CN112053253A - Game theory-based power grid planning method under optical storage access condition - Google Patents

Game theory-based power grid planning method under optical storage access condition Download PDF

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CN112053253A
CN112053253A CN202010015933.3A CN202010015933A CN112053253A CN 112053253 A CN112053253 A CN 112053253A CN 202010015933 A CN202010015933 A CN 202010015933A CN 112053253 A CN112053253 A CN 112053253A
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陈兴良
李海燕
余秋霞
朴哲勇
浦全军
舒大光
宋磊
刘海超
闫星宇
王春建
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State Grid Jilin Electric Power Corp
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Abstract

The invention belongs to the field of power supplies and power transmission networks of electric power systems, and particularly relates to a photovoltaic unit, energy storage equipment and power transmission network coordination planning method based on a game theory. With the gradual popularization of new energy, the light abandoning problem of a photovoltaic generator set is increasingly prominent, and the reason for blocking photovoltaic output is gradually analyzed from the directions of an economic structure, a grid structure, the operation condition of a power grid, local energy ratio and the like. And then analyzing the action mechanism of the energy storage equipment on the operation mode of the power grid, combing the profit modes of the photovoltaic power station, the energy storage equipment and the power grid company after the energy storage equipment is added, constructing a game model based on a game theory system under the action relationship of three parties, and providing basic elements such as strategies, benefits and the like of the three participants. And finally, solving the established game model based on a solving method of a game theory, wherein the system adopts an optimal economic dispatching strategy in the simulation solving process so as to find a scheme for building the photovoltaic unit, the energy storage equipment and the power grid with the highest cost performance.

Description

Game theory-based power grid planning method under optical storage access condition
Technical Field
The invention belongs to the field of power supplies and power transmission networks of electric power systems, and particularly relates to a photovoltaic unit, energy storage equipment and power transmission network coordination planning method based on a game theory.
Background
Under the support of new energy policy in China, photovoltaic power generation which is widely distributed and rich in resources is rapidly developed in recent years, but disorder planning construction and light abandon phenomena of photovoltaic power stations are more prominent. Firstly, when a large number of photovoltaic power stations are planned, a photovoltaic absorption solution cannot be synchronously carried out, the problem of light abandonment is prominent, and a large amount of investment waste is caused; secondly, due to the influx of a large amount of market capital, investors in each party are in pursuit of maximization of own benefits, are in pursuit of resources, are in game competition, and lack of effectiveness of collusion among the participants, a constrained protocol is difficult to achieve, a cooperative alliance cannot be formed, and therefore the photovoltaic power station, the energy storage system and the power grid company cannot realize coordinated planning and development.
How to fully consider the characteristics of centralized planning of a photovoltaic power station, distance from a load center, strong random fluctuation of output and the like under the existing new energy policy and electric power market reformation mechanism, consider the investment economy problem of power system planning construction and the photovoltaic solution, research the coordination planning construction of the photovoltaic power station, an energy storage system and a power grid, and have extremely important practical significance for reasonably planning the capacity layout of the photovoltaic power station, improving the comprehensive benefits of the power grid and the photovoltaic power station and promoting the economic, stable and safe operation of the power system.
Disclosure of Invention
The invention aims to provide a scientific and reasonable light storage access network source coordination planning method based on a non-cooperative game theory, so that coordination planning of a photovoltaic power station, an energy storage device and a net rack is realized, the photovoltaic consumption rate is effectively improved on the basis of meeting load requirements and reliability, and better economic and environmental protection values are obtained.
In order to achieve the purpose, horizontal year photovoltaic, energy storage and a power grid are taken as research objects, the influence of market environment is considered, a renewable energy quota and green certificate transaction mechanism is introduced, and an optical-storage-network coordinated planning game model is established based on a complete information dynamic game theory in a non-cooperative game.
When the photovoltaic, energy storage and power grid are subjected to game planning, the planning sequence of each main body is considered, and a capacity planning strategy P of a photovoltaic power station serving as a power supply side is firstly formulated by the photovoltaic power station serving as a power supply sidePOn the basis of power supply planning, the power grid carries out line extension planning and makes a strategy LGThen, according to the operation condition of the system, the energy storage makes a capacity planning strategy PBFinally, the photovoltaic, the energy storage and the power grid are all targeted to maximize respective income, and the game strategy is optimally adjusted to be optimal, so that the dynamic game process is realized. It should be noted that, strictly speaking, in the optical storage network game planning process, each information is not completely symmetrical and public, and the point is to discuss a planning method based on the game theory in order to avoid incomplete solutionThe complexity of the information is the same, and for the sake of simplicity, it is assumed that all the strategy information of each participant in the game stage is mutually mastered by each other, and the participants have complete rationality.
Based on the analysis, a network source coordination planning dynamic game model after optical storage access is established in the text to solve the Nash equilibrium strategy of the three-party participants, and an optimization objective function is as follows:
Figure RE-GSB0000190225860000021
in the formula:
Figure RE-GSB0000190225860000022
the Nash equilibrium strategy for the game participants represents the optimal strategy of the own party when the optimal strategy is selected by the opposite party, namely the highest profit of the optical-storage-network under the strategy combination in the sense of Nash equilibrium can be realized; argmax (·) represents the set of variables that maximizes the value of the objective function. The optimization objective needs to be optimized under the dispatching strategy of the power grid.
In the light-storage-network coordinated planning game mode, the benefit of each investment subject relates to the whole process of the whole life cycle, the equivalent year coefficient of the equipment is considered, the income of each game participant is calculated by adopting the annual income and the cost, and the specific income model of each investment subject is as follows.
A. Photovoltaic power station revenue
Yield F of photovoltaic power stationPComposed of its income and cost fees, the income includes annual electric power sale income Wp，SELNew energy subsidy of government Wp，SUBWaste income W of photovoltaic cellsp，SCR(ii) a The cost comprises the initial construction cost C of the photovoltaic power stationp，INVOperation maintenance cost Cp，WOMAnd running assessment cost Cp，ASS. China has strict assessment standards for power fluctuation and prediction of large-scale photovoltaic power stations after grid connection, and the method is as follows.
1) The maximum power change of the photovoltaic power station within 10min and 1min per month is regulated to be not more than 33% and 10% of the installed capacity respectively, the photovoltaic power station is examined according to 10 minutes per month when the maximum power change exceeds 1%, and 1000-element punishment amount is corresponding to each minute.
2) The average absolute errors of short-term and ultra-short-term power prediction months of the photovoltaic power station are regulated to be respectively less than 15% and 10%, and when the average absolute errors exceed 1%, the average absolute errors are evaluated according to the capacity of a loading machine multiplied by 0.2 min/MW, and each minute corresponds to 1000-element punishment amount.
The photovoltaic power station revenue function is as follows:
Figure RE-GSB0000190225860000023
in the formula: wP，SCR＝PPDPIn which P isPFor installed capacity of photovoltaic power stations, DPPhotovoltaic scrap revenue per unit power; cP，INV＝PPUPWherein U isPPhotovoltaic cost per unit power; cP，WOM＝PPMPWherein M isPThe photovoltaic annual maintenance cost per unit power; τ is Bank interest Rate, TPIn order to provide a photovoltaic power station with a long service life,
Figure RE-GSB0000190225860000039
is the equivalent annual coefficient of the equipment.
B. Energy storage system revenue
Similar to photovoltaic power plants, yield F of energy storage systemsBBut also by its revenue and various cost fees. The method mainly considers peak shaving and standby service of the energy storage system in the operation of a power grid, and the income W of the auxiliary service provided by the energy storage systemB，AUX(ii) a The cost comprises the cost C of purchasing electricity from the power gridB，PURInitial construction cost CB，INVAnd operating maintenance cost CB，WOM. Herein, the energy storage system auxiliary service revenue is calculated as follows:
Figure RE-GSB0000190225860000031
in the formula: c. CPEPeak shaving income as a unit; c. CRESpare income for the unit;
Figure RE-GSB0000190225860000032
the energy storage in a time interval participates in the standby capacity of the system,
Figure RE-GSB0000190225860000033
wherein
Figure RE-GSB0000190225860000034
The energy is stored for a period of time,
Figure RE-GSB0000190225860000035
and the time interval energy storage participates in peak shaving electric quantity.
The energy storage system revenue function is as follows:
Figure RE-GSB0000190225860000036
in the formula: cost of electricity purchase
Figure 100002_1
Wherein
Figure RE-GSB0000190225860000038
Storing the quantity of electricity, λ, purchased from the grid during periodsBA purchase price for a unit of electricity; initial construction cost CB，INVAnd operating maintenance cost CB，WOMThe calculation is similar to that of the photovoltaic power station, and only the corresponding variables need to be changed into the variables of the energy storage system, which is not described herein again. According to the 'implementation rules of auxiliary service management of grid-connected power plants' issued in China, compensation cost of the energy storage system participating in auxiliary service comes from power plant grid-connected operation management and assessment cost and generating set debugging and operating period difference fund.
C. Revenue for grid company
Income of the power grid company is income W from power selling thereofG，SELGreen certificate transaction revenue WG，TGCAnnual electricity purchase cost C from photovoltaic power stationG，PURAnd the grid expansion cost C for receiving photovoltaic powerG，TRAnd the like. The green certificate transaction income is calculated as follows, and the renewable energy of a power grid company is setThe source quota requirement is N, the actual holding capacity of the green certificate is M, and the available revenue of the power grid company through the renewable energy trading market is as follows:
WG，TGC＝λTGC(M-N) (5)
in the formula: wG，TGCEarnings for green certificate transactions; lambda [ alpha ]TGCThe trade price of unit electric quantity of green certificate.
The method takes 1kW & h photovoltaic electric quantity as a unit certificate face value and takes one year as a term as a green certificate settlement period. In the above equation, if M < N indicates that the grid company has failed to fulfill the government-defined renewable energy quota obligation, W isG，TGCThe expense of purchasing green certificates for grid companies from other stakeholders who over-complete the quota obligation.
The revenue function of the grid company is as follows:
Figure RE-GSB0000190225860000041
in the formula:
Figure 100002_2
wherein N isLFor alternative amplification of the total number of lines, CkIs the average cost of the kth line, LkThe line length is amplified for the kth alternative.
The method is based on an economic dispatching strategy, and checks each game scheme by taking the minimum coal consumption cost of the thermal power generating unit and the minimum auxiliary service cost of the energy storage system as targets. The economic dispatch objective function is as follows:
Figure RE-GSB0000190225860000043
in the formula: cGENAnd CBESSThe operation costs of the thermal power generating unit and the energy storage system are respectively calculated; n is a radical ofGNumber of thermal power generating units, NBThe number of energy storage systems;
Figure RE-GSB0000190225860000044
and
Figure RE-GSB0000190225860000045
representing the starting and stopping states of the thermal power generating unit before the t period and the t period,
Figure RE-GSB0000190225860000046
indicating that the thermal power generating unit is in a shutdown state,
Figure RE-GSB0000190225860000047
the thermal power generating unit is in a starting state;
Figure RE-GSB0000190225860000048
the output power of the motor set i in a time period t; alpha is alphai，βi，γiThe characteristic parameters of the operating consumption of the thermal power generating unit are obtained; etaiAnd (4) starting the consumption characteristic parameters of the thermal power generating unit. Energy storage operating cost CBESSI.e. its auxiliary service income W in the energy storage system profit modelB，AUXHere considered from a scheduling point of view.
The constraints are as follows:
(1) schedulable photovoltaic output constraint
Figure RE-GSB0000190225860000049
In the formula:
Figure RE-GSB00001902258600000410
the photovoltaic output is generated in a time period,
Figure RE-GSB00001902258600000411
and photovoltaic maximum output in a time period.
(2) Thermal power generating unit technical constraints
Output power upper and lower limit constraints:
Figure RE-GSB00001902258600000412
in the formula: pGi，maxAnd PGi，minThe upper limit and the lower limit of the output power of the thermal power generating unit i are respectively set.
And secondly, climbing rate constraint:
Figure RE-GSB00001902258600000413
in the formula: pGi，upAnd PGi，dwThe upward climbing speed and the downward climbing speed of the thermal power generating unit i are respectively.
And third, minimum start-stop time constraint:
Figure RE-GSB0000190225860000051
in the formula:
Figure RE-GSB0000190225860000052
respectively obtaining the minimum continuous operation time and the minimum continuous shutdown time of the thermal power generating unit i;
Figure RE-GSB0000190225860000053
the generator set i continues for the same period of time (running or shut down) before the t period.
(3) Energy storage system technology constraints
Charge and discharge power constraint:
Figure RE-GSB0000190225860000054
in the formula:
Figure RE-GSB0000190225860000055
and
Figure RE-GSB0000190225860000056
the energy storage charging and discharging power;
Figure RE-GSB0000190225860000057
and
Figure RE-GSB0000190225860000058
respectively an upper limit and a lower limit of the energy storage charging power;
Figure RE-GSB0000190225860000059
and
Figure RE-GSB00001902258600000510
the energy storage discharge power upper limit and the energy storage discharge power lower limit are respectively.
And the electric quantity is stored for constraint:
Figure RE-GSB00001902258600000511
in the formula:
Figure RE-GSB00001902258600000512
the stored electricity quantity of the stored energy i in the time period t is obtained; eBi，maxAnd EBi，minThe upper limit and the lower limit of the stored energy and stored electricity are respectively.
(4) System constraints
Power balance constraint:
Figure RE-GSB00001902258600000513
in the formula:
Figure RE-GSB00001902258600000514
is the active load of time period t.
Rotating standby constraint:
Figure RE-GSB00001902258600000515
Figure RE-GSB00001902258600000516
in the formula:
Figure RE-GSB00001902258600000517
and
Figure RE-GSB00001902258600000518
positive and negative rotation standby respectively set for the system to cope with photovoltaic power fluctuation in the period t;
Figure RE-GSB00001902258600000519
and
Figure RE-GSB00001902258600000520
and positive and negative rotation standby respectively set for the system to cope with load fluctuation in the t period.
Third, line capacity constraint:
Figure RE-GSB00001902258600000521
in the formula: plineThe actual trend of the line is obtained;
Figure RE-GSB00001902258600000522
and
Figure RE-GSB00001902258600000523
respectively, line minimum and maximum capacity constraints.
Drawings
FIG. 1 is a diagram of the photovoltaic power plant and grid development of the present invention;
FIG. 2 is a schematic diagram of the operation of the grid-connected optical storage system of the present invention;
fig. 3 is a flow chart of a source coordination planning method for an optical storage access network according to the present invention;
Detailed Description
The invention is further described below with reference to the accompanying drawings.
Fig. 1 is a development relationship diagram of a photovoltaic power station and a power transmission network.
The photovoltaic power generation system is different from the traditional stable and controllable power generation modes such as thermal power, hydroelectric power, nuclear power and the like, the photovoltaic power generation is greatly influenced by weather, environment and the like, and the absorption of the photovoltaic power generation system is limited by factors such as a power system power supply structure, a power grid structure, load level and load characteristics, a power grid scheduling plan and the like due to the characteristics of randomness, intermittence, volatility and the like of output. China's photovoltaic power generation bases are located at places far away from a main power system and a load center, and face a series of difficult problems that a grid frame is weak, the peak regulation capacity of the system is insufficient, the cross-province consumption and the stability of the power system are needed, and the like. Moreover, under the influence of new energy price policy and market environment factors, the rapid development of photovoltaic is disconnected with regional power system planning, and the factors all cause the current photovoltaic consumption problem.
As is well known, power system planning includes load prediction, power supply planning, and power grid planning, where the power supply planning and the power grid planning supplement each other and interact with each other. In order to support the development of new energy power generation, China gives great incentive and support to new energy enterprises in new energy policies, and accordingly, the investment of new energy industries is hot. Because the earlier stage work flow of the photovoltaic power station project is simple, the construction period is short, and China is in the process of developing photovoltaic power generation at a high speed, the phenomena of disordered planning construction and large amount of resource waste of the photovoltaic power station are increasingly prominent. In order to solve the problems of photovoltaic development and consumption, power grid enterprises in China have increased power grid construction strength in recent years, but power grid project auditing is relatively complex, scheme determination is slow, and construction period is long, so that construction of a photovoltaic power station and planning and construction of a power grid are asynchronous, and coordinated development of the planning and construction of the photovoltaic power station and the power grid cannot be realized.
Fig. 2 is a schematic diagram of the operation of the optical storage grid-connected system of the present invention.
Aiming at the problems of disordered construction, difficult photovoltaic consumption and the like of a large number of existing photovoltaic power stations, the coordination planning research of photovoltaic, energy storage and a power grid is provided on the basis of planning annual load prediction by considering the improvement effect of power grid expansion planning and energy storage system grid connection on photovoltaic consumption and combining a renewable energy quota system, and the game relation analysis of the optical storage network is firstly carried out.
Photovoltaic power stations, energy storage systems and power grid companies are interconnected and interactive in the operation process of the whole system, and benefits are related. The strategy of the photovoltaic power station is grid-connected capacity, and the installed capacity influences the green certificate transaction yield of a power grid enterprise and the auxiliary service yields of peak shaving, standby and the like of an energy storage system; the strategy of a power grid company is an expansion planning scheme of a grid structure, and the change of the grid structure is related to the on-grid consumption of photovoltaic electric quantity; the strategy of the energy storage system is planning capacity, peak regulation and standby capacity of the energy storage system restrict consumption of photovoltaic electric quantity, and the condition of completing the renewable energy quota system of the power grid is influenced. Therefore, decision variables of the photovoltaic system, the energy storage system and the power grid are mutually influenced to form a game relation.
Fig. 3 is a flowchart of a source coordination planning method for an optical storage access network according to the present invention.
Step S1: and configuring original data and related information parameters including output characteristic data of the photovoltaic generator set, load management information, electricity price related conditions, the generator set and related equipment cost and the like, and inputting the original data and the related information parameters into a model.
Step S2: and analyzing the strategy selection of each party to form a game strategy set. Grid company grid frame construction scheme strategy set: and simulating the system condition under each photovoltaic unit operation strategy, and removing the obvious grid construction scheme with low cost performance through a GA algorithm. Photovoltaic power plant and energy storage equipment strategy set: and in a reasonable capacity construction range, the capacities of the photovoltaic unit and the energy storage equipment are gradually increased from zero to an upper limit.
Step S3: and forming a game tree according to a game theory. The photovoltaic decision sets, the energy storage equipment decision sets and the grid planning decision sets are arranged in a sequencing and layering mode.
Step S4: and according to the original data and the relevant information parameters input in the step S1, performing analog simulation on the dispatching behavior of the power system, calculating the income conditions of the photovoltaic unit, the energy storage equipment and the power grid company on each branch line of the game tree, and measuring the income level of the game tree.
Step S5: game tree simplification. Searching forwards from the key position of the current game tree, finding out all the minimum sub-games in the game tree, calculating the Nash equilibrium solution of the minimum sub-games, then, regarding the initial point positions of the sub-games as the terminal position of the original game, and marking the three-party strategy selection and income conditions reaching the Nash equilibrium on the new terminal position to replace the sub-games; and repeating the steps on the simplified game tree, and reversely advancing to the initial knot of the original game tree.
Step S6: and judging whether the system finds the sub-game refining Nash equilibrium. If the balance is found, go to step S7; if no equalization is found, the process returns to step S2.
Step S7: and outputting the Nash equilibrium solution of the game. According to the method, horizontal year photovoltaic power station, energy storage system and power grid enterprise planning are taken as research objects, the influence of market environment is considered, renewable energy quota and a green certificate transaction mechanism are introduced, an optical-storage-network coordinated planning game model is established based on a non-cooperative game theory, the problem of uncoordinated planning of photovoltaic and power grid under the current market environment is researched and explored, the positivity of power grid for photovoltaic consumption is improved, disordered expansion of photovoltaic power stations is avoided, and an improvement scheme can be provided for the problem of uncoordinated field and network in the planning of the current photovoltaic power stations.

Claims (2)

1. A power grid planning method under a light storage access condition based on a game theory comprises the following steps:
step S1: and configuring original data and related information parameters including output characteristic data of the photovoltaic generator set, load management information, electricity price related conditions, the generator set and related equipment cost and the like, and inputting the original data and the related information parameters into a model.
Step S2: and analyzing the strategy selection of each party to form a game strategy set. Grid company grid frame construction scheme strategy set: and simulating the system condition under each photovoltaic unit operation strategy, and removing the obvious grid construction scheme with low cost performance through a GA algorithm. Photovoltaic power plant and energy storage equipment strategy set: and in a reasonable capacity construction range, the capacities of the photovoltaic unit and the energy storage equipment are gradually increased from zero to an upper limit.
Step S3: and forming a game tree according to a game theory. The photovoltaic decision sets, the energy storage equipment decision sets and the grid planning decision sets are arranged in a sequencing and layering mode.
Step S4: and according to the original data and the relevant information parameters input in the step S1, performing analog simulation on the dispatching behavior of the power system, calculating the income conditions of the photovoltaic unit, the energy storage equipment and the power grid company on each branch line of the game tree, and measuring the income level of the game tree.
Step S5: game tree simplification. Searching forwards from the key position of the current game tree, finding out all the minimum sub-games in the game tree, calculating the Nash equilibrium solution of the minimum sub-games, then, regarding the initial point positions of the sub-games as the terminal position of the original game, and marking the three-party strategy selection and income conditions reaching the Nash equilibrium on the new terminal position to replace the sub-games; and repeating the steps on the simplified game tree, and reversely advancing to the initial knot of the original game tree.
Step S6: and judging whether the system finds the sub-game refining Nash equilibrium. If the balance is found, go to step S7; if no equalization is found, the process returns to step S2.
Step S7: and outputting the Nash equilibrium solution of the game.
2. The power grid planning method under the optical storage access condition based on the game theory as claimed in claim 1, wherein the photovoltaic, energy storage and power grid three-way income expression in step S4 is as follows:
A. photovoltaic power station revenue
Yield F of photovoltaic power stationPComposed of its income and cost fees, the income includes annual electric power sale income WP，SELNew energy subsidy of government WP，SUBWaste income W of photovoltaic cellsP，SCR(ii) a The cost comprises the initial construction cost C of the photovoltaic power stationp，INVOperation maintenance cost Cp，WOMAnd running assessment cost Cp，ASS. China has strict assessment standards for power fluctuation and prediction of large-scale photovoltaic power stations after grid connection, and the method is as follows.
The average absolute errors of short-term and ultra-short-term power prediction months of the photovoltaic power station are regulated to be respectively less than 15% and 10%, and when the average absolute errors exceed 1%, the average absolute errors are evaluated according to the capacity of a loading machine multiplied by 0.2 min/MW, and each minute corresponds to 1000-element punishment amount.
The photovoltaic power station revenue function is as follows:
Figure FSA0000199644180000021
in the formula: wP，SCR＝PPDPIn which P isPFor installed capacity of photovoltaic power stations, DPPhotovoltaic scrap revenue per unit power; cP，INV＝PPUPWherein U isPPhotovoltaic cost per unit power; cP，WOM＝PPMPWherein M isPThe photovoltaic annual maintenance cost per unit power; τ is Bank interest Rate, TPIn order to provide a photovoltaic power station with a long service life,
Figure DEST_PATH_GSB0000190225860000039
is the equivalent annual coefficient of the equipment.
B. Energy storage system revenue
Similar to photovoltaic power plants, yield F of energy storage systemsBBut also by its revenue and various cost fees. The method mainly considers peak shaving and standby service of the energy storage system in the operation of a power grid, and the income W of the auxiliary service provided by the energy storage systemB，AUX(ii) a The cost comprises the cost C of purchasing electricity from the power gridB，PURInitial construction cost
Figure FSA00001996441800000212
And operating maintenance cost CB，WOM. Herein, the energy storage system auxiliary service revenue is calculated as follows:
Figure FSA0000199644180000022
in the formula: c. CPEPeak shaving income as a unit; c. CRESpare income for the unit;
Figure DEST_PATH_GSB0000190225860000032
the energy storage in a time interval participates in the standby capacity of the system,
Figure DEST_PATH_GSB0000190225860000033
wherein
Figure DEST_PATH_GSB0000190225860000034
The energy is stored for a period of time,
Figure DEST_PATH_GSB0000190225860000035
and the time interval energy storage participates in peak shaving electric quantity.
The energy storage system revenue function is as follows:
Figure 2
in the formula: cost of electricity purchase
Figure FSA0000199644180000028
Wherein
Figure FSA0000199644180000029
For a period t, storing the amount of power purchased from the grid, λBA purchase price for a unit of electricity; initial construction cost CB，INVAnd operating maintenance cost CB，WOMThe calculation is similar to that of the photovoltaic power station, and only the corresponding variables need to be changed into the variables of the energy storage system, which is not described herein again. The compensation cost of the energy storage system participating in the auxiliary service is derived from the power plant grid-connected operation management and examination cost and the difference fund of the generator set debugging and operation period.
C. Revenue for grid company
Income of the power grid company is income W from power selling thereofG，SELGreen certificate transaction revenue WG，TGCAnnual electricity purchase cost C from photovoltaic power stationG，PURGrid expansion cost for photovoltaic accommodation
Figure FSA00001996441800000216
And the like. The green certificate transaction income is calculated as follows, if the renewable energy quota requirement of a power grid company is N, the actual holding quantity of the green certificate is M, the power gridThe company can obtain the benefits through the renewable energy trading market as follows:
WG，TGC＝λTGC(M-N) (4)
in the formula: wG，TGCEarnings for green certificate transactions; lambda [ alpha ]TGCThe trade price of unit electric quantity of green certificate.
The method takes 1kW & h photovoltaic electric quantity as a unit certificate face value and takes one year as a term as a green certificate settlement period. In the above equation, if M < N indicates that the grid company has failed to fulfill the government-defined renewable energy quota obligation, W isG，TGCThe expense of purchasing green certificates for grid companies from other stakeholders who over-complete the quota obligation.
The revenue function of the grid company is as follows:
Figure 1
in the formula:
Figure FSA0000199644180000032
wherein N isLFor alternative amplification of the total number of lines, CkIs the average cost of the kth line, LkThe line length is amplified for the kth alternative.
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Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN112560284A (en) * 2020-12-24 2021-03-26 国网河北省电力有限公司经济技术研究院 Power distribution network planning method for multi-subject game and terminal equipment
CN113554219A (en) * 2021-07-02 2021-10-26 国网安徽省电力有限公司电力科学研究院 Renewable energy power station shared energy storage capacity planning method and device
CN117937474A (en) * 2024-03-20 2024-04-26 保定博堃元信息科技有限公司 New energy station energy storage management method and system

Cited By (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN112560284A (en) * 2020-12-24 2021-03-26 国网河北省电力有限公司经济技术研究院 Power distribution network planning method for multi-subject game and terminal equipment
CN112560284B (en) * 2020-12-24 2022-04-08 国网河北省电力有限公司经济技术研究院 Power distribution network planning method for multi-subject game and terminal equipment
CN113554219A (en) * 2021-07-02 2021-10-26 国网安徽省电力有限公司电力科学研究院 Renewable energy power station shared energy storage capacity planning method and device
CN113554219B (en) * 2021-07-02 2023-11-07 国网安徽省电力有限公司电力科学研究院 Method and device for planning shared energy storage capacity of renewable energy power station
CN117937474A (en) * 2024-03-20 2024-04-26 保定博堃元信息科技有限公司 New energy station energy storage management method and system

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