known quantity given in advance, the value will be generated during the process of solving for P2P trade balance.
Furthermore, the heat pump consumes electrical energy during operation, and its operating costs are already taken into account during the production of electrical energy, so that no separate calculation is necessary. Based on the above analysis, the total operating cost of the sub-thermal network n
Figure BDA00035112722700002210
Can be expressed as:
Figure BDA00035112722700002211
in the interconnected integrated energy network system, the goal of each sub-electric heating network main body is to pursue the maximization of self-interest or the minimization of self-operation cost. Therefore, the operation cost of all the electric heating networks can be added to obtain the total social operation cost (corresponding to the interconnected comprehensive energy network system). It can be seen that minimizing the total cost of social operations (maximizing social welfare) is a goal to be pursued, and therefore the following operational model for the interconnected integrated energy network system can be obtained:
Figure BDA0003511272270000231
wherein N represents a set of sub-electrothermal networks; t denotes a set of time instants.
It will be appreciated that there are two major obstacles to the solution of the model (30). One is that the objective function is not a well-defined expression. This is because P2P trades prices
Figure BDA0003511272270000232
Instead of a given known quantity, the corresponding market equilibrium price can only be obtained after solving the problem (30). This introduces a paradox to the problem solution. Secondly, each sub-electric heating network is a different beneficial agent and is unwilling to share the private data of the sub-electric heating network, so that the traditional centralized solving algorithm cannot be applied. Therefore, how to design a reasonable distributed solving algorithm becomes a problem to be researched urgently, wherein the existence of the coupling constraint (24) undoubtedly brings more obstacles to the distributed solving of the problem.
In order to design a reasonable distributed solving algorithm, the operation model is subjected to distributed solving to obtain a first electric energy quantity related to the purchase electric energy cost of a superior electric power network, active power output by a distributed generator set related to the operation cost of the distributed generator set, natural gas power input by a cogeneration set related to the operation cost of the cogeneration set and a second electric energy quantity related to the purchase electric energy cost of a same level electric heating network, so that the operation cost of each sub electric heating network and the operation cost of an interconnected comprehensive energy network system are the lowest.
It should be noted that the solution for processing the operation model of the interconnected integrated energy network system includes two key problems: firstly, how to design a distributed algorithm to solve a coordinated operation model (30); and secondly, how to design a reasonable mechanism in a distributed way to determine the price of P2P trading so as to stimulate each electric heating network main body to participate in the P2P trading market.
In order to further describe the method for scheduling the interconnected comprehensive energy network based on the P2P transaction mode, a process of performing distributed solution on the operation model will be described below.
FIG. 2 is a schematic flow chart of distributed solution of the operation model provided by the present invention.
In an exemplary embodiment of the present invention, as shown in fig. 2, the distributed solution of the operation model may include steps 210 to 240, which are described separately below.
In step 210, a target auxiliary variable is obtained, wherein the target auxiliary variable is an auxiliary variable related to a second amount of electric energy of the electric energy purchase cost of the peer electric heating network.
In step 220, based on the equality of demand and supply of P2P transaction pattern and the target auxiliary variable, the cost of purchasing electric energy from the peer electric heating network is hidden in the operation model, and a simplified operation model is obtained.
In step 230, a matrix transformation is performed on the simplified operation model to obtain a matrix model related to the simplified operation model, and an augmented lagrangian function related to the matrix model is constructed.
In step 240, the operational model is solved in a distributed manner by using an alternating direction multiplier method based on the augmented lagrange function.
In the P2P trading market, consumers spend money to purchase power (positive for P2P trading cost) and producers earn revenue by selling power (negative for P2P trading cost) as defined by P2P trading cost (28). Due to the equality of demand and supply, the sum of the transaction costs of P2P in the interconnected integrated energy network system is necessarily 0. In one embodiment, the objective function in the problem (30) can be further simplified, resulting in a simplified run model written in the form:
Figure BDA0003511272270000241
it will be appreciated that in question (31), P2P deals with the cost (also known as the cost of purchasing electrical energy from a peer electrical heating network)
Figure BDA0003511272270000242
It no longer appears explicitly in the objective function, and therefore, the objective function is no longer subject to P2P trading power and unknown P2P trading prices
Figure BDA0003511272270000243
The influence of (c).
To construct a distributed solution strategy, objective auxiliary variables may be introduced
Figure BDA0003511272270000244
Constraint in question (31)
Figure BDA0003511272270000245
The equivalence is converted into the following form:
Figure BDA0003511272270000246
Figure BDA0003511272270000247
wherein constraints (32) and (33) are to design P2P trade price
Figure BDA0003511272270000251
A feasible path is provided. From an economic point of view, the dual variables of the constraint (33) represent
Figure BDA0003511272270000252
The amount of change in the target function (total cost) per unit is changed, so that the dual variable can be used as the price of P2P trading in the sub-electric heating networks m and n.
In one example, z may ben、
Figure BDA0003511272270000253
And ynRespectively representing P2P transaction variables (also called second electric energy quantity related to the purchase electric energy cost of the same-level electric heating network of a constraint function in a simplified operation model)
Figure BDA0003511272270000254
Target auxiliary variable
Figure BDA0003511272270000255
And a remaining decision variable in the model (31) (also referred to as a remaining decision variable in the simplified post-operation model excluding a second amount of electrical energy related to a cost of purchasing electrical energy from the peer electrical heating network). Can be used forTo see, ynAnd znThe local variable belonging to each sub electric heating network n has no coupling relation with the rest sub electric heating networks no matter in an objective function or a constraint.
In one embodiment, the simplified post-operational model includes a constraint function including a second amount of electrical energy for a cost of purchasing electrical energy from the peer electrical heating network
Figure BDA0003511272270000256
Further, the simplified operation model (31) is subjected to matrix conversion, so that a matrix model related to the simplified operation model can be obtained and can be expressed in the form of a matrix as follows:
Figure BDA0003511272270000257
wherein, ynA decision variable remaining in the simplified operating model, z, in addition to a second amount of electrical energy relating to a cost of purchasing electrical energy from the peer electrical heating networknA second amount of electrical energy representing a cost of purchasing electrical energy for the peer electrical heating network for a constraint function in the simplified operational model;
Figure BDA0003511272270000258
representing a target auxiliary variable; f. ofn、dn、Cn、DnAnd EnAll represent constant coefficients.
It is noted that, in the matrix model (34), the first constraint represents a local constraint of each sub electric heating network; the second constraint represents the power balance of the P2P transaction between the different sub-electrocaloric networks, corresponding to constraint (32), which is obviously the coupling constraint between the sub-electrocaloric networks; the third constraint is in the form of a matrix of constraints (33) whose dual variables represent the transaction price of P2P.
To construct a distributed solution algorithm for the problem (34), an augmented Lagrangian function can be constructed with respect to the matrix model. In one example, the augmented Lagrangian function may be determined using the following equation:
Figure BDA0003511272270000261
wherein λ isnRepresenting functions about constraints
Figure BDA0003511272270000262
The dual variable of (a) is used for representing the unit price of electric energy purchased among peer electric heating networks based on the P2P transaction mode; p represents a penalty term parameter.
In yet another embodiment, the problem (34) may be solved distributively using a two-partition alternating direction multiplier method based on an augmented lagrange function (35). Namely, based on the augmented Lagrange function, the operation model is subjected to distributed solution by using an alternative direction multiplier method.
Fig. 3 is a schematic flow chart of distributed solution of the operation model by using an alternating direction multiplier method based on the augmented lagrangian function according to the present invention.
The process of performing distributed solution on the operation model by using the alternating direction multiplier method with respect to the augmented lagrangian function will be described below with reference to fig. 3.
In an exemplary embodiment of the present invention, as shown in fig. 3, the step of distributively solving the operation model by using the alternating direction multiplier method with the augmented lagrange function may include steps 310 to 350, which will be described separately below.
In step 310, S1: determining a convergence threshold epsilon, determining the unit price of purchasing electric energy among peer electric heating networks based on P2P transaction mode
Figure BDA0003511272270000263
And setting the iteration times k to be 0, wherein the convergence threshold epsilon is more than 0.
In step 320, S2: based on the independence of each sub electric heating network, the residual decision variable y except the second electric energy quantity related to the purchase electric energy cost of the same electric heating network in the simplified operation model is updated in parallelnAnd the limiting function in the simplified operation model relates to the same level of electric heatingSecond amount of energy z for cost of network purchasen。
Wherein the updated second amount of electric energy Zn k+1And updated residual decision variable yn k+1The following relationship is satisfied:
Figure BDA0003511272270000271
in one embodiment, the local variable y may be updatednAnd zn. Due to the variable ynAnd znEach sub-network can be solved (36) independently in parallel to update ynAnd znObtaining the updated second electric energy quantity zn k+1And updated residual decision variable yn k+1。
In step 330, S3: updating the second amount of electrical energy z of the sub-networksn k+1Share other sub-electric heating networks in the interconnected comprehensive energy network system and assist variables to the target
Figure BDA0003511272270000272
Performing an update, wherein the updated target auxiliary variable
Figure BDA0003511272270000273
The following relationship can be satisfied:
Figure BDA0003511272270000274
in one embodiment, the coupled variable (also called target auxiliary variable) can be updated
Figure BDA0003511272270000275
To obtain updated target auxiliary variables (also called updated coupling variables)
Figure BDA0003511272270000276
After being appliedIn the process, each sub-electric heating network can trade P2P for power quantity (also called second electric energy quantity) zn k+1Sharing to other sub-electric heating networks in the interconnected integrated energy network system, and updating coupling variables through solving (37)
Figure BDA0003511272270000277
In step 340, S4: updating unit price for purchasing electric energy among peer electric heating networks based on P2P transaction mode
Figure BDA0003511272270000278
Wherein, the unit price of purchasing electric energy among the same electric heating networks after updating
Figure BDA0003511272270000279
The following relationship is satisfied:
Figure BDA0003511272270000281
in one embodiment, the unit price of electric energy purchased between peer electric heating networks in P2P transaction mode is updated
Figure BDA0003511272270000282
Wherein, each sub-electric heating network can calculate (38) the unit price of electric energy purchased among peer electric heating networks updating the P2P transaction mode.
In step 350, S5: carrying out convergence test, and if the unit price of the electric energy purchased among the updated same-level electric heating networks is converged, stopping calculation and outputting a final result; otherwise, update and return to S2.
The updated unit price convergence of the electric energy purchased among the same-level electric heating networks can be represented by the following formula:
Figure BDA0003511272270000283
outputting the final result may include
Figure BDA0003511272270000284
Therefore, distributed solution of the operation model (30) of the interconnected comprehensive energy network system can be completed, and a reasonable mechanism is provided for determining the price of the P2P transaction.
The invention provides an interconnection comprehensive energy network scheduling method based on a P2P transaction mode, which has the advantages that: in interconnected electric heating systems, each electric heating system belongs to an independent subject and pursues maximization of own benefits, so that a reasonable mechanism is urgently needed to be designed to maximize the overall benefits of the system while guaranteeing the benefits of each subject. According to the invention, firstly, a mathematical model of the interconnected electric heating system is established, and then, a P2P trading mechanism is adopted to design trading rules among the electric heating systems, so that each main body is stimulated to participate in a P2P trading market, and a P2P trading-based coordinated operation model of the interconnected electric heating system is established. Finally, a distributed solving algorithm of the coordinated operation model of the interconnected electric heating systems based on P2P transaction is designed based on the alternative direction multiplier method, so that the privacy data of each electric heating system are protected. The method provided by the invention does not need each electric heating system to share private data, simultaneously, the designed method meets the incentive compatibility principle, each electric heating system pursues own benefits and simultaneously maximizes the overall benefits, and therefore, the method has the advantages of strong privacy, simple calculation, easiness in engineering practice and the like.
According to the above description, the interconnected comprehensive energy network scheduling method based on the P2P transaction mode is applied to an interconnected comprehensive energy network system, wherein the interconnected comprehensive energy network system comprises a plurality of sub electric heating networks. The invention determines the transaction rules among the sub electric heating networks through the P2P transaction mode, so as to stimulate each sub electric heating network to participate in the P2P transaction and establish an operation model of the interconnected comprehensive energy network system based on the P2P transaction. And then, carrying out distributed solving on the operation model, and obtaining a first electric energy quantity of the purchase electric energy cost of a superior electric power network, the active power output by the distributed generator set, the natural gas power input by the cogeneration set and a second electric energy quantity of the purchase electric energy cost of the same level electric heating network on the premise of protecting the privacy data of each sub electric heating network, so that the operation cost of each sub electric heating network and the operation cost of the interconnected comprehensive energy network system are the lowest. According to the P2P transaction mode-based interconnected comprehensive energy network scheduling method, private data does not need to be shared by all sub electric heating networks, the incentive compatibility principle is met, the maximized overall benefits of the interconnected comprehensive energy network system are achieved when each sub electric heating network pursues the benefits of the sub electric heating network, and therefore the maximization of the overall benefits of the interconnected comprehensive energy network system is achieved on the basis of ensuring the benefits of each electric heating main body.
Based on the same conception, the invention also provides an interconnection comprehensive energy network dispatching device based on the P2P transaction mode.
The interconnected integrated energy network dispatching device based on the P2P transaction mode provided by the invention is described below, and the interconnected integrated energy network dispatching device based on the P2P transaction mode described below and the interconnected integrated energy network dispatching method based on the P2P transaction mode described above can be referred to correspondingly.
Fig. 4 is a schematic structural diagram of the interconnected integrated energy network dispatching device based on the P2P transaction mode provided by the invention.
In an exemplary embodiment of the present invention, the interconnected integrated energy network dispatching device based on the P2P transaction mode may be applied to an interconnected integrated energy network system, wherein the interconnected integrated energy network system may include a plurality of sub-electric heating networks. The sub electric heating networks at least comprise an electric power network, a thermal power network, a distributed generator set, a wind turbine generator set, a cogeneration set, a heat pump, an electricity storage device and a heat storage device, and the sub electric heating networks can be connected through a soft switch and trade by adopting a P2P trading mode.
As shown in fig. 4, the interconnected integrated energy network dispatching device based on P2P transaction mode may include a creating module 410 and a processing module 420, each of which will be described below.
The establishing module 410 may be configured to establish an operation model for the interconnected integrated energy network system based on the P2P transaction pattern, wherein the operation model may include operation costs of each sub electric heating network, and the operation costs may include an upper level electric power network purchase electric energy cost, a distributed generator set operation cost, a cogeneration unit operation cost, and a peer electric heating network purchase electric energy cost.
The processing module 420 may be configured for performing a distributed solution on the operation model to obtain a first amount of electric energy with respect to an upper level electric power network purchase electric energy cost, an active power output by the distributed generator set with respect to a distributed generator set operation cost, a natural gas power input by the cogeneration unit with respect to a cogeneration unit operation cost, and a second amount of electric energy with respect to a peer electric heating network purchase electric energy cost, so as to minimize an operation cost of each sub electric heating network and an operation cost of the interconnected integrated energy network system.
In an exemplary embodiment of the invention, the operation model of the interconnected integrated energy network system may include a sum of operation costs of the respective sub-electric heating networks, and the establishing module 410 may determine the operation costs using the following formula:
Figure BDA0003511272270000301
wherein,
Figure BDA0003511272270000302
which represents the cost of the operation of the plant,
Figure BDA0003511272270000303
represents the purchase cost of electric energy of the upper power network,
Figure BDA0003511272270000304
represents the cost of operating the distributed power generation unit,
Figure BDA0003511272270000305
represents the running cost of the cogeneration unit,
Figure BDA0003511272270000306
representing the same levelThe cost of electric energy purchased by the electric heating network.
In an exemplary embodiment of the present invention, the establishing module 410 may determine the purchase power cost of the upper power network by using the following formula:
Figure BDA0003511272270000307
wherein,
Figure BDA0003511272270000308
representing the unit price of purchasing electric energy from an upper power network,
Figure BDA0003511272270000309
representing a first amount of electrical energy representing a cost of purchasing electrical energy with respect to a superior electrical power network, the electrical power network having a model of:
Figure BDA0003511272270000311
Figure BDA0003511272270000312
Vj,t＝Vi,t-(rijPij,t+xijQij,t)/V0 (3)
wherein p isj,tRepresenting the total active power injected at a node j in the power network, including a first amount of electrical energy with respect to the purchase cost of electrical energy of a superior power network
Figure BDA0003511272270000313
Second amount of electric energy related to cost of purchasing electric energy from peer electric heating network
Figure BDA0003511272270000314
Active power output of distributed generator set
Figure BDA0003511272270000315
Active power output of combined heat and power generation unit
Figure BDA0003511272270000316
Active power output of wind turbine generator
Figure BDA0003511272270000317
Charging power of an electrical storage device
Figure BDA0003511272270000318
And discharge power
Figure BDA0003511272270000319
Figure BDA00035112722700003110
Representing the total active load at node j in the power network, including the base electrical load and the active power consumed by the heat pump
Figure BDA00035112722700003111
qj,tRepresenting the total reactive power injected at node j in the power network, including the reactive power from the superior power network
Figure BDA00035112722700003112
And reactive power output of distributed generator set
Figure BDA00035112722700003113
Figure BDA00035112722700003114
Representing a reactive load at node j in the power network; p isij,tAnd Qij,tRespectively representing the active power and the reactive power of a line from a node i to a node j in the power network; r is a radical of hydrogenijAnd xijRespectively representing the line resistance and line reactance from a node i to a node j in the power network; vi,tRepresenting the voltage amplitude of node i in the power network; v0Represents a reference voltage;
Figure BDA00035112722700003115
representing a set of downstream nodes for node j.
In an exemplary embodiment of the invention, the establishment module 410 may determine the distributed genset operating cost using the following equation:
Figure BDA00035112722700003116
wherein,
Figure BDA00035112722700003117
representing the real power output by the distributed generator set,
Figure BDA00035112722700003118
the first constant coefficient is represented by a first constant coefficient,
Figure BDA0003511272270000321
the second constant coefficient is represented by a second constant coefficient,
Figure BDA0003511272270000322
and expressing a third constant coefficient, wherein the distributed power generation set has the following model:
Figure BDA0003511272270000323
Figure BDA0003511272270000324
wherein,
Figure BDA0003511272270000325
representing reactive power output by the distributed generator set;
Figure BDA0003511272270000326
and
Figure BDA0003511272270000327
respectively representing distributed dataThe upper limit and the lower limit of the active power of the motor set;
Figure BDA0003511272270000328
and
Figure BDA0003511272270000329
representing the upper and lower limits of reactive power of the distributed genset, respectively.
In an exemplary embodiment of the invention, the setup module 410 may determine the cogeneration unit operating cost using the following equation:
Figure BDA00035112722700003210
wherein,
Figure BDA00035112722700003211
which represents the unit price of the natural gas,
Figure BDA00035112722700003212
representing the natural gas power input by the cogeneration unit, wherein the cogeneration unit has the following model:
Figure BDA00035112722700003213
Figure BDA00035112722700003214
Figure BDA00035112722700003215
wherein,
Figure BDA00035112722700003216
and
Figure BDA00035112722700003217
individual watchDisplaying electric power and thermal power output by the cogeneration unit;
Figure BDA00035112722700003218
and
Figure BDA00035112722700003219
respectively representing the gas-to-electricity efficiency and the gas-to-heat efficiency of the cogeneration unit;
Figure BDA00035112722700003220
and
Figure BDA00035112722700003221
respectively representing the upper limit and the lower limit of the natural gas input power of the cogeneration unit.
In an exemplary embodiment of the present invention, the establishing module 410 may determine the purchase cost of the electric energy of the peer electric heating network by using the following formula:
Figure BDA00035112722700003222
wherein,
Figure BDA0003511272270000331
representing the unit price of electric energy purchased by peer electric heating networks based on P2P transaction mode,
Figure BDA0003511272270000332
a second amount of electrical energy representing a cost of purchasing electrical energy for a peer electrical heating network between the sub-electrical heating network m and the sub-electrical heating network n, wherein the soft switch connecting the sub-electrical heating network m and the sub-electrical heating network n has a model as follows:
Figure BDA0003511272270000333
Figure BDA0003511272270000334
wherein,
Figure BDA0003511272270000335
representing active power loss in the soft switch;
Figure BDA0003511272270000336
representing the power loss coefficient of the soft switch; mnRepresents a sub electric heating network set connected with the sub electric heating network n.
In an exemplary embodiment of the invention, the processing module 420 may perform distributed solution on the operation model in the following manner:
acquiring a target auxiliary variable, wherein the target auxiliary variable is an auxiliary variable of a second electric energy quantity related to the purchase electric energy cost of the electric heating network at the same level; based on the equality of the demand and supply of the P2P transaction mode and the target auxiliary variable, the cost of purchasing electric energy by the peer electric heating network is hidden in the operation model, and the simplified operation model is obtained; performing matrix conversion on the simplified operation model to obtain a matrix model of the simplified operation model, and constructing an augmented Lagrangian function of the matrix model; and based on the augmented Lagrange function, performing distributed solution on the operation model by using an alternative direction multiplier method.
In an exemplary embodiment of the invention, the simplified operating model may include a constraint function, the constraint function may include a second amount of power for a cost of purchasing power from the peer electric heating network, and the processing module 420 may determine the matrix model for the simplified operating model using the following model:
Figure BDA0003511272270000341
wherein, ynRepresenting a remaining decision variable, z, in the simplified operating model, in addition to said second amount of electrical energy relating to the cost of purchasing electrical energy from the same level of the electrical heating networknA second amount of electrical energy representing a cost of purchasing electrical energy for the peer electrical heating network for a constraint function in the simplified operational model;
Figure BDA0003511272270000342
representing a target auxiliary variable; f. ofn、dn、Cn、DnAnd EnAll represent constant coefficients.
In an exemplary embodiment of the present invention, the processing module 420 may determine the augmented lagrangian function using the following equation:
Figure BDA0003511272270000343
wherein λ isnRepresenting functions with respect to constraints
Figure BDA0003511272270000344
The dual variable of (a) is used for representing the unit price of electric energy purchased among peer electric heating networks based on the P2P transaction mode; p represents a penalty term parameter.
In an exemplary embodiment of the present invention, the processing module 420 may perform distributed solution on the operation model by using an alternating direction multiplier method based on the augmented lagrange function in the following manner:
s1: determining a convergence threshold epsilon, determining an initial price per unit for purchasing power among peer electrical heating networks based on a P2P transaction pattern
Figure BDA0003511272270000345
And setting the iteration times k to be 0, wherein the convergence threshold epsilon is more than 0;
s2: based on the independence of each sub electric heating network, the residual decision variable y except the second electric energy quantity related to the electric energy purchase cost of the same electric heating network in the simplified operation model is updated in parallelnAnd a second quantity z of electrical energy relating to the cost of purchasing electrical energy from the electric heating network of the same level, simplifying the constraint function of the post-operation modelnWherein
Figure BDA0003511272270000351
s3: updating the second amount of electrical energy of the sub-electric heating network
Figure BDA0003511272270000352
Share other sub-electric heating networks in the interconnected comprehensive energy network system and assist variables to the target
Figure BDA0003511272270000353
The update is performed, wherein,
Figure BDA0003511272270000354
s4: updating unit price for purchasing electric energy among peer electric heating networks based on P2P transaction mode
Figure BDA0003511272270000355
Wherein,
Figure BDA0003511272270000356
s5: performing a convergence test if
Figure BDA0003511272270000357
The calculation is terminated and the final result is output
Figure BDA0003511272270000358
Otherwise, k ← k +1 is updated and returns to S2.
In an exemplary embodiment of the invention, the building module 410 may determine the thermal network using the following model:
Figure BDA0003511272270000359
Figure BDA00035112722700003510
Figure BDA00035112722700003511
Figure BDA00035112722700003512
Figure BDA00035112722700003513
wherein b represents a pipe of a thermodynamic network;
Figure BDA00035112722700003514
representing the total thermal power injected into said thermal network by a heat source, including the thermal output of the cogeneration unit
Figure BDA0003511272270000361
Thermal output of heat pump
Figure BDA0003511272270000362
Charging power of heat storage device
Figure BDA0003511272270000363
And the heat-releasing power of the heat storage device
Figure BDA0003511272270000364
Figure BDA0003511272270000365
A heat dissipation power representing a heat load; c. CpRepresents the specific heat capacity of water;
Figure BDA0003511272270000366
representing the mass flow of circulating water injected into a water supply pipeline from a water return pipeline at a heat source;
Figure BDA0003511272270000367
representing the mass flow of circulating water from a water supply pipeline to a water return pipeline at a heat load;
Figure BDA0003511272270000368
and
Figure BDA0003511272270000369
respectively representing the water supply temperature and the water return temperature; m isb,tRepresenting the circulating water mass flow of the pipeline b;
Figure BDA00035112722700003610
and
Figure BDA00035112722700003611
respectively representing the inlet temperature and the outlet temperature of the pipeline b; gamma raybRepresents the temperature loss coefficient of the pipeline b; l isbRepresents the length of the pipe b;
Figure BDA00035112722700003612
represents the ambient temperature;
Figure BDA00035112722700003613
indicating a fluid mixing temperature at the junction;
Figure BDA00035112722700003614
representing a pipeline set taking the node i as a terminal;
Figure BDA00035112722700003615
representing a set of pipes headed by node i.
In an exemplary embodiment of the invention, the establishing module 410 may determine the heat pump using the following model:
Figure BDA00035112722700003616
Figure BDA00035112722700003617
wherein,
Figure BDA00035112722700003618
and
Figure BDA00035112722700003619
respectively representing the electric power consumed by the heat pump and the thermal power output; COPiRepresenting an energy efficiency coefficient of the heat pump;
Figure BDA00035112722700003620
and
Figure BDA00035112722700003621
respectively representing the upper limit and the lower limit of the heat pump output heat power.
In an exemplary embodiment of the invention, the establishing module 410 may determine the heat storage device using the following model:
Figure BDA00035112722700003622
Figure BDA00035112722700003623
Figure BDA0003511272270000371
wherein,
Figure BDA0003511272270000372
and
Figure BDA0003511272270000373
respectively representing the charging power and the discharging power of the heat storage device;
Figure BDA0003511272270000374
and
Figure BDA0003511272270000375
respectively representing the charging efficiency and the discharging efficiency of the heat storage device;
Figure BDA0003511272270000376
representing the rate of thermal energy loss from the heat storage device;
Figure BDA0003511272270000377
representing the thermal energy stored in the heat storage device;
Figure BDA0003511272270000378
and
Figure BDA0003511272270000379
respectively representing the upper limit and the lower limit of the charging power of the heat storage device;
Figure BDA00035112722700003710
and
Figure BDA00035112722700003711
respectively representing the upper limit and the lower limit of heat release power of the heat storage device;
Figure BDA00035112722700003712
and
Figure BDA00035112722700003713
respectively representing the upper limit and the lower limit of the stored heat energy of the heat storage device; Δ t represents a scheduled time interval.
In an exemplary embodiment of the invention, the establishing module 410 may determine the power storage device using the following model:
Figure BDA00035112722700003714
Figure BDA00035112722700003715
Figure BDA00035112722700003716
wherein,
Figure BDA00035112722700003717
and
Figure BDA00035112722700003718
respectively representing the charging power and the discharging power of the electric storage device;
Figure BDA00035112722700003719
and
Figure BDA00035112722700003720
respectively representing the charging efficiency and the discharging efficiency of the electric storage device;
Figure BDA00035112722700003721
representing a rate of power loss from the electrical storage device;
Figure BDA00035112722700003722
representing electrical energy stored in an electrical storage device;
Figure BDA00035112722700003723
and
Figure BDA00035112722700003724
respectively representing an upper limit and a lower limit of charging power of the electric storage device;
Figure BDA00035112722700003725
and
Figure BDA00035112722700003726
respectively representing an upper limit and a lower limit of the discharge power of the electric storage device;
Figure BDA00035112722700003727
and
Figure BDA00035112722700003728
respectively representing an upper limit and a lower limit of stored electric energy of the electric storage device; Δ t represents a scheduled time interval.
Fig. 5 illustrates a physical structure diagram of an electronic device, which may include, as shown in fig. 5: a processor (processor)510, a communication Interface (Communications Interface)520, a memory (memory)530 and a communication bus 540, wherein the processor 510, the communication Interface 520 and the memory 530 communicate with each other via the communication bus 540. The processor 510 may call the logic instructions in the memory 530 to execute a P2P transaction mode-based interconnected integrated energy network scheduling method, where the method is applied to an interconnected integrated energy network system, where the interconnected integrated energy network system includes a plurality of sub-electric heating networks, each sub-electric heating network at least includes an electric power network, a thermal power network, a distributed generator set, a wind turbine generator set, a cogeneration set, a heat pump, an electricity storage device, and a heat storage device, the sub-electric heating networks are connected by a soft switch and perform transactions in a P2P transaction mode, and the method includes: establishing an operation model of the interconnected comprehensive energy network system based on a P2P transaction mode, wherein the operation model comprises operation costs of all sub electric heating networks, and the operation costs comprise a higher-level electric power network purchase electric energy cost, a distributed generator set operation cost, a cogeneration unit operation cost and a peer electric heating network purchase electric energy cost; and carrying out distributed solving on the operation model to obtain a first electric energy quantity related to the purchase electric energy cost of a superior electric power network, active power output by the distributed generator set related to the operation cost of the distributed generator set, natural gas power input by the cogeneration set related to the operation cost of the cogeneration set, and a second electric energy quantity related to the purchase electric energy cost of the same-level electric heating networks, so that the operation cost of each sub-electric heating network and the operation cost of the interconnected comprehensive energy network system are the lowest.
Furthermore, the logic instructions in the memory 530 may be implemented in the form of software functional units and stored in a computer readable storage medium when the software functional units are sold or used as independent products. Based on such understanding, the technical solution of the present invention or a part thereof which substantially contributes to the prior art may be embodied in the form of a software product, which is stored in a storage medium and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
In another aspect, the present invention further provides a computer program product, where the computer program product includes a computer program, the computer program may be stored on a non-transitory computer-readable storage medium, and when the computer program is executed by a processor, the computer is capable of executing the P2P transaction mode-based interconnected integrated energy network scheduling method provided by the above methods, where the method is applied to an interconnected integrated energy network system, where the interconnected integrated energy network system includes multiple sub-electric heating networks, each sub-electric heating network at least includes an electric power network, a thermal power network, a distributed generator set, a wind turbine generator set, a cogeneration set, a heat pump, an electricity storage device, and a heat storage device, and the sub-electric heating networks are connected by soft switches and perform transactions in a P2P transaction mode, and the method includes: establishing an operation model of the interconnected comprehensive energy network system based on a P2P transaction mode, wherein the operation model comprises operation costs of all sub electric heating networks, and the operation costs comprise a higher-level electric power network purchase electric energy cost, a distributed generator set operation cost, a cogeneration unit operation cost and a peer electric heating network purchase electric energy cost; and performing distributed solution on the operation model to obtain a first electric energy quantity related to the purchase electric energy cost of a superior electric power network, active power output by the distributed generator sets related to the operation cost of the distributed generator sets, natural gas power input by the cogeneration sets related to the operation cost of the cogeneration sets, and a second electric energy quantity related to the purchase electric energy cost of the same-level electric heating networks, so that the operation cost of each sub electric heating network and the operation cost of the interconnected comprehensive energy network system are the lowest.
In still another aspect, the present invention further provides a non-transitory computer readable storage medium, on which a computer program is stored, where the computer program, when executed by a processor, implements a method for scheduling an interconnected integrated energy network based on a P2P transaction mode provided by the above methods, where the method is applied to an interconnected integrated energy network system, where the interconnected integrated energy network system includes a plurality of sub-electric heating networks, the sub-electric heating networks at least include an electric power network, a thermal power network, a distributed generator set, a wind turbine set, a cogeneration set, a heat pump, an electric storage device, and the sub-electric heating networks are connected by a soft switch and perform transactions in a P2P transaction mode, and the method includes: establishing an operation model of the interconnected comprehensive energy network system based on a P2P transaction mode, wherein the operation model comprises operation costs of all sub electric heating networks, and the operation costs comprise a higher-level electric power network purchase electric energy cost, a distributed generator set operation cost, a cogeneration unit operation cost and a peer electric heating network purchase electric energy cost; and carrying out distributed solving on the operation model to obtain a first electric energy quantity related to the purchase electric energy cost of a superior electric power network, active power output by the distributed generator set related to the operation cost of the distributed generator set, natural gas power input by the cogeneration set related to the operation cost of the cogeneration set, and a second electric energy quantity related to the purchase electric energy cost of the same-level electric heating networks, so that the operation cost of each sub-electric heating network and the operation cost of the interconnected comprehensive energy network system are the lowest.
The above-described embodiments of the apparatus are merely illustrative, and the units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment. One of ordinary skill in the art can understand and implement it without inventive effort.
Through the above description of the embodiments, those skilled in the art will clearly understand that each embodiment can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware. Based on the understanding, the above technical solutions substantially or otherwise contributing to the prior art may be embodied in the form of a software product, which may be stored in a computer-readable storage medium, such as ROM/RAM, magnetic disk, optical disk, etc., and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute the method according to the various embodiments or some parts of the embodiments.
It will be further appreciated that while operations are depicted in the drawings in a particular order, this should not be understood as requiring that such operations be performed in the particular order shown or in serial order, or that all illustrated operations be performed, to achieve desirable results. In certain environments, multitasking and parallel processing may be advantageous.
Finally, it should be noted that: the above examples are only intended to illustrate the technical solution of the present invention, and not to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, it should be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.

Claims (18)

1. The method for scheduling the interconnected comprehensive energy network based on the P2P transaction mode is applied to an interconnected comprehensive energy network system, wherein the interconnected comprehensive energy network system comprises a plurality of sub electric heating networks, each sub electric heating network at least comprises a power network, a heating power network, a distributed generator set, a wind turbine set, a cogeneration set, a heat pump, an electricity storage device and a heat storage device, the sub electric heating networks are connected through a soft switch and perform transactions in the P2P transaction mode, and the method comprises the following steps:
establishing an operation model about the interconnected comprehensive energy network system based on the P2P transaction mode, wherein the operation model comprises operation costs of each sub electric heating network, and the operation costs comprise purchase electric energy costs of a superior electric power network, operation costs of a distributed generator set, operation costs of a cogeneration set and purchase electric energy costs of a peer electric heating network;
and carrying out distributed solving on the operation model to obtain a first electric energy quantity related to the purchase electric energy cost of the superior electric power network, active power output by the distributed generator set related to the operation cost of the distributed generator set, natural gas power input by the cogeneration set related to the operation cost of the cogeneration set, and a second electric energy quantity related to the purchase electric energy cost of the same-level electric heating network, so that the operation cost of each sub-electric heating network and the operation cost of the interconnected comprehensive energy network system are the lowest.
2. The P2P transaction mode-based interconnected integrated energy network scheduling method as claimed in claim 1, wherein the operation model related to the interconnected integrated energy network system comprises a sum of operation costs of each of the sub electric heating networks, and the operation costs are determined by using the following formula:
Figure FDA0003511272260000011
wherein f ist nRepresenting said running cost, f1,t nRepresenting the cost of purchasing electric energy of the upper level electric power network, f2,t nRepresenting the operating cost of the distributed generator set, f3,t nRepresenting the operating cost of the cogeneration unit, f4,t nAnd representing the purchase electric energy cost of the peer electric heating network.
3. The P2P transaction pattern-based interconnected comprehensive energy network scheduling method according to claim 2, wherein the upper level power network purchase electric energy cost is determined by using the following formula:
Figure FDA0003511272260000021
wherein,
Figure FDA0003511272260000022
represents a unit price of purchasing electric energy from an upper power network,
Figure FDA0003511272260000023
a first amount of electrical energy representing a cost of purchasing electrical energy in relation to the upper level electrical power network, the electrical power network having a model of:
Figure FDA0003511272260000024
Figure FDA0003511272260000025
Vj,t＝Vi,t-(rijPij,t+xijQij,t)/V0
wherein p isj,tRepresenting the total active power injected at node j in the power network, including a first amount of power with respect to the cost of purchasing power from the superior power network
Figure FDA0003511272260000026
A second amount of electrical energy related to a cost of purchasing electrical energy from the peer electrical heating network
Figure FDA0003511272260000027
Active output of the distributed generator set
Figure FDA0003511272260000028
Of combined heat and power unitsActive power output
Figure FDA0003511272260000029
Active power output of the wind turbine generator
Figure FDA00035112722600000210
Charging power p of the energy storage devicej,t cAnd discharge power pj,t d；
Figure FDA00035112722600000211
Representing the total active load at node j in the power network, including the base electrical load and the active power consumed by the heat pump
Figure FDA00035112722600000212
qj,tRepresenting the total reactive power injected at node j in the power network, including the reactive power from the superior power network
Figure FDA00035112722600000213
And reactive power output of the distributed generator set
Figure FDA00035112722600000214
Figure FDA00035112722600000215
Representing a reactive load at node j in the electrical power network; pij,tAnd Qij,tRespectively representing the active power and the reactive power of a line from a node i to a node j in the power network; r is a radical of hydrogenijAnd xijRepresenting a line resistance and a line reactance from node i to node j in the power network, respectively; vi,tRepresenting a voltage magnitude of a node i in the power network; v0Represents a reference voltage;
Figure FDA00035112722600000216
representing a set of downstream nodes for node j.
4. The P2P transaction pattern-based interconnected comprehensive energy network scheduling method according to claim 2, wherein the operation cost of the distributed generator set is determined by using the following formula:
Figure FDA0003511272260000031
wherein,
Figure FDA0003511272260000032
representing the active power output by the distributed generator set,
Figure FDA0003511272260000033
a first constant coefficient is represented by a first coefficient,
Figure FDA0003511272260000034
the second constant coefficient is represented by a second constant coefficient,
Figure FDA0003511272260000035
representing a third constant coefficient, wherein the distributed power generation set has the following model:
Figure FDA0003511272260000036
Figure FDA0003511272260000037
wherein,
Figure FDA0003511272260000038
representing reactive power output by the distributed generator set;
Figure FDA0003511272260000039
and
Figure FDA00035112722600000310
respectively representing an upper limit and a lower limit of active power of the distributed generator set;
Figure FDA00035112722600000311
and
Figure FDA00035112722600000312
respectively representing an upper limit and a lower limit of reactive power of the distributed generator set.
5. The method for dispatching the interconnected comprehensive energy network based on the P2P transaction mode, wherein the operation cost of the cogeneration unit is determined by the following formula:
Figure FDA00035112722600000313
wherein,
Figure FDA00035112722600000314
the unit price of the natural gas is shown,
Figure FDA00035112722600000315
representing a natural gas power input by the cogeneration unit, wherein the cogeneration unit has a model as follows:
Figure FDA00035112722600000316
Figure FDA00035112722600000317
Figure FDA00035112722600000318
wherein,
Figure FDA00035112722600000319
and
Figure FDA00035112722600000320
respectively representing the electric power and the thermal power output by the combined heat and power generation unit;
Figure FDA00035112722600000321
and
Figure FDA00035112722600000322
respectively representing the gas-to-electricity efficiency and the gas-to-heat efficiency of the cogeneration unit;
Figure FDA00035112722600000323
and
Figure FDA00035112722600000324
respectively representing the upper limit and the lower limit of the input natural gas power of the cogeneration unit.
6. The P2P transaction pattern-based interconnected comprehensive energy network scheduling method of claim 2, wherein the cost of purchasing electric energy from the peer electric heating network is determined by using the following formula:
Figure FDA0003511272260000041
wherein,
Figure FDA0003511272260000042
the unit price of electric energy purchased among peer electric heating networks based on the P2P transaction mode is represented;
Figure FDA0003511272260000043
a second amount of electrical energy representing a cost of purchasing electrical energy for a peer electrical heating network between the sub-electrical heating network m and the sub-electrical heating network n, wherein the soft switch connecting the sub-electrical heating network m and the sub-electrical heating network n has a model as follows:
Figure FDA0003511272260000044
Figure FDA0003511272260000045
wherein,
Figure FDA0003511272260000046
representing active power loss in the soft switch;
Figure FDA0003511272260000047
representing a power loss coefficient of the soft switch; mnRepresents a set of sub-electric heating networks connected to the sub-electric heating network n.
7. The P2P transaction pattern-based interconnected comprehensive energy network scheduling method of claim 2, wherein the performing distributed solution on the operation model comprises:
acquiring a target auxiliary variable, wherein the target auxiliary variable is an auxiliary variable of a second electric energy quantity related to the purchase electric energy cost of the peer electric heating network;
based on the equality of demand and supply of the P2P transaction mode and the target auxiliary variable, hiding the cost of purchasing electric energy of the peer electric heating network in the operation model, and obtaining a simplified operation model;
performing matrix conversion on the simplified operation model to obtain a matrix model related to the simplified operation model, and constructing an augmented Lagrangian function related to the matrix model;
and based on the augmented Lagrange function, performing distributed solution on the operation model by using an alternative direction multiplier method.
8. The P2P transaction pattern-based interconnected energy network scheduling method as claimed in claim 7, wherein the simplified operation model comprises a constraint function, the constraint function comprises a second electric energy amount related to the purchase electric energy cost of the peer electric heating network, and the matrix model related to the simplified operation model has the following model:
Figure FDA0003511272260000051
s.t.Cnyn+Dnzn≤fn,
Figure FDA0003511272260000052
Figure FDA0003511272260000053
Figure FDA0003511272260000054
wherein, ynRepresenting a remaining decision variable in the simplified operational model other than the second amount of electrical energy regarding the cost of purchasing electrical energy for the peer electrical heating network; z is a radical ofnA second amount of electrical energy representing the constraint function in the simplified operating model for a cost of purchasing electrical energy for the peer electrical heating network;
Figure FDA0003511272260000055
representing the target auxiliary variable; f. ofn、dn、Cn、DnAnd EnAll represent constant coefficients.
9. The P2P transaction pattern-based interconnected comprehensive energy network scheduling method according to claim 8, wherein the augmented lagrangian function is determined using the following formula:
Figure FDA0003511272260000056
wherein λ isnRepresenting functions with respect to constraints
Figure FDA0003511272260000057
The dual variable of (2) is used for representing the unit price of purchasing electric energy among peer electric heating networks based on the P2P transaction mode; p represents a penalty term parameter.
10. The P2P trading mode-based interconnected comprehensive energy network scheduling method according to claim 9, wherein the performing distributed solution on the operation model by using an alternating direction multiplier method based on the augmented lagrangian function comprises:
s1: determining a convergence threshold epsilon, determining the unit price of purchasing electric energy among peer electric heating networks based on P2P transaction mode
Figure FDA0003511272260000058
And setting the iteration round times k to be 0, wherein the convergence threshold epsilon is more than 0;
s2: based on the independence of each sub electric heating network, the remaining decision variables y except the second electric energy quantity related to the electric energy purchase cost of the same electric heating network in the simplified operation model are updated in parallelnAnd a second quantity z of electrical energy of said constraint function in said simplified operating model relating to the cost of purchasing electrical energy by said peer electrical heating networknWherein
Figure FDA0003511272260000061
s.t.Cnyn+Dnzn≤fn
s3: updating the second amount of electrical energy z of the sub-gridn k+1Sharing other sub electric heating networks in the interconnected comprehensive energy network system and assisting variables for targets
Figure FDA0003511272260000062
The update is performed, wherein,
Figure FDA0003511272260000063
Figure FDA0003511272260000064
s4: updating unit price lambda of electric energy purchased among peer electric heating networks based on P2P transaction moden kWherein
Figure FDA0003511272260000065
s5: performing a convergence test if
Figure FDA0003511272260000066
The calculation is terminated and the final result is output
Figure FDA0003511272260000067
Otherwise, k ← k +1 is updated and returns to S2.
11. The P2P transaction pattern based interconnected integrated energy network dispatching method according to claim 1, wherein the thermodynamic network has the following model:
Figure FDA0003511272260000068
Figure FDA0003511272260000069
Figure FDA00035112722600000610
Figure FDA00035112722600000611
Figure FDA00035112722600000612
wherein b represents a pipe of the thermodynamic network;
Figure FDA00035112722600000613
representing the total thermal power injected into said thermodynamic network by a heat source, including the thermal output of said cogeneration unit
Figure FDA0003511272260000071
Thermal output of the heat pump
Figure FDA0003511272260000072
The heat charging power h of the heat storage devicei,t cAnd the heat-release power h of the heat storage devicei,t d；
Figure FDA0003511272260000073
A heat dissipation power representing a heat load; c. CpRepresents the specific heat capacity of water;
Figure FDA0003511272260000074
representing the mass flow of circulating water injected into a water supply pipeline from a water return pipeline at a heat source;
Figure FDA0003511272260000075
representing the mass flow of circulating water from a water supply pipeline to a water return pipeline at a heat load;
Figure FDA0003511272260000076
and
Figure FDA0003511272260000077
respectively representing the water supply temperature and the water return temperature; m isb,tRepresenting the circulating water mass flow of the pipeline b;
Figure FDA0003511272260000078
and
Figure FDA0003511272260000079
respectively representing the inlet temperature and the outlet temperature of the pipeline b; gamma raybRepresents the temperature loss coefficient of the pipeline b; l isbRepresents the length of the pipe b; t is a unit oft aRepresents the ambient temperature;
Figure FDA00035112722600000710
indicating a fluid mixing temperature at the junction;
Figure FDA00035112722600000711
representing a pipeline set taking the node i as a terminal;
Figure FDA00035112722600000712
representing a set of pipes headed by node i.
12. The P2P transaction pattern based interconnected integrated energy network dispatching method according to claim 1, wherein the heat pump has the following model:
Figure FDA00035112722600000713
Figure FDA00035112722600000714
wherein,
Figure FDA00035112722600000715
and
Figure FDA00035112722600000716
respectively representing the electric power consumed and the thermal power output by the heat pump; COPiRepresenting an energy efficiency coefficient of the heat pump;
Figure FDA00035112722600000717
andh i HPrespectively representing the upper limit and the lower limit of the heat pump output heat power.
13. The P2P transaction pattern-based interconnected comprehensive energy network dispatching method according to claim 1, wherein the heat storage device has the following model:
Figure FDA00035112722600000718
Figure FDA00035112722600000719
Figure FDA00035112722600000720
wherein,
Figure FDA00035112722600000721
and
Figure FDA00035112722600000722
respectively representing the charging power and the discharging power of the heat storage device;
Figure FDA00035112722600000723
and
Figure FDA00035112722600000724
respectively representing the heat charging efficiency and the heat discharging efficiency of the heat storage device;
Figure FDA00035112722600000725
representing a rate of thermal energy loss from the heat storage device;
Figure FDA00035112722600000726
representing thermal energy stored in the thermal storage device;
Figure FDA00035112722600000727
and
Figure FDA00035112722600000728
respectively representing the upper limit and the lower limit of the charging power of the heat storage device;
Figure FDA0003511272260000081
andh i drespectively representing the upper limit and the lower limit of heat release power of the heat storage device;
Figure FDA0003511272260000082
andW i Trespectively representing the upper limit and the lower limit of the stored heat energy of the heat storage device; Δ t represents a scheduled time interval.
14. The P2P transaction pattern-based interconnected comprehensive energy network dispatching method according to claim 1, wherein the power storage device has the following model:
Figure FDA0003511272260000083
Figure FDA0003511272260000084
Figure FDA0003511272260000085
wherein,
Figure FDA0003511272260000086
and
Figure FDA0003511272260000087
representing a charging power and a discharging power of the electric storage device, respectively;
Figure FDA0003511272260000088
and
Figure FDA0003511272260000089
respectively representing the charging efficiency and the discharging efficiency of the electric storage device;
Figure FDA00035112722600000810
representing a rate of power loss of the electric storage device;
Figure FDA00035112722600000811
representing electrical energy stored at the electrical storage device;
Figure FDA00035112722600000812
and
Figure FDA00035112722600000813
represents an upper limit and a lower limit of charging power of the electric storage device, respectively;
Figure FDA00035112722600000814
and
Figure FDA00035112722600000815
respectively representing an upper limit and a lower limit of discharge power of the electric storage device;
Figure FDA00035112722600000816
andW i Erepresents an upper limit and a lower limit of stored electric energy of the electric storage device, respectively; Δ t represents a scheduled time interval.
15. The utility model provides an interconnection comprehensive energy network scheduling device based on P2P transaction mode, a serial communication port, the device is applied to interconnection comprehensive energy network system, wherein, interconnection comprehensive energy network system includes a plurality of sub electric heat networks, sub electric heat network includes electric power network, heating power network, distributed generator set, wind turbine generator system, cogeneration unit, heat pump, power storage device and heat-retaining device at least, connect and adopt P2P transaction mode to trade through soft switch between the sub electric heat network, the device includes:
the establishing module is used for establishing an operation model of the interconnected comprehensive energy network system based on the P2P transaction mode, wherein the operation model comprises operation costs of each sub electric heating network, and the operation costs comprise a higher-level electric power network purchase electric energy cost, a distributed generator set operation cost, a cogeneration unit operation cost and a peer electric heating network purchase electric energy cost;
and the processing module is used for carrying out distributed solving on the operation model to obtain a first electric energy quantity related to the purchase electric energy cost of the superior power network, active power output by the distributed generator set related to the operation cost of the distributed generator set, natural gas power input by the cogeneration set related to the operation cost of the cogeneration set and a second electric energy quantity related to the purchase electric energy cost of the same-level electric heating networks, so that the operation cost of each sub-electric heating network and the operation cost of the interconnected comprehensive energy network system are the lowest.
16. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor executes the program to implement the method for scheduling interconnected integrated energy networks based on P2P transaction patterns according to any one of claims 1 to 14.
17. A non-transitory computer readable storage medium having a computer program stored thereon, wherein the computer program when executed by a processor implements the method for scheduling interconnected integrated energy networks based on P2P transaction patterns according to any one of claims 1 to 14.
18. A computer program product comprising a computer program, wherein the computer program when executed by a processor implements the method for interconnected integrated energy networks based on P2P transaction patterns according to any one of claims 1 to 14.
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