CN112381335A - Operation optimization method and device for regional comprehensive energy system - Google Patents

Operation optimization method and device for regional comprehensive energy system Download PDF

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CN112381335A
CN112381335A CN202011431587.3A CN202011431587A CN112381335A CN 112381335 A CN112381335 A CN 112381335A CN 202011431587 A CN202011431587 A CN 202011431587A CN 112381335 A CN112381335 A CN 112381335A
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赵鹏翔
李振
王楠
周喜超
丛琳
李娜
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State Grid Comprehensive Energy Service Group Co ltd
State Grid Corp of China SGCC
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Abstract

The invention discloses a method and a device for optimizing the operation of a regional comprehensive energy system, wherein the method comprises the following steps: establishing an operation economic model of the comprehensive energy system based on the Stackelberg game; and solving by adopting a particle swarm algorithm according to the running economic model of the comprehensive energy system, and optimizing the running parameters of the energy system according to the solving result, so that the running optimization control of each device is facilitated. Meanwhile, the energy consumption is introduced to favor the energy consumption comfort level of cost quantification, so that the defect that the single interruptible load compensation cannot truly reflect the energy consumption characteristics of the user is overcome.

Description

Operation optimization method and device for regional comprehensive energy system
Technical Field
The invention belongs to the technical field of regional comprehensive energy scheduling, and particularly relates to a method and a device for optimizing the operation of a regional comprehensive energy system.
Background
In recent years, global fossil energy is exhausted, ecological environment is continuously deteriorated, and human beings face double pressure of environmental pollution, resource shortage and the like. The traditional single energy system cannot meet the development requirements of the modern society because of the defects of low comprehensive utilization rate of energy, serious pollution and the like. The comprehensive energy system can comprehensively plan various energy sources, carry out coordinated dispatching, fully exert the energy supply advantages of different energy sources and improve the comprehensive utilization efficiency of the energy sources. The regional Integrated Energy System (DIES) is based on the typical scene of the region, has more pertinence and specificity in service, has relatively uniform asset attribution, and can reasonably collect the fund and resource advantages of different main bodies and coordinate the benefits of all main bodies. But different principals do not decide on management and production management plans. Therefore, how to make a system-wide operation optimization scheduling strategy while fully considering the benefits of each main body is a difficult problem which needs to be solved urgently at present.
At present, the research focus in the aspect of comprehensive energy mainly lies in the aspects of complementary operation scheduling of an electricity, gas and heat multi-energy coupling system, flexibility improvement of 'source-network-load-storage' and the like. On the charge side, demand response is usually carried out in the form of real-time electricity price and time-of-use electricity price, and in recent years, related researches have been carried out to expand single electric energy demand response to electricity, gas and heat comprehensive demand response, so that the energy utilization efficiency is improved. In the aspect of a regional comprehensive energy system, a region comprises three main bodies of an energy supplier, a regional service provider and a regional user, and in order to analyze the transaction interaction process between an energy seller and a buyer in a market, a leader and a follower in a master-slave game model are generally adopted for analysis. In the form of a leader and followers, and in the form of a leader and followers.
In the DIES operation optimization research field, only electric energy transaction is considered at present when demand response is analyzed, flexibility of natural gas and heat energy supply is not considered, and game interaction between an energy supplier on a source side and a regional service provider is ignored. The flexibility of the source side is explored, source-load double-side interaction is realized, and certain problems still exist in the overall economy and the energy utilization rate of the system.
Disclosure of Invention
In view of this, the present invention aims to provide a method and a device for optimizing operation of a regional integrated energy system, so as to solve the technical problems in the prior art that optimization of a regional energy system lacks fusion of multiple energy sources and lacks overall economy of the system.
In order to achieve the purpose, the technical scheme of the invention is realized as follows:
in one aspect, an embodiment of the present invention provides a method for optimizing operation of a regional integrated energy system, including:
establishing an operation economic model of the comprehensive energy system based on the Stackelberg game;
solving by adopting a particle swarm algorithm according to the running economic model of the comprehensive energy system, and optimizing the running parameters of the energy system according to the solving result;
the method for establishing the operation economic model of the comprehensive energy system based on the Stackelberg game comprises the following steps:
establishing an operation economic model of an energy supplier based on a Stackelberg game;
establishing an operation economic model of a regional energy supplier based on a Stackelberg game;
establishing an operation economic model of the regional users based on the Stackelberg game;
the method for establishing the running economic model of the energy supplier based on the Stackelberg game comprises the following steps: respectively establishing an economic objective function and a constraint condition of the energy supplier, wherein the economic objective function of the energy supplier comprises the following steps:
Figure BDA0002824247500000031
in the formula, CESNet revenue for the energy provider; t is the total time period, N is the number of generator sets,
Figure BDA0002824247500000032
and
Figure BDA0002824247500000033
respectively representing the energy selling price and selling power of the generator set i and the gas distribution station of an energy supplier; c. CnetRepresenting the net charge paid by the energy supplier to the grid company; ge,t,iAnd Gs,tRepresenting the operating cost of the ith genset and distribution station.
The function of the operating cost is as follows:
Figure BDA0002824247500000034
in the formula, ae,i、be,i、ce,iAnd as、bs、csAnd secondary term, primary term and constant term coefficients of the operation cost of the generator set and the gas distribution station are represented. The relationship between the selling price and the selling power obtained according to the marginal cost function is as follows:
Figure BDA0002824247500000035
in the formula, Ae,t,iAnd As,tDetermining the intercept of a price-power curve by an energy supplier;
the constraint conditions include:
the price-power curve intercept upper and lower limits are restricted:
Figure BDA0002824247500000041
in the formula (I), the compound is shown in the specification,
Figure BDA0002824247500000042
and
Figure BDA0002824247500000043
is the upper and lower limit of the price-power curve intercept of the ith generating set configured by an energy supplier,
Figure BDA0002824247500000044
and
Figure BDA0002824247500000045
is the price-power curve intercept upper and lower limits of the gas distribution station configured by the regional service provider;
the method for establishing the operation economic model of the regional energy supplier based on the Stackelberg game comprises the following steps: respectively establishing an economic objective function and a constraint condition of the regional service provider;
the economic objective function of the regional service provider comprises the following steps:
Figure BDA0002824247500000046
in the formula, CSPFor the net benefit of the regional service provider,
Figure BDA0002824247500000047
to account for the compensation cost of the load shedding to the user when responding to demand,
Figure BDA0002824247500000048
for the cost of energy purchase from the supply side,
Figure BDA0002824247500000049
the regional service provider needs to provide curtailment compensation to the user,
Figure BDA00028242475000000410
and the cost is reduced for environmental pollution treatment. The set K is { e, h, g }, e represents electric energy, h represents heat energy, and g represents electric energy;
Figure BDA00028242475000000411
and Pk,tRepresenting the class k utility selling price and load. The regional service provider needs to provide the customer with curtailment compensation as follows:
Figure BDA00028242475000000412
in the formula, cDRRepresenting a unit compensation price; l isk,tRepresenting the class k load demand when no demand response is made. Energy purchase cost for regional service provider
Figure BDA00028242475000000413
Including the cost of purchasing energy from an energy supplier
Figure BDA00028242475000000414
Cost of purchasing electricity to a grid company
Figure BDA00028242475000000415
And the cost of purchasing heat to the heat source plant
Figure BDA00028242475000000416
Figure BDA00028242475000000417
In the formula (I), the compound is shown in the specification,
Figure BDA0002824247500000051
and
Figure BDA0002824247500000052
and
Figure BDA0002824247500000053
the price and the quantity of electricity purchased from a power grid company and the price and the quantity of heat purchased from a heat source plant by a regional operator are respectively represented. Environmental pollution abatement cost
Figure BDA0002824247500000054
The following were used:
Figure BDA0002824247500000055
in the formula, Pwind,tAnd PPV,tRespectively representing wind power generation capacity and photovoltaic power generation capacity;
the constraint conditions include: power balance constraint of electric, gas and heat energy sources; and
limiting the upper and lower limits of the output power of each device of the regional operator;
the upper and lower limits of the output power of each device are constrained by the following formula:
Figure BDA0002824247500000056
d ∈ D, where D represents the device class, D ═ P2G, CHP, GB }.
Figure BDA0002824247500000057
And
Figure BDA0002824247500000058
respectively the upper limit and the lower limit of the equipment output;
the method for establishing the operation economic model of the regional users based on the Stackelberg game comprises the following steps:
respectively establishing an economic objective function and a constraint condition of the regional user;
the economic objective function of the regional users comprises the following steps:
Figure BDA0002824247500000059
in the formula, ω1And ω2Is a weight coefficient, CUFor the user's comprehensive cost function, CtCost to purchase energy for the user, DtTo bias the cost by energy, the expression is as follows:
Figure BDA00028242475000000510
Figure BDA00028242475000000511
in the formula, MkIs the preference coefficient of the user to k-type energy sources;
the constraint conditions include:
user actual energy use constraint
Figure BDA0002824247500000061
In the formula (I), the compound is shown in the specification,
Figure BDA0002824247500000062
and
Figure BDA0002824247500000063
the upper and lower limits of the energy consumption for the user.
On the other hand, the embodiment of the invention also provides a device for optimizing the operation of the regional comprehensive energy system, which comprises:
the operation economic model establishing module is used for establishing an operation economic model of the comprehensive energy system based on the Stackelberg game;
the optimization module is used for solving by adopting a particle swarm algorithm according to the operation economic model of the energy supplier, the operation economic model of the regional energy supplier and the operation economic model of the regional user, and optimizing the operation parameters of the energy system according to the solving result;
the operation economic model building module comprises:
the energy supplier operation economic model establishing unit is used for establishing an energy supplier operation economic model based on the Stackelberg game;
the system comprises a regional energy provider operation economic model establishing unit, a regional energy provider operation economic model establishing unit and a regional energy provider operation economic model establishing unit, wherein the regional energy provider operation economic model establishing unit is used for establishing a regional energy provider operation economic model based on a Stackelberg game;
the system comprises a region user operation economic model establishing unit, a region user operation economic model establishing unit and a region user operation economic model establishing unit, wherein the region user operation economic model establishing unit is used for establishing an operation economic model of a region user based on a Stackelberg game; .
Compared with the prior art, the operation optimization method and the device of the regional comprehensive energy system have the following advantages:
according to the operation optimization method and device for the regional integrated energy system, operation economic models of energy suppliers, regional energy suppliers and regional users are respectively established based on the Stackelberg game, and the operation economic models are solved by adopting a particle swarm algorithm. The energy utilization strategy of a regional operator is fully considered, the running characteristics of each configured device are considered, the output condition of each device is deeply researched, and the running optimization control of each device is facilitated. Meanwhile, the energy consumption is introduced to favor the energy consumption comfort level of cost quantification, so that the defect that the single interruptible load compensation cannot truly reflect the energy consumption characteristics of the user is overcome.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate an embodiment of the invention and, together with the description, serve to explain the invention and not to limit the invention. In the drawings:
fig. 1 is a schematic flow chart of a regional integrated energy operation optimization method according to a first embodiment of the present invention;
fig. 2 is a schematic diagram of a regional integrated energy system model in an application scenario in the regional integrated energy operation optimization method according to the first embodiment of the present invention;
fig. 3 is a schematic diagram of an initial energy consumption curve of electric heating gas and predicted output of wind power generation and photovoltaic power generation at a user side in an application scene in the regional comprehensive energy operation optimization method according to the first embodiment of the present invention;
fig. 4 is a schematic view of a fluctuation curve of the energy consumption preference coefficient of the user in the application scene in the regional integrated energy operation optimization method in the first embodiment of the present invention within 24 hours;
fig. 5 is a schematic structural diagram of a regional integrated energy operation optimization apparatus according to a second embodiment of the present invention.
Detailed Description
It should be noted that the embodiments and features of the embodiments may be combined with each other without conflict.
In the description of the present invention, it is to be understood that the terms "center", "longitudinal", "lateral", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", and the like, indicate orientations or positional relationships based on those shown in the drawings, and are used only for convenience in describing the present invention and for simplicity in description, and do not indicate or imply that the referenced devices or elements must have a particular orientation, be constructed and operated in a particular orientation, and thus, are not to be construed as limiting the present invention. Furthermore, the terms "first", "second", etc. are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first," "second," etc. may explicitly or implicitly include one or more of that feature. In the description of the present invention, "a plurality" means two or more unless otherwise specified.
In the description of the present invention, it should be noted that, unless otherwise explicitly specified or limited, the terms "mounted," "connected," and "connected" are to be construed broadly, e.g., as meaning either a fixed connection, a removable connection, or an integral connection; can be mechanically or electrically connected; they may be connected directly or indirectly through intervening media, or they may be interconnected between two elements. The specific meaning of the above terms in the present invention can be understood by those of ordinary skill in the art through specific situations.
The present invention will be described in detail below with reference to the embodiments with reference to the attached drawings.
Example one
Fig. 1 is a schematic flow chart of a method for optimizing operation of a regional integrated energy system according to an embodiment of the present invention, and referring to fig. 1, the method for optimizing operation of a regional integrated energy system includes:
and S110, establishing an operation economic model of the comprehensive energy system based on the Stackelberg game.
In this embodiment, the source-to-charge bilateral master-slave gaming architecture of the constructed regional integrated energy system includes three market participants, namely, an energy provider, a regional service provider and a regional user. The energy supplier on the "source" side, as the energy seller, owner, has a priority, so it is the leader in the game and the area service provider is the follower. And the energy supplier and the regional service provider have a sequence when making the strategy, namely after the energy supplier makes the energy selling price facing the service provider, the service provider adjusts the self energy purchasing strategy according to the strategy and feeds back the information to the energy supplier, the energy supplier makes a new energy selling price on the basis, and the game process is repeated continuously until the balance is reached.
The two parties can share information, namely, a supplier can accurately obtain the energy consumption information of a service provider, and the service provider can accurately obtain the energy selling price. The game is thus a full information dynamic game. Similarly, the demand side also belongs to the game. The leader and follower involved in the master-slave game (the Stackelberg game) can well describe this transactional interaction. Therefore, the embodiment of the invention adopts the Stackelberg game method to analyze the interest relationship among the main bodies of the areas.
The energy supplier is provided with a generator set and a gas distribution station, and sells electric energy and natural gas to the regional service providers.
Regional providers purchase gas from energy suppliers, heat from heat source plants, and electricity from energy suppliers or power grids. The service provider comprises traditional controllable energy conversion equipment such as a cogeneration unit, a gas boiler and P2G, and new energy equipment such as wind power generation and photovoltaic power generation. The electricity can be supplied by photovoltaic, fan and CHP, or directly purchased from the power grid, so as to meet the electric energy requirement of downstream users. In the aspect of heat energy supply, heat can be supplied through a heat source plant, GB and CHP. When the gas demand is satisfied, the natural gas purchased from a supplier can be directly used or the gas can be supplied through P2G. The service provider combines renewable energy power generation with traditional energy supply equipment to meet the multi-energy demand of regional users. The P2G and the configuration of the cogeneration unit couple the electric, gas and heat systems together, and realize complementary utilization of energy.
The market burden can be increased by the dispersed participation of a large number of regional users in market trading, and the user energy utilization characteristics of the same region are similar, so that all the users in the region are gathered together and uniformly participate in the market trading, and the flexibility of the user energy utilization is analyzed in the form of incentive type comprehensive demand response.
With reference to the above, in this embodiment, the establishing an economic model of operation of the integrated energy system based on the Stackelberg game may include: establishing an operation economic model of an energy supplier based on a Stackelberg game; establishing an operation economic model of a regional energy supplier based on a Stackelberg game; and establishing a running economic model of the regional users based on the Stackelberg game.
Correspondingly, the establishment of the economic model of the energy supplier operation based on the Stackelberg game comprises the following steps: respectively establishing an economic objective function and a constraint condition of the energy supplier, wherein the economic objective function of the energy supplier comprises the following steps:
Figure BDA0002824247500000101
in the formula, CESNet revenue for the energy provider; t is the total time period, N is the number of generator sets,
Figure BDA0002824247500000102
and
Figure BDA0002824247500000103
representing the sale of energy from energy supplier generator set i and distribution station, respectivelyPrice and sales power; c. CnetRepresenting the net charge paid by the energy supplier to the grid company; ge,t,iAnd Gs,tRepresenting the operating cost of the ith genset and distribution station.
The function of the operating cost is as follows:
Figure BDA0002824247500000111
in the formula, ae,i、be,i、ce,iAnd as、bs、csAnd secondary term, primary term and constant term coefficients of the operation cost of the generator set and the gas distribution station are represented. The relationship between the selling price and the selling power obtained according to the marginal cost function is as follows:
Figure BDA0002824247500000112
in the formula, Ae,t,iAnd As,tThe intercept of the price-power curve is determined by the energy supplier, and after the value is determined, the energy supplier issues the complete price to the regional service provider.
The constraint conditions include:
the price-power curve intercept upper and lower limits are restricted:
Figure BDA0002824247500000113
in the formula (I), the compound is shown in the specification,
Figure BDA0002824247500000114
and
Figure BDA0002824247500000115
is the upper and lower limit of the price-power curve intercept of the ith generating set configured by an energy supplier,
Figure BDA0002824247500000116
and
Figure BDA0002824247500000117
is the upper and lower limits of the price-power curve intercept for the gas distribution station configured by the regional service provider.
In addition, because the number of generator sets and gas distribution stations configured inside the energy supplier is limited, the energy that the energy supplier can provide to the regional service provider needs to meet the constraint of an upper limit value:
Figure BDA0002824247500000118
wherein
Figure BDA0002824247500000119
Is the upper limit of the power generation of the ith generating set configured by the energy supplier,
Figure BDA00028242475000001110
is the upper limit on the amount of natural gas provided by the gas distribution station configured by the energy supplier.
Regional service providers purchase electricity, heat and gas from energy suppliers. The electricity can be supplied by the configured photovoltaic, fan and CHP, or the electricity purchased from the supplier can be directly sold to meet the electricity demand of the downstream users. In terms of heat demand supply, heat purchased from suppliers can be directly utilized, or heat supply can be performed through GB, CHP. When the gas demand is satisfied, the natural gas purchased from a supplier can be directly used or the gas can be supplied through P2G. Specifically, the regional service provider has the following production model:
(1) power to Gas (P2G) equipment
Residual electric power generated by wind power generation, solar power generation and the like is used for electrolyzing water to generate hydrogen, and then the hydrogen is supplied to the existing gas pipeline network; alternatively, methane is produced by methanation using electricity, water and CO2 in the atmosphere to provide a fuel gas. The model is as follows:
Figure BDA0002824247500000121
in the formula (I), the compound is shown in the specification,
Figure BDA0002824247500000122
and Pt P2GInput and output powers, η, of P2G, respectivelyP2GIs the operating efficiency of P2G.
(2) Combined Heat and Power (CHP) equipment
After the steam generated by the boiler drives the steam turbine generator unit to generate electricity, the exhausted steam still contains most of heat and is taken away by cooling water, so that the thermal efficiency of the thermal power plant is only 30-40%. If the heat of the steam extraction or exhaust steam in the process of driving the steam turbine by the steam or after the process can be utilized, the power generation and the heat supply can be realized. This mode of production is known as cogeneration. The process has the advantages of electric energy production and heat energy production, and is a high-efficiency energy utilization mode with simultaneous heat and electricity production. The thermal efficiency can reach 80-90%, and the energy utilization efficiency is about doubled compared with that of the simple power generation. The heat energy grading and utilizing device utilizes different grades of heat energy in a grading way (namely, high-grade heat energy is used for power generation, and low-grade heat energy is used for central heating), improves the utilization efficiency of energy, reduces environmental pollution, and has comprehensive benefits of saving energy, improving environment, improving heating quality, increasing power supply and the like. The model is as follows:
Figure BDA0002824247500000123
in the formula (I), the compound is shown in the specification,
Figure BDA0002824247500000124
and Pt CHPInput and output power, η, of CHPCHPIs the operating efficiency of CHP.
(3) Gas Boiler (GB) equipment
Gas-fired boilers provide heat energy by burning natural gas. The model is as follows:
Figure BDA0002824247500000131
in the formula (I), the compound is shown in the specification,
Figure BDA0002824247500000132
and Pt GBInput and output powers, η, of GB, respectivelyGBThe operating efficiency of GB.
(4) Wind power generation plant
Wind power generation converts kinetic energy of wind into electric energy. Wind energy is a clean and pollution-free renewable energy source.
Figure BDA0002824247500000133
In the formula (I), the compound is shown in the specification,
Figure BDA0002824247500000134
is a predicted wind power generation value in the day ahead.
(5) Photovoltaic power generation equipment
Photovoltaic power generation is a technology of directly converting light energy into electric energy by using the photovoltaic effect of a semiconductor interface.
Figure BDA0002824247500000135
In the formula (I), the compound is shown in the specification,
Figure BDA0002824247500000136
the Maximum photovoltaic Power generation amount is set to be the Maximum photovoltaic Power generation amount in the Maximum Power Point Tracking (MPPT) working mode predicted in the day ahead.
The net revenue for the regional service provider is determined by the difference between the revenue available for energy sale to the regional customer and the cost of energy purchase to the energy provider.
The establishment of the operating economic model of the regional energy supplier based on the Stackelberg game comprises the following steps: and establishing an economic objective function and constraint conditions of the regional service provider.
The economic objective function of the regional service provider is as follows:
Figure BDA0002824247500000137
in the formula, CSPFor the net benefit of the regional service provider,
Figure BDA0002824247500000138
to account for the compensation cost of the load shedding to the user when responding to demand,
Figure BDA0002824247500000139
for the cost of energy purchase from the supply side,
Figure BDA00028242475000001310
the regional service provider needs to provide curtailment compensation to the user,
Figure BDA00028242475000001311
and the cost is reduced for environmental pollution treatment. The set K is { e, h, g }, e represents electric energy, h represents heat energy, and g represents electric energy;
Figure BDA0002824247500000141
and Pk,tRepresenting the class k utility selling price and load. The regional service provider needs to provide the customer with curtailment compensation as follows:
Figure BDA0002824247500000142
in the formula, cDRRepresenting a unit compensation price; l isk,tRepresenting the class k load demand when no demand response is made.
Energy purchase cost for regional service provider
Figure BDA0002824247500000143
Including the cost of purchasing energy from an energy supplier
Figure BDA0002824247500000144
Cost of purchasing electricity to a grid company
Figure BDA0002824247500000145
And the cost of purchasing heat to the heat source plant
Figure BDA0002824247500000146
Figure BDA0002824247500000147
In the formula (I), the compound is shown in the specification,
Figure BDA0002824247500000148
and
Figure BDA0002824247500000149
and
Figure BDA00028242475000001410
the price and the quantity of electricity purchased from a power grid company and the price and the quantity of heat purchased from a heat source plant by a regional operator are respectively represented.
Environmental pollution is generated in the process of power supply, so the treatment cost is needed
Figure BDA00028242475000001411
Taking into account the total cost.
Figure BDA00028242475000001412
In the formula, Pwind,tAnd PPV,tRespectively representing wind power generation capacity and photovoltaic power generation capacity.
Further, the constraints include the following:
1) from the upper power grid to purchase power constraint and from the heat source plant to purchase heat constraint
Figure BDA00028242475000001413
In the formula (I), the compound is shown in the specification,
Figure BDA00028242475000001414
and
Figure BDA00028242475000001415
respectively representing the upper limit value of the electricity purchasing quantity from a superior power grid and the upper limit value of the heat purchasing quantity from a heat source plant;
2) power balance constraint of electric, gas and heat energy sources
Figure BDA0002824247500000151
In the formula, PEin,t、PHin,t、PGin,tRespectively electric energy, heat energy and natural gas purchased by regional service. Alpha is alpha1、α2For the distribution coefficient of electric energy, beta1、β2、β2The natural gas distribution coefficient. The two sets of coefficients satisfy the following constraints:
Figure BDA0002824247500000152
3) upper and lower limit constraint of output power of each equipment of regional operator
Figure BDA0002824247500000153
In the formula, D ∈ D, D represents the device type, and D ═ P2G, CHP, GB }.
Figure BDA0002824247500000154
And
Figure BDA0002824247500000155
respectively the upper and lower limits of the equipment output.
4) Energy selling price constraint issued by regional service provider to regional user
Figure BDA0002824247500000156
In the formula (I), the compound is shown in the specification,
Figure BDA0002824247500000157
and
Figure BDA0002824247500000158
respectively the upper and lower limits of the energy selling price set by the service provider.
In the process of demand-side game, users participate in demand response through interruptible load, but the energy use characteristics of the users cannot be truly reflected by single interruptible load compensation, so the introduction of energy use preference cost DtAnd the cost-effective energy utilization comfort level. Energy cost C will be purchased in the form of linear weightingtEnergy consumption preference cost DtExpressed as a composite cost function CU。
An operational economic model for regional users comprising: an economic objective function and a constraint condition of the regional user;
the economic objective function of the regional users comprises the following steps:
Figure BDA0002824247500000161
in the formula, ω1And ω2Is a weight coefficient, CUFor the user's comprehensive cost function, CtCost to purchase energy for the user, DtTo bias the cost by energy, the expression is as follows:
Figure BDA0002824247500000162
Figure BDA0002824247500000163
in the formula, MkIs the preference coefficient of the user for the k-type energy sources. MkThe larger the value, the less tolerable the user can reduce the amount of energy, i.e., the smaller the amount of load that can be interrupted.
The constraint conditions include:
user actual energy use constraint
Figure BDA0002824247500000164
In the formula (I), the compound is shown in the specification,
Figure BDA0002824247500000165
and
Figure BDA0002824247500000166
the upper and lower limits of the energy consumption for the user.
The operation economic model of the energy supplier, the operation economic model of the regional energy supplier and the operation economic model of the regional user can be established in a non-sequential order. Can be flexibly adjusted according to the actual situation.
And S120, solving by adopting a particle swarm algorithm according to the operation economic model of the energy supplier, the operation economic model of the regional energy supplier and the operation economic model of the regional user, and optimizing the operation parameters of the energy system according to the solved result.
Illustratively, the solving according to the operational economic model of the energy provider, the operational economic model of the regional energy provider and the operational economic model of the regional user by using a particle swarm algorithm may include: determining the optimal load response under a certain energy source according to an objective function of a regional user in an operating economic model of a certain energy source demand; converting the double-layer objective function into a single objective function according to the optimal load response to solve so as to obtain the energy production, the output of conversion equipment and the price set by regional users, which are configured by regional service providers; and determining the energy used by each energy source of the regional users according to the energy production configured by the regional service provider, the output of the conversion equipment and the price set by the regional users.
Specifically, the calculation may be performed as follows:
solving a user objective function CUFor actual energy load Pk,tThe first order partial derivative of (A) can be obtained by the following formula：
Figure BDA0002824247500000171
And the equation is equal to 0, the optimal load response under a certain energy price can be obtained.
Figure BDA0002824247500000172
The above formula is brought into the objective function of the regional service provider, the double-layer objective function in the source side game interaction can be converted into a single objective function to be solved,
the regional service provider firstly makes an initial energy selling price and issues the initial energy selling price to the regional service provider; after receiving the energy price, the regional service provider selects a more appropriate energy purchasing strategy according to the target of the maximum net benefit on the premise of meeting the multi-energy demand of the user, optimizes the output of each configured device, formulates the energy price facing to the regional user and issues the energy price; after receiving the new energy price, the regional users participate in demand response, selectively reduce a certain load amount by taking the minimum self comprehensive cost as a target, and transmit a new load curve to an upstream regional service provider; after receiving a new load demand, the regional service provider formulates a new energy purchasing strategy, optimizes the output of each configured device, uploads the new energy purchasing strategy to the energy provider, and the energy provider formulates an energy price by taking the maximum self-energy selling profit as a target again and sends the energy price to the regional service provider to finish a first round of game; and then the source-load double sides continuously play until both sides of the source-load double sides cannot obtain larger income by only unilateral adjustment decision.
Through the Nash equilibrium solution finally obtained in the game process, the electric energy price matrix E issued to the regional service provider by the energy provider with the maximum self energy selling income can be obtainedeNatural gas energy price EgAs follows:
Figure BDA0002824247500000181
Figure BDA0002824247500000182
in the formula, n represents the total number of generators owned by an energy supplier, and m represents the number of distribution stations owned by the energy supplier; vector quantity
Figure BDA0002824247500000183
A 24-hour price matrix, vector, formulated by the ith generator
Figure BDA0002824247500000184
Representing the 24 hour price matrix made by the jth gas station. Can be expressed as follows:
Figure BDA0002824247500000185
Figure BDA0002824247500000186
obtaining the output P of each energy production and conversion device configured by the regional service provider with the maximum net income per seSPAnd a price E made to regional usersSPAs follows:
PSP＝[PP2G,PGB,PCHPe,PCHPh,PWind,PPV]
Figure BDA0002824247500000187
PP2G、PGB、PCHPe、PCHPh、PWind、PPVrespectively representing a gas generation power matrix of P2G, a heating power matrix of GB and a power generation power matrix of CHP for 24 hoursA heating power matrix of the CHP, a power matrix used for fan power generation, and a power matrix used for photovoltaic power generation.
Figure BDA0002824247500000188
Respectively representing 24-hour electricity, heat and gas energy selling price matrixes issued by a regional service provider to a user. Can be expressed as follows:
Figure BDA0002824247500000189
Figure BDA00028242475000001810
Figure BDA00028242475000001811
Figure BDA00028242475000001812
in the formula, D ∈ D, D ═ { P2G, GB, CHP, Wind, PV }.
Obtaining energy P of each energy source of regional users with the aim of minimizing self comprehensive costUAs follows:
Figure BDA0002824247500000191
in the formula
Figure BDA0002824247500000192
And respectively representing the electric energy demand, the heat energy demand and the natural gas demand of the regional users after demand response.
In the embodiment, a regional integrated energy system model that can be used is shown in fig. 2, and an energy supplier includes 3 generators and a gas distribution station.The initial energy consumption curve of the electric heating gas at the user side and the predicted output of the wind power generation and the photovoltaic power generation are shown in fig. 3. When considering the comprehensive cost function on the user side, the user energy preference coefficient plays an important role, and the fluctuation curve of the value in 24 hours is shown in fig. 4. The present embodiment sets the weighting coefficients of the energy purchase cost and the energy use preference cost to be equal. And during simulation verification, taking 1 hour as a simulation step length. Performing iterative solution by using a particle swarm algorithm, wherein the population number is set to be 50, the iteration times are 300, and the maximum allowable error epsilon of iterative convergence is 5 multiplied by 10-3。
In the system considered by the embodiment, no time coupling equipment such as an energy storage system and the like exists, so that each time period can be independently analyzed. Without loss of generality, the analysis was performed with the 12 th hour results, and the following 4 scenarios were set for analysis,
scene i: the service provider and the energy provider perform game interaction of multiple energy sources;
and scene II: the service provider and the energy supplier only carry out game interaction of electric energy, and the gas price sold by the gas distribution station is fixed;
scene III: the service provider and the energy provider only carry out game interaction of gas energy, and the price of electricity sold by each generator is fixed;
scene iv: the service provider and the energy provider do not carry out game interaction, and the energy provider issues fixed electricity price and gas price;
the 4 scenarios described above all account for demand side gaming. The 4 scenarios all account for demand side gaming. The fixed-price intercept referred to in scenarios 2, 3, 4 is the average of the 24 intercepts in scenario 1 over 24 hours, Ae,t,i93.37, 97.26, 81.91, A, respectivelys,tIs 86.26.
Analyzing the game interaction condition;
the following table is 12: net revenue situation for both regional service providers and energy providers at 00 hours. When the two parties carry out game interaction of multiple electric and gas energy sources, the profits of the two parties are the largest, and when the price of a certain energy source is fixed, the profits of the two parties can be reduced. When the game interaction is not carried out, the income of the two parties is the least. The game interaction method is characterized in that when the service provider and the energy provider carry out game interaction of multiple energies, complementary substitution of the multiple energies can be fully played, the service provider has more energy purchasing choices, and the provider has more flexible pricing strategies. Therefore, the source side game provided by the regional comprehensive energy system operation optimization method provided by the embodiment of the invention enables the economy of the participants to be improved.
TABLE 1 energy supplier and regional facilitator revenue (Unit: USD)
Figure BDA0002824247500000201
And the game of the two parties is realized through a particle swarm algorithm. In the initial state, the energy pricing is far away from the game equilibrium point, and the income fluctuation of the two parties is gradually reduced along with the increase of the iteration times until the two parties are stabilized near a certain value.
In the embodiment, the operating economic models of the energy suppliers, the regional energy suppliers and the regional users are respectively established based on the Stackelberg game, and the operating economic models are solved by adopting a particle swarm algorithm. The energy utilization strategy of a regional operator is fully considered, the running characteristics of each configured device are considered, the output condition of each device is deeply researched, and the running optimization control of each device is facilitated. Meanwhile, the energy consumption is introduced to favor the energy consumption comfort level of cost quantification, so that the defect that the single interruptible load compensation cannot truly reflect the energy consumption characteristics of the user is overcome.
In a preferred embodiment of this embodiment, after determining the energy consumption of each energy source of the regional users, the method may further add the following steps: and adjusting the output consumption condition of the renewable energy power generation equipment according to the energy used by each energy source of the regional user. After the regional service provider purchases energy from the energy supplier, the maximum self-selling energy yield is used as a target to optimize the output of each device so as to meet various energy utilization requirements of users. In the aspect of electric energy supply, service providers mainly apply photovoltaic power generation and fan power generation for power supply due to economy. When the renewable energy power generation can not meet the load demand, the power is supplied after the power is purchased from an upstream power grid. Meanwhile, the demand response can reduce the electricity purchasing cost of the service provider. In terms of heat energy and natural gas supply, due to the low conversion efficiency of CHP and P2G and the lower price of heat than electricity, the service provider will mainly choose to purchase heat directly from the heat source plant and gas from the gas distribution station. Meanwhile, the demand response can also reduce the heat and gas purchasing cost of the service provider.
Example two
Fig. 5 is a schematic structural diagram of a device for optimizing operation of a regional integrated energy system according to a second embodiment of the present invention. Referring to fig. 5, the regional integrated energy system operation optimizing apparatus includes:
the operation economic model establishing module 210 is used for establishing an operation economic model of the comprehensive energy system based on the Stackelberg game;
the optimization module 240 is used for solving by adopting a particle swarm algorithm according to the operation economic model of the energy supplier, the operation economic model of the regional energy supplier and the operation economic model of the regional user, and optimizing the operation parameters of the energy system according to the solving result;
the operation economic model building module comprises:
the energy supplier operation economic model establishing unit is used for establishing an energy supplier operation economic model based on the Stackelberg game;
the system comprises a regional energy provider operation economic model establishing unit, a regional energy provider operation economic model establishing unit and a regional energy provider operation economic model establishing unit, wherein the regional energy provider operation economic model establishing unit is used for establishing a regional energy provider operation economic model based on a Stackelberg game;
the system comprises a region user operation economic model establishing unit, a region user operation economic model establishing unit and a region user operation economic model establishing unit, wherein the region user operation economic model establishing unit is used for establishing an operation economic model of a region user based on a Stackelberg game;
the optimization module 240 is used for solving by adopting a particle swarm algorithm according to the operation economic model of the energy supplier, the operation economic model of the regional energy supplier and the operation economic model of the regional user, and optimizing the operation parameters of the energy system according to the solving result;
the method for establishing the running economic model of the energy supplier based on the Stackelberg game comprises the following steps: respectively establishing an economic objective function and a constraint condition of the energy supplier, wherein the economic objective function of the energy supplier comprises the following steps:
Figure BDA0002824247500000221
in the formula, CESNet revenue for the energy provider; t is the total time period, N is the number of generator sets,
Figure BDA0002824247500000222
and
Figure BDA0002824247500000223
respectively representing the energy selling price and selling power of the generator set i and the gas distribution station of an energy supplier; c. CnetRepresenting the net charge paid by the energy supplier to the grid company; ge,t,iAnd Gs,tRepresenting the operating cost of the ith genset and distribution station.
The function of the operating cost is as follows:
Figure BDA0002824247500000231
in the formula, ae,i、be,i、ce,iAnd as、bs、csRepresenting coefficients of a secondary term, a primary term and a constant term of the operation cost of the generator set i and the gas distribution station; the relationship between the selling price and the selling power obtained according to the marginal cost function is as follows:
Figure BDA0002824247500000232
in the formula, Ae,t,iAnd As,tDetermining the intercept of a price-power curve by an energy supplier;
the constraint conditions include:
the price-power curve intercept upper and lower limits are restricted:
Figure BDA0002824247500000233
wherein
Figure BDA0002824247500000234
And
Figure BDA0002824247500000235
is the upper and lower limit of the price-power curve intercept of the ith generating set configured by an energy supplier,
Figure BDA0002824247500000236
and
Figure BDA0002824247500000237
is the price-power curve intercept upper and lower limits of the gas distribution station configured by the regional service provider;
the method for establishing the operation economic model of the regional energy supplier based on the Stackelberg game comprises the following steps: respectively establishing an economic objective function and a constraint condition of the regional service provider;
the economic objective function of the regional service provider comprises the following steps:
Figure BDA0002824247500000238
in the formula, CSPFor the net benefit of the regional service provider,
Figure BDA0002824247500000239
to account for the compensation cost of the load shedding to the user when responding to demand,
Figure BDA00028242475000002310
for the cost of energy purchase from the supply side,
Figure BDA00028242475000002311
the regional service provider needs to provide curtailment compensation to the user,
Figure BDA0002824247500000241
cost for environmental pollution treatment. The set K is { e, h, g }, e represents electric energy, h represents heat energy, and g represents electric energy;
Figure BDA0002824247500000242
and Pk,tRepresenting the class k utility selling price and load. The regional service provider needs to provide the customer with curtailment compensation as follows:
Figure BDA0002824247500000243
in the formula, cDRRepresenting a unit compensation price; l isk,tRepresenting the class k load demand when no demand response is made.
Energy purchase cost for regional service provider
Figure BDA0002824247500000244
Including the cost of purchasing energy from an energy supplier
Figure BDA0002824247500000245
Cost of purchasing electricity to a grid company
Figure BDA0002824247500000246
And the cost of purchasing heat to the heat source plant
Figure BDA0002824247500000247
Figure BDA0002824247500000248
In the formula (I), the compound is shown in the specification,
Figure BDA0002824247500000249
and
Figure BDA00028242475000002410
and
Figure BDA00028242475000002411
respectively represents the price and the quantity of electricity purchased by the regional operator from the power grid company,and the price and heat quantity of heat purchased from a heat source plant.
Environmental pollution is generated in the process of power supply, so the treatment cost is needed
Figure BDA00028242475000002412
Taking into account the total cost.
Figure BDA00028242475000002413
In the formula, Pwind,tAnd PPV,tRespectively representing wind power generation capacity and photovoltaic power generation capacity;
the constraint conditions include: power balance constraint of electric, gas and heat energy sources; and
limiting the upper and lower limits of the output power of each device of the regional operator;
the upper and lower limits of the output power of each device are constrained by the following formula:
Figure BDA00028242475000002414
in the formula, D ∈ D, D represents the device type, and D ═ P2G, CHP, GB }.
Figure BDA0002824247500000251
And
Figure BDA0002824247500000252
respectively the upper limit and the lower limit of the equipment output;
the method for establishing the operation economic model of the regional users based on the Stackelberg game comprises the following steps:
respectively establishing an economic objective function and a constraint condition of the regional user;
the economic objective function of the regional users comprises the following steps:
Figure BDA0002824247500000253
in the formula, ω1And ω2Is a weight coefficient, CUFor the user's comprehensive cost function, CtCost to purchase energy for the user, DtTo bias the cost by energy, the expression is as follows:
Figure BDA0002824247500000254
Figure BDA0002824247500000255
in the formula, MkIs the preference coefficient of the user to k-type energy sources;
the constraint conditions include:
user actual energy use constraint
Figure BDA0002824247500000256
In the formula (I), the compound is shown in the specification,
Figure BDA0002824247500000257
and
Figure BDA0002824247500000258
the upper and lower limits of the energy consumption for the user.
In a preferred implementation manner of this embodiment, the optimization module includes:
the optimal load response determining unit is used for determining the optimal load response under a certain energy source according to an objective function of a regional user in an operating economic model of the certain energy source requirement;
the solving unit is used for converting the double-layer objective function into a single objective function according to the optimal load response and solving the single objective function so as to obtain the output of each energy production and conversion device configured by a regional service provider and the price set by a regional user;
and the configuration unit is used for determining each energy used by the regional users according to each energy production configured by the regional service provider, the output of the conversion equipment and the price set by the regional users.
In another preferred implementation of this embodiment, the apparatus further comprises:
and the adjusting module is used for adjusting the output consumption condition of the renewable energy power generation equipment according to the energy used by each energy source of the regional user.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents, improvements and the like that fall within the spirit and principle of the present invention are intended to be included therein.

Claims (6)

1. A regional integrated energy system operation optimization method is characterized by comprising the following steps:
establishing an operation economic model of the comprehensive energy system based on the Stackelberg game;
solving by adopting a particle swarm algorithm according to the running economic model of the comprehensive energy system, and optimizing the running parameters of the energy system according to the solving result;
the method for establishing the operation economic model of the comprehensive energy system based on the Stackelberg game comprises the following steps:
establishing an operation economic model of an energy supplier based on a Stackelberg game;
establishing an operation economic model of a regional energy supplier based on a Stackelberg game;
establishing an operation economic model of the regional users based on the Stackelberg game;
the method for establishing the running economic model of the energy supplier based on the Stackelberg game comprises the following steps: respectively establishing an economic objective function and a constraint condition of the energy supplier, wherein the economic objective function of the energy supplier comprises the following steps:
Figure FDA0002824247490000011
wherein, # CESIs net income of energy suppliersBenefiting; t is the total time period, N is the number of generator sets,
Figure FDA0002824247490000012
and
Figure FDA0002824247490000013
respectively representing the energy selling price and selling power of the generator set i and the gas distribution station of an energy supplier; c. CnetRepresenting the net charge paid by the energy supplier to the grid company; ge,t,iAnd Gs,tRepresenting the operating cost of the ith genset and distribution station.
The function of the operating cost is as follows:
Figure FDA0002824247490000014
in the formula, ae,i、be,i、ce,iAnd as、bs、csAnd secondary term, primary term and constant term coefficients of the operation cost of the generator set and the gas distribution station are represented. The relationship between the selling price and the selling power obtained according to the marginal cost function is as follows:
Figure FDA0002824247490000021
in the formula, Ae,t,iAnd As,tThe intercept of the price-power curve is determined by the energy supplier, and after the value is determined, the energy supplier issues the complete price to the regional service provider.
The constraint conditions include:
the price-power curve intercept upper and lower limits are restricted:
Figure FDA0002824247490000022
in the formula (I), the compound is shown in the specification,
Figure FDA0002824247490000023
and
Figure FDA0002824247490000024
is the upper and lower limit of the price-power curve intercept of the ith generating set configured by an energy supplier,
Figure FDA0002824247490000025
and
Figure FDA0002824247490000026
is the price-power curve intercept upper and lower limits of the gas distribution station configured by the regional service provider;
the method for establishing the operation economic model of the regional energy supplier based on the Stackelberg game comprises the following steps: respectively establishing an economic objective function and a constraint condition of the regional service provider;
the economic objective function of the regional service provider comprises the following steps:
Figure FDA0002824247490000027
in the formula, CSPFor the net benefit of the regional service provider,
Figure FDA0002824247490000028
to account for the compensation cost of the load shedding to the user when responding to demand,
Figure FDA0002824247490000029
for the cost of energy purchase from the supply side,
Figure FDA00028242474900000210
the regional service provider needs to provide curtailment compensation to the user,
Figure FDA00028242474900000211
and the cost is reduced for environmental pollution treatment. The set K ═ e, h, g, e stands for electricityEnergy, h represents heat energy, and g represents electric energy;
Figure FDA00028242474900000212
and Pk,tRepresenting the class k utility selling price and load. The regional service provider needs to provide the customer with curtailment compensation as follows:
Figure FDA00028242474900000213
in the formula, cDRRepresenting a unit compensation price; l isk,tRepresenting the class k load demand when no demand response is made. Energy purchase cost for regional service provider
Figure FDA00028242474900000214
Including the cost of purchasing energy from an energy supplier
Figure FDA00028242474900000215
Cost of purchasing electricity to a grid company
Figure FDA00028242474900000216
And the cost of purchasing heat to the heat source plant
Figure FDA00028242474900000217
Figure FDA0002824247490000031
In the formula (I), the compound is shown in the specification,
Figure FDA0002824247490000032
and
Figure FDA0002824247490000033
and
Figure FDA0002824247490000034
the price and the quantity of electricity purchased from a power grid company and the price and the quantity of heat purchased from a heat source plant by a regional operator are respectively represented. Environmental pollution abatement cost
Figure FDA0002824247490000035
The following were used:
Figure FDA0002824247490000036
in the formula, Pwind,tAnd PPV,tRespectively representing wind power generation capacity and photovoltaic power generation capacity;
the constraint conditions include: power balance constraint of electric, gas and heat energy sources; and
limiting the upper and lower limits of the output power of each device of the regional operator;
the upper and lower limits of the output power of each device are constrained by the following formula:
Figure FDA0002824247490000037
in the formula, d represents the device type, and K ═ P2G, CHP, GB }.
Figure FDA0002824247490000038
And
Figure FDA0002824247490000039
respectively the upper limit and the lower limit of the equipment output;
the method for establishing the operation economic model of the regional users based on the Stackelberg game comprises the following steps:
respectively establishing an economic objective function and a constraint condition of the regional user;
the economic objective function of the regional users comprises the following steps:
Figure FDA00028242474900000310
in the formula, ω1And ω2Is a weight coefficient, CUFor the user's comprehensive cost function, CtCost to purchase energy for the user, DtTo bias the cost by energy, the expression is as follows:
Figure FDA00028242474900000311
Figure FDA00028242474900000312
in the formula, MkIs the preference coefficient of the user to k-type energy sources;
the constraint conditions include:
user practical energy constraints:
Figure FDA0002824247490000041
in the formula (I), the compound is shown in the specification,
Figure FDA0002824247490000042
and
Figure FDA0002824247490000043
the upper and lower limits of the energy consumption for the user.
2. The method according to claim 1, wherein said solving using a particle swarm algorithm based on an operational economic model of said integrated energy system comprises:
determining the optimal load response under a certain energy source according to an objective function of a regional user in an operating economic model of a certain energy source demand;
converting the double-layer objective function into a single objective function according to the optimal load response to solve so as to obtain the energy production, the output of conversion equipment and the price set by regional users, which are configured by regional service providers;
and determining the energy used by each energy source of the regional users according to the energy production configured by the regional service provider, the output of the conversion equipment and the price set by the regional users.
3. The method of claim 2, wherein after determining the energy usage of each energy source by the regional user, the method further comprises:
and adjusting the output consumption condition of the renewable energy power generation equipment according to the energy used by each energy source of the regional user.
4. An apparatus for optimizing operation of a regional integrated energy system, the apparatus comprising:
the operation economic model establishing module is used for establishing an operation economic model of the comprehensive energy system based on the Stackelberg game;
the optimization module is used for solving by adopting a particle swarm algorithm according to the operation economic model of the energy supplier, the operation economic model of the regional energy supplier and the operation economic model of the regional user, and optimizing the operation parameters of the energy system according to the solving result;
the operation economic model building module comprises:
the energy supplier operation economic model establishing unit is used for establishing an energy supplier operation economic model based on the Stackelberg game;
the system comprises a regional energy provider operation economic model establishing unit, a regional energy provider operation economic model establishing unit and a regional energy provider operation economic model establishing unit, wherein the regional energy provider operation economic model establishing unit is used for establishing a regional energy provider operation economic model based on a Stackelberg game;
the system comprises a region user operation economic model establishing unit, a region user operation economic model establishing unit and a region user operation economic model establishing unit, wherein the region user operation economic model establishing unit is used for establishing an operation economic model of a region user based on a Stackelberg game;
the method for establishing the running economic model of the energy supplier based on the Stackelberg game comprises the following steps: respectively establishing an economic objective function and a constraint condition of the energy supplier, wherein the economic objective function of the energy supplier comprises the following steps:
Figure FDA0002824247490000051
wherein, # CESNet revenue for the energy provider; t is the total time period, N is the number of generator sets,
Figure FDA0002824247490000052
and
Figure FDA0002824247490000053
respectively representing the energy selling price and selling power of the generator set i and the gas distribution station of an energy supplier; c. CnetRepresenting the net charge paid by the energy supplier to the grid company; ge,t,iAnd Gs,tRepresenting the operating cost of the ith genset and distribution station.
The function of the operating cost is as follows:
Figure FDA0002824247490000054
in the formula, ae,i、be,i、ce,iAnd as、bs、csAnd secondary term, primary term and constant term coefficients of the operation cost of the generator set and the gas distribution station are represented. The relationship between the selling price and the selling power obtained according to the marginal cost function is as follows:
Figure FDA0002824247490000061
in the formula, Ae,t,iAnd As,tThe intercept of the price-power curve is determined by the energy supplier, and after the value is determined, the energy supplier issues the complete price to the regional service provider.
The constraint conditions include:
the price-power curve intercept upper and lower limits are restricted:
Figure FDA0002824247490000062
in the formula (I), the compound is shown in the specification,
Figure FDA0002824247490000063
and
Figure FDA0002824247490000064
is the upper and lower limit of the price-power curve intercept of the ith generating set configured by an energy supplier,
Figure FDA0002824247490000065
and
Figure FDA0002824247490000066
is the price-power curve intercept upper and lower limits of the gas distribution station configured by the regional service provider;
the method for establishing the operation economic model of the regional energy supplier based on the Stackelberg game comprises the following steps: respectively establishing an economic objective function and a constraint condition of the regional service provider;
the economic objective function of the regional service provider comprises the following steps:
Figure FDA0002824247490000067
in the formula, CSPFor the net benefit of the regional service provider,
Figure FDA0002824247490000068
to account for the compensation cost of the load shedding to the user when responding to demand,
Figure FDA0002824247490000069
for the cost of energy purchase from the supply side,
Figure FDA00028242474900000610
for regional service provider to needThe user provides the compensation for the cut-back,
Figure FDA00028242474900000611
and the cost is reduced for environmental pollution treatment. The set K is { e, h, g }, e represents electric energy, h represents heat energy, and g represents electric energy;
Figure FDA00028242474900000612
and Pk,tRepresenting the class k utility selling price and load. The regional service provider needs to provide the customer with curtailment compensation as follows:
Figure FDA00028242474900000613
in the formula, cDRRepresenting a unit compensation price; l isk,tRepresenting the class k load demand when no demand response is made. Energy purchase cost for regional service provider
Figure FDA00028242474900000614
Including the cost of purchasing energy from an energy supplier
Figure FDA0002824247490000071
Cost of purchasing electricity to a grid company
Figure FDA0002824247490000072
And the cost of purchasing heat to the heat source plant
Figure FDA0002824247490000073
Figure FDA0002824247490000074
In the formula (I), the compound is shown in the specification,
Figure FDA0002824247490000075
and
Figure FDA0002824247490000076
and
Figure FDA0002824247490000077
the price and the quantity of electricity purchased from a power grid company and the price and the quantity of heat purchased from a heat source plant by a regional operator are respectively represented. Environmental pollution abatement cost
Figure FDA0002824247490000078
The following were used:
Figure FDA0002824247490000079
in the formula, Pwind,tAnd PPV,tRespectively representing wind power generation capacity and photovoltaic power generation capacity;
the constraint conditions include: power balance constraint of electric, gas and heat energy sources; and
limiting the upper and lower limits of the output power of each device of the regional operator;
the upper and lower limits of the output power of each device are constrained by the following formula:
Figure FDA00028242474900000710
d ∈ D, where D represents the device class, D ═ P2G, CHP, GB }.
Figure FDA00028242474900000711
And
Figure FDA00028242474900000712
respectively the upper limit and the lower limit of the equipment output;
the method for establishing the operation economic model of the regional users based on the Stackelberg game comprises the following steps:
respectively establishing an economic objective function and a constraint condition of the regional user;
the economic objective function of the regional users comprises the following steps:
Figure FDA00028242474900000713
in the formula, ω1And ω2Is a weight coefficient, CUFor the user's comprehensive cost function, CtCost to purchase energy for the user, DtTo bias the cost by energy, the expression is as follows:
Figure FDA0002824247490000081
Figure FDA0002824247490000082
in the formula, MkIs the preference coefficient of the user to k-type energy sources;
the constraint conditions include:
user actual energy use constraint
Figure FDA0002824247490000083
In the formula (I), the compound is shown in the specification,
Figure FDA0002824247490000084
and
Figure FDA0002824247490000085
the upper and lower limits of the energy consumption for the user.
5. The regional integrated energy system operation optimization device of claim 4, wherein the optimization module comprises:
the optimal load response determining unit is used for determining the optimal load response under a certain energy source according to an objective function of a regional user in an operating economic model of the certain energy source requirement;
the solving unit is used for converting the double-layer objective function into a single objective function according to the optimal load response and solving the single objective function so as to obtain the output of each energy production and conversion device configured by a regional service provider and the price set by a regional user;
and the configuration unit is used for determining each energy used by the regional users according to each energy production configured by the regional service provider, the output of the conversion equipment and the price set by the regional users.
6. The regional integrated energy system operation optimization device of claim 4, further comprising:
and the adjusting module is used for adjusting the output consumption condition of the renewable energy power generation equipment according to the energy used by each energy source of the regional user.
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