CN111476412A - Photovoltaic power generation cost allocation research method considering carbon footprint and transaction - Google Patents

Photovoltaic power generation cost allocation research method considering carbon footprint and transaction Download PDF

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CN111476412A
CN111476412A CN202010259099.2A CN202010259099A CN111476412A CN 111476412 A CN111476412 A CN 111476412A CN 202010259099 A CN202010259099 A CN 202010259099A CN 111476412 A CN111476412 A CN 111476412A
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何后裕
何华琴
高领军
陈钢
王彦铭
黄东明
蔡秀雯
马会军
郑维明
李志伟
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State Grid Fujian Electric Power Co Ltd
Quanzhou Power Supply Co of State Grid Fujian Electric Power Co Ltd
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Abstract

The invention provides a photovoltaic power generation cost apportionment research method considering carbon footprint and transaction, which comprises the following steps: A. constructing a power generation cost allocation model based on a repeated game; B. and D, performing rolling optimization solution on the model constructed in the step A. Aiming at the PPGP and the COCE, a repeated game model for photovoltaic power generation cost sharing is established, influence factors of the power generation cost are researched by combining with a carbon transaction background, the carbon transaction can effectively improve the income of the power generation side, and the reasonability and the necessity of comprehensively considering double influences of carbon price discount and electricity price discount on the recovery years of the power generation cost when the PPGP takes preferential measures to users who consume nearby are verified.

Description

Photovoltaic power generation cost allocation research method considering carbon footprint and transaction
Technical Field
The invention belongs to the field of energy storage system optimization, and particularly relates to a photovoltaic power generation cost apportionment research method considering carbon footprint and transaction.
Background
With the improvement of marketization of distributed photovoltaic power generation, the distributed photovoltaic power generation gradually moves to market competition from policy subsidies, a criterion for properly reducing the distributed photovoltaic subsidies is provided from a notice about adjusting the power price of the new energy benchmarks on the internet in the release of a reform commission in 2017 until a distributed photovoltaic power generation project is permitted to enter market trading, the subsidies of the distributed photovoltaic power generation are further adjusted in 2019, subsidy objects comprise household distributed photovoltaic power generation grid-connected projects which are built into grid connection and do not fit into the national subsidy range, and a batch of flat price and bidding projects are also presented in the current market. In fact, at present, a considerable part of installation bodies of distributed power generation are producers and consumers of photovoltaic power generation, namely, self-service, and the rest electric quantity is connected to the grid for transaction. With the decrease of the supporting strength of the distributed Photovoltaic project and the fluctuation of the cost of the Photovoltaic material, the increasing of the internet competition degree of the distributed Photovoltaic project provides a new challenge for the power generation cost sharing of the PPGP (Photovoltaic power generation consumer).
At present, the carbon trading and the power generation market are fused deeply, the carbon trading provides a new way for cost allocation of a distributed photovoltaic power generation project, but decision support of specific cost allocation is not provided for distributed photovoltaic power generation providers under the background of the carbon trading. In addition, the distributed photovoltaic power generation project does not have carbon emission, the carbon emission is generated in the process from production to operation of the photovoltaic power generation project, fine modeling is not performed on the carbon emission in the whole process from production to abandonment of the photovoltaic power generation in the existing research, and if PPGP is added into carbon market trading, the carbon cost of power generation cannot be ignored, and the carbon emission cost should be brought into the power generation cost of the distributed photovoltaic power generation project. And less research is currently being conducted on this aspect.
Disclosure of Invention
The invention aims to provide a photovoltaic power generation cost apportionment research method considering Carbon footprint and transaction, which aims at the defects of the prior art, establishes a repeated game model for photovoltaic power generation cost apportionment aiming at PPGP and COCE (Consumer of Carbon and Electricity), develops research on influence factors of power generation cost by combining with Carbon transaction background, shows that the Carbon transaction can effectively improve the income of a power generation side, and verifies the reasonability and necessity of comprehensively considering double influences of Carbon price discount and Electricity price discount on the recovery age of the power generation cost when the PPGP takes preferential measures to users who consume nearby.
The invention is realized by the following technical scheme:
a photovoltaic power generation cost apportionment research method considering carbon footprint and transaction is characterized in that: the method comprises the following steps:
A. constructing a power generation cost allocation model based on a repeated game;
B. and D, performing rolling optimization solution on the model constructed in the step A.
Further, the step a comprises the following steps:
a1, under the condition of considering carbon footprint, determining total comprehensive electricity generation cost function of PPGP year
Figure BDA0002438608180000021
Figure BDA0002438608180000022
Wherein the content of the first and second substances,
Figure BDA0002438608180000023
annual electric quantity benefit for photovoltaic power generation;
Figure BDA0002438608180000024
subsidies are provided for annual photovoltaic power generation cost of government; cPPGPStatic investment for a project of photovoltaic power generation;
Figure BDA0002438608180000025
annual revenue for PPGP to participate in carbon trading; (A)0,A1,A2...At-1) Representing historical actions t years ago, the PPGP and COCE consider the influence of the past actions on the current strategy space omega and the revenue function phi;
a2, determining COCE minimum comprehensive energy cost model Celeccarbon：
Figure BDA0002438608180000031
Wherein, CelecAnnual electricity consumption cost for COCE;
Figure BDA0002438608180000032
the electric quantity income for annual partition wall trading; ccarbonAnnual carbon purchase cost for COCE;
Figure BDA0002438608180000033
cost for year on-site trading of COCE and PPGP;
Figure BDA0002438608180000034
carbon trading prices for the vth order for the xth entry into the carbon market;
Figure BDA0002438608180000035
carbon emissions at the v-th carbon exchange;
Figure BDA0002438608180000036
annual carbon trading costs for COCE at a carbon exchange; pcarbonIs a reference carbon number; k is a radical oflocalThe preferential coefficient of the PPGP for local consumption of carbon consumers is also used as a decision variable of the PPGP;
Figure BDA0002438608180000037
contract carbon emissions for the jth carbon on-site transaction; m and n are integers respectively;
a3, determining the operation constraint conditions of the photovoltaic unit, wherein the constraint conditions comprise:
constraint condition of photovoltaic absorption rate ηlocal+ηgrid+ηself1, wherein, ηlocalη for partition wall ratiogridη for the ratio of the network-access transactionsselfRatio for spontaneous self-use of PPGP;
the maximum photovoltaic annual utilization hour upper and lower limit constraint conditions are as follows: hpv·t,min≤Hpv·t≤Hpv·t,maxWherein H ispv·tThe number of photovoltaic utilization hours for the area;
unit photovoltaic cost upper and lower limit constraint conditions: c. Cq,min{qmin,qmax}≤cq≤cq,max{qmin,qmaxIn which c isqThe unit photovoltaic cost under q capacity, q represents the capacity range;
photovoltaic capacity upper and lower limit constraint conditions:
Figure BDA0002438608180000038
wherein the content of the first and second substances,
Figure BDA0002438608180000039
the capacity of a photovoltaic power generation project to be put into operation within the q capacity range;
carbon responsibility coefficient constraint conditions of each stage of COCE: 0 < pi1,π2,π3Less than or equal to 1, wherein, pi1Produced for photovoltaic modulesCarbon coefficient of responsibility,. pi2Carbon liability coefficient for photovoltaic module transportation; pi3The emission reduction distribution coefficient of the photovoltaic module in the recycling and disassembling process is obtained,
Figure BDA00024386081800000310
w is the life span of the photovoltaic power generation, and mu is the number of years consumed for recovering the photovoltaic module.
Further, in the step a1, the annual electric quantity benefit of photovoltaic power generation
Figure BDA0002438608180000041
Comprises the following steps:
Figure BDA0002438608180000042
wherein the content of the first and second substances,
Figure BDA0002438608180000043
in order to gain the annual network-access electric quantity,
Figure BDA0002438608180000044
the self-power utilization income for the year;
annual network electric quantity income
Figure BDA0002438608180000045
The method specifically comprises the following steps:
Figure BDA0002438608180000046
wherein the content of the first and second substances,
Figure BDA0002438608180000047
in order to gain the electric quantity for the annual partition wall transaction,
Figure BDA0002438608180000048
electric quantity profit for annual network-entry transaction, PpvIs the installed capacity of PPGP, PelecUser directory electricity prices for the grid where the PPGP is located, ξlocalThe preferential coefficient of PPGP for local consumption of user partition transactions can be taken as PA decision variable for PGP;
annual self-consumption of electricity
Figure BDA0002438608180000049
The method specifically comprises the following steps:
Figure BDA00024386081800000410
further, in the step A1, the static investment C for the project of photovoltaic power generationPPGPComprises the following steps:
Figure BDA00024386081800000411
wherein, CcThe investment for the construction of photovoltaic power generation, which is mainly related to capacity, CcarbonThe annual carbon cost for a photovoltaic power generation project,
Figure BDA00024386081800000412
as the amount of carbon emissions in the i-th production stage,
Figure BDA00024386081800000413
as the carbon emissions during the ith transportation phase,
Figure BDA00024386081800000414
is the carbon emission from the i-th recovery stage of the y-th year.
Further, in the step A1, the PPGP participates in the annual income of the carbon trading
Figure BDA00024386081800000415
The method specifically comprises the following steps:
Figure BDA00024386081800000416
wherein the content of the first and second substances,
Figure BDA00024386081800000417
match carbon price for j-th transaction, EtotalFor total annual carbon emissions, EcomIs the sum of the PPGP displacement reductions.
Further, the step a2 is specifically: and B, performing rolling solution on the model constructed in the step A based on the MOEA/D-DRA algorithm, and obtaining a Nash equilibrium solution on a Pareto surface.
The invention has the following beneficial effects:
1. the method is characterized in that the cost allocation problem of a distributed power generation project is emphasized, the influence of the participation of typical photovoltaic power generators such as PPGP in carbon trading on the power generation cost of the distributed power generators is explained under the mode that the distributed power generators can participate in carbon market trading and 'self-supply and surplus surfing', the carbon footprint of power generation is tracked based on the whole life cycle of the distributed photovoltaic project, a repeated game model for allocating the power generation cost is established, the established model is subjected to rolling optimization solution, the influence of the carbon footprint and the carbon trading on the power generation cost is researched, a basis is provided for establishing an admission rule of the distributed power generators entering the carbon market, a reference is provided for economy of the distributed power generators in measuring and calculating installed capacity, and the phenomenon that the PPGP gives a low electricity price discount rate to COCE in the nearby consumption of electric energy and carbon emission is avoided.
Drawings
The present invention will be described in further detail with reference to the accompanying drawings.
FIG. 1 is a Pareto chart for two types of transactions
FIG. 2 is a Pareto disaggregation diagram for two types of transactions
FIG. 3 is a graph showing the influence of carbon number on the cost of power generation
FIG. 4 is a graph of the impact of PPGP profitability on power generation cost
Detailed Description
As shown in fig. 1, in the context of carbon transaction, taking the PPGP and the COCE participating in the power generation cost apportionment game in the first year as an example, a MOEA/D-DRA algorithm is adopted to obtain a Pareto surface and a Nash solution; FIG. 2 is a graph showing Pareto solution sets of decision variables in two modes of traditional spontaneous self-use and carbon-containing transactions; FIG. 3 is a diagram illustrating an analysis of the impact of carbon price changes on the cost of electricity generation after PPGP participates in carbon trading; FIG. 4 shows an analysis of the impact of PPGP preferential rates on power generation costs.
The photovoltaic power generation cost apportionment research method considering the carbon footprint and the transaction comprises the following steps:
A. constructing a power generation cost allocation model based on a repeated game;
the power generation cost of the PPGP is shared between the PPGP and the COCE, so that the PPGP and the COCE have game behaviors, and the PPGP and the COCE respectively develop repeated games within the power generation operation period by taking the minimum comprehensive power generation cost and the minimum comprehensive energy cost (only including a transaction part with the PPGP) as targets in the process of ensuring the power and carbon emission;
the method specifically comprises the following steps:
a1, under the condition of considering carbon footprint, determining total comprehensive electricity generation cost function of PPGP year
Figure BDA0002438608180000061
Figure BDA0002438608180000062
Wherein the content of the first and second substances,
Figure BDA0002438608180000063
annual electric quantity benefit for photovoltaic power generation;
Figure BDA0002438608180000064
subsidies are provided for annual photovoltaic power generation cost of government; cPPGPStatic investment for a project of photovoltaic power generation;
Figure BDA0002438608180000065
annual revenue for PPGP to participate in carbon trading;
Figure BDA0002438608180000066
is that
Figure BDA0002438608180000067
Decision space representation on game theory, (A)0,A1,A2…At-1) Representing historical actions t years ago, PPGP and COCE consider the impact of past actions on the current policy space Ω and the revenue function Φ, A0,A1,A2…At-1Each decision space is represented respectively, and the strategy space omega and the revenue function phi are a defined way and are mathematical expressions of the theory;
annual electric quantity gain of photovoltaic power generation
Figure BDA0002438608180000068
Comprises the following steps:
Figure BDA0002438608180000069
wherein the content of the first and second substances,
Figure BDA00024386081800000610
in order to gain the annual network-access electric quantity,
Figure BDA00024386081800000611
the self-power utilization income for the year;
annual network electric quantity income
Figure BDA00024386081800000612
The method specifically comprises the following steps:
Figure BDA00024386081800000613
wherein the content of the first and second substances,
Figure BDA00024386081800000614
in order to gain the electric quantity for the annual partition wall transaction,
Figure BDA00024386081800000615
electric quantity profit for annual network-entry transaction, PpvIs the installed capacity of PPGP, PelecUser directory electricity prices for the grid where the PPGP is located, ηlocalη for partition wall ratiogridξ for the ratio of the network-access transactionslocalThe discount coefficient of the user partition wall transaction is consumed for the PPGP, and can be used as a decision variable of the PPGP;
annual self-consumption of electricity
Figure BDA0002438608180000071
The method specifically comprises the following steps:
Figure BDA0002438608180000072
wherein, ηlocalη for partition wall ratiogridIs the rate of the online transaction; ppvInstalled capacity of PPGP, Hpv·tFor the number of photovoltaic utilization hours, P, of the areaelecThe user catalog electricity price of the power grid where the PPGP is located;
static investment for photovoltaic power generation projects CPPGPComprises the following steps:
Figure BDA0002438608180000073
wherein, CcThe investment for the construction of photovoltaic power generation, which is mainly related to capacity, CcarbonAnnual carbon cost for photovoltaic power generation projects, cqThe cost per unit photovoltaic cost at q capacity, q denotes the capacity range,
Figure BDA0002438608180000074
for the capacity, P, of the photovoltaic power generation project to be put into operation within the q capacity rangecarbonIs taken as the carbon value of the standard,
Figure BDA0002438608180000075
as the amount of carbon emissions in the i-th production stage,
Figure BDA0002438608180000076
as the carbon emissions during the ith transportation phase,
Figure BDA0002438608180000077
carbon emissions for the ith recovery stage of the y-th year;
annual revenue for PPGP participation in carbon trading
Figure BDA0002438608180000078
The method specifically comprises the following steps:
Figure BDA0002438608180000079
wherein, PcarbonIs the base carbon number, klocalThe preferential coefficient of the PPGP for local consumption of carbon consumers is also used as a decision variable of the PPGP,
Figure BDA00024386081800000710
the contract carbon emissions for the jth carbon on site transaction,
Figure BDA00024386081800000711
for the matching carbon value of the jth transaction,
Figure BDA00024386081800000712
carbon emissions at the j-th carbon exchange, EtotalFor total annual carbon emissions, EcomIs the sum of PPGP displacement reduction when Etotal＞EcomIn time, the COCE may choose to divide the carbon quota into two parts, one part transacts with the PPGP locally, and the other part can enter the carbon exchange for transaction;
a2, determining COCE minimum comprehensive energy cost model Celeccarbon：
Figure BDA0002438608180000081
Wherein, CelecAnnual electricity consumption cost for COCE;
Figure BDA0002438608180000082
the electric quantity income for annual partition wall trading; ccarbonAnnual carbon purchase cost for COCE;
Figure BDA0002438608180000083
cost for year on-site trading of COCE and PPGP;
Figure BDA0002438608180000084
the carbon trading price for the xth order into the carbon market, and, correspondingly,
Figure BDA0002438608180000085
the carbon transaction amount in this order;
Figure BDA0002438608180000086
carbon emissions at the v-th carbon exchange;
Figure BDA0002438608180000087
annual carbon trading costs for COCE at a carbon exchange; pcarbonIs a reference carbon number; k is a radical oflocalThe preferential coefficient of the PPGP for local consumption of carbon consumers is also used as a decision variable of the PPGP;
Figure BDA0002438608180000088
contract carbon emissions for the jth carbon on-site transaction; m and n are integers respectively;
a3, determining the operation constraint conditions of the photovoltaic unit, wherein the constraint conditions comprise:
constraint condition of photovoltaic absorption rate ηlocal+ηgrid+η self1, wherein, ηlocalη for partition wall ratiogridη for the ratio of the network-access transactionsselfRatio for spontaneous self-use of PPGP;
the maximum photovoltaic annual utilization hour upper and lower limit constraint conditions are as follows: hpv·t,min≤Hpv·t≤Hpv·t,maxWherein H ispv·tThe number of photovoltaic utilization hours for the area;
unit photovoltaic cost upper and lower limit constraint conditions: c. Cq,min{qmin,qmax}≤cq≤cq,max{qmin,qmaxIn which c isqThe unit photovoltaic cost under q capacity, q represents the capacity range;
the marginal cost exists in photovoltaic modules with the same level capacity, and due to the restriction of production technology and production line on the upper and lower limits of the capacity, the corresponding cost also has the upper and lower limits, namely the constraint conditions of the upper and lower limits of the photovoltaic capacity:
Figure BDA0002438608180000089
wherein the content of the first and second substances,
Figure BDA00024386081800000810
the capacity of a photovoltaic power generation project to be put into operation within the q capacity range;
carbon responsibility coefficient constraint conditions of each stage of COCE: 0 < pi1,π2,π3Less than or equal to 1, wherein, pi1Carbon liability factor, pi, for photovoltaic module production2Carbon liability coefficient for photovoltaic module transportation; pi3The emission reduction distribution coefficient of the photovoltaic module in the recycling and disassembling process is obtained,
Figure BDA0002438608180000091
w is the life span of the photovoltaic power generation, and mu is the number of years consumed by recovering the photovoltaic module; the carbon responsibility coefficient of each stage cannot be 0 or 1, namely the carbon emission behavior of the photovoltaic power generation project cannot be exempted from responsibility or be identified as full responsibility;
B. and C, performing rolling optimization solution on the model constructed in the step A, specifically: and B, performing rolling solution on the model constructed in the step A based on the MOEA/D-DRA algorithm, and obtaining a Nash equilibrium solution on a Pareto surface.
Taking 1MW distributed photovoltaic power generation project of a certain town of spring city in Fujian province as an example, the typical annual utilization hours of photovoltaic power generation in the region is 1200h, the on-pole net power price is 0.3932 yuan/kw · h, the catalog power price of an industrial user is 0.5954 yuan/kw · h, the typical manufacturing cost of a photovoltaic power generation system is 5500 yuan/kw, the benchmark carbon price is assumed to be 20 yuan/T, the partition wall absorption ratio is 0.5, the ratio of network access transaction is 0.3, the carbon responsibility coefficient in the production and transportation stage is 0.5, the distributed photovoltaic power generation service life is 25 years, the carbon reduction volume in the photovoltaic recovery stage is 3.02 × 105kg according to 1MW capacity, the transport distance of a photovoltaic module is assumed to be 1000km, the carbon reduction volume in the production and transportation stage is about 2.03 × 105T, the carbon demand of COCE is greater than the annual reduction volume of PPGP, the carbon demand of COCE is 1800T, and the accounting process is as follows:
assume that COCE is a cement producer, coverage: carbon dioxide generated in the clinker production section and the cement grinding section is discharged. The distribution method comprises the following steps: the baseline method.
1) The calculation formula of the carbon emission in Fujian province is as follows:
Figure BDA0002438608180000092
in the formula (I), the compound is shown in the specification,
Figure BDA0002438608180000093
the emission of CO2 is ton per year of the cement plant; b isclinkerThe emission standard of CO2 in the clinker production section is set; qclinkerThe clinker yield is obtained; b isgrindDischarging reference for CO2 in the grinding section; qcementThe cement yield is obtained.
2) Calculating the value of a formula parameter, BclinkerTaking 0.8582T CO2/T clinker Bgrind0.0152T CO2/T cement is taken, 100 ten thousand tons of clinker is produced by the cement plant in a certain year, 50 ten thousand tons of cement has carbon quota of 0.8658 × 106T, actual carbon emission of 0.8676 × 106T and excess of 1.8 × 103T.
(2) Economic comparison of two transaction patterns
The economic indicators for the two transaction models are paired as shown in table 1:
TABLE 1 comparison of economics of two transaction patterns
Figure BDA0002438608180000101
After the carbon transaction is embedded into the electric energy transaction, the electricity generation cost of the PPGP is reduced by 5%, the age of static investment recovery is advanced by one year, the electricity price profit rate is improved by 0.4%, although the carbon cost of the PPGP photovoltaic system increases the comprehensive cost of electricity generation, the carbon transaction performed in the electricity generation process plays a positive role in reducing the cost, and the enthusiasm of the PPGP in participating in the electricity market and carbon market transactions is improved.
(3) Decisions under Pareto-Nash
According to the game analysis in the step A, taking the PPGP and COCE as an example of the game for sharing the power generation cost in the first year under the background of carbon transaction, and adopting an MOEA/D-DRA algorithm to obtain a Pareto surface and a Nash solution. In fig. 1, comparing the Pareto front of the spontaneous self-use margin internet of the traditional spontaneous self-use and carbon-containing transactions, f1 and f2 respectively represent the comprehensive power generation cost of PPGP and the comprehensive energy consumption cost of COCE, and it can be seen that there is a conflict between the two costs, which cannot be reduced simultaneously. Although the carbon-containing transaction increases the comprehensive energy cost of COCE, the cost still exists as long as the carbon exceeds the total cost, but the transaction object is no longer PPGP, and for PPGP, the carbon transaction shrinks the Pareto front, namely the comprehensive cost of generating electricity is obviously reduced.
FIG. 2 shows Pareto solution sets of decision variables in two transaction modes, each straight line represents a Pareto leading edge solution, and it can be seen that the solution sets have good distributionlocalAnd klocalThe values of (A) are respectively 0.84 and 0.95, the local carbon contract trading volume is 854.9T, and the waybill trading volume in the carbon market is 945.1T.
(4) Power generation cost impact analysis
1) Influence of carbon value on Power Generation cost
Fig. 3 shows that the fluctuation of the carbon price affects the costs of distributed photovoltaic power generation with different capacities, the higher the carbon price is, the shorter the recovery time of the power generation cost is, wherein the recovery years of the power generation cost within the fluctuation range of the carbon price are approximately the same for the two types of installed capacities of 0.5kW and 1MW, if the same recovery years are reached, the small capacity project only needs to be carried out at the carbon price of 10 yuan/T, and the 5MW capacity project needs to be carried out at the carbon price of about 30 yuan/T, so that the large installed capacity PPGP needs to enter the carbon market to be developed for trading in the carbon price view, and the apportionment of the power generation cost is more favorable. The cost contribution of electricity generation by the large installed capacity PPGP is less dependent on carbon value.
2) Influence of PPGP (Point-to-Point protocol) discount rate on power generation cost
The PPGP gives the COCE a discount in both the electricity price and the carbon price, the COCE cannot be attracted to participate in the transaction of local consumption due to insufficient discount, the power generation cost is increased due to too high discount rate, and the influence of the two types of discount rates on the recovery age of the power generation cost is shown in FIG. 4; on the other hand, the carbon price discount coefficient exerts an influence on the basis of the discount of the electricity price, when the discount strength of the electricity price is the maximum, the carbon price is not discounted, the cost recovery period is prolonged, the discount strength of the electricity price is moderate or small, and the carbon price is discounted, so that the cost recovery period is shortened. Therefore, the PPGP considers the negative impact of the power price discount due to the excessive power price discount when making the discount policy.
The above description is only a preferred embodiment of the present invention, and therefore should not be taken as limiting the scope of the invention, which is defined by the appended claims and their equivalents and modifications within the scope of the description.

Claims (6)

1. A photovoltaic power generation cost apportionment research method considering carbon footprint and transaction is characterized in that: the method comprises the following steps:
A. constructing a power generation cost allocation model based on a repeated game;
B. and D, performing rolling optimization solution on the model constructed in the step A.
2. The method of photovoltaic power generation cost sharing research considering carbon footprint and trading of claim 1, wherein: the step A comprises the following steps:
a1, under the condition of considering carbon footprint, determining total comprehensive electricity generation cost function of PPGP year
Figure FDA0002438608170000011
Figure FDA0002438608170000012
Wherein the content of the first and second substances,
Figure FDA0002438608170000013
annual electric quantity benefit for photovoltaic power generation;
Figure FDA0002438608170000014
subsidies are provided for annual photovoltaic power generation cost of government; cPPGPStatic investment for a project of photovoltaic power generation;
Figure FDA0002438608170000015
annual revenue for PPGP to participate in carbon trading; (A)0,A1,A2...At-1) Representing historical actions t years ago, the PPGP and COCE consider the influence of the past actions on the current strategy space omega and the revenue function phi;
a2, determining COCE minimum comprehensive energy cost model Celeccarbon：
Figure FDA0002438608170000016
Wherein, CelecAnnual electricity consumption cost for COCE;
Figure FDA0002438608170000017
the electric quantity income for annual partition wall trading; ccarbonAnnual carbon purchase cost for COCE;
Figure FDA0002438608170000018
cost for year on-site trading of COCE and PPGP;
Figure FDA0002438608170000019
carbon trading prices for the vth order for the xth entry into the carbon market;
Figure FDA00024386081700000110
carbon emissions at the v-th carbon exchange;
Figure FDA00024386081700000111
annual carbon trading costs for COCE at a carbon exchange; pcarbonIs a reference carbon number; k is a radical oflocalThe preferential coefficient of the PPGP for local consumption of carbon consumers is also used as a decision variable of the PPGP;
Figure FDA00024386081700000112
contract carbon emissions for the jth carbon on-site transaction; m and n are integers respectively;
a3, determining the operation constraint conditions of the photovoltaic unit, wherein the constraint conditions comprise:
constraint condition of photovoltaic absorption rate ηlocal+ηgrid+ηself1, wherein, ηlocalη for partition wall ratiogridη for the ratio of the network-access transactionsselfRatio for spontaneous self-use of PPGP;
the maximum photovoltaic annual utilization hour upper and lower limit constraint conditions are as follows: hpv·t,min≤Hpv·t≤Hpv·t,maxWherein H ispv·tThe number of photovoltaic utilization hours for the area;
unit photovoltaic cost upper and lower limit constraint conditions: c. Cq,min{qmin,qmax}≤cq≤cq,max{qmin,qmaxIn which c isqThe unit photovoltaic cost under q capacity, q represents the capacity range;
photovoltaic capacity upper and lower limit constraint conditions:
Figure FDA0002438608170000021
wherein the content of the first and second substances,
Figure FDA0002438608170000022
the capacity of a photovoltaic power generation project to be put into operation within the q capacity range;
carbon responsibility coefficient constraint conditions of each stage of COCE: 0 < pi1,π2,π3Less than or equal to 1, wherein, pi1Carbon liability factor, pi, for photovoltaic module production2Carbon liability coefficient for photovoltaic module transportation; pi3The emission reduction distribution coefficient of the photovoltaic module in the recycling and disassembling process is obtained,
Figure FDA0002438608170000023
w is the life span of the photovoltaic power generation, and mu is the number of years consumed for recovering the photovoltaic module.
3. The method of photovoltaic power generation cost sharing research considering carbon footprint and trading of claim 2, wherein: in the step A1, the annual electric quantity benefit of photovoltaic power generation
Figure FDA0002438608170000024
Comprises the following steps:
Figure FDA0002438608170000025
wherein the content of the first and second substances,
Figure FDA0002438608170000026
in order to gain the annual network-access electric quantity,
Figure FDA0002438608170000027
the self-power utilization income for the year;
annual network electric quantity income
Figure FDA0002438608170000028
The method specifically comprises the following steps:
Figure FDA0002438608170000029
wherein the content of the first and second substances,
Figure FDA00024386081700000210
in order to gain the electric quantity for the annual partition wall transaction,
Figure FDA00024386081700000211
electric quantity profit for annual network-entry transaction, PpvIs the installed capacity of PPGP, PelecUser directory electricity prices for the grid where the PPGP is located, ξlocalFor PPGP pair to be consumed in situThe discount coefficient of the user partition wall transaction can be used as a decision variable of the PPGP;
annual self-consumption of electricity
Figure FDA0002438608170000031
The method specifically comprises the following steps:
Figure FDA0002438608170000032
4. the method of photovoltaic power generation cost sharing research considering carbon footprint and trade according to claim 2 or 3, characterized by: static investment C for a photovoltaic power generation project in the step A1PPGPComprises the following steps:
Figure FDA0002438608170000033
wherein, CcThe investment for the construction of photovoltaic power generation, which is mainly related to capacity, CcarbonThe annual carbon cost for a photovoltaic power generation project,
Figure FDA0002438608170000034
as the amount of carbon emissions in the i-th production stage,
Figure FDA0002438608170000035
as the carbon emissions during the ith transportation phase,
Figure FDA0002438608170000036
is the carbon emission from the i-th recovery stage of the y-th year.
5. The method of photovoltaic power generation cost sharing research considering carbon footprint and trade according to claim 2 or 3, characterized by: in step A1, the annual income of the PPGP participating in the carbon transaction
Figure FDA0002438608170000037
The method specifically comprises the following steps:
Figure FDA0002438608170000038
wherein the content of the first and second substances,
Figure FDA0002438608170000039
match carbon price for j-th transaction, EtotalFor total annual carbon emissions, EcomIs the sum of the PPGP displacement reductions.
6. The method of photovoltaic power generation cost sharing research considering carbon footprint and trade according to claim 2 or 3, characterized by: the step a2 specifically includes: and B, performing rolling solution on the model constructed in the step A based on the MOEA/D-DRA algorithm, and obtaining a Nash equilibrium solution on a Pareto surface.
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