Multi-microgrid double-layer optimization scheme and system considering electricity and hydrogen hybrid shared energy storage configuration

Abstract

The invention discloses a multi-microgrid double-layer optimization scheme considering electricity and hydrogen hybrid shared energy storage configuration, and the scheme comprises the following steps: for a multi-microgrid architecture considering electricity and hydrogen hybrid shared energy storage configuration, taking the maximum annual profit of a hybrid energy storage station as a target, and building an upper-layer model comprising a first target function and a first constraint condition; establishing a lower-layer model comprising a second objective function and a second constraint condition by taking the minimum annual operation cost of the load balance of the multi-microgrid system as a target; solving a double-layer optimization model constructed according to the upper-layer model and the lower-layer model to obtain a configuration optimization scheme; and measuring the performance of the configuration optimization scheme obtained by the double-layer optimization model according to the evaluation index. The method is suitable for a combined cooling heating and power supply type multi-microgrid system with hydrogen energy requirements, provides an energy purchase approach with more economic benefits for users, solves the problems of light abandoning and wind abandoning, and improves the consumption rate of renewable energy sources; and meanwhile, by optimizing the capacity configuration of the energy storage equipment, the recovery period of investment is shortened, and the benefits of shared energy storage investors are guaranteed.

Description

Technical Field

[0001] The present invention relates to a multi-microgrid double-layer optimization scheme and system considering the configuration of electric and hydrogen hybrid shared energy storage, belonging to the technical field of electric and hydrogen hybrid shared energy storage. Background Art

[0003] The combined heat and power system is an energy-saving and environmentally friendly system that can simultaneously transmit cold energy, heat energy, and electricity to the outside world to meet the user's various energy needs. By introducing decoupling devices such as electric chillers and heat storage tanks into the traditional combined heat and power system, a combined heat and power microgrid can be constructed. This microgrid system has the advantages of promoting clean production and improving energy utilization efficiency. At the same time, it can effectively reduce carbon dioxide emissions and greatly help improve climate change.

[0004] In recent years, with the booming development of the sharing economy and the continuous advancement of energy storage technology, the new business model of energy storage sharing has received widespread attention from various industries. By building centralized energy storage stations, the need for users to independently install energy storage equipment can be effectively reduced, saving equipment costs. At the same time, by integrating decentralized resources and optimizing equipment configuration, the absorption rate of renewable energy is enhanced and the utilization rate of energy is maximized. In addition, this model can also smoothly output unstable electricity, promote supply and demand balance, and improve grid performance and stability. It is considered to be a key factor in promoting the green transformation of the energy industry.

[0005] Judging from the current research status, the shared energy storage business model is still in its infancy. The main research is still focused on the decision-making issues of shared energy storage operators and the scheduling issues between users. There is less research on the capacity configuration of energy storage stations and the maximization of benefits during the life cycle of equipment. The selection of shared energy categories is relatively simple, and most of them only focus on the sharing of electric energy. In addition, in the model of electric and hydrogen hybrid shared energy storage, there is a lack of consideration of the demand for hydrogen energy in the microgrid system. Summary of the invention

[0006] The present invention provides a multi-microgrid two-layer optimization solution and system that takes into account the configuration of electric and hydrogen hybrid shared energy storage, which is suitable for a multi-microgrid system of combined heat and power with hydrogen energy demand, and provides users with a more economical way to purchase energy, solves the problem of abandoned light and wind, and improves the absorption rate of renewable energy; at the same time, by optimizing the capacity configuration of energy storage equipment, it shortens the investment recovery period and protects the interests of shared energy storage investors.

[0007] The technical solution of the present invention is:

[0008] According to a first aspect of the present invention, a multi-microgrid two-layer optimization scheme considering electric and hydrogen hybrid shared energy storage configuration is provided, comprising the following steps:

[0009] Step 1. For a multi-microgrid architecture that considers a hybrid shared energy storage configuration of electricity and hydrogen, an upper model including a first objective function and a first constraint condition is established with the goal of maximizing the annual profit of the hybrid energy storage station; a lower model including a second objective function and a second constraint condition is established with the goal of minimizing the annual operating cost of the multi-microgrid system load balance; wherein, the multi-microgrid that considers a hybrid shared energy storage configuration of electricity and hydrogen includes a multi-microgrid system and a hybrid energy storage station invested and built by an operator; the hybrid energy storage station includes a power storage station and a hydrogen storage station, and the hydrogen storage station includes an electric-to-gas device and a hydrogen storage tank;

[0010] Step 2, solve the double-layer optimization model constructed based on the upper-layer model and the lower-layer model to obtain the configuration optimization solution;

[0011] Step 3: Measure the performance of the configuration optimization solution obtained by the two-layer optimization model based on the evaluation index.

[0012] Further, the establishing of the upper model including the first objective function and the first constraint condition comprises:

[0013] First, establish a hybrid energy storage station "cost-benefit" C u The first objective function with the minimum as the target is as follows:

[0014]

[0015] Where: W is the number of typical days; T w is the number of days corresponding to the wth typical day; C inv,w,ess is the daily average investment cost of the power station; C inv,w,hss is the average daily investment cost of the hydrogen storage station; C ess,w,s C is the cost of purchasing electricity from the microgrid for the wth typical day storage power station; hss,w,s C is the cost of purchasing electricity from the microgrid for the wth typical day; trans,w C is the cost of transporting hydrogen energy from the hydrogen storage station to the microgrid on the wth typical day; serve,w C is the service fee paid to the operator on the micro-network on the wth typical day; ess,w,b is the revenue of the wth typical day storage power station selling electricity to the microgrid; C hss,w,b is the revenue of the hydrogen storage station selling hydrogen to the microgrid on the wth typical day; C hss,w,q The revenue from selling hydrogen to the external hydrogen energy market on the wth typical day of the hydrogen storage station;

[0016] The average daily investment cost of the power storage station is expressed as:

[0017]

[0018] Where: α ess and β essThey are the unit power cost and unit capacity cost of the power storage station respectively; and are the maximum charging and discharging power and maximum capacity of the storage station respectively; T ess Y is the expected number of days of use of the power station; ess The daily maintenance cost of the power station;

[0019] The average daily investment cost of the hydrogen storage station is expressed as:

[0020]

[0021] Where: α p2g and β tank They are the unit power cost and unit capacity cost of the power-to-gas equipment and the hydrogen storage tank respectively; and are the maximum charging and discharging power and maximum capacity of the power-to-gas equipment and the hydrogen storage tank respectively; T p2g T is the expected service life of the power-to-gas equipment; tank Y is the expected number of days the hydrogen storage tank will be used; p2g is the daily maintenance cost of the power-to-gas equipment; tank is the daily maintenance cost of the hydrogen storage tank;

[0022] The cost of the power storage station purchasing electricity from the microgrid is expressed as:

[0023]

[0024] Where: N is the number of microgrids; N T is the number of scheduling cycle time periods; is the electricity price sold by the microgrid to the power storage station during period t; P ess,s,w,i (t) is the power sold by microgrid i to the power storage station in period t on the wth typical day; Δt is the dispatch period;

[0025] The cost of the hydrogen storage station purchasing electricity from the microgrid is expressed as:

[0026]

[0027] Where: is the electricity price sold by the microgrid to the hydrogen storage station during period t; P hss,s,w,i (t) is the power sold by microgrid i to the hydrogen storage station during period t on the wth typical day;

[0028] The cost of transporting hydrogen from the hydrogen storage station to the microgrid is expressed as:

[0029]

[0030] Where: P hss,b,w,i(t) is the power of hydrogen purchased from the hydrogen storage station by microgrid i in period t on the wth typical day; S i is the distance between microgrid i and the hydrogen storage station; The coefficient of converting 1kW of hydrogen into mass;

[0031] The service fee paid to the energy storage operator on the micro-network is expressed as:

[0032]

[0033] Where: κ(t) is the unit price of service fee paid by the microgrid to the energy storage operator during period t; P ess,b,w,i (t) Purchase power from the power storage station for the i-th microgrid t period on each typical day;

[0034] The revenue from the power storage station selling electricity to the microgrid is expressed as:

[0035]

[0036] Where: is the electricity price that the microgrid purchases from the power storage station during period t;

[0037] The revenue from the hydrogen storage station selling hydrogen to the microgrid is expressed as:

[0038]

[0039] Where: is the price at which the microgrid purchases hydrogen from the hydrogen storage station during period t;

[0040] The revenue from the hydrogen storage station selling hydrogen to the external hydrogen energy market is expressed as:

[0041]

[0042] Where: P is the price of hydrogen purchased from the hydrogen storage station by the external hydrogen energy market during period t; hss,q,w (t) is the hydrogen power purchased from the hydrogen storage station by the external hydrogen energy market during the period t on the wth typical day;

[0043] Second, determine the first constraint condition of the first objective function, which includes: the capacity of the power storage station and the hydrogen storage station is proportional to the rated power, the charge state and charging and discharging power constraints of the power storage station, the charge state and charging and discharging power constraints of the hydrogen storage station, and the hydrogen energy load constraints between the hydrogen storage station and the outside world.

[0044] Furthermore, the establishing of the lower model including the second objective function and the second constraint condition comprises:

[0045] First, establish the annual operating cost C to meet the load balance of the multi-microgrid system d The second objective function with minimum as the goal is as follows:

[0046]

[0047] Where: W is the number of typical days; T w is the number of days corresponding to the wth typical day; C grid,w C is the cost of purchasing electricity from the grid for the multi-microgrid system on the wth typical day; fuel,w is the gas cost of the gas turbine and gas boiler on the wth typical day; C ess,w,b C is the cost of the w-th typical day storage power station selling electricity to the microgrid; serve,w C is the service fee paid to the operator on the micro-network on the wth typical day; hss,w,b C is the cost of selling hydrogen from the hydrogen storage station to the microgrid on the wth typical day; ess,w,s C is the cost of purchasing electricity from the microgrid for the wth typical day storage power station; hss,w,s The cost of purchasing electricity from the microgrid for the hydrogen storage station on the wth typical day;

[0048] The cost of purchasing electricity from the power grid for the multi-microgrid system is expressed as:

[0049]

[0050] Where: N is the number of microgrids; N T is the number of scheduling cycle time periods; is the power grid price in period t; P grid,w,i (t) is the power purchased by microgrid i from the grid during period t on the wth typical day; Δt is the dispatch period;

[0051] The gas cost is expressed as:

[0052]

[0053] Where: is the unit volume price of gas; P GT,w,i (t) is the power output of the gas turbine of microgrid i in period t on the wth typical day; η GT is the power generation efficiency of the micro gas turbine; L NG is the calorific value of gas; Q GB,w,i (t) is the thermal power output of the gas boiler of microgrid i in period t on the wth typical day; η GB For the efficiency of gas boilers;

[0054] The cost of the power storage station selling electricity to the microgrid is expressed as:

[0055]

[0056] Where: is the electricity price that the microgrid purchases from the power storage station during period t; P ess,b,w,i(t) Purchase power from the power storage station for the i-th microgrid t period on each typical day;

[0057] The service fee paid to the energy storage operator on the micro-network is expressed as:

[0058]

[0059] Where: κ(t) is the unit price of service fee paid by the microgrid to the energy storage operator during period t; P hss,s,w,i (t) is the power sold by microgrid i to the hydrogen storage station during period t on the wth typical day; P ess,s,w,i (t) is the power sold by microgrid i to the power storage station in period t on the wth typical day;

[0060] The cost of selling hydrogen from the hydrogen storage station to the microgrid is expressed as:

[0061]

[0062] Where: is the price of hydrogen purchased by the microgrid from the hydrogen storage station during period t; P hss,b,w,i (t) is the power of hydrogen purchased from the hydrogen storage station by microgrid i in period t on the wth typical day;

[0063] The cost of the power storage station purchasing electricity from the microgrid is expressed as:

[0064]

[0065] Where: is the electricity price sold by the microgrid to the power storage station during period t;

[0066] The cost of the hydrogen storage station purchasing electricity from the microgrid is expressed as:

[0067]

[0068] Where: is the electricity price sold by the microgrid to the hydrogen storage station during period t;

[0069] Second, determine the second constraint condition of the second objective function, which includes: electric power balance constraint, cold power balance constraint, hot power balance constraint, waste heat boiler waste heat balance constraint, storage station charging and discharging power balance constraint, hydrogen storage station charging balance constraint, hydrogen storage station hydrogen discharge balance constraint, hydrogen load balance constraint, microgrid equipment output upper and lower limit constraints, power purchase from the power grid constraint, power purchase and sale of electricity between microgrid and storage station constraint, and power sale and hydrogen purchase constraint between microgrid and hydrogen storage station.

[0070] Furthermore, the two-layer optimization model constructed according to the upper model and the lower model is solved, specifically: first, the Lagrangian function of the lower model is constructed, and the KKT complementary relaxation condition is used to convert the lower model into the constraint conditions of the upper model, and then the big M method is used to linearize the nonlinear terms in the converted single-layer nonlinear model to form a single-layer mixed integer linear programming problem, and finally the CPLEX solver is called to solve it.

[0071] Furthermore, the evaluation indicators include:

[0072] The recycling period of the power station battery is expressed as:

[0073]

[0074] Where: M ess is the recycling period of the power station battery; C ess,serve,w Service fees earned for the storage station;

[0075] The payback period of the power-to-gas equipment is expressed as:

[0076]

[0077] Where: M p2g is the payback period of the power-to-gas equipment; C hss,serve,w Service fees earned for hydrogen storage stations;

[0078] The recycling period of the hydrogen storage tank is expressed as:

[0079]

[0080] Where: M tank The recycling period of the hydrogen storage tank;

[0081] The operator's payback period is expressed as:

[0082]

[0083] Where: M ope Recovery period for operators.

[0084] According to a second aspect of the present invention, there is provided a multi-microgrid two-layer optimization system considering a hybrid shared energy storage configuration of electricity and hydrogen, comprising a module of a multi-microgrid two-layer optimization scheme considering a hybrid shared energy storage configuration of electricity and hydrogen as described above.

[0085] The beneficial effects of the present invention are:

[0086] The present invention proposes a double-layer optimization model constructed based on an upper-layer model and a lower-layer model. The double-layer optimization model takes into account the interests of both the upper-layer operator and the lower-layer multi-microgrid system, solves the capacity configuration problem of energy storage equipment, and optimizes the operation mode of the multi-microgrid system; combines the combined heat and power microgrid system with electricity and hydrogen hybrid energy storage to promote energy complementarity and utilization, thereby reducing the operating cost of the multi-microgrid system and increasing the operator's income; determines the capacity configuration of each device in the hybrid energy storage station based on the load level and the output of new energy, and obtains the payback period of each device by calculation. BRIEF DESCRIPTION OF THE DRAWINGS

[0087] Figure 1 It is a flow chart of the present invention;

[0088] Figure 2 This is a diagram of the structure of electric and hydrogen hybrid shared energy storage;

[0089] Figure 3 Solve graph for bi-level optimization model;

[0090] Figure 4 This is the charging and discharging optimization diagram of the storage station in scenario 2;

[0091] Figure 5 This is the energy interaction diagram of the microgrid side in scenario 2; Figure 5 (a) is microgrid 1; Figure 5 (b) is microgrid 2; Figure 5 (c) is microgrid 3;

[0092] Figure 6 This is the charging and discharging optimization diagram of the storage power station and hydrogen storage station in scenario 3; Figure 6 (a) It is a power storage station; Figure 6 (b) a hydrogen storage station;

[0093] Figure 7 This is the energy interaction diagram of the microgrid side in scenario 3; Figure 7 (a) is microgrid 1; Figure 7 (b) is microgrid 2; Figure 7 (c) is microgrid 3. DETAILED DESCRIPTION

[0094] In order to make the purpose, technical scheme and advantages of the embodiments of the present invention clearer, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention. It should be noted that the embodiments in this application and the features in the embodiments can be combined with each other arbitrarily without conflict.

[0095] Example 1: Figure 1-7As shown, according to a first aspect of an embodiment of the present invention, a multi-microgrid dual-layer optimization scheme considering electric and hydrogen hybrid shared energy storage configuration is provided, comprising the following steps:

[0096] Step 1. For a multi-microgrid architecture that considers a hybrid shared energy storage configuration of electricity and hydrogen, an upper model including a first objective function and a first constraint condition is established with the goal of maximizing the annual profit of the hybrid energy storage station; a lower model including a second objective function and a second constraint condition is established with the goal of minimizing the annual operating cost of the multi-microgrid system load balance; wherein, the multi-microgrid that considers a hybrid shared energy storage configuration of electricity and hydrogen includes a multi-microgrid system and a hybrid energy storage station invested and built by an operator; the hybrid energy storage station includes a power storage station and a hydrogen storage station, and the hydrogen storage station includes an electric-to-gas device and a hydrogen storage tank;

[0097] Step 2, solve the double-layer optimization model constructed based on the upper-layer model and the lower-layer model to obtain the configuration optimization solution;

[0098] Step 3: Measure the performance of the configuration optimization solution obtained by the two-layer optimization model based on the evaluation index.

[0099] Furthermore, the operator signs a service agreement with the users of the microgrid that couples cooling, heating, electricity and hydrogen energy based on the obtained configuration optimization plan.

[0100] like Figure 2 As shown in the figure, the centralized electric and hydrogen hybrid energy storage station is invested and built by the operator, including storage station, power-to-gas equipment, hydrogen storage tanks and other equipment; the income of the energy storage station includes the service fee paid by the microgrid, the electricity purchase fee of the microgrid, the hydrogen purchase fee of the microgrid, and the hydrogen purchase fee of the external hydrogen energy market; the expenditure of the energy storage station includes the construction cost of the storage station, the construction cost of the hydrogen storage station, the electricity purchase fee of the storage station, the electricity purchase fee of the hydrogen storage station, and the hydrogen transportation fee; considering the economic and feasibility of electric and hydrogen hybrid shared energy storage, the maximum annual profit of the hybrid energy storage station during the planning period is taken as the criterion for measuring whether the scheme is reasonable or not, so the objective function of the upper model is:

[0101]

[0102] Where: W is the number of typical days; T w is the number of days corresponding to the wth typical day; C inv,w,ess is the daily average investment cost of the power station; C inv,w,hss is the average daily investment cost of the hydrogen storage station; C ess,w,s C is the cost of purchasing electricity from the microgrid for the wth typical day storage power station; hss,w,s C is the cost of purchasing electricity from the microgrid for the wth typical day; trans,w C is the cost of transporting hydrogen energy from the hydrogen storage station to the microgrid on the wth typical day; serve,wC is the service fee paid to the operator on the micro-network on the wth typical day; ess,w,b is the revenue of the wth typical day storage power station selling electricity to the microgrid; C hss,w,b is the revenue of the hydrogen storage station selling hydrogen to the microgrid on the wth typical day; C hss,w,q The revenue from selling hydrogen to the external hydrogen energy market on the wth typical day of the hydrogen storage station;

[0103] The average daily investment cost of the power station is:

[0104]

[0105] Where: α ess and β ess are the unit power cost and unit capacity cost of the power storage station, in units of RMB / kw and RMB / (kw·h) respectively; and are the maximum charging and discharging power and maximum capacity of the storage station respectively; T ess Y is the expected number of days of use of the power station; ess The daily maintenance cost of the power station;

[0106] The average daily investment cost of the hydrogen storage station is:

[0107]

[0108] Where: α p2g and β tank They are the unit power cost and unit capacity cost of the power-to-gas equipment and the hydrogen storage tank respectively; and are the maximum charging and discharging power and maximum capacity of the power-to-gas equipment and the hydrogen storage tank respectively; T p2g T is the expected service life of the power-to-gas equipment; tank Y is the expected number of days the hydrogen storage tank will be used; p2g is the daily maintenance cost of the power-to-gas equipment; tank is the daily maintenance cost of the hydrogen storage tank;

[0109] The cost of the power storage station purchasing electricity from the microgrid is:

[0110]

[0111] Where: N is the number of microgrids; N T is the number of scheduling cycle time periods; is the electricity price sold by the microgrid to the power storage station during period t; P ess,s,w,i (t) is the power sold by microgrid i to the power storage station in period t on the wth typical day; Δt is the dispatch period;

[0112] The cost of the hydrogen storage station purchasing electricity from the microgrid is:

[0113]

[0114] Where: is the electricity price sold by the microgrid to the hydrogen storage station during period t; P hss,s,w,i (t) is the power sold by microgrid i to the hydrogen storage station during period t on the wth typical day;

[0115] The cost of transporting hydrogen from the hydrogen storage station to the microgrid is:

[0116]

[0117] Where: P hss,b,w,i (t) is the power of hydrogen purchased from the hydrogen storage station by microgrid i in period t on the wth typical day; S i Hydrogen storage for microgrid i

[0118] The distance between stations, in km; The coefficient of converting 1kW of hydrogen into mass;

[0119] The service fee paid to the energy storage operator on the micro-network is:

[0120]

[0121] Where: κ(t) is the unit price of service fee paid by the microgrid to the energy storage operator during period t, in units of yuan / (kw·h); P ess,b,w,i (t) Purchase power from the power storage station for the i-th microgrid t period on each typical day;

[0122] The revenue from the power storage station selling electricity to the microgrid is:

[0123]

[0124] Where: is the electricity price that the microgrid purchases from the power storage station during period t;

[0125] The income from the hydrogen storage station selling hydrogen to the microgrid is:

[0126]

[0127] Where: is the price at which the microgrid purchases hydrogen from the hydrogen storage station during period t;

[0128] The income from selling hydrogen to the external hydrogen energy market is:

[0129]

[0130] Where: P is the price of hydrogen purchased from the hydrogen storage station by the external hydrogen energy market during period t; hss,q,w(t) is the hydrogen power purchased from the hydrogen storage station by the external hydrogen energy market during period t on the wth typical day.

[0131] Further, the description of the evaluation indicators is as follows:

[0132] The service fee earned by the storage station is:

[0133]

[0134] Where: C ess,serve,w Service fees earned for the storage station;

[0135] The service fee earned by the hydrogen storage station is:

[0136]

[0137] Where: C hss,serve,w Service fees earned for hydrogen storage stations;

[0138] The recycling period of power station batteries is:

[0139]

[0140] Where: M ess The recycling period of the power station battery;

[0141] The recycling period of power-to-gas equipment is:

[0142]

[0143] Where: M p2g is the payback period of the power-to-gas equipment; note that the service fee income earned by the power-to-gas equipment and the hydrogen storage tank is allocated according to the proportion of the investment cost in the hydrogen storage station;

[0144] The recycling period of hydrogen storage tanks is:

[0145]

[0146] Where: M tank The recycling period of the hydrogen storage tank;

[0147] The operator's redemption period is:

[0148]

[0149] Where: M ope It is the recycling period of hydrogen storage tank.

[0150] Furthermore, the upper model should consider the relationship between the rated power and capacity of the energy storage station, the constraints of the state of charge and the charging and discharging power, and the relationship with the external hydrogen energy market. Therefore, the constraints of the upper model are:

[0151] The capacity of the power storage station and hydrogen storage station is proportional to the rated power, specifically:

[0152]

[0153] Where: ess is the energy rate of the power station; δ hss is the energy multiplier of the hydrogen storage station;

[0154] State of charge and charging and discharging power constraints of storage stations:

[0155]

[0156] Where: E ess (t) is the electric energy stored in the power storage station at time t; and is the charging efficiency and discharging efficiency of the storage station; P ess,abs (t) and P ess,relea (t) is the charging power and discharging power of the power storage station at time t; E ess (0) is the initial storage capacity of the power station; U abs (t) and U relea (t) is the charging and discharging status of the storage station at time t, which is a 0-1 variable;

[0157] Hydrogen storage station charge state and charge and discharge power constraints:

[0158]

[0159] Where: E tank (t) is the hydrogen energy stored in the hydrogen storage station at time t; and are the charging efficiency and hydrogen discharging efficiency of the hydrogen storage station respectively; P hss,abs (t) and P hss,relea (t) is the charging power and discharging power of the hydrogen storage station at time t; E tank (0) is the hydrogen energy initially stored in the hydrogen storage station;

[0160] Hydrogen storage station and external hydrogen energy load constraints:

[0161] 0≤P hss,q,w (t)≤P hload,w (t);

[0162] Where: P hload,w (t) is the hydrogen load power of the external hydrogen energy market on the wth typical day.

[0163] like Figure 2As shown in the figure, the microgrid users participating in the electricity and hydrogen sharing service must be a combined cooling, heating and power microgrid system, which includes: wind turbines, photovoltaic devices, gas turbine units, waste heat boilers, heat exchangers, gas boilers, electric refrigerators, absorption refrigerators and other devices, and at the same time, the multi-microgrid system has hydrogen energy demand; reducing user operating costs is the premise for microgrids to participate in shared energy storage services, and by reducing the high cost of purchasing energy and selling excess green electricity, the annual operating cost C of the multi-microgrid system load balance can be achieved. d Therefore, the objective function of the lower model is:

[0164]

[0165] Where: C grid,w C is the cost of purchasing electricity from the grid for the multi-microgrid system on the wth typical day; fuel,w is the gas cost of the gas turbine and gas boiler on the wth typical day;

[0166] The cost of purchasing electricity from the grid for a multi-microgrid system is:

[0167]

[0168] Where: is the power grid price in period t; P grid,w,i (t) is the power purchased by microgrid i from the grid during period t on the wth typical day;

[0169] Gas costs are:

[0170]

[0171] Where: is the unit volume price of gas, yuan / m 3 ;P GT,w,i (t) is the power output of the gas turbine of microgrid i in period t on the wth typical day; η GT is the power generation efficiency of the micro gas turbine; L NG is the calorific value of gas, taking 9.7kW·h / m 3 ;Q GB,w,i (t) is the thermal power output of the gas boiler of microgrid i in period t on the wth typical day; η GB For the efficiency of gas boilers.

[0172] Furthermore, the lower-level model should consider the load balance constraints of cooling, heating, electricity, and hydrogen in the microgrid system, as well as the constraints of energy interaction with the energy storage station. The constraints of the lower-level model are:

[0173] Electrical power balance:

[0174] P grid,w,i (t)+P GT,w,i (t)+Pess,b,w,i (t)+P WT,w,i (t)+P PV,w,i (t) = P ess,s,w,i (t)+P hss,s,w,i (t)+P load,w,i (t)+P EC,w,i (t);

[0175] Where: P WT,w,i (t) is the wind power generation power of microgrid i in period t on the wth typical day; P PV,w,i (t) is the photovoltaic power generation power of microgrid i in period t on the wth typical day; P EC,w,i (t) is the power consumed by the refrigerator in microgrid i during period t on the wth typical day; P load,w,i (t) is the electric load power of microgrid i in period t on the wth typical day;

[0176] Cold Power Balance:

[0177] P EC,w,i (t)η EC +Q AC,w,i (t) = P cool,w,i (t);

[0178] Where: η EC is the energy efficiency ratio of the electric refrigerator; Q AC,w,i (t) is the cooling power output of the absorption chiller of microgrid i in period t on the wth typical day; P cool,w,i (t) is the cooling load power of microgrid i in period t on the wth typical day;

[0179] Thermal power balance:

[0180] Q GB,w,i (t)+P HX,w,i (t) = P heat,w,i (t);

[0181] Where: P HX,w,i (t) is the heating power output of the heat exchanger of microgrid i in period t on the wth typical day; P heat,w,i (t) is the heat load power of microgrid i in period t on the wth typical day;

[0182] Waste heat balance of waste heat boiler:

[0183]

[0184] Where: η HX is the efficiency of the heat exchange device; η AC is the energy efficiency ratio of the absorption chiller; γ GT is the thermal power ratio of the gas turbine; η WH is the efficiency of the waste heat boiler;

[0185] Charging and discharging power balance of storage station:

[0186]

[0187] Hydrogen storage station charging balance:

[0188]

[0189] Hydrogen storage station hydrogen release balance:

[0190]

[0191] Hydrogen load balance:

[0192]

[0193] Where: P hload,w,i (t) is the hydrogen load power of microgrid i in period t on the wth typical day;

[0194] Microgrid equipment output upper and lower limits constraints:

[0195]

[0196] Where: and The minimum and maximum values ​​for the gas turbine output; and The minimum and maximum outputs of the absorption chiller; and The minimum and maximum values ​​for the output of the electric refrigerator; and The minimum and maximum output values ​​of the gas boiler; and The minimum and maximum outputs of the heat exchanger;

[0197] Power purchase constraints from the power grid:

[0198]

[0199] Where: The maximum power that the microgrid can purchase from the grid;

[0200] Power purchase and sales constraints for microgrids and power storage stations:

[0201]

[0202] Where: U b,w,i (t) and U s,w,i (t) are the status of power purchase and power sale between microgrid i and power storage station on the wth typical day; is the maximum interactive power between the microgrid and the power storage station;

[0203] Constraints on electricity sales and hydrogen purchases for microgrids and hydrogen storage stations:

[0204]

[0205] Where: The maximum power of electricity sold by the microgrid to the hydrogen storage station; The maximum power for the microgrid to purchase hydrogen from the hydrogen storage station.

[0206] Construct the Lagrangian function L of the underlying model:

[0207]

[0208]

[0209] Where: 1,i,t,w ,λ 2,i,t,w ,λ 3i,t,w ,λ 4,i,t,w ,λ 5,i,t,w ,λ 6,i,t,w ,λ 7,i,t,w and λ 8,i,t,w is the Lagrange multiplier corresponding to the equality constraint;

[0210]

[0211] and is the Lagrange multiplier corresponding to the inequality constraint; L is the Lagrange function of the lower model;

[0212] The upper layer of the two-layer model includes integer variables such as U abs (t)∈{0,1} and continuous variables such as And there are nonlinear constraints such as The lower layer is a mixed integer linear programming problem. There is a coupling relationship between the upper and lower models, which makes it difficult to solve directly. It is necessary to first construct the Lagrangian function L of the lower model and use the KKT complementary relaxation condition to transform the lower model into the constraint conditions of the upper model. Then use the big M method to linearize the nonlinear terms in the transformed single-layer nonlinear model as follows: 0≤P ess,abs (t)≤U abs (t)M, forming a single-layer mixed integer linear programming problem, and finally calling CPLEX in MATLAB to solve it. The flowchart of the two-layer optimization model solution is as follows: Figure 3 As shown in the formula, M is a sufficiently large constant.

[0213] According to a second aspect of an embodiment of the present invention, a multi-microgrid dual-layer optimization system considering electric and hydrogen hybrid shared energy storage configuration is provided, comprising:

[0214] The first module is used to execute Step 1: for a multi-microgrid architecture considering a hybrid shared energy storage configuration of electricity and hydrogen, an upper model including a first objective function and a first constraint condition is established with the goal of maximizing the annual profit of the hybrid energy storage station; a lower model including a second objective function and a second constraint condition is established with the goal of minimizing the annual operating cost of the multi-microgrid system load balance; wherein the multi-microgrid considering a hybrid shared energy storage configuration of electricity and hydrogen includes a multi-microgrid system and a hybrid energy storage station invested and built by an operator; the hybrid energy storage station includes a power storage station and a hydrogen storage station, and the hydrogen storage station includes an electric-to-gas device and a hydrogen storage tank;

[0215] The second module is used to execute Step 2: solving the two-layer optimization model constructed based on the upper-layer model and the lower-layer model to obtain a configuration optimization solution;

[0216] The third module is used to execute Step 3: measure the performance of the configuration optimization solution obtained by the two-layer optimization model according to the evaluation index.

[0217] The term "module" as used above may be a combination of software and / or hardware that implements a predetermined function. For parts not described in detail for each module, please refer to the relevant description of this embodiment.

[0218] According to a third aspect of an embodiment of the present invention, there is provided an electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the steps of a two-layer optimization scheme for a multi-microgrid considering a hybrid shared energy storage configuration of electricity and hydrogen are implemented as described in any one of the above.

[0219] The present invention is verified by combining the following examples:

[0220] (1) Parameter settings:

[0221] The example selects three unconnected combined cooling, heating and power microgrids as the main body of the lower multi-microgrid system, named microgrid 1, microgrid 2, and microgrid 3, respectively. Each microgrid is directly connected to the hybrid energy storage station. A typical day is selected in each of the four seasons of spring, summer, autumn and winter to simulate the annual operation of the multi-microgrid system. Each typical day has 91 days, and the scheduling time of the typical day is 24 hours. Microgrid 1 is a multi-energy microgrid with a large input of renewable energy, a small and relatively stable electric load, which can meet the electric load demand, and the hydrogen load is mainly concentrated during the day; Microgrid 2 is a power-deficient microgrid with no wind power generation, a large electric load and concentrated during the day, photovoltaic power generation can meet part of the electric load, and there is no hydrogen load; Microgrid 3 is a power-deficient microgrid with a large electric load and a relatively balanced distribution. The photovoltaic power generation and wind power generation are both small, which can only meet a small part of the electric load, and the hydrogen load distribution is relatively balanced.

[0222] To demonstrate the advantages of the proposed solution, the present invention will conduct comparative analysis on the following three scenarios:

[0223] Scenario 1: The combined heat and power multi-microgrid system does not have a separate energy storage device. Excess electricity is directly discarded, and insufficient electricity is purchased from the grid. Hydrogen demand is purchased at market prices.

[0224] Scenario 2: A multi-microgrid system with combined cooling, heating and power generation participates in the electricity sharing service, obtains the charging and discharging rights provided by the storage power station, and purchases hydrogen energy at market prices.

[0225] Scenario 3: A multi-microgrid system with combined heat and power generation participates in the shared energy storage service of electricity and hydrogen, and obtains the charging, discharging and hydrogen purchasing rights provided by the hybrid energy storage station.

[0226] (2) Comparison of optimization results

[0227] Table 1 Comparison of costs, profits, and renewable energy consumption rates under three scenarios

[0228] <![CDATA[Annual operating cost C of multi - microgrid system d / 10,000 yuan]]> <![CDATA[Annual profit of energy storage station - C u / 10,000 yuan]]> Renewable energy consumption rate Scenario 1 3814.43 0 70.13％ Scenario 2 3182.77 360.51 100％ Scenario 3 3105.54 631.95 100％

[0229] Table 2 Comparison of energy storage configuration results for scenario 2 and scenario 3

[0230]

[0231] Table 3 Comparison of equipment recovery years between scenario 2 and scenario 3

[0232] Lifespan / year <![CDATA[Scenario 2 Recovery Period M ess / M ope / year]]> <![CDATA[Scenario 3 Recovery period M ess / M p2g / M tank / M ope / year]]> Power station battery 8 3.39 1.13 Power-to-gas equipment 15 / 5.54 Hydrogen storage tank 25 / 8.41 Operators / 3.39 3.13

[0233] As can be seen from the above table, the introduction of shared energy storage services can effectively reduce the operating costs of microgrid users, increase the absorption rate of renewable energy to 100%, and operators can also obtain considerable profits. Compared with traditional electric energy sharing services, the electric and hydrogen hybrid shared energy storage service proposed in the present invention that takes into account the demand for hydrogen energy has increased equipment investment, but it has achieved a shortened investment recovery period by relying on high returns and long-life equipment. At the same time, it provides microgrid users with a more economical channel for purchasing and selling energy, and further reduces user operating costs.

[0234] It should be noted that the operator's initial configuration cost expression in Table 2 is:

[0235]

[0236] Where: C inv It is the initial configuration cost of the operator.

[0237] (3) Energy interaction analysis

[0238] Taking a typical day in spring as an example, this section conducts a specific analysis of shared energy storage services in this quarter, combining the energy interaction between energy storage stations and microgrids as well as the external hydrogen energy market.

[0239] 1) Energy interaction analysis of scenario 2

[0240] In scenario 2, the optimization of charging and discharging of the storage station and the energy interaction on the microgrid side are as follows: Figure 4 , Figure 5 As shown. Figure 4 It can be seen that the storage power station has no change in the time periods of 02:00-04:00, 06:00-07:00, and 21:00-24:00, and the total charging and discharging power is zero. The power is only exchanged through the busbar of the storage power station to achieve the transfer of energy in space. In the remaining time periods, the storage power station is in a charging or discharging state, and the balance of the entire system is maintained by exchanging energy with the microgrid. The first wave of electric energy accumulation was achieved from 00:00 to 08:00. Figure 5 It can be seen that Microgrid 1 input a large amount of wind power to the power storage station during this period. At the same time, the two energy-deficient microgrids did not consume too much power from the power storage station. Instead, they chose to purchase electricity from the grid and gas from the gas distribution network to generate electricity during the low electricity price period to make up for the lack of electricity. After 08:00, the power price of the power grid soared rapidly. The microgrid stopped purchasing electricity from the grid and relied on cheaper power storage stations for power supply. The power storage station's inventory dropped rapidly. From 10:00 to 14:00, the second wave of electricity accumulation was achieved, and a dynamic balance was maintained near the peak in the following hours. Figure 5It can be seen that during this period, the three microgrids all made different degrees of photovoltaic output, especially microgrid 2 with more photovoltaic equipment, which output a total of 16773.51kW of photovoltaic power during this period. The output of new energy is intermittent, especially photovoltaic equipment. As the sun sets, the output of photovoltaic equipment gradually decreases until it reaches 0. The multi-microgrid system is short of energy supply and begins to purchase energy from the storage power station to maintain load demand. After 21:00, the energy storage in the storage power station quickly drops to the bottom state and lasts until the next morning.

[0241] 2) Energy interaction analysis of scenario 3

[0242] Figure 6 and Figure 7 They are respectively the charging and discharging optimization diagram of the hybrid energy storage station and the energy interaction diagram of the microgrid side. Figure 6 (b) It can be seen that the energy release of the hydrogen storage station is mainly concentrated in 07:00-20:00, and the hydrogen load is concentrated in the daytime. Due to the setting of time-of-use electricity prices, the electricity price of the microgrid is the highest at 08:00-12:00 and 17:00-21:00. The hydrogen storage station needs to avoid purchasing electricity at the peak of the electricity price while meeting the hydrogen load. Therefore, the charging of the hydrogen storage station is mainly concentrated in the low electricity price period of 00:00-8:00. In the early morning period, the hydrogen load is small and the hydrogen storage station is charged more. The overall hydrogen inventory shows an upward trend, reaching a peak of 6693.13kW·h at 08:00. In the period of 08:00-12:00, due to the high electricity price, the hydrogen storage station reduced the purchase of electricity to produce hydrogen and began to transport hydrogen to meet the load demand. After 12:00, the electricity price dropped. In order to meet the load demand, the hydrogen storage station continued to choose hydrogen production. Because the hydrogen load during this period was large and concentrated, the produced hydrogen was consumed in large quantities, and the inventory fluctuated but did not change much. It was not until 17:00 that the electricity price reached its peak again, the hydrogen storage station stopped purchasing electricity, the inventory gradually decreased, and finally fell to the bottom.

[0243] like Figure 6 As shown in (a), the maximum storage capacity of the energy storage station drops to 1613.72kW·h due to the emergence of hydrogen load. During the period of 00:00-08:00, the energy purchase decision of the energy storage station is similar to that of the hydrogen storage station. Both choose to charge during the period of low electricity prices. However, the sum of the charging capacity of the two energy storage stations far exceeds the green electricity support that the microgrid system can provide. The microgrid must sacrifice some of its profits to purchase energy from the power grid or gas distribution network to maintain the economy of the entire system. Figure 7 It can be seen that Microgrid 2 and Microgrid 3 purchased a large amount of low-priced electricity from the power grid during this period. At the same time, relying on their own high thermal load, they generated electricity through gas turbines, which not only balanced the system power but also met part of the thermal load demand. Figure 6 There are two periods with large energy fluctuations in (a), 08:00-14:00 and 18:00-21:00. Figure 7It can be seen that after 08:00, the grid electricity price reached its peak, and microgrid 3 began to purchase electricity from the storage power station to balance the load, and the storage power station's inventory dropped significantly. From 10:00 to 14:00, as the photovoltaic output in the microgrid increased, the storage power station's inventory also increased. After 17:00, the photovoltaic output decreased, and the storage power station began to discharge to maintain the system balance, and the inventory began to decrease and stabilize.

[0244] The specific implementation modes of the present invention are described in detail above in conjunction with the accompanying drawings, but the present invention is not limited to the above implementation modes, and various changes can be made within the knowledge scope of ordinary technicians in this field without departing from the purpose of the present invention.

Claims

1. A multi-microgrid two-layer optimization scheme considering the configuration of electric and hydrogen hybrid shared energy storage, characterized in that: The following steps are involved: Step 1. For a multi-microgrid architecture that considers a hybrid shared energy storage configuration of electricity and hydrogen, an upper model including a first objective function and a first constraint condition is established with the goal of maximizing the annual profit of the hybrid energy storage station; a lower model including a second objective function and a second constraint condition is established with the goal of minimizing the annual operating cost of the multi-microgrid system load balance; wherein, the multi-microgrid that considers a hybrid shared energy storage configuration of electricity and hydrogen includes a multi-microgrid system and a hybrid energy storage station invested and built by an operator; the hybrid energy storage station includes a power storage station and a hydrogen storage station, and the hydrogen storage station includes an electric-to-gas device and a hydrogen storage tank; Step 2, solve the double-layer optimization model constructed based on the upper-layer model and the lower-layer model to obtain the configuration optimization solution; Step 3: Measure the performance of the configuration optimization solution obtained by the two-layer optimization model based on the evaluation index.

2. The multi-microgrid dual-layer optimization scheme considering the configuration of electric and hydrogen hybrid shared energy storage according to claim 1 is characterized in that: The establishing of the upper model including the first objective function and the first constraint condition comprises: First, establish a hybrid energy storage station "cost-benefit" C u The first objective function with the minimum as the target is as follows: Where: W is the number of typical days; T w is the number of days corresponding to the wth typical day; C inv,w,ess is the daily average investment cost of the power station; C inv,w,hss is the average daily investment cost of the hydrogen storage station; C ess,w,s C is the cost of purchasing electricity from the microgrid for the wth typical day storage power station; hss,w,s C is the cost of purchasing electricity from the microgrid for the wth typical day; trans,w C is the cost of transporting hydrogen energy from the hydrogen storage station to the microgrid on the wth typical day; serve,w C is the service fee paid to the operator on the micro-network on the wth typical day; ess,w,b is the revenue of the wth typical day storage power station selling electricity to the microgrid; C hss,w,b is the revenue of the hydrogen storage station selling hydrogen to the microgrid on the wth typical day; C hss,w,q The revenue from selling hydrogen to the external hydrogen energy market on the wth typical day of the hydrogen storage station; The average daily investment cost of the power storage station is expressed as: Where: α ess and β ess They are the unit power cost and unit capacity cost of the power storage station respectively; and are the maximum charging and discharging power and maximum capacity of the storage station respectively; T ess Y is the expected number of days of use of the power station; ess The daily maintenance cost of the power station; The average daily investment cost of the hydrogen storage station is expressed as: Where: α p2g and β tank They are the unit power cost and unit capacity cost of the power-to-gas equipment and the hydrogen storage tank respectively; and are the maximum charging and discharging power and maximum capacity of the power-to-gas equipment and the hydrogen storage tank respectively; T p2g T is the expected service life of the power-to-gas equipment; tank Y is the expected number of days the hydrogen storage tank will be used; p2g is the daily maintenance cost of the power-to-gas equipment; tank is the daily maintenance cost of the hydrogen storage tank; The cost of the power storage station purchasing electricity from the microgrid is expressed as: Where: N is the number of microgrids; N T is the number of scheduling cycle time periods; is the electricity price sold by the microgrid to the power storage station during period t; P ess,s,w,i (t) is the power sold by microgrid i to the power storage station in period t on the wth typical day; Δt is the dispatch period; The cost of the hydrogen storage station purchasing electricity from the microgrid is expressed as: Where: is the electricity price sold by the microgrid to the hydrogen storage station during period t; P hss,s,w,i (t) is the power sold by microgrid i to the hydrogen storage station during period t on the wth typical day; The cost of transporting hydrogen from the hydrogen storage station to the microgrid is expressed as: Where: P hss,b,w,i (t) is the power of hydrogen purchased from the hydrogen storage station by microgrid i in period t on the wth typical day; S i is the distance between microgrid i and the hydrogen storage station; The coefficient of converting 1kW of hydrogen into mass; The service fee paid to the energy storage operator on the micro-network is expressed as: Where: κ(t) is the unit price of service fee paid by the microgrid to the energy storage operator during period t; P ess,b,w,i (t) Purchase power from the power storage station for the i-th microgrid t period on each typical day; The revenue from the power storage station selling electricity to the microgrid is expressed as: Where: is the electricity price that the microgrid purchases from the power storage station during period t; The revenue from the hydrogen storage station selling hydrogen to the microgrid is expressed as: Where: is the price at which the microgrid purchases hydrogen from the hydrogen storage station during period t; The revenue from the hydrogen storage station selling hydrogen to the external hydrogen energy market is expressed as: Where: P is the price of hydrogen purchased from the hydrogen storage station by the external hydrogen energy market during period t; hss,q,w (t) is the hydrogen power purchased from the hydrogen storage station by the external hydrogen energy market during the period t on the wth typical day; Second, determine the first constraint condition of the first objective function, which includes: the capacity of the power storage station and the hydrogen storage station is proportional to the rated power, the charge state and charging and discharging power constraints of the power storage station, the charge state and charging and discharging power constraints of the hydrogen storage station, and the hydrogen energy load constraints between the hydrogen storage station and the outside world.

3. The multi-microgrid dual-layer optimization scheme considering the configuration of electric and hydrogen hybrid shared energy storage according to claim 1 is characterized in that: The step of establishing a lower model including a second objective function and a second constraint condition comprises: First, establish the annual operating cost C to meet the load balance of the multi-microgrid system d The second objective function with the minimum as the goal is as follows: Where: W is the number of typical days; T w is the number of days corresponding to the wth typical day; C grid,w C is the cost of purchasing electricity from the grid for the multi-microgrid system on the wth typical day; fuel,w is the gas cost of the gas turbine and gas boiler on the wth typical day; C ess,w,b C is the cost of the w-th typical day storage power station selling electricity to the microgrid; serve,w C is the service fee paid to the operator on the micro-network on the wth typical day; hss,w,b C is the cost of selling hydrogen from the hydrogen storage station to the microgrid on the wth typical day; ess,w,s C is the cost of purchasing electricity from the microgrid for the wth typical day storage power station; hss,w,s The cost of purchasing electricity from the microgrid for the hydrogen storage station on the wth typical day; The cost of purchasing electricity from the power grid for the multi-microgrid system is expressed as: Where: N is the number of microgrids; N T is the number of scheduling cycle time periods; is the power grid price in period t; P grid,w,i (t) is the power purchased by microgrid i from the grid during period t on the wth typical day; Δt is the dispatch period; The gas cost is expressed as: Where: is the unit volume price of gas; P GT,w,i (t) is the power output of the gas turbine of microgrid i in period t on the wth typical day; η GT is the power generation efficiency of the micro gas turbine; L NG is the calorific value of gas; Q GB,w,i (t) is the thermal power output of the gas boiler of microgrid i in period t on the wth typical day; η GB For the efficiency of gas boilers; The cost of the power storage station selling electricity to the microgrid is expressed as: Where: is the electricity price that the microgrid purchases from the power storage station during period t; P ess,b,w,i (t) Purchase power from the power storage station for the i-th microgrid t period on each typical day; The service fee paid to the energy storage operator on the micro-network is expressed as: Where: κ(t) is the unit price of service fee paid by the microgrid to the energy storage operator during period t; P hss,s,w,i (t) is the power sold by microgrid i to the hydrogen storage station during period t on the wth typical day; P ess,s,w,i (t) is the power sold by microgrid i to the power storage station in period t on the wth typical day; The cost of selling hydrogen from the hydrogen storage station to the microgrid is expressed as: Where: is the price of hydrogen purchased by the microgrid from the hydrogen storage station during period t; P hss,b,w,i (t) is the power of hydrogen purchased from the hydrogen storage station by microgrid i in period t on the wth typical day; The cost of the power storage station purchasing electricity from the microgrid is expressed as: Where: is the electricity price sold by the microgrid to the power storage station during period t; The cost of the hydrogen storage station purchasing electricity from the microgrid is expressed as: Where: is the electricity price sold by the microgrid to the hydrogen storage station during period t; Second, determine the second constraint condition of the second objective function, which includes: electric power balance constraint, cold power balance constraint, hot power balance constraint, waste heat boiler waste heat balance constraint, storage station charging and discharging power balance constraint, hydrogen storage station charging balance constraint, hydrogen storage station hydrogen discharge balance constraint, hydrogen load balance constraint, microgrid equipment output upper and lower limit constraints, power purchase from the power grid constraint, power purchase and sale of electricity between microgrid and storage station constraint, and power sale and hydrogen purchase constraint between microgrid and hydrogen storage station.

4. The multi-microgrid dual-layer optimization scheme considering the configuration of electric and hydrogen hybrid shared energy storage according to claim 1 is characterized in that: The two-layer optimization model constructed according to the upper model and the lower model is solved, specifically: firstly, the Lagrangian function of the lower model is constructed, and the KKT complementary relaxation condition is used to convert the lower model into the constraint condition of the upper model, and then the big M method is used to linearize the nonlinear terms in the converted single-layer nonlinear model to form a single-layer mixed integer linear programming problem, and finally the CPLEX solver is called to solve it.

5. The multi-microgrid dual-layer optimization scheme considering the configuration of electric and hydrogen hybrid shared energy storage according to claim 1 is characterized in that: The evaluation indicators include: The recycling period of the power station battery is expressed as: Where: M ess is the recycling period of the power station battery; C ess,serve,w Service fees earned for the storage station; The payback period of the power-to-gas equipment is expressed as: Where: M p2g is the payback period of the power-to-gas equipment; C hss,serve,w Service fees earned for hydrogen storage stations; The recycling period of the hydrogen storage tank is expressed as: Where: M tank The recycling period of the hydrogen storage tank; The operator's payback period is expressed as: Where: M ope Recovery period for operators.

6. A multi-microgrid two-layer optimization system considering the configuration of electric and hydrogen hybrid shared energy storage, characterized in that: A module comprising a multi-microgrid dual-layer optimization solution considering electric and hydrogen hybrid shared energy storage configuration as described in any one of claims 1-5.

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