Photovoltaic and hydrogen multi-agent cooperation method considering green certificate transaction under risk management

Abstract

The application discloses a photovoltaic and hydrogen multi-agent cooperation method under risk control and considering green certificate transaction, relates to the technical field of energy cooperation, and comprises S1 green certificate modeling, S2 renewable energy consumption task modeling and S3 cooperation modeling; comprises SS1 photovoltaic model based on green certificate, SS2 introduction of CVaR of the photovoltaic model, SS3 optimization of the risk control photovoltaic model, SS4 electric hydrogen production model, SS5 introduction of CVaR of the electric hydrogen production model and SS6 optimization of the risk control electric hydrogen production model. Green certificates can bring additional benefits to each agent, stimulate each agent to obtain excess profits, and through the method, the cooperation operation of the photovoltaic system and the green hydrogen system can meet the reasonable distribution of electric energy and green certificates at the same time, and through the use of the optimization model, each agent is optimized to realize the minimization of operation cost, and through the introduction of the CvaR risk index in the cooperation model, the unnecessary risk caused by the uncertainty of the electric energy of the photovoltaic system and the load of the green hydrogen system in the cooperation in the prior art is solved.

Description

Technical Field

[0001] This invention relates to the field of energy cooperation technology, specifically to a multi-entity cooperation method for photovoltaic and hydrogen projects that takes into account green certificate trading under risk management. Background Technology

[0002] Green certificates, also known as renewable energy certificates or green labels, are used to trade renewable energy. Specialized certification bodies issue a unique code for every 1000 kilowatt-hours of electricity generated from renewable energy sources, proving its validity. In other words, 1 megawatt of green electricity is equivalent to one green certificate. Green electricity mainly comes from non-fossil energy sources such as wind, solar, geothermal, and biomass energy, with photovoltaic (PV) power generation being a part of this. Currently, people are meeting their energy needs through the development of PV power generation systems; however, the uncertainty of PV electricity leads to low consumption. Using photovoltaic power to produce hydrogen can be called "green hydrogen."

[0003] As green hydrogen systems grow larger, photovoltaic hydrogen production alone can no longer meet the demand. Therefore, photovoltaic power generation systems and green hydrogen systems can be decomposed into different themes for cooperative operation and optimization. However, in existing technologies, when green hydrogen systems involving renewable energy consumption and photovoltaic systems involving green certificates are operated in cooperation, the cooperation model involves electricity trading and green certificate trading. Electricity trading is a day-ahead transaction, while green certificate trading is a day-after transaction. The two transactions are on different time scales, which often leads to the neglect of energy randomness when dealing with energy cooperation issues, thus limiting the robustness of cooperation. In addition, the uncertainty of photovoltaic system electricity and green hydrogen system load leads to unnecessary risks in cooperation. Summary of the Invention

[0004] The purpose of this invention is to provide a multi-entity cooperation method for photovoltaic and hydrogen projects that takes into account green certificate trading under risk management, in order to solve the risks mentioned in the background art, such as the limitation of the robustness of cooperation due to the neglect of energy randomness when dealing with energy cooperation, and the uncertainty of the load of photovoltaic and green hydrogen systems.

[0005] To achieve the above objectives, this invention provides the following technical solution: a multi-entity cooperation method for photovoltaic and hydrogen green certificate trading. This method establishes a photovoltaic model based on existing green certificates and an electro-hydrogen production model based on renewable energy consumption tasks, enabling photovoltaic and electro-hydrogen production to cooperate in trading. The method includes S1 green certificate modeling, S2 renewable energy consumption task modeling, and S3 cooperation modeling; specifically as follows:

[0006] S1 Green Certificate Modeling: A mathematical model is derived based on the renewable energy generation capacity of green certificates and the conceptual representation of green certificates; the specific formula is as follows:

[0007] (1)

[0008] Modeling of the S2 renewable energy consumption task: A mathematical model is derived based on the amount of renewable energy electricity purchased by buyers; the specific formula is as follows:

[0009] (2)

[0010] S3 Cooperation Model: Based on the mathematical models obtained in S1 and S2, a multi-entity cooperation model for realizing green certificate trading in photovoltaic and hydrogen industries is obtained.

[0011] Preferably, the renewable energy generation capacity for the green certificate is 1 MWh.

[0012] A multi-entity cooperation method for photovoltaic and hydrogen projects under risk management and considering green certificate trading is presented. Based on the cooperation model obtained from the aforementioned multi-entity cooperation method for photovoltaic and hydrogen projects under green certificate trading, the Value at Risk (VaR) approach is used for risk management. A photovoltaic-to-hydrogen (HHH) cooperation model is established based on risk management and solved using the alternating direction multiplier method. The solution process includes: SS1 photovoltaic model based on green certificates; SS2 photovoltaic model with CVaR introduction; SS3 risk-controlled photovoltaic model; SS4 HHH model with CVaR introduction; SS5 HHH model with CVaR introduction; SS6 risk-controlled HHH model; SS7 multi-entity cooperation model for photovoltaic and hydrogen projects under risk management and considering green certificate trading; and SS8 cooperation model under risk management. The specific solutions are as follows:

[0013] When the photovoltaic system operates independently of the hydrogen production system, its optimization objective is to minimize its own operating costs. This includes revenue from the sale of electricity to the grid. Green certificate revenue from the sale of green certificates to the green certificate market and operation and maintenance costs ;

[0014] set up Let w be the decision variable vector for the nth photovoltaic system, including the power of electricity sold to the grid. and the number of green certificates sold to the green certificate market ;

[0015] Introduction of CVaR in SS2 Photovoltaic Model: The CVaR method is introduced to control the impact of output uncertainty on cost in the green certificate-based photovoltaic model of SS1.

[0016] SS3 risk-controlled photovoltaic model: Under the condition of taking risk into account, the CVaR index photovoltaic model in SS2 is obtained through optimization tools;

[0017] SS4 Hydrogen Production by Electricity Model: When the hydrogen production by electricity system operates independently of the photovoltaic system, the decision variables of the hydrogen production by electricity system are expressed as follows: ,in, The amount of electricity purchased from the grid by the electro-hydrogen production system at time t under scenario w; Green certificates purchased from the green certificate market for the electro-hydrogen production system within the T-cycle of scenario w; The green electricity purchased from the grid by the electro-hydrogen production system at time t under scenario w;

[0018] The operating cost of an electrohydrogen production system includes the cost of purchasing electricity from the grid. Green certificate costs Green electricity cost and maintenance costs Among these, operation and maintenance costs include the operation and maintenance costs of energy storage and EL (Energy Storage and Electron).

[0019] The CVaR introduction of the SS5 electro-hydrogen production model: The uncertainty of hydrogen load leads to operational risks in electro-hydrogen production. This represents the operational risk indicator of EL, and is used for risk control of the hydrogen load uncertainty in the electro-hydrogen production model in SS4.

[0020] SS6 Risk-Controlled Electric Hydrogen Production Model: Taking risk into account, the CVaR index electric hydrogen production model in SS5 is obtained through optimization tools;

[0021] SS7 risk management and green certificate trading multi-entity cooperation model for photovoltaic and hydrogen: including electricity cooperation and green certificate cooperation;

[0022] Electricity trading agreement: The photovoltaic system expects to sell electricity to the hydrogen-to-electricity system at a price no lower than the grid-connected electricity price, while the hydrogen-to-electricity system expects to purchase electricity from the photovoltaic system at a price no higher than the industrial electricity price; when the photovoltaic system's electricity sales price and the hydrogen-to-electricity system's electricity purchase price reach an agreement, the photovoltaic system and the hydrogen-to-electricity system reach an electricity trading agreement; the photovoltaic system sells surplus electricity to the grid, and the hydrogen-to-electricity system purchases electricity from the grid to meet surplus load demand;

[0023] Green certificate cooperation: The photovoltaic system expects to sell green certificates to the electro-hydrogen system at a price no lower than the market green certificate purchase price, while the electro-hydrogen system expects to purchase green certificates from the photovoltaic system at a price no higher than the market green certificate selling price; when the green certificate purchase price of the electro-hydrogen system and the green certificate selling price of the photovoltaic system are equal, the photovoltaic system and the electro-hydrogen system reach a green certificate transaction agreement; the photovoltaic system sells its remaining green certificates to the green certificate market, and the electro-hydrogen system purchases green certificates from the green certificate market to meet its remaining renewable energy consumption tasks;

[0024] Solving the cooperation model under SS8 risk management: The cooperation model is solved using the alternating multiplier algorithm, and the effectiveness of the proposed cooperation model is verified through numerical examples.

[0025] Preferably, the specific formula in SS1 is as follows:

[0026] (3)

[0027] (4)

[0028] (5)

[0029] (6)

[0030] (7)

[0031] In the formula: T is the scheduling period; N is the number of photovoltaic entities; W is the set of photovoltaic power output scenarios; and Z is a positive integer. Let n be the probability of the nth photovoltaic cell in scenario w. Let be the unit power generation maintenance factor for the nth photovoltaic cell; Let be the feed-in tariff of the nth photovoltaic power generation at time t; This is the price at which the nth photovoltaic model sells green certificates to the green certificate market within the T trading cycle; Let be the electrical power sold to the grid by the nth photovoltaic cell at time t under scenario w; Let be the number of green certificates sold to the grid by the nth photovoltaic power generation unit in scenario w; Let be the power generation of the nth photovoltaic cell at time t under scenario w.

[0032] Preferably, the model in SS2 that includes the photovoltaic model is:

[0033] (8)

[0034] (9)

[0035] In the formula: Let CVaR be the risk control cost indicator for the nth photovoltaic cell. Confidence level; for The nth photovoltaic cost VaR value corresponding to the quantile; As a non-negative auxiliary variable, specifically representing the operating cost of the nth photovoltaic cell in scenario w exceeding... The amount.

[0036] Preferably, the photovoltaic optimization model in SS3 that includes the CVaR index is:

[0037] (10)

[0038] (11)

[0039] (12)

[0040] In the formula: The risk aversion coefficient for the nth photovoltaic cell;

[0041] When photovoltaics are not combined with hydrogen production via electricity, the solution to the optimization problem is denoted as m*, and the optimal cost is set as... .

[0042] The preferred electro-hydrogen production model in SS4 has the following specific formula:

[0043] (13)

[0044] (14)

[0045] (15)

[0046] (16)

[0047] (17)

[0048] (18)

[0049] (19)

[0050] (20)

[0051] (twenty one)

[0052] (twenty two)

[0053] (twenty three)

[0054] (twenty four)

[0055] (25)

[0056] In the formula: Let $\math$ be the probability of hydrogen production by electrolysis in scenario $w$. For EL energy conversion rate; Let be the hydrogen production power of EL at time t; Let be the power consumption of EL at time t; This represents the upper limit of EL power consumption; This is the upper limit of climbing power; Let t be the power consumption of the compressor. The specific heat capacity constant of hydrogen; Let t be the flow rate of hydrogen compressed by the compressor. The temperature at which hydrogen is input to the compressor; The compressor efficiency is represented by K, which is the isentropic exponent of hydrogen. This refers to the compression ratio; Let t be the internal gas pressure of the hydrogen storage tank; This refers to the internal temperature of the hydrogen storage tank. This refers to the molar mass of hydrogen gas. Let t be the amount of hydrogen compressed by the compressor. Let t be the hydrogen load demand. , These represent the minimum and maximum gas pressures of the hydrogen storage tank, respectively. Store energy at time t; , These represent the minimum and maximum energy storage capacity of the energy storage system, respectively. , These represent the charging and discharging power at time t, respectively; , These are the charge and discharge efficiencies, respectively. , These are the maximum charging power and the maximum discharging power, respectively. It is a binary variable used to prevent charging and discharging processes from occurring simultaneously; The price at which electricity is purchased from the grid for hydrogen production at time t; Let t be the price at which green electricity is purchased from the grid. The price of the green certificate within cycle T; , These are the operation and maintenance coefficients for EL and energy storage, respectively. The proportion of non-hydro renewable energy consumption in EH.

[0057] Preferably, the CvaR model for introducing the electro-hydrogen production model in SS5 is:

[0058] (26)

[0059] (27)

[0060] In the formula: CVaR risk control cost indicator for electro-hydrogen production; for The VaR value of the cost of hydrogen production by electro-hydrogen at the quantile point; The operating cost of electro-hydrogen production in scenario w exceeds The amount.

[0061] Preferably, the optimized electro-hydrogen production model for SS6 that includes the CVaR index is:

[0062] (28)

[0063] (29)

[0064] (30)

[0065] The solution to the optimization problem is denoted as... Energy scheduling is represented by n0.

[0066] Preferably, the cooperation model in SS7 is analyzed using the cooperation benefit model, and the specific formula is as follows:

[0067] (31)

[0068] (32)

[0069] (33)

[0070] (34)

[0071] (35)

[0072] (36)

[0073] (37)

[0074] (38)

[0075] (39)

[0076] (40)

[0077] (41)

[0078] (42)

[0079] In the formula: This represents the revenue that the photovoltaic system receives from the electro-hydrogen production system; This represents the cost paid by the electro-hydrogen production system to the photovoltaic system; Let be the decision variable vector for the nth photovoltaic system, then Let be the set of decision variables for all photovoltaic systems; let... Represents the decision variable vector of an electro-hydrogen production system; The cost of the nth photovoltaic system under cooperative operation, taking into account risk management; Let the grid access fee be the nth photovoltaic system at time t under scenario w; This refers to the basic grid access fee for industrial and commercial electricity use. The cost of the electro-hydrogen production system is considered in the context of the cooperation model and risk management.

[0080] Preferably, the distribution of benefits is based on the analysis of the cooperation benefit model, and the specific formula is as follows:

[0081] (43)

[0082] (44)

[0083] (45)

[0084] (46)

[0085] (47)

[0086] In the formula: Let n be the selling price of the photovoltaic system to the electro-hydrogen production system. The purchase price that the electro-hydrogen production system pays to the nth photovoltaic system; The solution for direct transaction volume in the equation is represented as: ,in: , .

[0087] Preferably, in SS8, the alternating multiplier algorithm is used to solve the cooperation model for cooperation benefits. This is achieved by transforming formula (31) into the augmented Lagrangian function of formula (48) and then iteratively solving it as follows:

[0088] (48)

[0089] (49)

[0090] (50)

[0091] (51)

[0092] (52)

[0093] (53)

[0094] (54)

[0095] In the formula: , Given the penalty parameters, , These are dual multiplier vectors; , These are the residuals for problem P1;

[0096] Formula (49) is the iterative formula of the PV optimization model. A total of n sub-problems are solved in parallel by PV, where each photovoltaic system needs current information from the electro-hydrogen production system. Formula (50) is an iterative equation for the optimization model of the electro-hydrogen production system, where the electro-hydrogen production system requires current information from the photovoltaic system. ;when , If the value is less than the convergence threshold, then the computation of problem P1 ends; let... This represents the optimal solution for P1. , These represent the energy costs of photovoltaic systems and electro-hydrogen production systems in energy cooperation, respectively.

[0097] Preferably, in SS8, the alternating multiplier algorithm is used to solve the benefit allocation problem of the cooperative model. By taking the maximum value of the logarithm of the objective function formula (43), it can be equivalently transformed into an augmented Lagrange function with a separable objective function:

[0098] (55)

[0099] In the formula: Given the penalty parameters, It is the dual multiplier vector of the coupling constraint formula (23).

[0100] Compared with the prior art, the beneficial effects of the present invention are:

[0101] This invention can bring additional benefits to all parties through green certificates, stimulating them to obtain excess profits. This method enables the cooperative operation of photovoltaic systems and green hydrogen systems to simultaneously meet the reasonable allocation of electricity and green certificates. Furthermore, by using an optimization model to optimize each party, the operating costs can be minimized. At the same time, by introducing the CvaR risk index into the cooperation model, unnecessary risks arising in the cooperation due to the uncertainty of photovoltaic system electricity and green hydrogen system load in existing technologies are resolved. Attached Figure Description

[0102] Figure 1 This is a CvaR-revenue correlation curve for a multi-entity cooperation method for photovoltaic and hydrogen projects that takes into account green certificate trading under the risk management of this invention.

[0103] Figure 2 The slope of the CvaR-revenue correlation curve for the photovoltaic and hydrogen multi-entity cooperation method considering green certificate transactions under the risk management of this invention;

[0104] Figure 3This describes the iterative convergence process of P1 and P2 in the photovoltaic and hydrogen multi-entity cooperation method considering green certificate trading under the risk management of this invention;

[0105] Figure 4 This is a schematic diagram comparing the photovoltaic and hydrogen multi-entity cooperation method under the risk management of this invention and the green certificate trading before and after cooperation. Detailed Implementation

[0106] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0107] Example

[0108] A multi-stakeholder cooperation approach for photovoltaic and hydrogen projects, considering green certificate trading under risk management, is proposed. This approach establishes a photovoltaic model based on existing green certificates and an electro-hydrogen production model based on renewable energy consumption targets. This enables cooperative operation and trading of photovoltaic and electro-hydrogen projects, as detailed below:

[0109] S1 Green Certificate Modeling: A mathematical model is derived based on the renewable energy generation of the green certificate and the conceptual representation of the green certificate; the renewable energy generation of the green certificate is set at 1 MWh; the specific formula is as follows:

[0110] (1)

[0111] Modeling of the S2 renewable energy consumption task: A mathematical model is derived based on the amount of renewable energy electricity purchased by buyers; the specific formula is as follows:

[0112] (2)

[0113] S3 Cooperation Model: Based on the mathematical models obtained in S1 and S2, a multi-entity cooperation model for realizing green certificate trading in photovoltaic and hydrogen industries is obtained.

[0114] Based on the photovoltaic and hydrogen multi-entity cooperation model for green certificate trading obtained in S3, the risk management method is used to manage risk. A photovoltaic and hydrogen production cooperation model is then established based on this risk management, and the alternating direction multiplier method is used to solve it, as follows:

[0115] SS1 Photovoltaic Model Based on Green Certificates: Introducing a mathematical model based on green certificates into a photovoltaic model to form a photovoltaic model that can be traded with the electro-hydrogen production model based on green certificates;

[0116] When the photovoltaic model operates independently of the electro-hydrogen production model, the optimization objective of the photovoltaic model is to minimize its own operating cost. This includes revenue from the sale of electricity to the grid. Green certificate revenue from the sale of green certificates to the green certificate market and operation and maintenance costs ;

[0117] set up Let w be the decision variable vector for the nth photovoltaic model, including the power of electricity sold to the grid. and the number of green certificates sold to the green certificate market The specific formula is as follows:

[0118] (3)

[0119] (4)

[0120] (5)

[0121] (6)

[0122] (7)

[0123] In the formula: T is the scheduling period; N is the number of photovoltaic entities; W is the set of photovoltaic power output scenarios; and Z is a positive integer. Let n be the probability of the nth photovoltaic cell in scenario w. Let be the unit power generation maintenance factor for the nth photovoltaic cell; Let be the feed-in tariff of the nth photovoltaic power generation at time t; This is the price at which the nth photovoltaic model sells green certificates to the green certificate market within the T trading cycle; Let be the electrical power sold to the grid by the nth photovoltaic cell at time t under scenario w; Let be the number of green certificates sold to the grid by the nth photovoltaic power generation unit in scenario w; Let be the power generation of the nth photovoltaic cell at time t under scenario w.

[0124] Introduction of CVaR in SS2 Photovoltaic Model: The CVaR method is introduced to control the impact of output uncertainty on cost in the green certificate-based photovoltaic model of SS1; the photovoltaic model introduced includes:

[0125] (8)

[0126] (9)

[0127] In the formula: Let CVaR be the risk control cost indicator for the nth photovoltaic cell. Confidence level; for The nth photovoltaic cost VaR value corresponding to the quantile; As a non-negative auxiliary variable, specifically representing the operating cost of the nth photovoltaic cell in scenario w exceeding... The amount.

[0128] SS3 risk-controlled photovoltaic model: Taking risk into account, the CVaR index photovoltaic model in SS2 is obtained through optimization tools; the photovoltaic optimization model including the CVaR index is as follows:

[0129] (10)

[0130] (11)

[0131] (12)

[0132] In the formula: The risk aversion coefficient for the nth photovoltaic cell;

[0133] When photovoltaics are not combined with hydrogen production via electricity, the solution to the optimization problem is denoted as m*, and the optimal cost is set as... .

[0134] SS4 Hydrogen Production by Electricity Model: When the hydrogen production by electricity system operates independently of the photovoltaic system, the decision variables of the hydrogen production by electricity system are expressed as follows: ,in, The amount of electricity purchased from the grid by the electro-hydrogen production system at time t under scenario w; Green certificates purchased from the green certificate market for the electro-hydrogen production system within the T-cycle of scenario w; The green electricity purchased from the grid by the electro-hydrogen production system at time t under scenario w;

[0135] The operating cost of an electrohydrogen production system includes the cost of purchasing electricity from the grid. Green certificate costs Green electricity cost and maintenance costs The operation and maintenance costs include the operating and maintenance costs of energy storage and EL (Energy Array); the specific formula is as follows:

[0136] (13)

[0137] (14)

[0138] (15)

[0139] (16)

[0140] (17)

[0141] (18)

[0142] (19)

[0143] (20)

[0144] (twenty one)

[0145] (twenty two)

[0146] (twenty three)

[0147] (twenty four)

[0148] (25)

[0149] In the formula: Let $\math$ be the probability of hydrogen production by electrolysis in scenario $w$. For EL energy conversion rate; Let be the hydrogen production power of EL at time t; Let be the power consumption of EL at time t; This represents the upper limit of EL power consumption; This is the upper limit of climbing power; Let t be the power consumption of the compressor. The specific heat capacity constant of hydrogen; Let t be the flow rate of hydrogen compressed by the compressor. The temperature at which hydrogen is input to the compressor; The compressor efficiency is represented by K, which is the isentropic exponent of hydrogen. This refers to the compression ratio; Let t be the internal gas pressure of the hydrogen storage tank; This refers to the internal temperature of the hydrogen storage tank. This refers to the molar mass of hydrogen gas. Let t be the amount of hydrogen compressed by the compressor. Let t be the hydrogen load demand. , These represent the minimum and maximum gas pressures of the hydrogen storage tank, respectively. Store energy at time t; , These represent the minimum and maximum energy storage capacity of the energy storage system, respectively. , These represent the charging and discharging power at time t, respectively; , These are the charge and discharge efficiencies, respectively. , These are the maximum charging power and the maximum discharging power, respectively. It is a binary variable used to prevent charging and discharging processes from occurring simultaneously; The price at which electricity is purchased from the grid for hydrogen production at time t; Let t be the price at which green electricity is purchased from the grid. The price of the green certificate within cycle T; , These are the operation and maintenance coefficients for EL and energy storage, respectively. The proportion of non-hydro renewable energy consumption in EH.

[0150] The CVaR introduction of the SS5 electro-hydrogen production model: The uncertainty of hydrogen load leads to operational risks in electro-hydrogen production. This represents the operational risk index of EL, used for risk control of hydrogen load uncertainty in the electro-hydrogen production model in SS4; the CvaR model introduced into the electro-hydrogen production model is:

[0151] (26)

[0152] (27)

[0153] In the formula: CVaR risk control cost indicator for electro-hydrogen production; for The VaR value of the cost of hydrogen production by electro-hydrogen at the quantile point; The operating cost of electro-hydrogen production in scenario w exceeds The amount.

[0154] SS6 Risk-Controlled Hydrogen Production Model: Taking risk into account, the CVaR index-based hydrogen production model in SS5 is obtained through optimization tools; the optimized hydrogen production model including the CVaR index is as follows:

[0155] (28)

[0156] (29)

[0157] (30)

[0158] The solution to the optimization problem is denoted as... Energy scheduling is represented by n0.

[0159] SS7 risk management and green certificate trading multi-entity cooperation model for photovoltaic and hydrogen: including electricity cooperation and green certificate cooperation;

[0160] Electricity trading agreement: The photovoltaic system expects to sell electricity to the hydrogen-to-electricity system at a price no lower than the grid-connected electricity price, while the hydrogen-to-electricity system expects to purchase electricity from the photovoltaic system at a price no higher than the industrial electricity price; when the photovoltaic system's electricity sales price and the hydrogen-to-electricity system's electricity purchase price reach an agreement, the photovoltaic system and the hydrogen-to-electricity system reach an electricity trading agreement; the photovoltaic system sells surplus electricity to the grid, and the hydrogen-to-electricity system purchases electricity from the grid to meet surplus load demand;

[0161] Green certificate cooperation: The photovoltaic system expects to sell green certificates to the electro-hydrogen system at a price no lower than the market green certificate purchase price, while the electro-hydrogen system expects to purchase green certificates from the photovoltaic system at a price no higher than the market green certificate selling price; when the green certificate purchase price of the electro-hydrogen system and the green certificate selling price of the photovoltaic system are equal, the photovoltaic system and the electro-hydrogen system reach a green certificate transaction agreement; the photovoltaic system sells its remaining green certificates to the green certificate market, and the electro-hydrogen system purchases green certificates from the green certificate market to meet its remaining renewable energy consumption tasks;

[0162] The cooperation model is analyzed using a cooperation benefit model, and the specific formula is as follows:

[0163] (31)

[0164] (32)

[0165] (33)

[0166] (34)

[0167] (35)

[0168] (36)

[0169] (37)

[0170] (38)

[0171] (39)

[0172] (40)

[0173] (41)

[0174] (42)

[0175] In the formula: This represents the revenue that the photovoltaic system receives from the electro-hydrogen production system; This represents the cost paid by the electro-hydrogen production system to the photovoltaic system; Let be the decision variable vector for the nth photovoltaic system, then Let be the set of decision variables for all photovoltaic systems; let... Represents the decision variable vector of an electro-hydrogen production system; The cost of the nth photovoltaic system under cooperative operation, taking into account risk management; Let the grid access fee be the nth photovoltaic system at time t under scenario w; This refers to the basic grid access fee for industrial and commercial electricity use. The cost of the electro-hydrogen production system is considered in the context of the cooperation model and risk management.

[0176] The distribution of benefits is based on the analysis of the cooperation benefit model, and the specific formula is as follows:

[0177] (43)

[0178] (44)

[0179] (45)

[0180] (46)

[0181] (47)

[0182] In the formula: Let n be the selling price of the photovoltaic system to the electro-hydrogen production system. The purchase price that the electro-hydrogen production system pays to the nth photovoltaic system; The solution for direct transaction volume in the equation is represented as: ,in: , .

[0183] Solving the cooperation model under SS8 risk management: The cooperation model is solved using the alternating multiplier algorithm, and the effectiveness of the proposed cooperation model is verified through numerical examples.

[0184] The cooperative model is solved using the alternating multiplier algorithm to determine the cooperative benefits. This is achieved by transforming formula (31) into the augmented Lagrangian function of formula (48) and then iteratively solving the problem as follows:

[0185] (48)

[0186] (49)

[0187] (50)

[0188] (51)

[0189] (52)

[0190] (53)

[0191] (54)

[0192] In the formula: , Given the penalty parameters, , These are dual multiplier vectors; , These are the residuals for problem P1;

[0193] Formula (49) is the iterative formula of the PV optimization model. A total of n sub-problems are solved in parallel by PV, where each photovoltaic system needs current information from the electro-hydrogen production system. Formula (50) is an iterative equation for the optimization model of the electro-hydrogen production system, where the electro-hydrogen production system requires current information from the photovoltaic system. ;when , If the value is less than the convergence threshold, then the computation of problem P1 ends; let... This represents the optimal solution for P1. , These represent the energy costs of photovoltaic systems and electro-hydrogen production systems in energy cooperation, respectively.

[0194] The cooperative model is solved by using the alternating multiplier algorithm to allocate benefits. By taking the maximum value of the logarithm of the objective function formula (43), it can be equivalently transformed into an augmented Lagrangian function with a separable objective function:

[0195] (55)

[0196] In the formula: Given the penalty parameters, It is the dual multiplier vector of the coupling constraint formula (23).

[0197] Please see Figures 1-4 ,like Figure 1 As shown, the CvaR return correlation curve illustrates the relationship between different risk aversion coefficients. This raises the question of how photovoltaic (PV) systems can strike a balance between returns and CVaR (Constant Viability and Return). A negative CVaR indicates that risk leads to loss, while a positive CVaR indicates that risk brings returns. It can be seen that as the risk aversion coefficient decreases, CVaR losses increase while CVaR gains decrease. Therefore, for PV systems to achieve higher returns, they must accept higher risks. When PV = 0.005, PV seeks to maximize returns while ignoring risk; when When the value is 50, the photovoltaic system chooses to minimize risk at the expense of returns.

[0198] The slope of the CvaR-return correlation curve is statistically analyzed, and the interval where the absolute value is greater than 1 is called the "excess profit" interval. Figure 2 As shown, excess profit is defined as the return that exceeds the loss due to CVaR (Constant Volatility and Risk-Averse Ratio) as the risk aversion coefficient decreases. It can be observed that photovoltaic systems need to make a reasonable choice between returns and CVaR in order to obtain "excess profit." Both excessively high and excessively low risk aversion coefficients will affect the pursuit of "excess profit." Too small a value will lead to increased CvaR losses without a significant increase in returns, making it impossible to pursue "excess profits". Too large a value can protect against CvaR losses, but it will result in a significant reduction in returns. Although "excess profits" exist, risk management limits the entity's ability to pursue them.

[0199] Although embodiments of the present invention have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present invention. Those skilled in the art can make changes, modifications, substitutions and variations to the above embodiments within the scope of the present invention.

Claims

1. A multi-entity cooperation method for photovoltaic and hydrogen projects under risk management and considering green certificate trading, characterized by: This method establishes a photovoltaic model based on existing green certificates and an electro-hydrogen production model based on renewable energy consumption tasks, enabling cooperative operation and trading of photovoltaic and electro-hydrogen production, including: S1 Green Certificate Modeling: A mathematical model is derived based on the renewable energy generation capacity of green certificates and the conceptual representation of green certificates; the specific formula is as follows: （1）； Modeling of the S2 renewable energy consumption task: A mathematical model is derived based on the amount of renewable energy electricity purchased by buyers; the specific formula is as follows: （2）； S3 Cooperation Model: A multi-entity cooperation model for photovoltaic and hydrogen industries to realize green certificate trading, based on the mathematical models obtained in S1 and S2. Of which, the renewable energy generation capacity for green certificates is 1 MWh; Risk management using the Value at Risk (VaR) approach; establishing a photovoltaic-to-hydrogen-electricity cooperation model based on risk management; and solving the model using the alternating direction multiplier method; including: SS1 Photovoltaic Model Based on Green Certificates: Introducing a mathematical model based on green certificates into a photovoltaic system to form a photovoltaic model that can be traded with an electro-hydrogen production model based on green certificates; When the photovoltaic system operates independently of the hydrogen production system, its optimization objective is to minimize its own operating costs. This includes revenue from selling electricity to the grid. Green certificate revenue from the sale of green certificates to the green certificate market and operation and maintenance costs ; set up Let w be the decision variable vector for the nth photovoltaic system, including the power of electricity sold to the grid. and the number of green certificates sold to the green certificate market ; Introduction of CVaR in SS2 Photovoltaic Model: The CVaR method is introduced to control the impact of output uncertainty on cost in the green certificate-based photovoltaic model of SS1. SS3 risk-controlled photovoltaic model: Under the condition of taking risk into account, the CVaR index photovoltaic model in SS2 is obtained through optimization tools; SS4 Hydrogen Production by Electricity Model: When the hydrogen production by electricity system operates independently of the photovoltaic system, the decision variables of the hydrogen production by electricity system are expressed as follows: ,in, The amount of electricity purchased from the grid by the electro-hydrogen production system at time t under scenario w; Green certificates purchased from the green certificate market for the electro-hydrogen production system within the T-cycle of scenario w; The green electricity purchased from the grid by the electro-hydrogen production system at time t under scenario w; The operating cost of an electro-hydrogen production system includes the cost of purchasing electricity from the grid. Green certificate costs Green electricity cost and maintenance costs Among these, operation and maintenance costs include the operation and maintenance costs of energy storage and EL (Energy Storage and Electron). The CVaR introduction of the SS5 electro-hydrogen production model: The uncertainty of hydrogen load leads to operational risks in electro-hydrogen production. This represents the operational risk indicator of EL, and is used for risk control of the hydrogen load uncertainty in the electro-hydrogen production model in SS4. SS6 Risk-Controlled Electric Hydrogen Production Model: Taking risk into account, the CVaR index electric hydrogen production model in SS5 is obtained through optimization tools; SS7 risk management and green certificate trading multi-entity cooperation model for photovoltaic and hydrogen: including electricity cooperation and green certificate cooperation; Electricity trading agreement: The photovoltaic system expects to sell electricity to the hydrogen-to-electricity system at a price no lower than the grid-connected electricity price, while the hydrogen-to-electricity system expects to purchase electricity from the photovoltaic system at a price no higher than the industrial electricity price; when the photovoltaic system's electricity sales price and the hydrogen-to-electricity system's electricity purchase price reach an agreement, the photovoltaic system and the hydrogen-to-electricity system reach an electricity trading agreement; the photovoltaic system sells surplus electricity to the grid, and the hydrogen-to-electricity system purchases electricity from the grid to meet surplus load demand; Green certificate cooperation: The photovoltaic system expects to sell green certificates to the electro-hydrogen system at a price no lower than the market green certificate purchase price, while the electro-hydrogen system expects to purchase green certificates from the photovoltaic system at a price no higher than the market green certificate selling price; when the green certificate purchase price of the electro-hydrogen system and the green certificate selling price of the photovoltaic system are equal, the photovoltaic system and the electro-hydrogen system reach a green certificate transaction agreement; the photovoltaic system sells its remaining green certificates to the green certificate market, and the electro-hydrogen system purchases green certificates from the green certificate market to meet its remaining renewable energy consumption tasks; Solving the cooperation model under SS8 risk management: The cooperation model is solved using the alternating multiplier algorithm by transforming the cooperation benefit model into an augmented Lagrangian function and solving it iteratively; The alternating multiplier algorithm is used to allocate benefits in the cooperative model. The maximum value of the logarithm of the objective function formula is taken, and it is equivalently transformed into an augmented Lagrange function with a separable objective function.

2. The photovoltaic and hydrogen multi-entity cooperation method considering green certificate trading under risk management as described in claim 1, characterized in that: The specific formula in SS1 is as follows: （3） （4） （5） （6） （7） In the formula: T is the scheduling period; N is the number of photovoltaic entities; W is the set of photovoltaic power output scenarios; and Z is a positive integer. Let n be the probability of the nth photovoltaic cell in scenario w. Let be the unit power generation maintenance factor for the nth photovoltaic cell; Let be the feed-in tariff of the nth photovoltaic power generation at time t; This is the price at which the nth photovoltaic model sells green certificates to the green certificate market within the T trading cycle; Let be the electrical power sold to the grid by the nth photovoltaic cell at time t under scenario w; Let be the number of green certificates sold to the grid by the nth photovoltaic power generation unit in scenario w; Let be the power generation of the nth photovoltaic cell at time t under scenario w.

3. The photovoltaic and hydrogen multi-entity cooperation method considering green certificate trading under risk management as described in claim 1, characterized in that: The model that includes the photovoltaic model in SS2 is as follows: （8） （9） In the formula: Let CVaR be the risk control cost indicator for the nth photovoltaic cell. Confidence level; for The nth photovoltaic cost VaR value corresponding to the quantile; As a non-negative auxiliary variable, specifically representing the operating cost of the nth photovoltaic cell in scenario w exceeding... The amount.

4. The photovoltaic and hydrogen multi-entity cooperation method considering green certificate trading under risk management as described in claim 1, characterized in that: The photovoltaic optimization model in SS3 that includes the CVaR index is: （10） （11） （12） In the formula: The risk aversion coefficient for the nth photovoltaic cell; When photovoltaics are not combined with hydrogen production via electricity, the solution to the optimization problem is denoted as m*, and the optimal cost is set as... .

5. The photovoltaic and hydrogen multi-entity cooperation method considering green certificate trading under risk management as described in claim 1, characterized in that: The specific formula for the electro-hydrogen production model in SS4 is as follows: （13） （14） （15） （16） （17） （18） （19） （20） （21） （22） （23） （24） （25） In the formula: Let $\math$ be the probability of hydrogen production by electrolysis in scenario $w$. For EL energy conversion rate; Let be the hydrogen production power of EL at time t; Let be the power consumption of EL at time t; This represents the upper limit of EL power consumption; This is the upper limit of climbing power; Let t be the power consumption of the compressor. The specific heat capacity constant of hydrogen; Let t be the flow rate of hydrogen compressed by the compressor. The temperature at which hydrogen is input to the compressor; The compressor efficiency is represented by K, which is the isentropic exponent of hydrogen. This refers to the compression ratio; Let t be the internal gas pressure of the hydrogen storage tank; This refers to the internal temperature of the hydrogen storage tank. This refers to the molar mass of hydrogen gas. Let t be the amount of hydrogen compressed by the compressor. Let t be the hydrogen load demand. , These represent the minimum and maximum gas pressures of the hydrogen storage tank, respectively. Store energy at time t; , These represent the minimum and maximum energy storage capacity of the energy storage system, respectively. , These represent the charging and discharging power at time t, respectively; , These are the charge and discharge efficiencies, respectively. , These are the maximum charging power and the maximum discharging power, respectively. It is a binary variable used to prevent charging and discharging processes from occurring simultaneously; The price at which electricity is purchased from the grid for hydrogen production at time t; Let t be the price at which green electricity is purchased from the grid. The price of the green certificate within cycle T; , These are the operation and maintenance coefficients for EL and energy storage, respectively. The proportion of non-hydro renewable energy consumption in EH.

6. The photovoltaic and hydrogen multi-entity cooperation method considering green certificate trading under risk management as described in claim 1, characterized in that: The CvaR model used in SS5 to introduce an electro-hydrogen production model is: （26） （27） In the formula: CVaR risk control cost indicator for electro-hydrogen production; for The VaR value of the electro-hydrogen production cost corresponding to the quantile point; The operating cost of electro-hydrogen production in scenario w exceeds The amount.

7. The photovoltaic and hydrogen multi-entity cooperation method under risk management and considering green certificate trading as described in claim 1, characterized in that: The SS6 optimization model for electro-hydrogen production that includes the CVaR index is as follows: （28） （29） （30） The solution to the optimization problem is denoted as... Energy scheduling is represented by n0.

8. The photovoltaic and hydrogen multi-entity cooperation method considering green certificate trading under risk management as described in claim 1, characterized in that: In SS7, the cooperation model is analyzed using a cooperation benefit model, with the specific formula as follows: （31） （32） （33） （34） （35） （36） （37） （38） （39） （40） （41） （42） In the formula: This represents the revenue that the photovoltaic system receives from the electro-hydrogen production system; This represents the cost paid by the electro-hydrogen production system to the photovoltaic system; Let be the decision variable vector for the nth photovoltaic system, then Let be the set of decision variables for all photovoltaic systems; let... Represents the decision variable vector of an electro-hydrogen production system; The cost of the nth photovoltaic system under cooperative operation, taking into account risk management; Let the grid access fee be the nth photovoltaic system at time t under scenario w; This is the basic grid access fee price for industrial and commercial electricity use; The cost of the electro-hydrogen production system is considered in the context of the cooperation model and risk management.

9. The photovoltaic and hydrogen multi-entity cooperation method under risk management and considering green certificate trading as described in claim 8, characterized in that: The distribution of benefits is based on the analysis of the cooperation benefit model, and the specific formula is as follows: （43） （44） （45） （46） （47） In the formula: Let n be the selling price of the photovoltaic system to the electro-hydrogen production system. The purchase price that the electro-hydrogen production system pays to the nth photovoltaic system; The solution for direct transaction volume in the equation is represented as: ,in: , .

10. The photovoltaic and hydrogen multi-entity cooperation method considering green certificate trading under risk management as described in claim 8, characterized in that: In SS8, the alternating multiplier algorithm is used to solve the cooperation model for cooperation benefits. Formula (31) is transformed into the augmented Lagrangian function of formula (48), and the solution is obtained iteratively as follows: （48） （49） （50） （51） （52） （53） （54） In the formula: , Given the penalty parameters, , These are dual multiplier vectors; , These are the residuals for problem P1; Formula (49) is the iterative formula of the PV optimization model. A total of n sub-problems are solved in parallel by PV, where each photovoltaic system needs current information from the electro-hydrogen production system. Formula (50) is an iterative equation for the optimization model of the electro-hydrogen production system, where the electro-hydrogen production system requires current information from the photovoltaic system. ;when , When the value is less than the convergence threshold, the computation of problem P1 ends; let... This represents the optimal solution for P1. , These represent the energy costs of photovoltaic systems and electro-hydrogen production systems in energy cooperation, respectively.

11. The photovoltaic and hydrogen multi-entity cooperation method considering green certificate trading under risk management as described in claim 9, characterized in that: In SS8, the alternating multiplier algorithm is used to solve the benefit allocation problem of the cooperative model. By taking the maximum value of the logarithm of the objective function formula (43), it is equivalently transformed into an augmented Lagrangian function with a separable objective function: （55） In the formula: Given the penalty parameters, It is the dual multiplier vector of the coupling constraint formula (23).

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