CN114077934A - Comprehensive energy microgrid interconnection system and scheduling method thereof - Google Patents

Comprehensive energy microgrid interconnection system and scheduling method thereof Download PDF

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CN114077934A
CN114077934A CN202210058626.2A CN202210058626A CN114077934A CN 114077934 A CN114077934 A CN 114077934A CN 202210058626 A CN202210058626 A CN 202210058626A CN 114077934 A CN114077934 A CN 114077934A
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CN114077934B (en
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桑子夏
方仍存
雷何
杨东俊
詹智红
赵红生
郑旭
颜炯
侯婷婷
杨洁
王娅镭
陈竹
王琪鑫
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Economic and Technological Research Institute of State Grid Hubei Electric Power Co Ltd
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Abstract

A scheduling method of an integrated energy microgrid interconnection system comprises the following steps: s1, acquiring parameter information of the comprehensive energy microgrid interconnection system; s2, establishing an energy coupling equipment model, wherein the energy coupling equipment model comprises a combined heat and power system model, a gas boiler model, an electric gas conversion equipment model, an electric boiler model and an energy storage equipment model, and the combined heat and power system model comprises a gas turbine model and a waste heat boiler model; s3, establishing an energy router model; s4, establishing a unified steady-state power flow model of the electric power, thermal power and natural gas system; s5, establishing an optimized scheduling model of the comprehensive energy microgrid interconnection system; and S6, solving the optimized scheduling model of the comprehensive energy microgrid interconnection system to obtain an optimal scheduling strategy. The design improves the energy efficiency utilization level of the system, thereby improving the environmental benefit and the economic benefit of the comprehensive energy microgrid.

Description

Comprehensive energy microgrid interconnection system and scheduling method thereof
Technical Field
The invention relates to the technical field of energy, in particular to an integrated energy microgrid interconnection system and a scheduling method thereof, which are mainly suitable for improving the energy efficiency utilization level.
Background
With the development of energy crisis, distributed energy such as photovoltaic and wind power is widely concerned, and the distributed energy cannot be applied on a large scale due to the defects of decentralization, intermittence, volatility and the like. Traditionally, energy management systems such as electric energy, heat energy and natural gas are mutually independent, interaction does not exist among various energy sources, the comprehensive utilization rate of the energy sources is low, the condition of energy abandonment is easy to occur, and then the concept of an energy internet is provided. The energy internet is a novel energy utilization system for realizing safe, efficient and coordinated sharing by closely coupling energy and information, can flexibly and efficiently utilize various energy sources, relieves the energy crisis, and simultaneously conforms to the low-carbon, green and sustainable development concept. The energy router is used as important equipment in an energy internet, is a plug-in capable of controlling energy transmission and distribution and regulating and controlling energy, integrates the modern power electronic technology and the information communication technology, integrates a power electronic transformer, an energy converter, distributed energy, an energy storage device, a load, an information acquisition and transmission device and the like, and extends the characteristics of peer-to-peer opening, plug-and-play and open interconnection in the field of information networks.
With the diversification and distribution trend of energy demand, the interconnection of multiple energy systems becomes an important development direction of energy internet. In all aspects of energy production, transmission, storage, utilization and the like, the method of interconnection integration, cooperative scheduling and flexible configuration is required to be considered to analyze the whole energy system, so that energy interconnection is enhanced, and the necessary trend of development of a future energy system is formed by promoting the cooperative optimization and complementation of various energy sources. In the prior energy system, planning and design are mostly carried out independently, and the correlation among various energy systems is ignored; in the energy system considering energy coupling, the optimized operation and energy management aiming at a single comprehensive energy system are more realized, the interconnection and intercommunication of the comprehensive energy systems under multiple regions are not considered, and the characteristic mining on the energy Internet is insufficient.
In summary, currently, researches on the collaborative operation optimization of a plurality of comprehensive energy systems in the energy internet are few, and under the background of the rapid development of related researches on the energy internet, the energy management strategy of the comprehensive energy microgrid interconnection system has important research values and application prospects.
Disclosure of Invention
The invention aims to overcome the defects and problems of low energy efficiency utilization level in the prior art, and provides a comprehensive energy microgrid interconnection system with high energy efficiency utilization level and a scheduling method thereof.
In order to achieve the above purpose, the technical solution of the invention is as follows: a scheduling method of an integrated energy microgrid interconnection system comprises the following steps:
s1, acquiring parameter information of the comprehensive energy microgrid interconnection system;
s2, establishing an energy coupling equipment model, wherein the energy coupling equipment model comprises a combined heat and power system model, a gas boiler model, an electric gas conversion equipment model, an electric boiler model and an energy storage equipment model, and the combined heat and power system model comprises a gas turbine model and a waste heat boiler model;
s3, establishing an energy router model;
s4, establishing a unified steady-state power flow model of the electric power, thermal power and natural gas system;
s5, establishing an optimized scheduling model of the comprehensive energy microgrid interconnection system;
and S6, solving the optimized scheduling model of the comprehensive energy microgrid interconnection system to obtain an optimal scheduling strategy.
In step S1, the parameter information includes an energy coupling device parameter, an energy router parameter, a sub-energy system parameter inside the microgrid, interconnection topology information, economic cost information, carbon emission information, safe operation constraint information, and various microgrid load information.
In step S2, the gas turbine model is:
Figure DEST_PATH_IMAGE001
Figure 563961DEST_PATH_IMAGE002
in the formula (I), the compound is shown in the specification,
Figure DEST_PATH_IMAGE003
in order to achieve the power generation efficiency of the gas turbine,
Figure 746681DEST_PATH_IMAGE004
in order to achieve the waste heat recovery efficiency of the gas turbine,
Figure DEST_PATH_IMAGE005
for the recovery of power from the exhaust waste heat of the gas turbine,
Figure 854314DEST_PATH_IMAGE006
is the power generated by the gas turbine,
Figure DEST_PATH_IMAGE007
for operating time internal combustionThe amount of natural gas consumed by the gas turbine,
Figure 46261DEST_PATH_IMAGE008
is the heat value of natural gas;
the waste heat boiler model is as follows:
Figure DEST_PATH_IMAGE009
in the formula (I), the compound is shown in the specification,
Figure 689994DEST_PATH_IMAGE010
is the output power of the waste heat boiler,
Figure DEST_PATH_IMAGE011
for the recovery of power from the exhaust waste heat of the gas turbine,
Figure 574774DEST_PATH_IMAGE012
the heat conversion efficiency of the waste heat boiler is obtained;
the gas boiler model is as follows:
Figure DEST_PATH_IMAGE013
in the formula (I), the compound is shown in the specification,
Figure 107386DEST_PATH_IMAGE014
is the thermal power of the gas-fired boiler,
Figure DEST_PATH_IMAGE015
is a gas boiler
Figure 195035DEST_PATH_IMAGE016
The amount of gas consumed in the time period,
Figure DEST_PATH_IMAGE017
the heat efficiency of the gas boiler;
the electric gas conversion equipment model is as follows:
Figure 129492DEST_PATH_IMAGE018
in the formula (I), the compound is shown in the specification,
Figure DEST_PATH_IMAGE019
is the natural gas production of an electric gas-to-gas plant,
Figure 716332DEST_PATH_IMAGE020
in order for the electric power conversion equipment to consume electric power,
Figure DEST_PATH_IMAGE021
in order to improve the working efficiency of the electric gas conversion equipment,
Figure 798557DEST_PATH_IMAGE022
in order to be the energy conversion factor,
Figure DEST_PATH_IMAGE023
a high calorific value;
the electric boiler model is as follows:
Figure 801148DEST_PATH_IMAGE024
in the formula (I), the compound is shown in the specification,
Figure DEST_PATH_IMAGE025
for the output heating power of the electric boiler,
Figure 153894DEST_PATH_IMAGE026
is the input electrical power for the electrical refrigerator,
Figure DEST_PATH_IMAGE027
the energy efficiency ratio of the electric refrigerator;
the energy storage equipment model is as follows:
Figure 646056DEST_PATH_IMAGE028
in the formula (I), the compound is shown in the specification,
Figure DEST_PATH_IMAGE029
for energy storage devices in
Figure 153260DEST_PATH_IMAGE030
The amount of energy stored over a period of time,
Figure DEST_PATH_IMAGE031
is composed of
Figure 756280DEST_PATH_IMAGE030
Time period to
Figure 134172DEST_PATH_IMAGE032
The time interval of the time period is,
Figure DEST_PATH_IMAGE033
is composed of
Figure 30190DEST_PATH_IMAGE030
The power stored in the energy storage device is used for a period of time,
Figure 555849DEST_PATH_IMAGE034
in order to achieve the energy storage efficiency of the energy storage device,
Figure DEST_PATH_IMAGE035
is composed of
Figure 900243DEST_PATH_IMAGE030
The power that is discharged in a time period,
Figure 929379DEST_PATH_IMAGE036
the energy coefficient of the energy loss or self-loss of the energy storage device to the environment,
Figure DEST_PATH_IMAGE037
the discharging efficiency of the energy storage device is improved.
In step S3, the energy router model is:
Figure 28922DEST_PATH_IMAGE038
Figure DEST_PATH_IMAGE039
in the formula (I), the compound is shown in the specification,
Figure 245140DEST_PATH_IMAGE040
is an input matrix of the energy router,
Figure DEST_PATH_IMAGE041
is a translation and transmission matrix of the energy router,
Figure 957006DEST_PATH_IMAGE042
is the output matrix of the energy router,
Figure DEST_PATH_IMAGE043
and
Figure 371807DEST_PATH_IMAGE044
are respectively the first
Figure DEST_PATH_IMAGE045
Output and input of seed energy, off-diagonal elements
Figure 579934DEST_PATH_IMAGE046
As a source of energy
Figure DEST_PATH_IMAGE047
And energy source
Figure 345765DEST_PATH_IMAGE048
Coefficient of conversion between, diagonal elements
Figure DEST_PATH_IMAGE049
Is the same energy source
Figure 31961DEST_PATH_IMAGE047
Distribution and loss factor of (2);
Figure 35689DEST_PATH_IMAGE050
Figure DEST_PATH_IMAGE051
in the formula (I), the compound is shown in the specification,
Figure 975570DEST_PATH_IMAGE052
and
Figure DEST_PATH_IMAGE053
the distribution coefficient, the sum of the distribution coefficients of the same energy sources is 1,
Figure 166380DEST_PATH_IMAGE054
；
Figure DEST_PATH_IMAGE055
coupling the conversion efficiency of the equipment for energy;
Figure 718584DEST_PATH_IMAGE056
the transmission loss coefficient between the same energy sources.
In step S4, the unified steady-state power flow model of the power, thermal and natural gas system includes:
the thermodynamic system model is as follows:
Figure DEST_PATH_IMAGE057
Figure 45660DEST_PATH_IMAGE058
in the formula (I), the compound is shown in the specification,
Figure DEST_PATH_IMAGE059
is a node
Figure 392328DEST_PATH_IMAGE060
The heat source at the location supplies thermal power or the thermal load demands thermal power,
Figure DEST_PATH_IMAGE061
the specific heat capacity of the hot water is,
Figure 634216DEST_PATH_IMAGE062
for flowing out of heat sources or into heat load nodes
Figure 396635DEST_PATH_IMAGE060
The quality of the water flow of (a),
Figure DEST_PATH_IMAGE063
is the output heat power of the waste heat boiler,
Figure 640535DEST_PATH_IMAGE064
is the output thermal power of the gas-fired boiler,
Figure DEST_PATH_IMAGE065
is used for outputting the thermal power of the electric boiler,
Figure 158104DEST_PATH_IMAGE066
is the thermal power of the thermal energy port of the energy router,
Figure DEST_PATH_IMAGE067
in order to be the thermal load power,
Figure 323506DEST_PATH_IMAGE068
is a node
Figure 686354DEST_PATH_IMAGE060
The temperature at which hot water flows out of the heat source or into the heat load,
Figure DEST_PATH_IMAGE069
is a node
Figure 548875DEST_PATH_IMAGE060
The temperature at which the hot water flows into the heat source or out of the heat load;
the loss of thermal energy in the thermal conduit transmission is described by the drop in temperature of the water stream in the conduit:
Figure 643870DEST_PATH_IMAGE070
in the formula (I), the compound is shown in the specification,
Figure DEST_PATH_IMAGE071
、
Figure 358885DEST_PATH_IMAGE072
、
Figure DEST_PATH_IMAGE073
are respectively pipelines
Figure 791003DEST_PATH_IMAGE074
The ambient temperature, the head end temperature, the tail end temperature,
Figure DEST_PATH_IMAGE075
、
Figure 947178DEST_PATH_IMAGE076
、
Figure DEST_PATH_IMAGE077
are respectively pipelines
Figure 308014DEST_PATH_IMAGE074
Heat transfer coefficient, pipe length, mass flow rate;
at the junction of the pipelines, the hot water meets the law of conservation of energy, and the inflow and outflow relations at the junction of the nodes are as follows:
Figure 713588DEST_PATH_IMAGE078
Figure DEST_PATH_IMAGE079
Figure 152659DEST_PATH_IMAGE080
in the formula (I), the compound is shown in the specification,
Figure DEST_PATH_IMAGE081
、
Figure 491237DEST_PATH_IMAGE082
are respectively inflow nodes
Figure 990351DEST_PATH_IMAGE060
The temperature and the mass flow of the hot water at the tail end of the pipeline,
Figure DEST_PATH_IMAGE083
、
Figure 352063DEST_PATH_IMAGE084
are respectively outflow nodes
Figure 860404DEST_PATH_IMAGE060
The temperature and mass flow of the hot water at the beginning of the pipeline;
the natural gas system model is as follows:
Figure DEST_PATH_IMAGE085
in the formula (I), the compound is shown in the specification,
Figure 286444DEST_PATH_IMAGE086
、
Figure DEST_PATH_IMAGE087
、
Figure 690881DEST_PATH_IMAGE088
、
Figure DEST_PATH_IMAGE089
respectively is natural gas flow, pipeline characteristic parameters, natural gas flow direction variable and pressure intensity; subscript
Figure 602205DEST_PATH_IMAGE090
、
Figure DEST_PATH_IMAGE091
、
Figure 914237DEST_PATH_IMAGE092
Respectively a pipeline head end node, a pipeline tail end node and a pipeline;
the compressor model is as follows:
Figure DEST_PATH_IMAGE093
in the formula (I), the compound is shown in the specification,
Figure 463293DEST_PATH_IMAGE094
a pressure generated for the compressor;
Figure DEST_PATH_IMAGE095
、
Figure 38631DEST_PATH_IMAGE096
、
Figure DEST_PATH_IMAGE097
respectively a compressor characteristic parameter, a compressor consumed flow and a compressor factor related parameter; subscript
Figure 171672DEST_PATH_IMAGE098
Is a compressor;
Figure DEST_PATH_IMAGE099
、
Figure 552974DEST_PATH_IMAGE100
、
Figure DEST_PATH_IMAGE101
is a compressor consumption characteristic curve parameter;
nodes in the natural gas system satisfy the law of conservation of flow, namely:
Figure 891290DEST_PATH_IMAGE102
in the formula (I), the compound is shown in the specification,
Figure DEST_PATH_IMAGE103
in order to purchase the gas quantity,
Figure 463960DEST_PATH_IMAGE104
for connecting to nodes of distribution network
Figure 943352DEST_PATH_IMAGE060
The set of devices of (a) is,
Figure DEST_PATH_IMAGE105
in the gas distribution network
Figure 98652DEST_PATH_IMAGE060
A set of branch end nodes that are head-end nodes,
Figure 324097DEST_PATH_IMAGE106
in the gas distribution network
Figure 365871DEST_PATH_IMAGE060
Is a set of branch head-end nodes of the end node,
Figure DEST_PATH_IMAGE107
for flowing into end nodes
Figure 473504DEST_PATH_IMAGE060
The amount of the natural gas of (a),
Figure 921845DEST_PATH_IMAGE108
to flow into the head-end node
Figure 1796DEST_PATH_IMAGE060
The amount of the natural gas of (a),
Figure DEST_PATH_IMAGE109
is composed of
Figure 152155DEST_PATH_IMAGE030
Time interval gas load
Figure 950347DEST_PATH_IMAGE110
The predicted value of (a) is determined,
Figure DEST_PATH_IMAGE111
、
Figure 414826DEST_PATH_IMAGE112
、
Figure DEST_PATH_IMAGE113
are respectively as
Figure 146022DEST_PATH_IMAGE030
The natural gas consumption of the gas turbine, the natural gas consumption of the gas boiler and the natural gas generation amount of the electric gas conversion equipment in a time interval;
the power system model is as follows:
Figure 437588DEST_PATH_IMAGE114
in the formula (I), the compound is shown in the specification,
Figure DEST_PATH_IMAGE115
、
Figure 457496DEST_PATH_IMAGE116
、
Figure DEST_PATH_IMAGE117
are respectively nodes
Figure 522404DEST_PATH_IMAGE118
To a node
Figure DEST_PATH_IMAGE119
Branch circuit
Figure 311369DEST_PATH_IMAGE120
Active power, reactive power, current;
Figure DEST_PATH_IMAGE121
and
Figure 69109DEST_PATH_IMAGE122
are respectively a sectionDot
Figure 576314DEST_PATH_IMAGE119
To a node
Figure 851438DEST_PATH_IMAGE118
Branch circuit
Figure DEST_PATH_IMAGE123
Active power and reactive power of;
Figure 55761DEST_PATH_IMAGE124
and
Figure DEST_PATH_IMAGE125
are respectively a branch
Figure 718823DEST_PATH_IMAGE120
Resistance and reactance of (d);
Figure 182165DEST_PATH_IMAGE126
and
Figure DEST_PATH_IMAGE127
are respectively nodes
Figure 588876DEST_PATH_IMAGE118
And node
Figure 618012DEST_PATH_IMAGE119
Voltage of (d);
Figure 655238DEST_PATH_IMAGE128
and
Figure DEST_PATH_IMAGE129
respectively the active power and the reactive power of the power supporting equipment in the microgrid;
Figure 638500DEST_PATH_IMAGE130
and
Figure DEST_PATH_IMAGE131
are respectively a littleActive power and reactive power of loads inside the network;
Figure 848901DEST_PATH_IMAGE132
and
Figure DEST_PATH_IMAGE133
respectively generating active power and reactive power for the combined heat and power system;
Figure 466964DEST_PATH_IMAGE134
and
Figure DEST_PATH_IMAGE135
respectively the active power and the reactive power consumed by the electric gas conversion equipment;
Figure 737409DEST_PATH_IMAGE136
and
Figure DEST_PATH_IMAGE137
respectively the active power and the reactive power consumed by the electric boiler;
Figure 237660DEST_PATH_IMAGE138
indicating the starting point of the branch as
Figure 392698DEST_PATH_IMAGE118
End point is
Figure 894961DEST_PATH_IMAGE119
。
In step S5, the objective function of the integrated energy microgrid interconnection system optimization scheduling model is to minimize the operating cost of the system, as follows:
Figure DEST_PATH_IMAGE139
in the formula (I), the compound is shown in the specification,
Figure 70728DEST_PATH_IMAGE140
in order to achieve the cost of gas purchase,
Figure DEST_PATH_IMAGE141
in order to achieve the cost of electricity purchase,
Figure 58275DEST_PATH_IMAGE142
in order to achieve the cost of heat supply,
Figure DEST_PATH_IMAGE143
in order to reduce the cost of operating and maintaining the energy coupling equipment,
Figure 344900DEST_PATH_IMAGE144
in order to reduce the cost of the energy network,
Figure DEST_PATH_IMAGE145
punishing cost for wind and light abandonment;
cost of gas purchase
Figure 937555DEST_PATH_IMAGE140
Comprises the following steps:
Figure 254530DEST_PATH_IMAGE146
in the formula (I), the compound is shown in the specification,
Figure DEST_PATH_IMAGE147
in order to be the price of the natural gas,
Figure 994952DEST_PATH_IMAGE148
is as follows
Figure DEST_PATH_IMAGE149
The gas purchasing quantity of a natural gas plant;
cost of electricity purchase
Figure 819689DEST_PATH_IMAGE141
Comprises the following steps:
Figure 735692DEST_PATH_IMAGE150
in the formula (I), the compound is shown in the specification,
Figure DEST_PATH_IMAGE151
the price of the electricity is the price of the electricity,
Figure 253261DEST_PATH_IMAGE152
is as follows
Figure 949822DEST_PATH_IMAGE149
The electricity purchasing power of the electric power equipment is planted;
cost of heat supply
Figure 545626DEST_PATH_IMAGE142
Comprises the following steps:
Figure DEST_PATH_IMAGE153
in the formula (I), the compound is shown in the specification,
Figure 847295DEST_PATH_IMAGE154
in order to provide the heat at a price,
Figure DEST_PATH_IMAGE155
is as follows
Figure 801344DEST_PATH_IMAGE149
Thermal power requirements of the seed thermal device;
operating and maintaining cost of energy coupling equipment
Figure 719621DEST_PATH_IMAGE143
Comprises the following steps:
Figure 558264DEST_PATH_IMAGE156
in the formula (I), the compound is shown in the specification,
Figure DEST_PATH_IMAGE157
is as follows
Figure 776756DEST_PATH_IMAGE149
The coefficient of the maintenance cost of the equipment is determined,
Figure 370549DEST_PATH_IMAGE158
is as follows
Figure 12008DEST_PATH_IMAGE149
Power of the energy source coupling device;
energy network loss cost
Figure 919921DEST_PATH_IMAGE144
Comprises the following steps:
Figure DEST_PATH_IMAGE159
in the formula (I), the compound is shown in the specification,
Figure 258498DEST_PATH_IMAGE160
is the loss of the network of the natural gas,
Figure DEST_PATH_IMAGE161
in order to be a loss of the network of electric power,
Figure 288771DEST_PATH_IMAGE162
network losses for thermal energy;
wind and light abandoning punishment cost
Figure 119324DEST_PATH_IMAGE145
Comprises the following steps:
Figure DEST_PATH_IMAGE163
in the formula (I), the compound is shown in the specification,
Figure 893245DEST_PATH_IMAGE164
in order to discard the wind power,
Figure DEST_PATH_IMAGE165
to discard the optical power.
In the step S5, the constraint conditions of the integrated energy microgrid interconnection system optimized scheduling model include energy coupling device operation constraints, integrated energy microgrid system operation constraints and power balance constraints;
(1) energy coupling device operational constraints
The power constraints of the energy coupling device are:
Figure 289591DEST_PATH_IMAGE166
in the formula (I), the compound is shown in the specification,
Figure 458142DEST_PATH_IMAGE149
is as follows
Figure 572729DEST_PATH_IMAGE149
The energy source-like coupling device is connected with the power supply,
Figure DEST_PATH_IMAGE167
is as follows
Figure 150341DEST_PATH_IMAGE149
Energy-like coupling device
Figure 870035DEST_PATH_IMAGE168
The power of the time period is,
Figure DEST_PATH_IMAGE169
in order to be the lower limit of the power,
Figure 507690DEST_PATH_IMAGE170
is the upper power limit;
for energy storage devices, the capacity constraint is:
Figure DEST_PATH_IMAGE171
in the formula (I), the compound is shown in the specification,
Figure 640731DEST_PATH_IMAGE172
for energy storage devices in
Figure 428558DEST_PATH_IMAGE030
The amount of energy stored over a period of time,
Figure DEST_PATH_IMAGE173
for the lower limit of the capacity of the energy storage device,
Figure 97699DEST_PATH_IMAGE174
is the upper limit of the capacity of the energy storage equipment;
(2) operation constraint of comprehensive energy micro-grid interconnection system
The operating constraints of the thermodynamic system are:
Figure DEST_PATH_IMAGE175
in the formula (I), the compound is shown in the specification,
Figure 640676DEST_PATH_IMAGE176
and
Figure DEST_PATH_IMAGE177
the lower limit and the upper limit of the temperature of the hot water for supplying water to the node are respectively,
Figure 198696DEST_PATH_IMAGE178
and
Figure DEST_PATH_IMAGE179
respectively is the lower limit and the upper limit of the temperature of the node return water hot water,
Figure 383690DEST_PATH_IMAGE180
and
Figure DEST_PATH_IMAGE181
respectively is the lower limit and the upper limit of the mass flow of the thermal power pipeline;
the operating constraints of a natural gas system are:
Figure 343556DEST_PATH_IMAGE182
in the formula (I), the compound is shown in the specification,
Figure DEST_PATH_IMAGE183
and
Figure 821548DEST_PATH_IMAGE184
respectively the lower limit and the upper limit of the node pressure,
Figure DEST_PATH_IMAGE185
and
Figure 132444DEST_PATH_IMAGE186
respectively the lower limit and the upper limit of the natural gas flow of the pipeline,
Figure DEST_PATH_IMAGE187
and
Figure 589970DEST_PATH_IMAGE188
the lower limit and the upper limit of the compression ratio of the compressor are respectively;
the operating constraints of the power system are:
Figure DEST_PATH_IMAGE189
Figure 466659DEST_PATH_IMAGE190
in the formula (I), the compound is shown in the specification,
Figure DEST_PATH_IMAGE191
and
Figure 820280DEST_PATH_IMAGE192
are respectively nodes
Figure 119937DEST_PATH_IMAGE118
The lower and upper limits of the voltage are,
Figure DEST_PATH_IMAGE193
is a branch
Figure 646733DEST_PATH_IMAGE194
Upper limit of current value of (1).
In step S6, an improved quantum-behaved particle swarm optimization is used to solve the optimized scheduling model of the integrated energy microgrid interconnection system, and the solving step is:
(1) inputting initial data;
(2) initializing a particle population according to the probability amplitude of the qubit;
(3) solving the electricity, heat and gas comprehensive power flow in each microgrid, judging whether the optimized scheduling has a solution or not, and if not, setting a fitness function value to be infinite; otherwise, storing the solution;
(4) calculating a fitness function value;
(5) checking whether the iteration times reach an upper limit, and if so, outputting an optimal scheduling strategy; otherwise, updating the particles and returning to the step (3).
In step S6, the quantum-behaved particle swarm optimization is improved as follows:
(1) particle encoding
The improved quantum particle swarm algorithm adopts the probability amplitude of the quantum bit as the current position code of the particle, and the formula is as follows:
Figure DEST_PATH_IMAGE195
in the formula (I), the compound is shown in the specification,
Figure 643508DEST_PATH_IMAGE196
is as follows
Figure DEST_PATH_IMAGE197
A particle position;
Figure 168030DEST_PATH_IMAGE045
is the solution space dimension;
Figure 453518DEST_PATH_IMAGE198
and
Figure DEST_PATH_IMAGE199
are respectively the first
Figure 16961DEST_PATH_IMAGE197
A particle of
Figure 274767DEST_PATH_IMAGE045
The cosine position and the sine position corresponding to the dimension are maintained;
converting two unit space positions of particles into solution space sine positions of optimization problem
Figure 970190DEST_PATH_IMAGE200
And cosine position
Figure DEST_PATH_IMAGE201
The conversion formula is as follows:
Figure 539712DEST_PATH_IMAGE202
in the formula (I), the compound is shown in the specification,
Figure DEST_PATH_IMAGE203
and
Figure 345994DEST_PATH_IMAGE204
are respectively quantum of
Figure 255044DEST_PATH_IMAGE048
Maximum and minimum values for each position;
(2) particle location update
Updating the preferred position with the quantum behavioral position update equation, and returning
Figure DEST_PATH_IMAGE205
Value, thereby constituting an updated second
Figure 685151DEST_PATH_IMAGE197
The sine position and the cosine position of each particle form a new generation
Figure 679652DEST_PATH_IMAGE197
Encoding the current position of each particle; the position update equation is as follows:
Figure 758466DEST_PATH_IMAGE206
Figure DEST_PATH_IMAGE207
Figure 318760DEST_PATH_IMAGE208
Figure DEST_PATH_IMAGE209
in the formula (I), the compound is shown in the specification,
Figure 152724DEST_PATH_IMAGE197
the number is given to the current particle,
Figure 103363DEST_PATH_IMAGE168
is as follows
Figure 517026DEST_PATH_IMAGE168
The number of sub-iterations is,
Figure 666248DEST_PATH_IMAGE210
and
Figure DEST_PATH_IMAGE211
respectively as the particle individual optimal position and the population global optimal position,
Figure 107331DEST_PATH_IMAGE212
and
Figure DEST_PATH_IMAGE213
are all made of
Figure 404321DEST_PATH_IMAGE214
The random number of (2) is greater than,
Figure DEST_PATH_IMAGE215
the size of the population is the number of cells,
Figure 356096DEST_PATH_IMAGE216
is the average value of the optimal positions of all particle individuals in the population,
Figure DEST_PATH_IMAGE217
is a contraction-expansion factor.
The comprehensive energy microgrid interconnection system comprises a comprehensive energy microgrid and an energy router, wherein the comprehensive energy microgrid comprises an electric power network, a heat network, a natural gas network, a combined heat and power system, an electric heating boiler, a gas boiler and electric gas conversion equipment, the electric power network is connected with the heat network through the electric heating boiler, the electric power network is connected with the natural gas network through the electric gas conversion equipment, the electric power network is connected with the natural gas network and the heat network through the combined heat and power system, the natural gas network is connected with the heat network through the gas boiler, the combined heat and power system comprises a gas turbine and a waste heat boiler, the comprehensive energy microgrids are mutually connected through energy, the energy router comprises an electric energy port, a heat energy port, a gas port, an electric energy conversion power module, an energy conversion power module and a control center, and the control center is respectively connected with the electric energy conversion power module, the energy router, The energy conversion power module is connected.
Compared with the prior art, the invention has the beneficial effects that:
in the comprehensive energy microgrid interconnection system and the scheduling method thereof, the power, heat and natural gas system is cooperatively scheduled by strengthening the coupling complementary relationship between different energy flow forms such as electricity, heat and gas in the microgrid and between the microgrid, so that the multi-energy coordination complementary benefit potential can be exerted, the economy, low carbon and flexibility of the interconnection system are improved, and the capability of resource optimization configuration is improved; the interconnection of the electric and thermal gas systems provides more flexibility for operation scheduling, and distributed optimization realizes coordinated optimization scheduling considering all areas, balance low carbon and economic targets. Therefore, the invention improves the energy efficiency utilization level of the system, thereby improving the environmental benefit and the economic benefit of the comprehensive energy microgrid.
Drawings
Fig. 1 is a flowchart of a scheduling method of the integrated energy microgrid interconnection system according to the present invention.
Fig. 2 is a schematic structural diagram of the integrated energy microgrid interconnection system.
FIG. 3 is a schematic diagram of an energy router according to the present invention.
Fig. 4 is a schematic diagram of the electrical/thermal/gas energy conversion of the present invention.
Fig. 5 is a schematic diagram of a solving process of the optimization scheduling model of the integrated energy microgrid interconnection system in the invention.
Detailed Description
The present invention will be described in further detail with reference to the following description and embodiments in conjunction with the accompanying drawings.
Referring to fig. 1, a scheduling method of an integrated energy microgrid interconnection system includes the following steps:
s1, acquiring parameter information of the comprehensive energy microgrid interconnection system;
the parameter information comprises energy coupling equipment parameters, energy router parameters, energy subsystem parameters in the micro-grid, interconnection topological structure information, economic cost information, carbon emission information, safe operation constraint information and various micro-grid load information;
s2, establishing an energy coupling equipment model, wherein the energy coupling equipment model comprises a combined heat and power system model, a gas boiler model, an electric gas conversion equipment model, an electric boiler model and an energy storage equipment model, and the combined heat and power system model comprises a gas turbine model and a waste heat boiler model;
the gas turbine model is as follows:
Figure 890983DEST_PATH_IMAGE001
Figure 738853DEST_PATH_IMAGE002
in the formula (I), the compound is shown in the specification,
Figure 195242DEST_PATH_IMAGE003
in order to achieve the power generation efficiency of the gas turbine,
Figure 717752DEST_PATH_IMAGE004
in order to achieve the waste heat recovery efficiency of the gas turbine,
Figure 575987DEST_PATH_IMAGE005
for the recovery of power from the exhaust waste heat of the gas turbine,
Figure 594759DEST_PATH_IMAGE006
is the power generated by the gas turbine,
Figure 272865DEST_PATH_IMAGE007
the amount of natural gas consumed by the gas turbine for runtime;
Figure 97601DEST_PATH_IMAGE008
for the heat value of natural gas, generally 9.7kW multiplied by h/m is taken3；
The exhaust-heat boiler collects the exhaust heat generated by the gas turbine, the output power is related to the efficiency of the exhaust-heat boiler, and the exhaust-heat boiler model is as follows:
Figure 810342DEST_PATH_IMAGE009
in the formula (I), the compound is shown in the specification,
Figure 15DEST_PATH_IMAGE010
is the output power of the waste heat boiler,
Figure 430996DEST_PATH_IMAGE011
for the recovery of power from the exhaust waste heat of the gas turbine,
Figure 793845DEST_PATH_IMAGE012
the heat conversion efficiency of the waste heat boiler is obtained;
the heat quantity generated by the gas boiler is related to the boiler efficiency and the fuel quantity, and the gas boiler model is as follows:
Figure 361092DEST_PATH_IMAGE013
in the formula (I), the compound is shown in the specification,
Figure 721666DEST_PATH_IMAGE014
is the thermal power of the gas-fired boiler,
Figure 896337DEST_PATH_IMAGE015
is a gas boiler
Figure 797297DEST_PATH_IMAGE016
The amount of gas consumed in the time period,
Figure 750210DEST_PATH_IMAGE017
the heat efficiency of the gas boiler;
the electric gas conversion equipment is regarded as a gas source in a natural gas network and regarded as a load in an electric power system, and the electric gas conversion equipment model is as follows:
Figure 78423DEST_PATH_IMAGE018
in the formula (I), the compound is shown in the specification,
Figure 421680DEST_PATH_IMAGE019
is the natural gas production of an electric gas-to-gas plant,
Figure 126330DEST_PATH_IMAGE020
in order for the electric power conversion equipment to consume electric power,
Figure 668170DEST_PATH_IMAGE021
the working efficiency of the electric gas conversion equipment is improved;
Figure 167285DEST_PATH_IMAGE022
for the energy conversion coefficient, it is usually taken as
Figure 997837DEST_PATH_IMAGE218
；
Figure 506179DEST_PATH_IMAGE023
At a high calorific value, the value is taken
Figure DEST_PATH_IMAGE219
；
The heating power provided by the electric boiler is related to the input electric power and the energy efficiency ratio, and the electric boiler model is as follows:
Figure 403990DEST_PATH_IMAGE024
in the formula (I), the compound is shown in the specification,
Figure 74006DEST_PATH_IMAGE025
for the output heating power of the electric boiler,
Figure 188592DEST_PATH_IMAGE026
is the input electrical power for the electrical refrigerator,
Figure 235046DEST_PATH_IMAGE027
the energy efficiency ratio of the electric refrigerator;
the energy storage device comprises energy storage devices of various energy sources, including heat storage, electricity storage, gas storage devices and the like, and the energy storage device model is as follows:
Figure 751478DEST_PATH_IMAGE028
in the formula (I), the compound is shown in the specification,
Figure 795657DEST_PATH_IMAGE029
for energy storage devices in
Figure 397540DEST_PATH_IMAGE030
The amount of energy stored over a period of time,
Figure 982105DEST_PATH_IMAGE031
is composed of
Figure 556306DEST_PATH_IMAGE030
Time period to
Figure 568124DEST_PATH_IMAGE032
Time interval of the period，
Figure 155838DEST_PATH_IMAGE033
Is composed of
Figure 544094DEST_PATH_IMAGE030
The power stored in the energy storage device is used for a period of time,
Figure 35118DEST_PATH_IMAGE034
in order to achieve the energy storage efficiency of the energy storage device,
Figure 421100DEST_PATH_IMAGE035
is composed of
Figure 997575DEST_PATH_IMAGE030
The power that is discharged in a time period,
Figure 923943DEST_PATH_IMAGE036
the energy coefficient of the energy loss or self-loss of the energy storage device to the environment,
Figure 472736DEST_PATH_IMAGE037
the discharging efficiency of the energy storage equipment is obtained; the energy storage device cannot store and release energy simultaneously within a certain time period;
s3, establishing an energy router model, wherein the energy router model comprises a transmission and conversion model of various energies;
as shown in fig. 3, the energy router uses a matrix to describe the energy flow characteristics in the energy router, and connects the input, conversion, and output of multiple energy sources together, so as to more intuitively embody energy interaction and coupling, and the energy router model is as follows:
Figure 826357DEST_PATH_IMAGE038
Figure 624548DEST_PATH_IMAGE039
in the formula (I), the compound is shown in the specification,
Figure 620186DEST_PATH_IMAGE040
is an input matrix of the energy router,
Figure 321688DEST_PATH_IMAGE041
is a translation and transmission matrix of the energy router,
Figure 49473DEST_PATH_IMAGE042
is the output matrix of the energy router,
Figure 334961DEST_PATH_IMAGE043
and
Figure 134290DEST_PATH_IMAGE044
are respectively the first
Figure 188833DEST_PATH_IMAGE045
Seed energy source output and input; off diagonal elements
Figure 87519DEST_PATH_IMAGE046
As a source of energy
Figure 860303DEST_PATH_IMAGE047
And energy source
Figure 197743DEST_PATH_IMAGE048
The conversion coefficient mainly comprises an energy distribution coefficient and the efficiency of energy elements, wherein the distribution coefficient is that the input energy is distributed to different energy conversion devices in proportion; diagonal line element
Figure 106794DEST_PATH_IMAGE049
Is the same energy source
Figure 441960DEST_PATH_IMAGE047
Distribution and loss factor of (2);
Figure 436461DEST_PATH_IMAGE050
Figure 76127DEST_PATH_IMAGE051
in the formula (I), the compound is shown in the specification,
Figure 839684DEST_PATH_IMAGE052
and
Figure 345752DEST_PATH_IMAGE053
the distribution coefficient, the sum of the distribution coefficients of the same energy sources is 1,
Figure 827549DEST_PATH_IMAGE054
；
Figure 506792DEST_PATH_IMAGE055
coupling the conversion efficiency of the equipment for energy;
Figure 390434DEST_PATH_IMAGE056
the transmission loss coefficient between the same energy sources;
s4, establishing a unified steady-state power flow model of the electric power, thermal power and natural gas system;
the unified steady-state power flow model of the electric power, thermal power and natural gas system comprises the following steps:
the thermodynamic system generally comprises a heat source, a heat supply network and a heat load, the heat energy transmitted or consumed by the thermodynamic system is determined by the flow rate and the temperature of water, and the thermodynamic system model is as follows:
Figure 67403DEST_PATH_IMAGE057
Figure 36496DEST_PATH_IMAGE058
in the formula (I), the compound is shown in the specification,
Figure 253851DEST_PATH_IMAGE059
is a node
Figure 257579DEST_PATH_IMAGE060
Heat source ofSupplying thermal power or thermal load demand thermal power,
Figure 403652DEST_PATH_IMAGE061
the specific heat capacity of the hot water is,
Figure 63303DEST_PATH_IMAGE062
for flowing out of heat sources or into heat load nodes
Figure 818769DEST_PATH_IMAGE060
The quality of the water flow of (a),
Figure 942583DEST_PATH_IMAGE063
is the output heat power of the waste heat boiler,
Figure 492513DEST_PATH_IMAGE064
is the output thermal power of the gas-fired boiler,
Figure 436199DEST_PATH_IMAGE065
is used for outputting the thermal power of the electric boiler,
Figure 198618DEST_PATH_IMAGE066
is the thermal power of the thermal energy port of the energy router,
Figure 911359DEST_PATH_IMAGE067
in order to be the thermal load power,
Figure 163349DEST_PATH_IMAGE068
is a node
Figure 328751DEST_PATH_IMAGE060
The temperature at which hot water flows out of the heat source or into the heat load,
Figure 629282DEST_PATH_IMAGE069
is a node
Figure 960644DEST_PATH_IMAGE060
The temperature at which the hot water flows into the heat source or out of the heat load;
the loss of thermal energy in the thermal conduit transmission is described by the drop in temperature of the water stream in the conduit:
Figure 383536DEST_PATH_IMAGE070
in the formula (I), the compound is shown in the specification,
Figure 36234DEST_PATH_IMAGE071
、
Figure 140456DEST_PATH_IMAGE072
、
Figure 827789DEST_PATH_IMAGE073
are respectively pipelines
Figure 421582DEST_PATH_IMAGE074
The ambient temperature, the head end temperature, the tail end temperature,
Figure 561576DEST_PATH_IMAGE075
、
Figure 203910DEST_PATH_IMAGE076
、
Figure 745750DEST_PATH_IMAGE077
are respectively pipelines
Figure 510443DEST_PATH_IMAGE074
Heat transfer coefficient, pipe length, mass flow rate;
at the junction of the pipelines, the hot water meets the law of conservation of energy, and the inflow and outflow relations at the junction of the nodes are as follows:
Figure 639199DEST_PATH_IMAGE078
Figure 85223DEST_PATH_IMAGE079
Figure 481570DEST_PATH_IMAGE080
in the formula, due to the inflow node
Figure 417165DEST_PATH_IMAGE060
Different pipelines have different water flow quality and temperature, and the slave node
Figure 531751DEST_PATH_IMAGE060
The temperature of the water flow flowing out is the same,
Figure 578205DEST_PATH_IMAGE081
、
Figure 32320DEST_PATH_IMAGE082
are respectively inflow nodes
Figure 873237DEST_PATH_IMAGE060
The temperature and the mass flow of the hot water at the tail end of the pipeline,
Figure 740699DEST_PATH_IMAGE083
、
Figure 528526DEST_PATH_IMAGE084
are respectively outflow nodes
Figure 899465DEST_PATH_IMAGE060
The temperature and mass flow of the hot water at the beginning of the pipeline;
the natural gas system mainly comprises a natural gas pipeline, a pressurizing station, a gas load, a regulating valve and the like; can realize the control to the natural gas line gas flow effectively through adjusting air-vent valve etc. and the natural gas line gas flow is closely related with the pressure and the pipeline transmission condition of pipeline both sides node, and the natural gas system model is:
Figure 409818DEST_PATH_IMAGE085
in the formula (I), the compound is shown in the specification,
Figure 764576DEST_PATH_IMAGE086
、
Figure 887253DEST_PATH_IMAGE087
、
Figure 315960DEST_PATH_IMAGE088
、
Figure 764259DEST_PATH_IMAGE089
respectively is natural gas flow, pipeline characteristic parameters, natural gas flow direction variable and pressure intensity; subscript
Figure 340734DEST_PATH_IMAGE090
、
Figure 267102DEST_PATH_IMAGE091
、
Figure 815895DEST_PATH_IMAGE092
Respectively a pipeline head end node, a pipeline tail end node and a pipeline; when in use
Figure 169515DEST_PATH_IMAGE220
When the temperature of the water is higher than the set temperature,
Figure DEST_PATH_IMAGE221
(ii) a If not, then,
Figure 265910DEST_PATH_IMAGE222
；
the pressurization station comprises gas turbine, engine and compressor, offsets the pressure that consumes in the transportation process through the natural gas pressurization in to the pipeline, and gas turbine draws the natural gas from the filling station and provides required electric energy for compressor work, and the compressor model is:
Figure 199231DEST_PATH_IMAGE093
in the formula (I), the compound is shown in the specification,
Figure 399268DEST_PATH_IMAGE094
a pressure generated for the compressor;
Figure 189369DEST_PATH_IMAGE095
、
Figure 474857DEST_PATH_IMAGE096
、
Figure 946290DEST_PATH_IMAGE097
respectively a compressor characteristic parameter, a compressor consumed flow and a compressor factor related parameter; subscript
Figure 833DEST_PATH_IMAGE098
Is a compressor;
Figure 227415DEST_PATH_IMAGE099
、
Figure 199DEST_PATH_IMAGE100
、
Figure 9744DEST_PATH_IMAGE101
is a compressor consumption characteristic curve parameter;
nodes in the natural gas system satisfy the law of conservation of flow, namely:
Figure DEST_PATH_IMAGE223
in the formula (I), the compound is shown in the specification,
Figure 479646DEST_PATH_IMAGE103
in order to purchase the gas quantity,
Figure 345971DEST_PATH_IMAGE104
for connecting to nodes of distribution network
Figure 809313DEST_PATH_IMAGE060
The set of devices of (a) is,
Figure 419286DEST_PATH_IMAGE105
in the gas distribution network
Figure 714001DEST_PATH_IMAGE060
A set of branch end nodes that are head-end nodes,
Figure 16806DEST_PATH_IMAGE106
in the gas distribution network
Figure 498603DEST_PATH_IMAGE060
Is a set of branch head-end nodes of the end node,
Figure 115530DEST_PATH_IMAGE107
for flowing into end nodes
Figure 999172DEST_PATH_IMAGE060
The amount of the natural gas of (a),
Figure 738458DEST_PATH_IMAGE108
to flow into the head-end node
Figure 209016DEST_PATH_IMAGE060
The amount of the natural gas of (a),
Figure 364053DEST_PATH_IMAGE109
is composed of
Figure 367782DEST_PATH_IMAGE030
Time interval gas load
Figure 277969DEST_PATH_IMAGE110
The predicted value of (a) is determined,
Figure 999937DEST_PATH_IMAGE111
、
Figure 20983DEST_PATH_IMAGE112
、
Figure 613638DEST_PATH_IMAGE113
are respectively as
Figure 632410DEST_PATH_IMAGE030
The natural gas consumption of the gas turbine, the natural gas consumption of the gas boiler and the natural gas generation amount of the electric gas conversion equipment in a time interval;
the electric power system adopts a DistFlow power flow model of an alternating-current power distribution network, and the electric power system model is as follows:
Figure 605789DEST_PATH_IMAGE114
in the formula (I), the compound is shown in the specification,
Figure 430525DEST_PATH_IMAGE115
、
Figure 143266DEST_PATH_IMAGE116
、
Figure 67360DEST_PATH_IMAGE117
are respectively nodes
Figure 498341DEST_PATH_IMAGE118
To a node
Figure 861189DEST_PATH_IMAGE119
Branch circuit
Figure 694016DEST_PATH_IMAGE120
Active power, reactive power, current;
Figure 789011DEST_PATH_IMAGE121
and
Figure 707289DEST_PATH_IMAGE122
are respectively nodes
Figure 873828DEST_PATH_IMAGE119
To a node
Figure 797047DEST_PATH_IMAGE118
Branch circuit
Figure 328522DEST_PATH_IMAGE123
Active power and reactive power of;
Figure 468516DEST_PATH_IMAGE124
and
Figure 173167DEST_PATH_IMAGE125
are respectively a branch
Figure 980586DEST_PATH_IMAGE120
Resistance and reactance of (d);
Figure 479701DEST_PATH_IMAGE126
and
Figure 106991DEST_PATH_IMAGE127
are respectively nodes
Figure 553016DEST_PATH_IMAGE118
And node
Figure 949362DEST_PATH_IMAGE119
Voltage of (d);
Figure 884957DEST_PATH_IMAGE128
and
Figure 498079DEST_PATH_IMAGE129
respectively the active power and the reactive power of the power supporting equipment in the microgrid;
Figure 278953DEST_PATH_IMAGE130
and
Figure 998647DEST_PATH_IMAGE131
respectively the active power and the reactive power of the internal load of the microgrid;
Figure 839564DEST_PATH_IMAGE132
and
Figure 707026DEST_PATH_IMAGE133
are respectively provided withActive power and reactive power generated by the combined heat and power system;
Figure 291591DEST_PATH_IMAGE134
and
Figure 865792DEST_PATH_IMAGE135
respectively the active power and the reactive power consumed by the electric gas conversion equipment;
Figure 877611DEST_PATH_IMAGE136
and
Figure 701210DEST_PATH_IMAGE137
respectively the active power and the reactive power consumed by the electric boiler;
Figure 355045DEST_PATH_IMAGE138
indicating the starting point of the branch as
Figure 81955DEST_PATH_IMAGE118
End point is
Figure 467937DEST_PATH_IMAGE119
With reference direction of power as starting point
Figure 44412DEST_PATH_IMAGE118
To the end point
Figure 236359DEST_PATH_IMAGE119
；
S5, establishing an optimized scheduling model of the comprehensive energy microgrid interconnection system;
the objective function of the optimization scheduling model of the comprehensive energy microgrid interconnection system is the operation cost of the minimized system, and the following formula is adopted:
Figure 316310DEST_PATH_IMAGE139
in the formula (I), the compound is shown in the specification,
Figure 138773DEST_PATH_IMAGE140
in order to achieve the cost of gas purchase,
Figure 936965DEST_PATH_IMAGE141
in order to achieve the cost of electricity purchase,
Figure 932602DEST_PATH_IMAGE142
in order to achieve the cost of heat supply,
Figure 867060DEST_PATH_IMAGE143
in order to reduce the cost of operating and maintaining the energy coupling equipment,
Figure 860424DEST_PATH_IMAGE144
in order to reduce the cost of the energy network,
Figure 145912DEST_PATH_IMAGE145
punishing cost for wind and light abandonment;
cost of gas purchase
Figure 936055DEST_PATH_IMAGE140
Comprises the following steps:
Figure 256178DEST_PATH_IMAGE146
in the formula (I), the compound is shown in the specification,
Figure 217181DEST_PATH_IMAGE147
in order to be the price of the natural gas,
Figure 927648DEST_PATH_IMAGE148
is as follows
Figure 999509DEST_PATH_IMAGE149
The gas purchasing quantity of a natural gas plant;
cost of electricity purchase
Figure 439717DEST_PATH_IMAGE141
Comprises the following steps:
Figure 509305DEST_PATH_IMAGE150
in the formula (I), the compound is shown in the specification,
Figure 769385DEST_PATH_IMAGE151
the price of the electricity is the price of the electricity,
Figure 379358DEST_PATH_IMAGE152
is as follows
Figure 674073DEST_PATH_IMAGE149
The electricity purchasing power of the electric power equipment is planted;
cost of heat supply
Figure 212764DEST_PATH_IMAGE142
Comprises the following steps:
Figure 163402DEST_PATH_IMAGE153
in the formula (I), the compound is shown in the specification,
Figure 577066DEST_PATH_IMAGE154
in order to provide the heat at a price,
Figure 726288DEST_PATH_IMAGE155
is as follows
Figure 199994DEST_PATH_IMAGE149
Thermal power requirements of the seed thermal device;
operating and maintaining cost of energy coupling equipment
Figure 169087DEST_PATH_IMAGE143
Comprises the following steps:
Figure 324125DEST_PATH_IMAGE156
in the formula (I), the compound is shown in the specification,
Figure 593432DEST_PATH_IMAGE157
is as follows
Figure 972461DEST_PATH_IMAGE149
A seed equipment maintenance cost coefficient;
Figure 632113DEST_PATH_IMAGE158
is as follows
Figure 387579DEST_PATH_IMAGE149
The power of the energy coupling equipment comprises electric gas conversion equipment, a combined heat and power system, a gas boiler, an electric boiler and an energy router;
energy network loss cost
Figure 744349DEST_PATH_IMAGE144
Comprises the following steps:
Figure 825437DEST_PATH_IMAGE159
in the formula (I), the compound is shown in the specification,
Figure 769122DEST_PATH_IMAGE160
is the loss of the network of the natural gas,
Figure 265963DEST_PATH_IMAGE161
in order to be a loss of the network of electric power,
Figure 244283DEST_PATH_IMAGE162
network losses for thermal energy;
wind and light abandoning punishment cost
Figure 230694DEST_PATH_IMAGE145
Comprises the following steps:
Figure 864937DEST_PATH_IMAGE163
in the formula (I), the compound is shown in the specification,
Figure 962206DEST_PATH_IMAGE164
in order to discard the wind power,
Figure 795033DEST_PATH_IMAGE165
the optical power is abandoned;
the constraint conditions of the optimization scheduling model of the comprehensive energy microgrid interconnection system comprise energy coupling equipment operation constraint, comprehensive energy microgrid system operation constraint and power balance constraint;
(1) energy coupling device operational constraints
The energy coupling equipment comprises a gas turbine, a waste heat boiler, a gas boiler, electric gas conversion equipment, an electric heating boiler and energy storage equipment, and the operation constraint of the energy coupling equipment mainly comprises the following power constraint of the energy coupling equipment:
Figure 952345DEST_PATH_IMAGE166
in the formula (I), the compound is shown in the specification,
Figure 73885DEST_PATH_IMAGE149
is as follows
Figure 210730DEST_PATH_IMAGE149
The energy source-like coupling device is connected with the power supply,
Figure 22697DEST_PATH_IMAGE167
is as follows
Figure 616490DEST_PATH_IMAGE149
Energy-like coupling device
Figure 756484DEST_PATH_IMAGE168
The power of the time period is,
Figure 664397DEST_PATH_IMAGE169
in order to be the lower limit of the power,
Figure 704772DEST_PATH_IMAGE170
is the upper power limit;
for energy storage devices, the capacity constraint is:
Figure 203887DEST_PATH_IMAGE171
in the formula (I), the compound is shown in the specification,
Figure 96756DEST_PATH_IMAGE172
for energy storage devices in
Figure 73940DEST_PATH_IMAGE030
The amount of energy stored over a period of time,
Figure 735865DEST_PATH_IMAGE173
for the lower limit of the capacity of the energy storage device,
Figure 609143DEST_PATH_IMAGE174
is the upper limit of the capacity of the energy storage equipment;
(2) operation constraint of comprehensive energy micro-grid interconnection system
The operating constraints of the thermodynamic system are:
Figure 723730DEST_PATH_IMAGE175
in the formula (I), the compound is shown in the specification,
Figure 504604DEST_PATH_IMAGE176
and
Figure 286615DEST_PATH_IMAGE177
the lower limit and the upper limit of the temperature of the hot water for supplying water to the node are respectively,
Figure 628997DEST_PATH_IMAGE178
and
Figure 434142DEST_PATH_IMAGE179
respectively is the lower limit and the upper limit of the temperature of the node return water hot water,
Figure 284286DEST_PATH_IMAGE180
and
Figure 655225DEST_PATH_IMAGE181
respectively is the lower limit and the upper limit of the mass flow of the thermal power pipeline;
the operating constraints of a natural gas system are:
Figure 667043DEST_PATH_IMAGE182
in the formula (I), the compound is shown in the specification,
Figure 693905DEST_PATH_IMAGE183
and
Figure 82161DEST_PATH_IMAGE184
respectively the lower limit and the upper limit of the node pressure,
Figure 573185DEST_PATH_IMAGE185
and
Figure 755905DEST_PATH_IMAGE186
respectively the lower limit and the upper limit of the natural gas flow of the pipeline,
Figure 535642DEST_PATH_IMAGE187
and
Figure 462010DEST_PATH_IMAGE188
the lower limit and the upper limit of the compression ratio of the compressor are respectively;
the operating constraints of the power system are:
Figure 40496DEST_PATH_IMAGE189
Figure 925276DEST_PATH_IMAGE190
in the formula (I), the compound is shown in the specification,
Figure 926730DEST_PATH_IMAGE191
and
Figure 391209DEST_PATH_IMAGE192
are respectively nodes
Figure 856826DEST_PATH_IMAGE118
Lower limit of voltageAnd an upper limit of the number of the units,
Figure 381348DEST_PATH_IMAGE193
is a branch
Figure 666836DEST_PATH_IMAGE194
Upper limit of current value of (1);
s6, solving the optimized scheduling model of the comprehensive energy microgrid interconnection system to obtain the output of the energy coupling equipment and the power of each port of the energy router, so as to obtain an optimal scheduling strategy;
referring to fig. 5, the optimized scheduling model of the integrated energy microgrid interconnection system is solved by using an improved quantum particle swarm algorithm, and the solving steps are as follows:
(1) inputting initial data; the method comprises the steps of calculating the power price, the gas price and the heat price, the network structures of a power network, a heating power network and a natural gas network, original parameters and operation constraints, and photovoltaic and wind power day-ahead predicted output data in the micro-grid;
(2) initializing a particle population according to the probability amplitude of the qubit; the system comprises electric gas conversion equipment, an electric boiler, a combined heat and power system, a gas boiler and power of each port of an energy router;
(3) solving the electricity, heat and gas comprehensive power flow in each microgrid, judging whether the optimized scheduling has a solution or not, and if not, setting a fitness function value to be infinite; otherwise, storing the solution;
(4) calculating a fitness function value;
(5) checking whether the iteration times reach an upper limit, and if so, outputting an optimal scheduling strategy; otherwise, updating the particles and returning to the step (3).
The quantum particle swarm algorithm is improved as follows:
(1) particle encoding
The improved quantum particle swarm algorithm adopts the probability amplitude of the quantum bit as the current position code of the particle, and the formula is as follows:
Figure 200585DEST_PATH_IMAGE195
in the formula (I), the compound is shown in the specification,
Figure 458391DEST_PATH_IMAGE196
is as follows
Figure 153815DEST_PATH_IMAGE197
A particle position;
Figure 693643DEST_PATH_IMAGE045
is the solution space dimension;
Figure 765504DEST_PATH_IMAGE198
and
Figure 877816DEST_PATH_IMAGE199
are respectively the first
Figure 9720DEST_PATH_IMAGE197
A particle of
Figure 269800DEST_PATH_IMAGE045
Cosine position and sine position corresponding to dimension, the cosine position and the sine position respectively corresponding to quantum state
Figure 145353DEST_PATH_IMAGE224
And
Figure DEST_PATH_IMAGE225
the probability amplitude of (c); the current positions of the particles are coded in such a way, so that one particle can simultaneously represent two states, and the convergence rate of the algorithm can be accelerated and the search accuracy of the algorithm can be improved corresponding to the positions of two solution spaces;
converting two unit space positions of particles into solution space sine positions of optimization problem
Figure 908909DEST_PATH_IMAGE200
And cosine position
Figure 211715DEST_PATH_IMAGE201
The conversion formula is as follows:
Figure 959091DEST_PATH_IMAGE202
in the formula (I), the compound is shown in the specification,
Figure 576017DEST_PATH_IMAGE203
and
Figure 958194DEST_PATH_IMAGE204
are respectively quantum of
Figure 166322DEST_PATH_IMAGE048
Location (for optimization problem the first
Figure 400994DEST_PATH_IMAGE048
Variables) maximum and minimum values;
(2) particle location update
Updating the preferred position with the quantum behavioral position update equation, and returning
Figure 618349DEST_PATH_IMAGE205
Value, thereby constituting an updated second
Figure 559760DEST_PATH_IMAGE197
The sine position and the cosine position of each particle form a new generation
Figure 469947DEST_PATH_IMAGE197
Encoding the current position of each particle; the position update equation is as follows:
Figure 926336DEST_PATH_IMAGE206
Figure 681803DEST_PATH_IMAGE207
Figure 743300DEST_PATH_IMAGE208
Figure 558809DEST_PATH_IMAGE209
in the formula (I), the compound is shown in the specification,
Figure 3959DEST_PATH_IMAGE197
the number is given to the current particle,
Figure 563116DEST_PATH_IMAGE168
is as follows
Figure 479120DEST_PATH_IMAGE168
The number of sub-iterations is,
Figure 465530DEST_PATH_IMAGE210
and
Figure 162091DEST_PATH_IMAGE211
respectively as the particle individual optimal position and the population global optimal position,
Figure 259360DEST_PATH_IMAGE212
and
Figure 29870DEST_PATH_IMAGE213
are all made of
Figure 187182DEST_PATH_IMAGE214
The random number of (2) is greater than,
Figure 105459DEST_PATH_IMAGE215
the size of the population is the number of cells,
Figure 6419DEST_PATH_IMAGE216
the average value of the optimal positions of all particle individuals in the population is obtained;
Figure 897015DEST_PATH_IMAGE217
for the contraction-expansion factor, the reduction is generally linear.
Referring to fig. 2, an integrated energy microgrid interconnection system comprises an integrated energy microgrid and an energy router, wherein the integrated energy microgrid comprises a power network, a thermal network, a natural gas network, a cogeneration system, an electric heating boiler, a gas boiler, an electric-to-gas device, electric-to-steam gas and other multi-energy loads, coupling relations among the devices are shown in fig. 4, the power network is connected with the thermal network through the electric heating boiler, the power network is connected with the natural gas network through the electric-to-gas device, the power network is connected with the natural gas network and the thermal network through the cogeneration system, the natural gas network is connected with the thermal network through the gas boiler, the cogeneration system comprises energy conversion devices such as a gas turbine and a waste heat boiler, and the integrated energy microgrids are connected with each other through the energy router; referring to fig. 3, the energy router includes an electric energy port, a thermal energy port, a gas port, an electric energy conversion power module, an energy conversion power module, and a management and control center, and the management and control center is connected to the electric energy conversion power module and the energy conversion power module, respectively. The energy router can acquire external information such as system parameters including load data, network structures and the like, has the functions of energy optimization, energy management, risk assessment, path optimization, perception protection, electrical measurement and the like, is applied to the energy internet, and can improve the conversion, transmission and utilization efficiency of energy.
The method comprises the steps of obtaining an equipment parameter aggregate, energy network structure parameters and multi-energy load data acquired in preset time duration of each energy equipment in any scheduling period of the comprehensive energy microgrid; and constructing an energy device dynamic efficiency model, an energy router energy transmission and conversion model and a multi-energy flow network steady-state power flow model, and further constructing an environment-friendly economic system operation model to obtain an optimal scheduling scheme.
The invention constructs a collaborative optimization mathematical model of a regional distributed energy Internet topological structure, equipment configuration and operation strategy, thereby improving the comprehensive energy utilization efficiency of the system. The method comprises the steps of optimizing and scheduling in the microgrid and optimizing and scheduling among the microgrids; the optimized scheduling for the interior of the microgrid comprises the output of the energy coupling equipment, so that the energy optimization for the interior of the microgrid can be ensured; the dispatching among the micro-grids comprises that the power, heat and natural gas systems of different micro-grids realize energy conversion and transmission through the energy router, so that energy complementation of different areas is realized, the operation cost of the whole interconnection system is further reduced, and the economic benefit and the environmental benefit are improved.

Claims (10)

1. A scheduling method of an integrated energy microgrid interconnection system is characterized by comprising the following steps:
s1, acquiring parameter information of the comprehensive energy microgrid interconnection system;
s2, establishing an energy coupling equipment model, wherein the energy coupling equipment model comprises a combined heat and power system model, a gas boiler model, an electric gas conversion equipment model, an electric boiler model and an energy storage equipment model, and the combined heat and power system model comprises a gas turbine model and a waste heat boiler model;
s3, establishing an energy router model;
s4, establishing a unified steady-state power flow model of the electric power, thermal power and natural gas system;
s5, establishing an optimized scheduling model of the comprehensive energy microgrid interconnection system;
and S6, solving the optimized scheduling model of the comprehensive energy microgrid interconnection system to obtain an optimal scheduling strategy.
2. The scheduling method of the integrated energy microgrid interconnection system according to claim 1, characterized in that: in step S1, the parameter information includes an energy coupling device parameter, an energy router parameter, a sub-energy system parameter inside the microgrid, interconnection topology information, economic cost information, carbon emission information, safe operation constraint information, and various microgrid load information.
3. The scheduling method of the integrated energy microgrid interconnection system according to claim 1, characterized in that:
in step S2, the gas turbine model is:
Figure DEST_PATH_IMAGE002
Figure DEST_PATH_IMAGE004
in the formula (I), the compound is shown in the specification,
Figure DEST_PATH_IMAGE006
in order to achieve the power generation efficiency of the gas turbine,
Figure DEST_PATH_IMAGE008
in order to achieve the waste heat recovery efficiency of the gas turbine,
Figure DEST_PATH_IMAGE010
for the recovery of power from the exhaust waste heat of the gas turbine,
Figure DEST_PATH_IMAGE012
is the power generated by the gas turbine,
Figure DEST_PATH_IMAGE014
for the amount of natural gas consumed by the gas turbine during operation,
Figure DEST_PATH_IMAGE016
is the heat value of natural gas;
the waste heat boiler model is as follows:
Figure DEST_PATH_IMAGE018
in the formula (I), the compound is shown in the specification,
Figure DEST_PATH_IMAGE020
is the output power of the waste heat boiler,
Figure DEST_PATH_IMAGE022
for the recovery of power from the exhaust waste heat of the gas turbine,
Figure DEST_PATH_IMAGE024
the heat conversion efficiency of the waste heat boiler is obtained;
the gas boiler model is as follows:
Figure DEST_PATH_IMAGE026
in the formula (I), the compound is shown in the specification,
Figure DEST_PATH_IMAGE028
is the thermal power of the gas-fired boiler,
Figure DEST_PATH_IMAGE030
is a gas boiler
Figure DEST_PATH_IMAGE032
The amount of gas consumed in the time period,
Figure DEST_PATH_IMAGE034
the heat efficiency of the gas boiler;
the electric gas conversion equipment model is as follows:
Figure DEST_PATH_IMAGE036
in the formula (I), the compound is shown in the specification,
Figure DEST_PATH_IMAGE038
is the natural gas production of an electric gas-to-gas plant,
Figure DEST_PATH_IMAGE040
in order for the electric power conversion equipment to consume electric power,
Figure DEST_PATH_IMAGE042
in order to improve the working efficiency of the electric gas conversion equipment,
Figure DEST_PATH_IMAGE044
in order to be the energy conversion factor,
Figure DEST_PATH_IMAGE046
a high calorific value;
the electric boiler model is as follows:
Figure DEST_PATH_IMAGE048
in the formula (I), the compound is shown in the specification,
Figure DEST_PATH_IMAGE050
for the output heating power of the electric boiler,
Figure DEST_PATH_IMAGE052
is the input electrical power for the electrical refrigerator,
Figure DEST_PATH_IMAGE054
the energy efficiency ratio of the electric refrigerator;
the energy storage equipment model is as follows:
Figure DEST_PATH_IMAGE056
in the formula (I), the compound is shown in the specification,
Figure DEST_PATH_IMAGE058
for energy storage devices in
Figure DEST_PATH_IMAGE060
The amount of energy stored over a period of time,
Figure DEST_PATH_IMAGE062
is composed of
Figure 530504DEST_PATH_IMAGE060
Time period to
Figure DEST_PATH_IMAGE064
The time interval of the time period is,
Figure DEST_PATH_IMAGE066
is composed of
Figure 938393DEST_PATH_IMAGE060
The power stored in the energy storage device is used for a period of time,
Figure DEST_PATH_IMAGE068
in order to achieve the energy storage efficiency of the energy storage device,
Figure DEST_PATH_IMAGE070
is composed of
Figure 529911DEST_PATH_IMAGE060
The power that is discharged in a time period,
Figure DEST_PATH_IMAGE072
the energy coefficient of the energy loss or self-loss of the energy storage device to the environment,
Figure DEST_PATH_IMAGE074
the discharging efficiency of the energy storage device is improved.
4. The scheduling method of the integrated energy microgrid interconnection system according to claim 1, characterized in that:
in step S3, the energy router model is:
Figure DEST_PATH_IMAGE076
Figure DEST_PATH_IMAGE078
in the formula (I), the compound is shown in the specification,
Figure DEST_PATH_IMAGE080
is an input matrix of the energy router,
Figure DEST_PATH_IMAGE082
is a translation and transmission matrix of the energy router,
Figure DEST_PATH_IMAGE084
is the output matrix of the energy router,
Figure DEST_PATH_IMAGE086
and
Figure DEST_PATH_IMAGE088
are respectively the first
Figure DEST_PATH_IMAGE090
Output and input of seed energy, off-diagonal elements
Figure DEST_PATH_IMAGE092
As a source of energy
Figure DEST_PATH_IMAGE094
And energy source
Figure DEST_PATH_IMAGE096
Coefficient of conversion between, diagonal elements
Figure DEST_PATH_IMAGE098
Is the same energy source
Figure 833985DEST_PATH_IMAGE094
Distribution and loss factor of (2);
Figure DEST_PATH_IMAGE100
Figure DEST_PATH_IMAGE102
in the formula (I), the compound is shown in the specification,
Figure DEST_PATH_IMAGE104
and
Figure DEST_PATH_IMAGE106
the distribution coefficient, the sum of the distribution coefficients of the same energy sources is 1,
Figure DEST_PATH_IMAGE108
；
Figure DEST_PATH_IMAGE110
coupling the conversion efficiency of the equipment for energy;
Figure DEST_PATH_IMAGE112
the transmission loss coefficient between the same energy sources.
5. The scheduling method of the integrated energy microgrid interconnection system according to claim 1, characterized in that:
in step S4, the unified steady-state power flow model of the power, thermal and natural gas system includes:
the thermodynamic system model is as follows:
Figure DEST_PATH_IMAGE114
Figure DEST_PATH_IMAGE116
in the formula (I), the compound is shown in the specification,
Figure DEST_PATH_IMAGE118
is a node
Figure DEST_PATH_IMAGE120
The heat source at the location supplies thermal power or the thermal load demands thermal power,
Figure DEST_PATH_IMAGE122
the specific heat capacity of the hot water is,
Figure DEST_PATH_IMAGE124
for flowing out of heat sources or into heat load nodes
Figure 859447DEST_PATH_IMAGE120
The quality of the water flow of (a),
Figure DEST_PATH_IMAGE126
is the output heat power of the waste heat boiler,
Figure DEST_PATH_IMAGE128
is the output thermal power of the gas-fired boiler,
Figure DEST_PATH_IMAGE130
is used for outputting the thermal power of the electric boiler,
Figure DEST_PATH_IMAGE132
is the thermal power of the thermal energy port of the energy router,
Figure DEST_PATH_IMAGE134
in order to be the thermal load power,
Figure DEST_PATH_IMAGE136
is a node
Figure 386987DEST_PATH_IMAGE120
The temperature at which hot water flows out of the heat source or into the heat load,
Figure DEST_PATH_IMAGE138
is a node
Figure 47776DEST_PATH_IMAGE120
The temperature at which the hot water flows into the heat source or out of the heat load;
the loss of thermal energy in the thermal conduit transmission is described by the drop in temperature of the water stream in the conduit:
Figure DEST_PATH_IMAGE140
in the formula (I), the compound is shown in the specification,
Figure DEST_PATH_IMAGE142
、
Figure DEST_PATH_IMAGE144
、
Figure DEST_PATH_IMAGE146
are respectively pipelines
Figure DEST_PATH_IMAGE148
The ambient temperature, the head end temperature, the tail end temperature,
Figure DEST_PATH_IMAGE150
、
Figure DEST_PATH_IMAGE152
、
Figure DEST_PATH_IMAGE154
are respectively pipelines
Figure 347301DEST_PATH_IMAGE148
Heat transfer coefficient, pipe length, mass flow rate;
at the junction of the pipelines, the hot water meets the law of conservation of energy, and the inflow and outflow relations at the junction of the nodes are as follows:
Figure DEST_PATH_IMAGE156
Figure DEST_PATH_IMAGE158
Figure DEST_PATH_IMAGE160
in the formula (I), the compound is shown in the specification,
Figure DEST_PATH_IMAGE162
、
Figure DEST_PATH_IMAGE164
are respectively inflow nodes
Figure 714304DEST_PATH_IMAGE120
The temperature and the mass flow of the hot water at the tail end of the pipeline,
Figure DEST_PATH_IMAGE166
、
Figure DEST_PATH_IMAGE168
are respectively outflow nodes
Figure 450179DEST_PATH_IMAGE120
The temperature and mass flow of the hot water at the beginning of the pipeline;
the natural gas system model is as follows:
Figure DEST_PATH_IMAGE170
in the formula (I), the compound is shown in the specification,
Figure DEST_PATH_IMAGE172
、
Figure DEST_PATH_IMAGE174
、
Figure DEST_PATH_IMAGE176
、
Figure DEST_PATH_IMAGE178
respectively is natural gas flow, pipeline characteristic parameters, natural gas flow direction variable and pressure intensity; subscript
Figure DEST_PATH_IMAGE180
、
Figure DEST_PATH_IMAGE182
、
Figure DEST_PATH_IMAGE184
Respectively a pipeline head end node, a pipeline tail end node and a pipeline;
the compressor model is as follows:
Figure DEST_PATH_IMAGE186
in the formula (I), the compound is shown in the specification,
Figure DEST_PATH_IMAGE188
a pressure generated for the compressor;
Figure DEST_PATH_IMAGE190
、
Figure DEST_PATH_IMAGE192
、
Figure DEST_PATH_IMAGE194
respectively a compressor characteristic parameter, a compressor consumed flow and a compressor factor related parameter; subscript
Figure DEST_PATH_IMAGE196
Is a compressor;
Figure DEST_PATH_IMAGE198
、
Figure DEST_PATH_IMAGE200
、
Figure DEST_PATH_IMAGE202
is a compressor consumption characteristic curve parameter;
nodes in the natural gas system satisfy the law of conservation of flow, namely:
Figure DEST_PATH_IMAGE204
in the formula (I), the compound is shown in the specification,
Figure DEST_PATH_IMAGE206
in order to purchase the gas quantity,
Figure DEST_PATH_IMAGE208
for connecting to nodes of distribution network
Figure 600144DEST_PATH_IMAGE120
The set of devices of (a) is,
Figure DEST_PATH_IMAGE210
in the gas distribution network
Figure 144389DEST_PATH_IMAGE120
A set of branch end nodes that are head-end nodes,
Figure DEST_PATH_IMAGE212
in the gas distribution network
Figure 91747DEST_PATH_IMAGE120
Is a set of branch head-end nodes of the end node,
Figure DEST_PATH_IMAGE214
for flowing into end nodes
Figure 49339DEST_PATH_IMAGE120
The amount of the natural gas of (a),
Figure DEST_PATH_IMAGE216
to flow into the head-end node
Figure 973302DEST_PATH_IMAGE120
The amount of the natural gas of (a),
Figure DEST_PATH_IMAGE218
is composed of
Figure 762266DEST_PATH_IMAGE060
Time interval gas load
Figure DEST_PATH_IMAGE220
The predicted value of (a) is determined,
Figure DEST_PATH_IMAGE222
、
Figure DEST_PATH_IMAGE224
、
Figure DEST_PATH_IMAGE226
are respectively as
Figure 487383DEST_PATH_IMAGE060
The natural gas consumption of the gas turbine, the natural gas consumption of the gas boiler and the natural gas generation amount of the electric gas conversion equipment in a time interval;
the power system model is as follows:
Figure DEST_PATH_IMAGE228
in the formula (I), the compound is shown in the specification,
Figure DEST_PATH_IMAGE230
、
Figure DEST_PATH_IMAGE232
、
Figure DEST_PATH_IMAGE234
are respectively nodes
Figure DEST_PATH_IMAGE236
To a node
Figure DEST_PATH_IMAGE238
Branch circuit
Figure DEST_PATH_IMAGE240
Active power, reactive power, current;
Figure DEST_PATH_IMAGE242
and
Figure DEST_PATH_IMAGE244
are respectively nodes
Figure 745320DEST_PATH_IMAGE238
To a node
Figure 20444DEST_PATH_IMAGE236
Branch circuit
Figure DEST_PATH_IMAGE246
Active power and reactive power of;
Figure DEST_PATH_IMAGE248
and
Figure DEST_PATH_IMAGE250
are respectively a branch
Figure 54128DEST_PATH_IMAGE240
Resistance and reactance of (d);
Figure DEST_PATH_IMAGE252
and
Figure DEST_PATH_IMAGE254
are respectively nodes
Figure 481305DEST_PATH_IMAGE236
And node
Figure 944647DEST_PATH_IMAGE238
Voltage of (d);
Figure DEST_PATH_IMAGE256
and
Figure DEST_PATH_IMAGE258
respectively the active power and the reactive power of the power supporting equipment in the microgrid;
Figure DEST_PATH_IMAGE260
and
Figure DEST_PATH_IMAGE262
respectively the active power and the reactive power of the internal load of the microgrid;
Figure DEST_PATH_IMAGE264
and
Figure DEST_PATH_IMAGE266
respectively generating active power and reactive power for the combined heat and power system;
Figure DEST_PATH_IMAGE268
and
Figure DEST_PATH_IMAGE270
are respectively electricityActive power and reactive power consumed by the gas transfer equipment;
Figure DEST_PATH_IMAGE272
and
Figure DEST_PATH_IMAGE274
respectively the active power and the reactive power consumed by the electric boiler;
Figure DEST_PATH_IMAGE276
indicating the starting point of the branch as
Figure 226724DEST_PATH_IMAGE236
End point is
Figure 255860DEST_PATH_IMAGE238
。
6. The scheduling method of the integrated energy microgrid interconnection system according to claim 1, characterized in that:
in step S5, the objective function of the integrated energy microgrid interconnection system optimization scheduling model is to minimize the operating cost of the system, as follows:
Figure DEST_PATH_IMAGE278
in the formula (I), the compound is shown in the specification,
Figure DEST_PATH_IMAGE280
in order to achieve the cost of gas purchase,
Figure DEST_PATH_IMAGE282
in order to achieve the cost of electricity purchase,
Figure DEST_PATH_IMAGE284
in order to achieve the cost of heat supply,
Figure DEST_PATH_IMAGE286
in order to reduce the cost of operating and maintaining the energy coupling equipment,
Figure DEST_PATH_IMAGE288
in order to reduce the cost of the energy network,
Figure DEST_PATH_IMAGE290
punishing cost for wind and light abandonment;
cost of gas purchase
Figure 322780DEST_PATH_IMAGE280
Comprises the following steps:
Figure DEST_PATH_IMAGE292
in the formula (I), the compound is shown in the specification,
Figure DEST_PATH_IMAGE294
in order to be the price of the natural gas,
Figure DEST_PATH_IMAGE296
is as follows
Figure DEST_PATH_IMAGE298
The gas purchasing quantity of a natural gas plant;
cost of electricity purchase
Figure 820888DEST_PATH_IMAGE282
Comprises the following steps:
Figure DEST_PATH_IMAGE300
in the formula (I), the compound is shown in the specification,
Figure DEST_PATH_IMAGE302
the price of the electricity is the price of the electricity,
Figure DEST_PATH_IMAGE304
is as follows
Figure 172235DEST_PATH_IMAGE298
The electricity purchasing power of the electric power equipment is planted;
cost of heat supply
Figure 180511DEST_PATH_IMAGE284
Comprises the following steps:
Figure DEST_PATH_IMAGE306
in the formula (I), the compound is shown in the specification,
Figure DEST_PATH_IMAGE308
in order to provide the heat at a price,
Figure DEST_PATH_IMAGE310
is as follows
Figure 326322DEST_PATH_IMAGE298
Thermal power requirements of the seed thermal device;
operating and maintaining cost of energy coupling equipment
Figure 942021DEST_PATH_IMAGE286
Comprises the following steps:
Figure DEST_PATH_IMAGE312
in the formula (I), the compound is shown in the specification,
Figure DEST_PATH_IMAGE314
is as follows
Figure 97059DEST_PATH_IMAGE298
The coefficient of the maintenance cost of the equipment is determined,
Figure DEST_PATH_IMAGE316
is as follows
Figure 959842DEST_PATH_IMAGE298
Power of the energy source coupling device;
energy network loss cost
Figure 604450DEST_PATH_IMAGE288
Comprises the following steps:
Figure DEST_PATH_IMAGE318
in the formula (I), the compound is shown in the specification,
Figure DEST_PATH_IMAGE320
is the loss of the network of the natural gas,
Figure DEST_PATH_IMAGE322
in order to be a loss of the network of electric power,
Figure DEST_PATH_IMAGE324
network losses for thermal energy;
wind and light abandoning punishment cost
Figure 155779DEST_PATH_IMAGE290
Comprises the following steps:
Figure DEST_PATH_IMAGE326
in the formula (I), the compound is shown in the specification,
Figure DEST_PATH_IMAGE328
in order to discard the wind power,
Figure DEST_PATH_IMAGE330
to discard the optical power.
7. The scheduling method of the integrated energy microgrid interconnection system according to claim 6, characterized in that:
in the step S5, the constraint conditions of the integrated energy microgrid interconnection system optimized scheduling model include energy coupling device operation constraints, integrated energy microgrid system operation constraints and power balance constraints;
(1) energy coupling device operational constraints
The power constraints of the energy coupling device are:
Figure DEST_PATH_IMAGE332
in the formula (I), the compound is shown in the specification,
Figure 504721DEST_PATH_IMAGE298
is as follows
Figure 566218DEST_PATH_IMAGE298
The energy source-like coupling device is connected with the power supply,
Figure DEST_PATH_IMAGE334
is as follows
Figure 788252DEST_PATH_IMAGE298
Energy-like coupling device
Figure DEST_PATH_IMAGE336
The power of the time period is,
Figure DEST_PATH_IMAGE338
in order to be the lower limit of the power,
Figure DEST_PATH_IMAGE340
is the upper power limit;
for energy storage devices, the capacity constraint is:
Figure DEST_PATH_IMAGE342
in the formula (I), the compound is shown in the specification,
Figure DEST_PATH_IMAGE344
for energy storage devices in
Figure 745319DEST_PATH_IMAGE060
The amount of energy stored over a period of time,
Figure DEST_PATH_IMAGE346
for the lower limit of the capacity of the energy storage device,
Figure DEST_PATH_IMAGE348
is the upper limit of the capacity of the energy storage equipment;
(2) operation constraint of comprehensive energy micro-grid interconnection system
The operating constraints of the thermodynamic system are:
Figure DEST_PATH_IMAGE350
in the formula (I), the compound is shown in the specification,
Figure DEST_PATH_IMAGE352
and
Figure DEST_PATH_IMAGE354
the lower limit and the upper limit of the temperature of the hot water for supplying water to the node are respectively,
Figure DEST_PATH_IMAGE356
and
Figure DEST_PATH_IMAGE358
respectively is the lower limit and the upper limit of the temperature of the node return water hot water,
Figure DEST_PATH_IMAGE360
and
Figure DEST_PATH_IMAGE362
respectively is the lower limit and the upper limit of the mass flow of the thermal power pipeline;
the operating constraints of a natural gas system are:
Figure DEST_PATH_IMAGE364
in the formula (I), the compound is shown in the specification,
Figure DEST_PATH_IMAGE366
and
Figure DEST_PATH_IMAGE368
respectively the lower limit and the upper limit of the node pressure,
Figure DEST_PATH_IMAGE370
and
Figure DEST_PATH_IMAGE372
respectively the lower limit and the upper limit of the natural gas flow of the pipeline,
Figure DEST_PATH_IMAGE374
and
Figure DEST_PATH_IMAGE376
the lower limit and the upper limit of the compression ratio of the compressor are respectively;
the operating constraints of the power system are:
Figure DEST_PATH_IMAGE378
Figure DEST_PATH_IMAGE380
in the formula (I), the compound is shown in the specification,
Figure DEST_PATH_IMAGE382
and
Figure DEST_PATH_IMAGE384
are respectively nodes
Figure 740694DEST_PATH_IMAGE236
The lower and upper limits of the voltage are,
Figure DEST_PATH_IMAGE386
is a branch
Figure DEST_PATH_IMAGE388
Upper limit of current value of (1).
8. The scheduling method of the integrated energy microgrid interconnection system according to claim 1, characterized in that:
in step S6, an improved quantum-behaved particle swarm optimization is used to solve the optimized scheduling model of the integrated energy microgrid interconnection system, and the solving step is:
(1) inputting initial data;
(2) initializing a particle population according to the probability amplitude of the qubit;
(3) solving the electricity, heat and gas comprehensive power flow in each microgrid, judging whether the optimized scheduling has a solution or not, and if not, setting a fitness function value to be infinite; otherwise, storing the solution;
(4) calculating a fitness function value;
(5) checking whether the iteration times reach an upper limit, and if so, outputting an optimal scheduling strategy; otherwise, updating the particles and returning to the step (3).
9. The scheduling method of the integrated energy microgrid interconnection system according to claim 8, characterized in that:
in step S6, the quantum-behaved particle swarm optimization is improved as follows:
(1) particle encoding
The improved quantum particle swarm algorithm adopts the probability amplitude of the quantum bit as the current position code of the particle, and the formula is as follows:
Figure DEST_PATH_IMAGE390
in the formula (I), the compound is shown in the specification,
Figure DEST_PATH_IMAGE392
is as follows
Figure DEST_PATH_IMAGE394
A particle position;
Figure 79534DEST_PATH_IMAGE090
is the solution space dimension;
Figure DEST_PATH_IMAGE396
and
Figure DEST_PATH_IMAGE398
are respectively the first
Figure 393841DEST_PATH_IMAGE394
A particle of
Figure 28084DEST_PATH_IMAGE090
The cosine position and the sine position corresponding to the dimension are maintained;
converting two unit space positions of particles into solution space sine positions of optimization problem
Figure DEST_PATH_IMAGE400
And cosine position
Figure DEST_PATH_IMAGE402
The conversion formula is as follows:
Figure DEST_PATH_IMAGE404
in the formula (I), the compound is shown in the specification,
Figure DEST_PATH_IMAGE406
and
Figure DEST_PATH_IMAGE408
are respectively quantum of
Figure 748522DEST_PATH_IMAGE096
Maximum and minimum values for each position;
(2) particle location update
Updating the preferred position with the quantum behavioral position update equation, and returning
Figure DEST_PATH_IMAGE410
Value, thereby constituting an updated second
Figure 987874DEST_PATH_IMAGE394
The sine position and the cosine position of each particle form a new generation
Figure 269819DEST_PATH_IMAGE394
Encoding the current position of each particle; the position update equation is as follows:
Figure DEST_PATH_IMAGE412
Figure DEST_PATH_IMAGE414
Figure DEST_PATH_IMAGE416
Figure DEST_PATH_IMAGE418
in the formula (I), the compound is shown in the specification,
Figure 17458DEST_PATH_IMAGE394
the number is given to the current particle,
Figure 652838DEST_PATH_IMAGE336
is as follows
Figure 215538DEST_PATH_IMAGE336
The number of sub-iterations is,
Figure DEST_PATH_IMAGE420
and
Figure DEST_PATH_IMAGE422
respectively as the particle individual optimal position and the population global optimal position,
Figure DEST_PATH_IMAGE424
and
Figure DEST_PATH_IMAGE426
are all made of
Figure DEST_PATH_IMAGE428
The random number of (2) is greater than,
Figure DEST_PATH_IMAGE430
the size of the population is the number of cells,
Figure DEST_PATH_IMAGE432
is the average value of the optimal positions of all particle individuals in the population,
Figure DEST_PATH_IMAGE434
is a contraction-expansion factor.
10. An integrated energy microgrid interconnection system, characterized in that the system uses the scheduling method as claimed in any one of claims 1 to 9, the system comprises an integrated energy microgrid and an energy router, the integrated energy microgrid comprises an electric power network, a heat power network, a natural gas network, a cogeneration system, an electric boiler, a gas boiler and an electric gas conversion device, the electric power network is connected with the heat power network through the electric boiler, the electric power network is connected with the natural gas network through the electric gas conversion device, the electric power network is connected with the natural gas network and the heat power network through the cogeneration system, the natural gas network is connected with the heat power network through the gas boiler, the cogeneration system comprises a gas turbine and a waste heat boiler, the integrated energy microgrid is connected with each other through the energy router, and the energy router comprises an electric energy port, a gas outlet, and a gas outlet, The system comprises a heat energy port, a gas port, an electric energy conversion power module, an energy conversion power module and a control center, wherein the control center is respectively connected with the electric energy conversion power module and the energy conversion power module.
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