Electricity-hydrogen coupling enterprise market transaction method and system in electricity-hydrogen-carbon multi-element coupling market

Abstract

The invention relates to an electricity-hydrogen coupling enterprise market transaction method and system in an electricity-hydrogen-carbon coupling market. The method comprises the following steps: constructing an electricity-hydrogen coupling enterprise spot transaction upper decision model and constraint conditions in the electricity-hydrogen-carbon coupling market transaction; constructing a lower-layer power spot market optimal clearing model; constructing an optimal clearing model of the lower-layer hydrogen market; constructing a lower-layer carbon market optimal clearing model; obtaining a typical scene set based on the wind power and photovoltaic power generation power uncertainty scene set; constructing an electricity-hydrogen coupling enterprise market balanced transaction model in the electricity-hydrogen-carbon multi-element coupling market considering the uncertainty of the new energy output, and solving the model; and judging whether balance clearing is carried out or not. According to the method, under the condition that the new energy permeability is continuously improved, an electricity-hydrogen coupling enterprise balanced transaction decision-making model under multi-element coupling market transaction is considered, and the influence on bidding decision-making under uncertainty is considered in a prospective manner.

Description

Technical Field

[0001] The present invention belongs to the technical field of balanced trading in the electricity spot market, and relates to a market balanced trading method and system for electricity-hydrogen coupling enterprises in an electricity-hydrogen-carbon multi-coupling market, and in particular to a market trading method and system for electricity-hydrogen coupling enterprises in an electricity-hydrogen-carbon coupling market. Background Art

[0002] In recent years, the global traditional energy crisis has continued to threaten the environment and economic development. The development of hydrogen energy is an important way to achieve the global "dual carbon" goal. As a secondary energy with abundant sources, green and low carbon, and wide application, hydrogen energy can be used for new energy to produce hydrogen and help large-scale consumption of renewable energy. As the main body of the power market, hydrogen market and carbon market, the electric hydrogen coupling system participates in trading decisions, which helps to accelerate the low-carbonization of the power system and provides a new idea for the coordinated promotion of large-scale development of new energy.

[0003] At present, the trading decisions of electric-hydrogen coupled enterprises in the multi-coupled market that considers the electricity market, hydrogen market and carbon market are mainly divided into issues related to energy economic scheduling under electric-hydrogen coupling and issues related to electric-carbon coupling transactions and low-carbon economic scheduling. Since the electric-hydrogen coupled system, as a multi-market entity, can participate in multiple market trading decisions, it is of great significance to analyze the trading optimization of the electric-hydrogen coupled system under the multi-coupled market.

[0004] Therefore, the present invention proposes a market transaction method and system for electricity-hydrogen coupling enterprises in the electricity-hydrogen-carbon coupling market.

[0005] After searching, no public documents of the prior art identical or similar to the present invention were found. Summary of the invention

[0006] The purpose of the present invention is to overcome the shortcomings of the prior art and propose a market trading method and system for electric-hydrogen coupling enterprises in the electric-hydrogen-carbon coupling market, which can proactively emphasize the equilibrium trading decision model of electric-hydrogen coupling enterprises under multi-coupling market transactions under the condition of increasing penetration of new energy, as well as the impact on bidding decisions under uncertainty.

[0007] The present invention solves the practical problem by adopting the following technical solutions:

[0008] Based on the electricity-hydrogen-carbon multi-coupling market mechanism and trading rules, an upper-level decision-making model for spot trading of electricity-hydrogen coupling enterprises under the electricity-hydrogen-carbon coupling market transaction is constructed;

[0009] Based on the market mechanism and transaction constraints of market players participating in the coupled market, a set of constraint conditions for the upper-level decision-making model of spot transactions of electricity-hydrogen coupled enterprises under the electricity-hydrogen-carbon coupled market transaction is constructed;

[0010] According to the electricity-hydrogen-carbon coupling market mechanism and trading rules, the optimal clearing model of the lower-level electricity spot market, the optimal clearing model of the lower-level hydrogen market and the optimal clearing model of the lower-level carbon market are constructed respectively, with the maximization of social welfare of each market transaction as the objective function;

[0011] Based on the uncertain scenario set of wind power and photovoltaic power generation, a typical scenario set and the probability of occurrence of the corresponding typical scenario are obtained;

[0012] According to the upper-level decision-making model of spot transactions of electric-hydrogen coupled enterprises under the constructed electric-hydrogen-carbon coupled market transactions and its set of constraints, the optimal clearing model of the lower-level electricity spot market, the optimal clearing model of the lower-level hydrogen market and the optimal clearing model of the lower-level carbon market, and the typical scenario set as well as the probability of occurrence of the corresponding typical scenarios, based on the conditional risk value, the market equilibrium transaction model of electric-hydrogen coupled enterprises in the electric-hydrogen-carbon multi-coupling market considering the uncertainty of new energy output is constructed and solved;

[0013] Based on the solution results of the market equilibrium trading model of electricity-hydrogen-carbon coupled enterprises in the electricity-hydrogen-carbon multi-coupled market, it is judged whether to carry out equilibrium clearing. If equilibrium clearing is achieved, the clearing results of the electricity spot market, hydrogen market and carbon market are obtained. The clearing results include the winning electricity volume of electricity market entities, the winning hydrogen volume of hydrogen market entities, and the winning carbon emission rights volume of carbon market entities.

[0014] Moreover, the objective function of the upper-level decision-making model for spot trading of electricity-hydrogen coupling enterprises under the electricity-hydrogen-carbon coupling market transaction is:

[0015] maxF U =C E +C H +C CCER

[0016]

[0017] Where: F U is the total economic benefit of the electricity-hydrogen coupling enterprise; C E , C H and C CCER The economic benefits obtained by electricity-hydrogen coupling enterprises in the electricity spot market, hydrogen market and carbon market respectively; The power generation capacity of the jth electricity-hydrogen coupling enterprise winning the bid in period l during period t; is the marginal electricity price at the electricity spot market node in time period t; is the marginal power generation cost of the jth electricity-hydrogen coupling enterprise in period t in period l; The amount of hydrogen sold by the j-th electricity-hydrogen coupling enterprise in the hydrogen market during period t; The amount of hydrogen purchased by the j-th electricity-hydrogen coupling enterprise in the hydrogen market during period t; is the hydrogen market price of hydrogen in period t; is the marginal power generation cost of the jth electric-hydrogen coupling enterprise in the hydrogen market during period t; is the CEA price in the carbon market during period t.

[0018] Moreover, the constraint condition set for constructing the upper-level decision-making model for spot trading of electricity-hydrogen-carbon coupled enterprises under the electricity-hydrogen-carbon coupled market transaction includes:

[0019] 1) Quotation constraints:

[0020]

[0021]

[0022] Where: is the bid of the jth electricity-hydrogen coupling system in period l during period t; are the upper and lower limits of the price quoted by the jth electricity-hydrogen coupling enterprise in the electricity spot market; is the bid price of the j-th electricity-hydrogen coupling enterprise in the hydrogen market for buying and selling hydrogen in period t; are the upper and lower limits of the hydrogen sales quotation of the jth electricity-hydrogen coupling enterprise in the hydrogen market; They are the upper and lower limits of the hydrogen purchase quotation of the jth electricity-hydrogen coupling enterprise in the hydrogen market; The price quoted by the j-th electricity-hydrogen coupling enterprise in period t to sell CCER in the carbon market; They are the upper and lower limits of CCER quotation in the carbon market of the jth electricity-hydrogen coupling enterprise;

[0023] 2) Electrolyzer operation constraints:

[0024] The electrolyzer is the key equipment for producing hydrogen by electrolyzing water, and its operation model is:

[0025]

[0026] Where: is the hydrogen production mass of the electrolyzer during time period t; The power consumption of electrolytic cell for water electrolysis during time period t; is the electrolysis efficiency of the electrolyzer device; It is the high calorific value of hydrogen;

[0027] 3) Hydrogen storage tank operation constraints:

[0028] The electrolyzed hydrogen is stored in a hydrogen storage tank. Based on the ideal gas state equation, the following hydrogen storage tank model is established:

[0029]

[0030] Where: is the pressure of the hydrogen storage tank during time period t; V LHSis the volume of the hydrogen storage tank; R is the ideal gas constant; T H is the gas temperature; is the mass of hydrogen in the hydrogen storage tank during time period t; is the relative molecular mass of hydrogen;

[0031] 4) Compressor operation constraints:

[0032] The power consumption of the compressor is mainly related to the hydrogen compression ratio and intake volume, and its operation model is:

[0033]

[0034] Where: is the specific heat capacity of hydrogen; T in is the hydrogen temperature input to the compressor; γ is the isentropic index of hydrogen; are the output hydrogen pressure and input hydrogen pressure of the compressor, is the compression ratio; is the total power consumption of the compressor during time period t; is the hydrogen mass entering the compressor during period t; η CP The working efficiency of the compressor;

[0035] 5) Operation constraints of liquefied hydrogen production equipment:

[0036] The operation model of hydrogen liquefaction equipment is:

[0037]

[0038] Where: is the unit energy consumption of hydrogen liquefaction process in time period t; is the power consumption of the compressor during time period t; is the power consumption of the expander during period t; The heat output of the cooler for time period t; is the quality of liquid hydrogen product in time period t; is the total power consumption of the hydrogen liquefaction process during period t; is the hydrogen quality of the hydrogen liquefaction process during period t; The efficiency of the hydrogen liquefaction process;

[0039] 6) Electric power balance constraints:

[0040]

[0041] Where: It is the predicted value of new energy output.

[0042] Moreover, the optimal clearing model for the lower-level electricity spot market is constructed as follows:

[0043]

[0044]

[0045] Where: The power bid by the vth power user in the cth segment during time period t; is the bid of the vth electricity user in period c during period t; The upper and lower limits of the winning bid of the i-th traditional energy power generation enterprise in the o-th segment; The upper and lower limits of the winning bid of the jth electricity-hydrogen coupling enterprise in the lth section; The upper and lower limits of the winning bid of the vth power user in the cth segment; is the node set associated with node n; is the set of power user loads associated with node n; is the set of traditional energy generators associated with node n; B is the set of electricity-hydrogen coupling enterprise units associated with node n; n,m is the line susceptance from node n to node m; are the phase angles of node n and node m in time period t respectively; is the transmission power limit of the line from node n to node m; and The upper and lower limits of the phase angle of node n in time period t; The node marginal electricity price of node n.

[0046] Moreover, the optimal clearing model for the lower hydrogen market is constructed as follows:

[0047]

[0048]

[0049] Where: The price quoted by the u-th hydrogen user in the hydrogen market for purchasing hydrogen in period t; They are the bids for buying and selling hydrogen for the jth electricity-hydrogen coupling enterprise in period t, respectively; The hydrogen selling price of the rth other hydrogen selling enterprise in period t; The quality of hydrogen that won the bid for the u-th hydrogen user in time period t; and are the quality of hydrogen purchased and sold by the jth electricity-hydrogen coupling enterprise winning the bid in period t, respectively; The quality of hydrogen that won the bid for the rth other hydrogen sales enterprise in period t; The upper and lower limits of hydrogen quality for the u-th hydrogen user's winning bid; are the upper and lower limits of hydrogen quality purchased by the jth electricity-hydrogen coupling enterprise that wins the bid; are the upper and lower limits of hydrogen quality sold by the jth electricity-hydrogen coupling enterprise that wins the bid; The upper and lower limits of hydrogen quality for the rth other hydrogen sales enterprise to win the bid; is the dual variable, which is the clearing hydrogen price in the hydrogen market.

[0050] Moreover, the optimal clearing model for constructing the lower carbon market is:

[0051]

[0052] Where: are the bids for buying and selling carbon quotas in the carbon market by the i-th traditional energy power generation enterprise in period t; The price quoted by the j-th electricity-hydrogen coupling enterprise in period t for selling CCER in the carbon market; The price quoted by the fth other market entity for selling carbon quotas in the carbon market during period t; are the winning bids of the i-th traditional energy power generation enterprise in the carbon market for purchasing and selling carbon quotas in period t; The winning bid amount of CCER sold by the j-th electricity-hydrogen coupling enterprise in the carbon market during period t; The winning bid amount of carbon quota sold by other market entities in the carbon market in period t. The upper limit of purchasing and selling carbon quota for the i-th traditional energy power generation enterprise; The CCER cap for the jth electricity-hydrogen coupling enterprise; The upper limit of selling carbon quotas to other market players participating in the carbon market; b is the set of buyers in the carbon market; s A collection of sellers in the carbon market; The clearing price of carbon emission quotas in the carbon market.

[0053] Moreover, the specific method for obtaining the typical scenario set and the probability of occurrence of each scenario based on the uncertain scenario set of wind power and photovoltaic power generation is as follows:

[0054] Latin hypercube sampling is used to generate a large number of wind power output scenarios subject to probability distribution constraints, and a set of uncertain wind power and photovoltaic power generation scenarios is obtained. The scenario reduction technology of fast backward reduction is used to process the scenario, and the scenario reduction is performed to obtain a typical scenario set and the probability of each scenario occurring.

[0055] The market equilibrium transaction model of the electric-hydrogen coupling enterprise in the electric-hydrogen-carbon multi-coupling market based on the conditional risk value considering the uncertainty of new energy output is constructed as follows:

[0056] The CVaR value of the multi-coupling bidding model for electricity-hydrogen coupling enterprises can be expressed as:

[0057]

[0058] Where: F CVaRThe CVaR value of the multi-coupling market revenue of the electricity-hydrogen coupling enterprise; is the VaR value of the multi-coupling market benefits of the electric-hydrogen coupling enterprise; S is the typical scenario set; ρ s is the probability corresponding to scene s; ζ s It is an auxiliary variable, indicating that the multi-coupling market benefits of electric-hydrogen coupling enterprises in various scenarios are very high. part of;

[0059] In the optimization model of the multi-coupling market of the upper-level electric-hydrogen coupling enterprise, the maximum benefit of the coupling bid under each uncertain scenario is first calculated, and then the maximum expected benefit of the coupling bid is obtained based on the weighted sum of the scenario probabilities. The maximum plus the minimum risk optimization goal is introduced, and the risk aversion coefficient is introduced to transform the multi-objective function of the upper-level model into a single objective function for solution; after considering the uncertain risk of wind and solar power output, the market equilibrium transaction model of the electric-hydrogen coupling enterprise in the electric-hydrogen-carbon multi-coupling market is finally shown as follows:

[0060]

[0061] Where: τ is the risk aversion coefficient, ranging from 0 to 1, τ = 0, which means that risk is not considered.

[0062] An electricity-hydrogen coupling enterprise market trading system under an electricity-hydrogen-carbon coupling market comprises:

[0063] The upper-level decision-making model construction module builds the upper-level decision-making model for spot transactions of electricity-hydrogen coupling enterprises under the electricity-hydrogen-carbon coupling market transaction based on the electricity-hydrogen-carbon multi-coupling market mechanism and trading rules;

[0064] The constraint set construction module builds the constraint set of the upper-level decision-making model of spot trading of electricity-hydrogen coupling enterprises under the electricity-hydrogen-carbon coupling market transaction based on the market mechanism and transaction constraints of market players participating in the coupling market;

[0065] The lower-level model construction module constructs the optimal clearing model of the lower-level electricity spot market, the optimal clearing model of the lower-level hydrogen market, and the optimal clearing model of the lower-level carbon market according to the electricity-hydrogen-carbon coupling market mechanism and trading rules, with the maximization of social welfare of each market transaction as the objective function;

[0066] The typical scenario set construction module obtains the typical scenario set and the probability of occurrence of the corresponding typical scenario based on the uncertain scenario set of wind power and photovoltaic power generation;

[0067] The module for constructing the market equilibrium trading model of the electric-hydrogen coupling enterprise under the electric-hydrogen-carbon multi-coupling market is to construct and solve the market equilibrium trading model of the electric-hydrogen coupling enterprise under the electric-hydrogen-carbon coupling market based on the conditional risk value, according to the upper-level decision-making model of the electric-hydrogen coupling enterprise spot trading under the constructed electric-hydrogen-carbon coupling market and its set of constraints, the optimal clearing model of the lower-level electricity spot market, the optimal clearing model of the lower-level hydrogen market and the optimal clearing model of the lower-level carbon market, the typical scenario set and the probability of the corresponding typical scenarios;

[0068] The clearing module determines whether to carry out balanced clearing based on the solution of the market equilibrium trading model of electricity-hydrogen-carbon coupled enterprises in the electricity-hydrogen-carbon multi-coupled market. If balanced clearing is achieved, the clearing results of the electricity spot market, hydrogen market and carbon market are obtained, that is, the electricity market players win the bid for the amount of electricity, the hydrogen market players win the bid for the amount of hydrogen, and the carbon market players win the bid for the amount of carbon emission rights.

[0069] Moreover, the objective function of the upper-level decision model for spot trading of electricity-hydrogen coupling enterprises under the electricity-hydrogen-carbon coupling market transaction in the upper-level decision model construction module is:

[0070] maxF U =C E +C H +C CCER

[0071]

[0072] Where: F U is the total economic benefit of the electricity-hydrogen coupling enterprise; C E , C H and C CCER The economic benefits obtained by electricity-hydrogen coupling enterprises in the electricity spot market, hydrogen market and carbon market respectively; The power generation capacity of the jth electricity-hydrogen coupling enterprise winning the bid in period l during period t; is the marginal electricity price at the electricity spot market node in time period t; is the marginal power generation cost of the jth electricity-hydrogen coupling enterprise in period t in period l; The amount of hydrogen sold by the j-th electricity-hydrogen coupling enterprise in the hydrogen market during period t; The amount of hydrogen purchased by the j-th electricity-hydrogen coupling enterprise in the hydrogen market during period t; is the hydrogen market price of hydrogen in period t; is the marginal power generation cost of the jth electric-hydrogen coupling enterprise in the hydrogen market during period t; is the CEA price in the carbon market during period t.

[0073] A computer-readable storage medium stores a computer program, wherein the computer program implements the steps of the method when executed by a processor.

[0074] Advantages and beneficial effects of the present invention:

[0075] 1. The present invention proposes a market transaction method and system for electric-hydrogen coupling enterprises in the electric-hydrogen-carbon coupling market, and establishes a two-layer optimization model for bidding strategies in the electric-hydrogen-carbon multi-coupling market: the upper layer is for maximizing the interests of the market entities in the electric-hydrogen coupling system; the lower layer is for the optimal clearing process of the electric-hydrogen-carbon coupling market, supporting the upper-layer market entities to determine the bidding strategy. The present invention adopts conditional risk value to measure the market risk caused by the uncertainty of new energy output, and considers risk factors as the decision maker's risk preference into the bidding decision process.

[0076] 2. The present invention takes into account that the coupling relationship between the electricity-hydrogen-carbon multi-coupled markets is difficult to characterize, and the mutual influence of transactions between markets is unclear, and constructs a two-layer optimization model for the bidding strategy of the electricity-hydrogen-carbon multi-coupled market: the upper layer is for maximizing the interests of the market entities of the electricity-hydrogen-carbon coupled enterprises; the lower layer is the optimal clearing process of the electricity-hydrogen-carbon coupled market, which supports the upper-layer market entities to determine the bidding strategy, and realize their reasonable quotation and quotation in the multi-coupled market, so as to determine their own bidding strategy, maximize the economic benefits of the spot market, and achieve balance among the multi-markets. Considering the uncertainty of new energy output, the conditional risk value is used to measure the market risk caused by uncertainty, and the risk factor is considered as the decision maker's risk preference and included in the bidding decision process. It proactively emphasizes the balanced transaction decision model of the electricity-hydrogen coupled enterprises under the multi-coupled market transactions under the condition of increasing new energy penetration, as well as the impact on bidding decisions under uncertainty. BRIEF DESCRIPTION OF THE DRAWINGS

[0077] Figure 1 It is a multi-coupling market joint decision-making flow chart of the present invention;

[0078] Figure 2 A schematic diagram of a typical wind power output scenario set of the present invention;

[0079] Figure 3 A schematic diagram of a typical photovoltaic output scenario set of the present invention;

[0080] Figure 4 The electricity spot market clearing electricity price and winning bid electricity quantity diagram of the present invention;

[0081] Figure 5 A hydrogen market clearing hydrogen price and a winning hydrogen quantity diagram of the present invention;

[0082] Figure 6 It is a graph of the carbon market clearing carbon price and the winning carbon quantity of the present invention. DETAILED DESCRIPTION

[0083] The embodiments of the present invention are further described in detail below with reference to the accompanying drawings:

[0084] A market transaction method for electricity-hydrogen coupling enterprises in the electricity-hydrogen-carbon coupling market, such as Figure 1 As shown, the following steps are included:

[0085] Step 1: Based on the electricity-hydrogen-carbon multi-coupling market mechanism and trading rules, build an upper-level decision-making model for spot trading of electricity-hydrogen coupling enterprises under the electricity-hydrogen-carbon coupling market transaction;

[0086] The upper-level decision-making model for spot transactions of electricity-hydrogen coupling enterprises in the electricity-hydrogen-carbon coupling market is mainly a bidding model for electricity-hydrogen coupling enterprises, and the objective function is to maximize the profits of market entities of electricity-hydrogen coupling enterprises.

[0087] The upper model is the electricity-hydrogen-carbon coupling transaction spot market electricity-hydrogen coupling enterprise decision model, which takes the maximization of the electricity-hydrogen coupling system revenue as the decision objective function. Its revenue includes electricity spot market revenue, hydrogen market revenue, and carbon market revenue. The electricity spot market revenue includes electricity sales revenue and power generation costs. The hydrogen market revenue includes hydrogen sales revenue, hydrogen purchase costs, and power generation costs. The carbon market revenue includes the CCER sales revenue.

[0088] The objective function of the upper-level decision-making model for spot trading of electricity-hydrogen-carbon coupled enterprises under the electricity-hydrogen-carbon coupled market transaction is:

[0089] maxF U =C E +C H +C CCER

[0090]

[0091] Where: F U is the total economic benefit of the electricity-hydrogen coupling enterprise; C E , C H and C CCER The economic benefits obtained by electricity-hydrogen coupling enterprises in the electricity spot market, hydrogen market and carbon market respectively; The power generation capacity of the jth electricity-hydrogen coupling enterprise winning the bid in period l during period t; is the marginal electricity price at the electricity spot market node in time period t; is the marginal power generation cost of the jth electricity-hydrogen coupling enterprise in period t in period l; The amount of hydrogen sold by the j-th electricity-hydrogen coupling enterprise in the hydrogen market during period t; The amount of hydrogen purchased by the j-th electricity-hydrogen coupling enterprise in the hydrogen market during period t; is the hydrogen market price of hydrogen in period t; is the marginal power generation cost of the jth electric-hydrogen coupling enterprise in the hydrogen market during period t; is the CEA price in the carbon market during period t.

[0092] Step 2: Based on the market mechanism and transaction constraints of market players participating in the coupled market, a set of constraint conditions for the upper-level decision-making model of spot transactions of electricity-hydrogen coupled enterprises under the electricity-hydrogen-carbon coupled market transaction is constructed;

[0093] The constraint condition set for constructing the upper-level decision-making model for spot trading of electricity-hydrogen-carbon coupled enterprises under the electricity-hydrogen-carbon coupled market transaction includes:

[0094] 1) Quotation constraints:

[0095]

[0096]

[0097]

[0098] Where: is the bid of the jth electricity-hydrogen coupling system in period l during period t; are the upper and lower limits of the price quoted by the jth electricity-hydrogen coupling enterprise in the electricity spot market; is the bid price of the j-th electricity-hydrogen coupling enterprise in the hydrogen market for buying and selling hydrogen in period t; are the upper and lower limits of the hydrogen sales quotation of the jth electricity-hydrogen coupling enterprise in the hydrogen market; They are the upper and lower limits of the hydrogen purchase quotation of the jth electricity-hydrogen coupling enterprise in the hydrogen market; The price quoted by the j-th electricity-hydrogen coupling enterprise in period t to sell CCER in the carbon market; They are respectively the upper and lower limits of CCER quotations in the j-th electricity-hydrogen coupled enterprise carbon market.

[0099] 2) Electrolyzer operation constraints:

[0100] The electrolyzer is the key equipment for producing hydrogen by electrolyzing water, and its operation model is:

[0101]

[0102] Where: is the hydrogen production mass of the electrolyzer during time period t; The power consumption of electrolytic cell for water electrolysis during time period t; is the electrolysis efficiency of the electrolyzer device; Hydrogen has a high calorific value.

[0103] 3) Hydrogen storage tank operation constraints:

[0104] The electrolyzed hydrogen is stored in a hydrogen storage tank; based on the ideal gas state equation, the following hydrogen storage tank model is established:

[0105]

[0106] Where: is the pressure of the hydrogen storage tank during time period t; V LHS is the volume of the hydrogen storage tank; R is the ideal gas constant; T H is the gas temperature; is the mass of hydrogen in the hydrogen storage tank during time period t; is the relative molecular mass of hydrogen.

[0107] 4) Compressor operation constraints:

[0108] In order to increase the energy density of hydrogen, a compressor is used to pressurize hydrogen. The power consumption of the compressor is mainly related to the hydrogen compression ratio and intake volume. Its operation model is:

[0109]

[0110] Where: is the specific heat capacity of hydrogen; T in is the hydrogen temperature input to the compressor; γ is the isentropic index of hydrogen; are the output hydrogen pressure and input hydrogen pressure of the compressor, is the compression ratio; is the total power consumption of the compressor during time period t; is the hydrogen mass entering the compressor during period t; η CP The working efficiency of the compressor.

[0111] 5) Operation constraints of liquefied hydrogen production equipment:

[0112] In order to convert normal hydrogen into liquid hydrogen, it needs to be compressed, expanded and cooled. In order to take the power consumption of producing liquid hydrogen into consideration, the unit energy consumption of hydrogen liquefaction is an indicator to measure the power consumption of producing liquid hydrogen.

[0113] The unit energy consumption of hydrogen liquefaction is the ratio of the total energy consumption of the liquefaction process to the unit mass flow rate of the product. For the hydrogen liquefaction process, the main power-consuming equipment is the compressor, expander and cooler, which can output work and heat to the outside. The operation model of hydrogen liquefaction equipment is:

[0114]

[0115] Where: is the unit energy consumption of hydrogen liquefaction process in time period t; is the power consumption of the compressor during time period t; is the power consumption of the expander during period t; The heat output of the cooler for time period t; is the quality of liquid hydrogen product in time period t; is the total power consumption of the hydrogen liquefaction process during period t; is the hydrogen quality of the hydrogen liquefaction process during period t; The efficiency of the hydrogen liquefaction process.

[0116] 6) Electric power balance constraints:

[0117]

[0118] Where: It is the predicted value of new energy output.

[0119] Step 3: According to the electricity-hydrogen-carbon coupling market mechanism and trading rules, the optimal clearing model of the lower electricity spot market, the optimal clearing model of the lower hydrogen market and the optimal clearing model of the lower carbon market are respectively constructed, with the maximization of social welfare of each market transaction as the objective function;

[0120] The optimal clearing model for the lower-level electricity spot market is:

[0121] In the electricity spot market, the market players are traditional energy power generation companies, electricity-hydrogen coupling companies and electricity users. The objective function of the day-ahead market clearing is to maximize the social welfare of electricity trading:

[0122]

[0123]

[0124]

[0125] Where: The power bid by the vth power user in the cth segment during time period t; is the bid of the vth electricity user in period c during period t; The upper and lower limits of the winning bid of the i-th traditional energy power generation enterprise in the o-th segment; The upper and lower limits of the winning bid of the jth electricity-hydrogen coupling enterprise in the lth section; The upper and lower limits of the winning bid of the vth power user in the cth segment; is the node set associated with node n; is the set of power user loads associated with node n; is the set of traditional energy generators associated with node n; B is the set of electricity-hydrogen coupling enterprise units associated with node n; n,m is the line susceptance from node n to node m; are the phase angles of node n and node m in time period t respectively; is the transmission power limit of the line from node n to node m; and The upper and lower limits of the phase angle of node n in time period t; The node marginal electricity price of node n.

[0126] An optimal clearing model for the lower-level hydrogen market is constructed, with maximizing social welfare as the objective function, to obtain the hydrogen market clearing results.

[0127] The optimal clearing model for the lower hydrogen market is:

[0128] In the hydrogen market, the market players are electricity-hydrogen coupling enterprises, hydrogen energy users and other hydrogen selling enterprises. The objective function of hydrogen market clearing is to maximize the social welfare of hydrogen energy trading:

[0129]

[0130]

[0131]

[0132] Where: The price quoted by the u-th hydrogen user in the hydrogen market for purchasing hydrogen in period t; They are the bids for buying and selling hydrogen for the jth electricity-hydrogen coupling enterprise in period t, respectively; The hydrogen selling price of the rth other hydrogen selling enterprise in period t; The quality of hydrogen that won the bid for the u-th hydrogen user in time period t; and are the quality of hydrogen purchased and sold by the jth electricity-hydrogen coupling enterprise winning the bid in period t, respectively; The quality of hydrogen that won the bid for the rth other hydrogen sales enterprise in period t; The upper and lower limits of hydrogen quality for the u-th hydrogen user's winning bid; are the upper and lower limits of hydrogen quality purchased by the jth electricity-hydrogen coupling enterprise that wins the bid; are the upper and lower limits of hydrogen quality sold by the jth electricity-hydrogen coupling enterprise that wins the bid; The upper and lower limits of hydrogen quality for the rth other hydrogen sales enterprise to win the bid; is the dual variable, which is the clearing hydrogen price in the hydrogen market.

[0133] Construct an optimal clearing model for the lower carbon market, take social welfare maximization as the objective function, and obtain the carbon clearing results;

[0134] The optimal clearing model for constructing the lower carbon market is:

[0135] In the carbon market, the market players are electricity-hydrogen coupling enterprises, traditional energy power generation enterprises and other market players participating in the carbon market. The objective function of carbon market clearing is to maximize the social welfare of carbon market transactions:

[0136]

[0137]

[0138] Where: are the bids for buying and selling carbon quotas in the carbon market by the i-th traditional energy power generation enterprise in period t; The price quoted by the j-th electricity-hydrogen coupling enterprise in period t for selling CCER in the carbon market; The price quoted by the fth other market entity for selling carbon quotas in the carbon market during period t; are the winning bids of the i-th traditional energy power generation enterprise in the carbon market for purchasing and selling carbon quotas in period t; The winning bid amount of CCER sold by the j-th electricity-hydrogen coupling enterprise in the carbon market during period t; The winning bid amount of carbon quota sold by other market entities in the carbon market in period t. The upper limit of purchasing and selling carbon quota for the i-th traditional energy power generation enterprise; The CCER cap for the jth electricity-hydrogen coupling enterprise; The upper limit of selling carbon quotas to other market players participating in the carbon market; b is the set of buyers in the carbon market; s A collection of sellers in the carbon market; The clearing price of carbon emission quotas in the carbon market.

[0139] Step 4: Based on the uncertain scenario set of wind power and photovoltaic power generation, obtain the typical scenario set and the probability of occurrence of the corresponding typical scenario;

[0140] The specific method for obtaining the typical scenario set and the probability of occurrence of each scenario based on the uncertain scenario set of wind power and photovoltaic power generation is as follows:

[0141] Latin hypercube sampling is used to generate a large number of wind power output scenarios subject to probability distribution constraints, and a set of uncertain scenarios of wind power and photovoltaic power generation is obtained. The scenario reduction technology of fast backward reduction is used to process the scenario, and scenario reduction is performed to obtain a typical scenario set and the probability of occurrence of each scenario.

[0142] Step 5: Based on the constructed upper-level decision-making model of spot transactions of electric-hydrogen coupled enterprises under the electric-hydrogen-carbon coupled market transaction and its constraint condition set, the optimal clearing model of the lower-level electricity spot market, the optimal clearing model of the lower-level hydrogen market and the optimal clearing model of the lower-level carbon market, and the typical scenario set as well as the probability of occurrence of the corresponding typical scenarios, a market equilibrium transaction model of electric-hydrogen coupled enterprises under the electric-hydrogen-carbon multi-coupling market considering the uncertainty of new energy output is constructed and solved based on the conditional risk value;

[0143] The specific method for constructing a market equilibrium transaction model for electric-hydrogen coupling enterprises in the electric-hydrogen-carbon multi-coupling market based on conditional risk value considering the uncertainty of new energy output is as follows:

[0144] The CVaR value of the multi-coupling bidding model for electricity-hydrogen coupling enterprises can be expressed as:

[0145]

[0146] Where: F CVaR The CVaR value of the multi-coupling market revenue of the electricity-hydrogen coupling enterprise; is the VaR value of the multi-coupling market benefits of the electric-hydrogen coupling enterprise; S is the typical scenario set; ρ s is the probability corresponding to scene s; ζ s It is an auxiliary variable, indicating that the multi-coupling market benefits of electric-hydrogen coupling enterprises in various scenarios are very high. part.

[0147] In the optimization model of the multi-coupling market of the upper-level electric-hydrogen coupling enterprise, the maximum benefit of the coupling bid under each uncertain scenario is first calculated, and then the maximum expected benefit of the coupling bid is obtained based on the weighted sum of the scenario probabilities. The maximum plus the minimum risk optimization goal is introduced, and the risk aversion coefficient is introduced to transform the multi-objective function of the upper-level model into a single objective function for solution; after considering the uncertain risk of wind and solar power output, the final market equilibrium transaction model of the electric-hydrogen coupling enterprise in the electric-hydrogen-carbon multi-coupling market is:

[0148]

[0149] Where: τ is the risk aversion coefficient, ranging from 0 to 1, τ = 0, which means that risk is not considered.

[0150] Step 6. Based on the solution results of the market equilibrium trading model of the electricity-hydrogen-carbon coupled enterprise in the electricity-hydrogen-carbon multi-coupled market, determine whether to perform equilibrium clearing. If equilibrium clearing is achieved, the clearing results of the electricity spot market, hydrogen market and carbon market are obtained. The clearing results include the winning electricity volume of the electricity market entities, the winning hydrogen volume of the hydrogen market entities, and the winning carbon emission rights volume of the carbon market entities.

[0151] An electricity-hydrogen coupling enterprise market trading system under an electricity-hydrogen-carbon coupling market comprises:

[0152] The upper-level decision-making model construction module builds the upper-level decision-making model for spot transactions of electricity-hydrogen coupling enterprises under the electricity-hydrogen-carbon coupling market transaction based on the electricity-hydrogen-carbon multi-coupling market mechanism and trading rules;

[0153] The constraint set construction module builds the constraint set of the upper-level decision-making model of spot trading of electricity-hydrogen coupling enterprises under the electricity-hydrogen-carbon coupling market transaction based on the market mechanism and transaction constraints of market players participating in the coupling market;

[0154] The lower-level model construction module constructs the optimal clearing model of the lower-level electricity spot market, the optimal clearing model of the lower-level hydrogen market, and the optimal clearing model of the lower-level carbon market according to the electricity-hydrogen-carbon coupling market mechanism and trading rules, with the maximization of social welfare of each market transaction as the objective function;

[0155] The typical scenario set construction module obtains the typical scenario set and the probability of occurrence of the corresponding typical scenario based on the uncertain scenario set of wind power and photovoltaic power generation;

[0156] The module for constructing the market equilibrium trading model of the electric-hydrogen coupling enterprise under the electric-hydrogen-carbon multi-coupling market is to construct and solve the market equilibrium trading model of the electric-hydrogen coupling enterprise under the electric-hydrogen-carbon coupling market based on the conditional risk value, according to the upper-level decision-making model of the electric-hydrogen coupling enterprise spot trading under the constructed electric-hydrogen-carbon coupling market and its set of constraints, the optimal clearing model of the lower-level electricity spot market, the optimal clearing model of the lower-level hydrogen market and the optimal clearing model of the lower-level carbon market, the typical scenario set and the probability of the corresponding typical scenarios;

[0157] The clearing module determines whether to carry out balanced clearing based on the solution of the market equilibrium trading model of electricity-hydrogen-carbon coupled enterprises in the electricity-hydrogen-carbon multi-coupled market. If balanced clearing is achieved, the clearing results of the electricity spot market, hydrogen market and carbon market are obtained, that is, the electricity market players win the bid for the amount of electricity, the hydrogen market players win the bid for the amount of hydrogen, and the carbon market players win the bid for the amount of carbon emission rights.

[0158] The objective function of the upper-level decision-making model for spot trading of electricity-hydrogen coupling enterprises under the electricity-hydrogen-carbon coupling market transaction constructed in the upper-level decision-making model construction module is:

[0159] maxF U =C E +C H +C CCER

[0160]

[0161] Where: F U is the total economic benefit of the electricity-hydrogen coupling enterprise; C E , C H and C CCER The economic benefits obtained by electricity-hydrogen coupling enterprises in the electricity spot market, hydrogen market and carbon market respectively; The power generation capacity of the jth electricity-hydrogen coupling enterprise winning the bid in period l during period t; is the marginal electricity price at the electricity spot market node in time period t; is the marginal power generation cost of the jth electricity-hydrogen coupling enterprise in period t in period l; The amount of hydrogen sold by the j-th electricity-hydrogen coupling enterprise in the hydrogen market during period t; The amount of hydrogen purchased by the j-th electricity-hydrogen coupling enterprise in the hydrogen market during period t; is the hydrogen market price of hydrogen in period t; is the marginal power generation cost of the jth electric-hydrogen coupling enterprise in the hydrogen market during period t; is the CEA price in the carbon market during period t.

[0162] A computer-readable storage medium stores a computer program, wherein the computer program implements the steps of the method when executed by a processor.

[0163] The present invention is further described below by means of specific examples:

[0164] The following is a market equilibrium optimization trading method for an electricity-hydrogen coupling system in an electricity-hydrogen-carbon multi-coupling market of the present invention, with reference to examples and drawings.

[0165] The improved PJM5 machine 5-node system is selected as an example for simulation analysis. Consider that there are 4 traditional energy power generation companies, electric hydrogen coupling companies and power users participating in the power market competition. Electric hydrogen coupling companies, traditional power generation companies and 3 other companies selling carbon quotas participate in the carbon market competition. Electric hydrogen coupling companies, 2 other hydrogen supply companies and hydrogen purchasers participate in the hydrogen market competition. Electric hydrogen coupling companies predict wind power and photovoltaic output as shown. Power generation companies and users all use five-stage quotation quotation, and electric hydrogen coupling companies also use five-stage quotation to participate in market bidding.

[0166] Figure 4 It is represented by the clearing price of the electricity spot market and the amount of electricity that the market players won the bid for. Figure 4It can be seen that during the period of 0:00-6:00, the amount of electricity cleared by the electric-hydrogen coupling system in the electricity spot market increased. In the 3:00 period, the clearing rate was the largest, reaching 60%. In the morning period, as the load demand increased, the clearing electricity price gradually increased, and the clearing rate of the electric-hydrogen coupling system was above 1 / 3. In the afternoon period, as the load demand changed, the clearing electricity price first dropped and then rose, and the clearing rate remained at around 30%, which was less than the amount of electricity won by unit 1. This is because the amount of hydrogen won by the electric-hydrogen coupling system in the hydrogen market increased, the amount of electricity cleared in the electricity market decreased, and the clearing of G1 units increased, resulting in an increase in the clearing electricity price. In the evening period, as the demand for electricity tightened significantly, the electricity price decreased, the amount of electricity won by the electric-hydrogen coupling system decreased, and the amount of electricity won in the hydrogen market increased. Since G1 has the largest unit capacity, its clearing rate in the day-ahead spot market is basically greater than 30%, and its maximum clearing rate is 41.67%. Due to the large CEI, G2 has less electricity volume in the market, and the maximum clearance rate is only 14.23%. G4 and G5 have smaller unit capacities and are low-carbon emission units. As the clearing electricity price increases, the number of electricity volume won increases, and the clearance rates remain at around 15% and 20%.

[0167] Figure 5 It is represented by the hydrogen market clearing hydrogen price and the hydrogen quantity won by the market players. Figure 5 It can be seen that during the period of 0:00-8:00, in order to reduce wind curtailment, the electric-hydrogen coupling system cleared the hydrogen market through green electricity hydrogen production, and the maximum clearing rate reached 77.91%. During the day, as the demand for hydrogen load gradually increased, the clearing hydrogen price increased. Since the profit of the electricity market is higher than that of the hydrogen market, the electric-hydrogen coupling system gives priority to the electricity market for supply, resulting in a decrease in the amount of hydrogen winning bids and a clearing rate fluctuating around 30%. In the evening, as the clearing electricity price decreases, the amount of hydrogen winning bids in the hydrogen market of the electric-hydrogen coupling system increases, and the clearing rate accounts for more than 40%, with the highest being 62.45%. Due to the use of green electricity to produce hydrogen, the cost of hydrogen production is lower than that of hydrogen produced by traditional energy generation, so green electricity hydrogen production has economic advantages in clearing the hydrogen market. On the basis of meeting the hydrogen load, the electric-hydrogen coupling system achieves an increase in the amount of hydrogen winning bids and an ideal market clearing situation under the electric-hydrogen coupling condition. At the same time, according to the mutual influence of the coupling market, the bidding strategy of the electric-hydrogen coupling system in the hydrogen market is determined.

[0168] Figure 6 Indicates the carbon market clearing carbon price and the number of CEAs that market players have won. Figure 6It can be seen that EHCS won a total of 172.68tCCER. In the early stage of carbon compliance, due to the abundant number of CEAs of traditional units, EHCS's clearing CCER in the carbon market decreased, and the maximum winning bid was 12.29tCCER. As the compliance deadline approaches, the demand for quotas of traditional units increases, resulting in an increase in the clearing carbon price in the carbon market. During the period of 18:00-24:00, EHCS's winning CCER in the carbon market increased, with a maximum of 20t and a minimum of 5.97t. G1 has the largest CEI and the largest amount of electricity, and its carbon emissions exceed the number of carbon quotas allocated by the state. It needs to fulfill the contract with a large number of CEAs and needs to purchase excess CEAs to complete the full clearance task. It purchased 100.05tCCER. G2 and G1 have similar market behaviors. Due to the tight quota resources, they purchase carbon quotas during most of the time period. It purchased 27.09tCCER. G1 and G2 units are both high-emission units. In order to obtain income in the carbon market, they only sell a certain amount of carbon quotas in the early stage of compliance, and purchase quotas most of the other time. G4 is a low-carbon emission unit. After accounting, there is a surplus quota. When the carbon price is low, it buys quotas in the market and sells them when the carbon price is high, realizing arbitrage in the carbon market. It sold 230.41t. G5 is a low-carbon emission gas unit. After accounting, there is a small amount of surplus CEA, so its market behavior in the carbon market is relatively small, and it only sells 32.4t. In the carbon market that adopts a bidding strategy, as the compliance deadline approaches, the carbon price rises, and EHCS clears more CCERs in the carbon market, obtaining more income.

[0169] Compared with the electricity-carbon coupling model, the multi-coupling transaction results of electricity-hydrogen coupling enterprises are analyzed. Model 1 is the model proposed in this invention, and model 2 is the electricity-carbon coupling model, which mainly considers the carbon quota constraint and adopts a fixed price in the hydrogen market.

[0170] As shown in Table 1, the model proposed in the present invention has certain advantages over other proposed models in terms of revenue in multiple markets, and the total economic benefit of Model 1 is 22.24% higher than that of Model 2. In Model 2, the traditional units have a total carbon quota limit, which is a full electricity-carbon coupling benefit, resulting in more electricity market clearing than Model 1, and the economic benefits of electricity-hydrogen coupling enterprises in the electricity market are slightly less; the hydrogen market model proposed in Model 1 is in the form of bidding, which obtains more market benefits than Model 2. The difference in economic benefits between Models 1 and 2 mainly comes from the hydrogen market, indicating that the market mechanism under the electricity-hydrogen-carbon coupling market transaction and the coupling transaction decisions made by the electricity-hydrogen coupling enterprises have economic benefits advantages.

[0171] In order to verify the impact of different risk aversion coefficients on bidding returns and CVaR, Table 2 shows the impact of risk aversion coefficients on market returns. The results show that the expected return decreases as the risk aversion coefficient increases, indicating that in order to resist risks, reduce self-generated economic returns, and minimize the market risks caused by uncertainty parameters, enterprises adopt more conservative bidding strategies in all scenarios. CVaR increases with the increase of risk aversion coefficient, indicating that the more risk-averse the enterprise is, the more conservative the bidding strategy of the decision-making is, and the lower the risk faced, that is, the value of CVaR increases.

[0172] Table 1 Results of electricity-hydrogen coupling enterprise profits under different proposed models

[0173]

[0174] Table 2 Return-risk results under different risk aversion coefficients

[0175] Risk aversion coefficient Expected income (ten thousand yuan) CVaR value (ten thousand yuan) 0 77.378 77.1183 0.2 77.3658 77.1300 0.4 77.352 77.1312 0.6 77.3441 77.1406 0.8 77.3321 77.1498 1 77.3262 77.1584

[0176] It should be emphasized that the embodiments of the present invention are illustrative rather than restrictive. Therefore, the present invention includes but is not limited to the embodiments described in the specific implementation modes. Any other implementation modes derived by those skilled in the art based on the technical solutions of the present invention also fall within the scope of protection of the present invention.

Claims

1. A market transaction method for electricity-hydrogen coupling enterprises in an electricity-hydrogen-carbon coupling market, characterized by: The following steps are involved: Based on the electricity-hydrogen-carbon multi-coupling market mechanism and trading rules, an upper-level decision-making model for spot trading of electricity-hydrogen coupling enterprises under the electricity-hydrogen-carbon coupling market transaction is constructed; Based on the market mechanism and transaction constraints of market players participating in the coupled market, a set of constraint conditions for the upper-level decision-making model of spot transactions of electricity-hydrogen coupled enterprises under the electricity-hydrogen-carbon coupled market transaction is constructed; According to the electricity-hydrogen-carbon coupling market mechanism and trading rules, the optimal clearing model of the lower-level electricity spot market, the optimal clearing model of the lower-level hydrogen market and the optimal clearing model of the lower-level carbon market are constructed respectively, with the maximization of social welfare of each market transaction as the objective function; Based on the uncertain scenario set of wind power and photovoltaic power generation, a typical scenario set and the probability of occurrence of the corresponding typical scenario are obtained; According to the upper-level decision-making model of spot transactions of electric-hydrogen coupled enterprises under the constructed electric-hydrogen-carbon coupled market transactions and its set of constraints, the optimal clearing model of the lower-level electricity spot market, the optimal clearing model of the lower-level hydrogen market and the optimal clearing model of the lower-level carbon market, and the typical scenario set as well as the probability of occurrence of the corresponding typical scenarios, based on the conditional risk value, the market equilibrium transaction model of electric-hydrogen coupled enterprises in the electric-hydrogen-carbon multi-coupling market considering the uncertainty of new energy output is constructed and solved; Based on the solution results of the market equilibrium trading model of electricity-hydrogen-carbon coupled enterprises in the electricity-hydrogen-carbon multi-coupled market, it is judged whether to carry out equilibrium clearing. If equilibrium clearing is achieved, the clearing results of the electricity spot market, hydrogen market and carbon market are obtained. The clearing results include the winning electricity volume of electricity market entities, the winning hydrogen volume of hydrogen market entities, and the winning carbon emission rights volume of carbon market entities.

2. The market transaction method for electricity-hydrogen coupling enterprises in the electricity-hydrogen-carbon coupling market according to claim 1 is characterized by: The objective function of the upper-level decision-making model for spot trading of electricity-hydrogen-carbon coupled enterprises under the electricity-hydrogen-carbon coupled market transaction is: maxF U =C E +C H +C CCER Where: F U is the total economic benefit of the electricity-hydrogen coupling enterprise; C E , C H and C CCER The economic benefits obtained by electricity-hydrogen coupling enterprises in the electricity spot market, hydrogen market and carbon market respectively; The power generation capacity of the jth electricity-hydrogen coupling enterprise winning the bid in period l during period t; is the marginal electricity price at the electricity spot market node in time period t; is the marginal power generation cost of the jth electricity-hydrogen coupling enterprise in period t in period l; The amount of hydrogen sold by the j-th electricity-hydrogen coupling enterprise in the hydrogen market during period t; The amount of hydrogen purchased by the j-th electricity-hydrogen coupling enterprise in the hydrogen market during period t; is the hydrogen market price of hydrogen in period t; is the marginal power generation cost of the jth electric-hydrogen coupling enterprise in the hydrogen market during period t; is the CEA price in the carbon market during period t.

3. The market transaction method for electricity-hydrogen coupling enterprises in the electricity-hydrogen-carbon coupling market according to claim 1 is characterized by: The constraint condition set for constructing the upper-level decision-making model for spot trading of electricity-hydrogen-carbon coupled enterprises under the electricity-hydrogen-carbon coupled market transaction includes: 1) Quotation constraints: Where: is the bid of the jth electricity-hydrogen coupling system in period l during period t; and are the upper and lower limits of the price quoted by the jth electricity-hydrogen coupling enterprise in the electricity spot market; and is the bid price of the j-th electricity-hydrogen coupling enterprise in the hydrogen market for buying and selling hydrogen in period t; and are the upper and lower limits of the hydrogen sales quotation of the jth electricity-hydrogen coupling enterprise in the hydrogen market; and They are the upper and lower limits of the hydrogen purchase quotation of the jth electricity-hydrogen coupling enterprise in the hydrogen market; The price quoted by the j-th electricity-hydrogen coupling enterprise in period t to sell CCER in the carbon market; and They are the upper and lower limits of CCER quotation in the carbon market of the jth electricity-hydrogen coupling enterprise; 2) Electrolyzer operation constraints: The electrolyzer is the key equipment for producing hydrogen by electrolyzing water, and its operation model is: Where: is the hydrogen production mass of the electrolyzer during time period t; The power consumption of the electrolytic cell for water electrolysis during time period t; is the electrolysis efficiency of the electrolyzer device; It is the high calorific value of hydrogen; 3) Hydrogen storage tank operation constraints: The electrolyzed hydrogen is stored in a hydrogen storage tank. Based on the ideal gas state equation, the following hydrogen storage tank model is established: Where: is the pressure of the hydrogen storage tank during time period t; V LHS is the volume of the hydrogen storage tank; R is the ideal gas constant; T H is the gas temperature; is the mass of hydrogen in the hydrogen storage tank during time period t; is the relative molecular mass of hydrogen; 4) Compressor operation constraints: The power consumption of the compressor is mainly related to the hydrogen compression ratio and intake volume, and its operation model is: Where: is the specific heat capacity of hydrogen; T in is the hydrogen temperature input to the compressor; γ is the isentropic index of hydrogen; and are the output hydrogen pressure and input hydrogen pressure of the compressor, is the compression ratio; P t CP is the total power consumption of the compressor during time period t; is the hydrogen mass entering the compressor during period t; η CP The working efficiency of the compressor; 5) Operation constraints of liquefied hydrogen production equipment: The operation model of hydrogen liquefaction equipment is: Where: W is the unit energy consumption of hydrogen liquefaction process in period t; t CP is the power consumption of the compressor during period t; W t EX is the power consumption of the expander during period t; W t HEX The heat output of the cooler for time period t; is the quality of liquid hydrogen product in time period t; is the total power consumption of the hydrogen liquefaction process during period t; is the hydrogen quality of the hydrogen liquefaction process during period t; The efficiency of the hydrogen liquefaction process; 6) Electric power balance constraints: Where: It is the predicted value of new energy output.

4. The market transaction method for electricity-hydrogen coupling enterprises in the electricity-hydrogen-carbon coupling market according to claim 1 is characterized by: The optimal clearing model for the lower-level electricity spot market is: Where: The power bid by the vth power user in the cth segment during time period t; is the bid of the vth electricity user in period c during period t; and The upper and lower limits of the winning bid of the i-th traditional energy power generation enterprise in the o-th segment; and The upper and lower limits of the winning bid of the jth electricity-hydrogen coupling enterprise in the lth section; and The upper and lower limits of the winning bid of the vth power user in the cth segment; is the node set associated with node n; is the set of power user loads associated with node n; is the set of traditional energy generators associated with node n; B is the set of electricity-hydrogen coupling enterprise units associated with node n; n,m is the line susceptance from node n to node m; and are the phase angles of node n and node m in time period t respectively; is the transmission power limit of the line from node n to node m; and The upper and lower limits of the phase angle of node n in time period t; The node marginal electricity price of node n.

5. The market transaction method for electricity-hydrogen coupling enterprises in the electricity-hydrogen-carbon coupling market according to claim 1 is characterized by: The optimal clearing model for the lower hydrogen market is: Where: The price quoted by the u-th hydrogen user in the hydrogen market for purchasing hydrogen in period t; and They are the bids for buying and selling hydrogen for the jth electricity-hydrogen coupling enterprise in period t, respectively; The hydrogen selling price of the rth other hydrogen selling enterprise in period t; The quality of hydrogen that won the bid for the u-th hydrogen user in time period t; and are the quality of hydrogen purchased and sold by the jth electricity-hydrogen coupling enterprise winning the bid in period t, respectively; The quality of hydrogen that won the bid for the rth other hydrogen sales enterprise in period t; and The upper and lower limits of hydrogen quality for the u-th hydrogen user's winning bid; and are the upper and lower limits of hydrogen quality purchased by the jth electricity-hydrogen coupling enterprise that wins the bid; and are the upper and lower limits of hydrogen quality sold by the jth electricity-hydrogen coupling enterprise that wins the bid; and The upper and lower limits of hydrogen quality for the rth other hydrogen sales enterprise to win the bid; is the dual variable, which is the clearing hydrogen price in the hydrogen market.

6. The market transaction method for electricity-hydrogen coupling enterprises in the electricity-hydrogen-carbon coupling market according to claim 1 is characterized by: The optimal clearing model for constructing the lower carbon market is: Where: and are the bids for buying and selling carbon quotas in the carbon market by the i-th traditional energy power generation enterprise in period t; The price quoted by the j-th electricity-hydrogen coupling enterprise in period t for selling CCER in the carbon market; The price quoted by the fth other market entity for selling carbon quotas in the carbon market during period t; and are the winning bids of the i-th traditional energy power generation enterprise in the carbon market for purchasing and selling carbon quotas in period t; The winning bid amount of CCER sold by the j-th electricity-hydrogen coupling enterprise in the carbon market during period t; The winning bid amount of carbon quota sold by other market entities in the carbon market in period t. and The upper limit of purchasing and selling carbon quota for the i-th traditional energy power generation enterprise; The CCER cap for the jth electricity-hydrogen coupling enterprise; Selling carbon quota caps to other market players participating in the carbon market; Γ b is the set of buyers in the carbon market; s A collection of sellers in the carbon market; The clearing price of carbon emission quotas in the carbon market.

7. The market transaction method for electricity-hydrogen-carbon coupling enterprises in the electricity-hydrogen-carbon coupling market according to claim 1 is characterized by: The specific method for obtaining the typical scenario set and the probability of occurrence of each scenario based on the uncertain scenario set of wind power and photovoltaic power generation is as follows: Latin hypercube sampling is used to generate a large number of wind power output scenarios subject to probability distribution constraints, and a set of uncertain wind power and photovoltaic power generation scenarios is obtained. The scenario reduction technology of fast backward reduction is used to process the scenario, and the scenario reduction is performed to obtain a typical scenario set and the probability of each scenario occurring. The market equilibrium transaction model of the electric-hydrogen coupling enterprise in the electric-hydrogen-carbon multi-coupling market based on the conditional risk value considering the uncertainty of new energy output is constructed as follows: The CVaR value of the multi-coupling bidding model for electricity-hydrogen coupling enterprises can be expressed as: Where: F CVaR The CVaR value of the multi-coupling market revenue of the electricity-hydrogen coupling enterprise; is the VaR value of the multi-coupling market benefits of the electric-hydrogen coupling enterprise; S is the typical scenario set; ρ s is the probability corresponding to scene s; ζ s It is an auxiliary variable, indicating that the multi-coupling market benefits of electric-hydrogen coupling enterprises in various scenarios are very high. part of; In the optimization model of the multi-coupling market of the upper-level electric-hydrogen coupling enterprise, the maximum benefit of the coupling bid under each uncertain scenario is first calculated, and then the maximum expected benefit of the coupling bid is obtained based on the weighted sum of the scenario probabilities. The maximum plus the minimum risk optimization goal is introduced, and the risk aversion coefficient is introduced to transform the multi-objective function of the upper-level model into a single objective function for solution; after considering the uncertain risk of wind and solar power output, the market equilibrium transaction model of the electric-hydrogen coupling enterprise in the electric-hydrogen-carbon multi-coupling market is finally shown as follows: Where: τ is the risk aversion coefficient, ranging from 0 to 1, τ = 0, which means that risk is not considered.

8. A market trading system for electricity-hydrogen-carbon coupled enterprises under the electricity-hydrogen-carbon coupled market, characterized by: include: The upper-level decision-making model construction module builds the upper-level decision-making model for spot transactions of electricity-hydrogen coupling enterprises under the electricity-hydrogen-carbon coupling market transaction based on the electricity-hydrogen-carbon multi-coupling market mechanism and trading rules; The constraint set construction module builds the constraint set of the upper-level decision-making model of spot trading of electricity-hydrogen coupling enterprises under the electricity-hydrogen-carbon coupling market transaction based on the market mechanism and transaction constraints of market players participating in the coupling market; The lower-level model construction module constructs the optimal clearing model of the lower-level electricity spot market, the optimal clearing model of the lower-level hydrogen market, and the optimal clearing model of the lower-level carbon market according to the electricity-hydrogen-carbon coupling market mechanism and trading rules, with the maximization of social welfare of each market transaction as the objective function; The typical scenario set construction module obtains the typical scenario set and the probability of occurrence of the corresponding typical scenario based on the uncertain scenario set of wind power and photovoltaic power generation; The module for constructing the market equilibrium trading model of the electric-hydrogen coupling enterprise under the electric-hydrogen-carbon multi-coupling market is to construct and solve the market equilibrium trading model of the electric-hydrogen coupling enterprise under the electric-hydrogen-carbon coupling market based on the conditional risk value, according to the upper-level decision-making model of the electric-hydrogen coupling enterprise spot trading under the constructed electric-hydrogen-carbon coupling market and its set of constraints, the optimal clearing model of the lower-level electricity spot market, the optimal clearing model of the lower-level hydrogen market and the optimal clearing model of the lower-level carbon market, the typical scenario set and the probability of the corresponding typical scenarios; The clearing module determines whether to carry out balanced clearing based on the solution of the market equilibrium trading model of electricity-hydrogen-carbon coupled enterprises in the electricity-hydrogen-carbon multi-coupled market. If balanced clearing is achieved, the clearing results of the electricity spot market, hydrogen market and carbon market are obtained, that is, the electricity market players win the bid for the amount of electricity, the hydrogen market players win the bid for the amount of hydrogen, and the carbon market players win the bid for the amount of carbon emission rights.

9. The electricity-hydrogen-carbon coupled market electricity-hydrogen-carbon coupled market trading system according to claim 8, characterized in that: The objective function of the upper-level decision-making model for spot trading of electricity-hydrogen coupling enterprises under the electricity-hydrogen-carbon coupling market transaction constructed in the upper-level decision-making model construction module is: maxF U =C E +C H +C CCER Where: F U is the total economic benefit of the electricity-hydrogen coupling enterprise; C E , C H and C CCER The economic benefits obtained by electricity-hydrogen coupling enterprises in the electricity spot market, hydrogen market and carbon market respectively; The power generation capacity of the jth electricity-hydrogen coupling enterprise winning the bid in period l during period t; is the marginal electricity price at the electricity spot market node in time period t; is the marginal power generation cost of the jth electricity-hydrogen coupling enterprise in period t in period l; The amount of hydrogen sold by the j-th electricity-hydrogen coupling enterprise in the hydrogen market during period t; The amount of hydrogen purchased by the j-th electricity-hydrogen coupling enterprise in the hydrogen market during period t; is the hydrogen market price of hydrogen in period t; is the marginal power generation cost of the jth electric-hydrogen coupling enterprise in the hydrogen market during period t; is the CEA price in the carbon market during period t.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the steps of the method as claimed in any one of claims 1 to 7 are implemented.

Images