Cooperative operation optimization method based on hydrogen energy micro-grid and power distribution network

Abstract

The invention relates to the technical field of micro-grids, and particularly discloses a hydrogen energy micro-grid and power distribution network collaborative operation optimization method, which comprises the following steps that a micro-grid operation model is constructed according to equipment parameters of a grid-connected hydrogen energy micro-grid, and the micro-grid operation model comprises an operation constraint and a total operation cost function; constructing a power distribution network operation model based on an IEEE-33 node power distribution model; coupling variables are adopted, the micro-grid operation model and the power distribution network operation model are coupled to form a coupling model, the coupling model is solved based on a mixed integer second-order cone programming method, and peak-valley difference changes of the power distribution network after coupling and wind and light absorption of the micro-grid are analyzed; the method has the advantages that renewable energy sources such as solar energy and wind energy are gathered to be connected into the power distribution network and consumed and utilized on site, consumption of fossil energy is effectively reduced, and the power distribution network is promoted to develop towards the clean and low-carbon direction.

Description

Technical Field

[0001] The present invention relates to the technical field of microgrids, and in particular to a method for optimizing the coordinated operation of a hydrogen energy microgrid and a distribution network. Background Art

[0002] With the rapid development of the economy, energy shortage crisis and environmental pollution have attracted widespread attention around the world, and energy structure reform is imminent. Hydrogen energy is clean, efficient, and widely used. It is in line with future development trends and is beginning to attract more and more countries and regions to pay attention to the development and utilization of hydrogen energy. Microgrid systems based on hydrogen energy have therefore become low-carbon, environmentally friendly, and have huge development potential, and are an important development direction for renewable energy microgrids.

[0003] Hydrogen energy microgrids achieve efficient energy utilization by integrating renewable energy sources such as wind and solar energy, as well as hydrogen energy storage technology. When there is an excess of wind or solar energy, the energy is stored by producing hydrogen through water electrolysis, which not only solves the problem of large fluctuations in renewable energy production capacity, but also improves the overall energy utilization efficiency. By using hydrogen fuel cells instead of traditional gas turbines for power generation and using green electricity to produce hydrogen, carbon emissions are significantly reduced, which helps to achieve low-carbon operation and environmental protection goals. By introducing a hydrogen energy storage system, a hydrogen energy microgrid can effectively smooth out the volatility of wind and solar power generation and improve the stability and reliability of the power grid. At the same time, the hydrogen energy storage system can also serve as an emergency power supply, providing power support in the event of a power grid failure to ensure continuous power supply to critical loads.

[0004] As one of the main carriers of energy transmission and distribution in the power network, the safe and stable operation of the distribution system is the basis for ensuring the reliability of power supply. With the grid connection of distributed energy such as renewable energy generation, electric vehicles, and energy storage, the traditional distribution network is developing into an active distribution network with a certain degree of controllability and gradually transforming into an active distribution network that can return energy to the transmission network. The multi-source access and diversified utilization of energy in the active distribution network have improved the economy and sustainability of the power system, but at the same time, it also faces difficulties such as complex operating scenarios and uneven energy distribution. Therefore, efficient control and optimization strategies are needed to ensure the stable operation of the system and improve energy management efficiency. Optimal Power Flow (OPF) analysis, as the basis of steady-state operation of the power system, aims to ensure the safe and stable operation of the power system while maximizing economic benefits. At present, many studies have not considered the coupling characteristics of hydrogen energy microgrids and distribution networks, and have not conducted detailed research on the characteristics of the coupled distribution network. Summary of the invention

[0005] The purpose of the present invention is to overcome the shortcomings of the prior art and provide a method for optimizing the coordinated operation of a hydrogen energy microgrid and a distribution network.

[0006] The purpose of the present invention is achieved through the following technical solutions: A method for optimizing the coordinated operation of a hydrogen energy microgrid and a distribution network, comprising the following steps:

[0007] Step S1: constructing a microgrid operation model according to the equipment parameters of the grid-connected hydrogen energy microgrid, wherein the microgrid operation model includes operation constraints and a total operation cost function;

[0008] Step S2: constructing a distribution network operation model based on the IEEE-33 node distribution model;

[0009] Step S3: Using coupling variables, the microgrid operation model is coupled with the distribution network operation model to form a mixed integer second-order cone programming model. The model is solved by a solver to analyze the peak-to-valley difference change of the distribution network after coupling and the wind and solar power consumption of the microgrid; Step S4: Taking the total operation cost function as the objective function, the mixed integer linear programming method is used to achieve optimal scheduling:

[0010] F=min{C OM +C fuel +C gas} (1)

[0011] Among them, C OM is the operation and maintenance cost, C fuel is the fuel cost, C gas The cost of polluted gas treatment.

[0012] Specifically, the calculation formula of the operation and maintenance cost is as follows:

[0013]

[0014] Where T is the scheduling period; P hss (t) is the charging and discharging power of the hydrogen energy storage system at time t; ρ w , pv , hss , bat , eb , gb , tst are the unit operation and maintenance costs (yuan / kW·h) of wind turbines, photovoltaics, hydrogen energy storage system batteries, electric boilers, gas boilers, and heat storage tanks; P w (t) is the power generated by the wind turbine in the microgrid at time t; P pv (t) PV power of the microgrid at time t; P eb (t) is the charge and discharge power of the energy storage system at time t; P gb (t) is the amount of gas consumed by the gas boiler at time t; P tst (t) is the heat storage and release power of the heat storage tank at time t.

[0015] Specifically, the calculation formula of the fuel cost is as follows:

[0016]

[0017] Among them, T is the scheduling period, R gas is the unit price of natural gas (yuan / m 3 );L H is the calorific value of natural gas (kWh / m 3 );H gb (t) is the heat generated by the gas boiler at time t.

[0018] Specifically, the calculation formula for the pollution gas treatment cost is:

[0019]

[0020] Where T is the scheduling period, and They are the emission coefficients and treatment costs of the pollutants SO2, CO2 and NO2 generated by gas boilers.

[0021] Specifically, the electric power balance constraint condition of the microgrid operation model is:

[0022] P w (t)+P buy (t)+P pv (t)+P fc (t) = P load (t)+P eb (t)+P el (t)+P sell (t)+P bat (t) (5)

[0023] Where: P w is the output power of the wind turbine; P buy is the output power of the grid to the load side. When the microgrid cannot meet the load power, it needs to purchase electricity from the grid. Similarly, P sell is the output power of the microgrid to the grid; P pv is the output power of the photovoltaic generator; P fc is the electrical power; P load is the load power; P bat P is the battery charging and discharging power. When it is negative, it is considered as discharging, otherwise it is charging. el P is the electric power obtained by the electrolyzer from the electric bus; eb is the charging and discharging power of the battery;

[0024] The thermal power balance constraint condition of the microgrid operation model is:

[0025] Hload (t)+H tst-ch (t) = H gb (t)+H eb (t)+H tst-dis (t)+H el (t)+H fc (t) (6)

[0026] Where: H load (t) is the heat load at time t; H tst-ch (t), H tst-dis (t) is the heat storage and release of the heat storage tank at time t; H gb (t) is the heat generated by the gas boiler at time t; H eb (t) is the heat generated by the electric boiler at time t; H el (t) is the power used by the electrolytic cell to generate heat at time t; H fc (t) is the residual heat power at time t.

[0027] Specifically, the operation-related constraints of the battery in the microgrid operation model are:

[0028] P batmin ≤P bat (t)≤P batmax (7)

[0029] S OCmin ≤S OC (t)≤S OCmax (8)

[0030] Where: P batmin , P batmax They are the upper and lower limits of battery charge and discharge power respectively; S OCmin , S OCmax They are the upper and lower limits of the battery state of charge respectively;

[0031] The constraints related to the thermal energy storage system in the microgrid operation model are:

[0032] H tstmin ≤H tst (t)≤H tstmax (9)

[0033] H OCmin ≤H OC (t)≤H OCmax (10)

[0034] Where: H tstmin , H tstmax are the upper and lower limits of the heat storage and release power of the heat storage tank; H OCmin , H OCmax They are the upper and lower limits of the heat storage state of the heat storage tank respectively;

[0035] The constraints related to the hydrogen energy system in the microgrid operation model are:

[0036] P fcmin ≤P fc (t)≤P fcmax (11)

[0037] P elmin ≤P el (t)≤P elmax (12)

[0038] S OHCmin ≤S OHC (t)≤S OHCmax (13)

[0039] P hy (t) = a fc P fc (t)+a el P el (t) (14)

[0040] a fc +a el ≤1 (15)

[0041] Among them, P fcmin , P fcmax are the upper and lower limits of fuel cell power respectively; P elmin , P elmax are the upper and lower limits of the electrolytic cell power respectively; S OHCmin and S OHCmax They are respectively hydrogen storage state S OHC (t) upper and lower limits; P hy (t) is the operating power of the hydrogen energy system at time t; a fc 、a el They are the working flags of the fuel cell and battery respectively, and their values ​​are 0 or 1, 0 means not working and 1 means working.

[0042] Specifically, the objective function of the distribution network operation model in step S2 is:

[0043] minf(p,q,P,Q,V,I)(16)

[0044] Where p and q are the node injection powers, P and Q are the branch currents, V is the node voltage, and I is the branch current.

[0045] Based on the IEEE-33 node power distribution model, the peak-to-valley difference f1 of the reference point is as follows:

[0046] f1=maxp1-minp1 (17)

[0047] Specifically, the constraints of the distribution network operation model include:

[0048] Injection power constraint:

[0049]

[0050] Where: p, q are the injected powers of the nodes, ij indicates that the positive direction of the power flow is from node i to node j; δ(j) is the set of branch end nodes with j as the head node, π(j) is the set of branch head nodes with j as the end node; (P, Q) is the branch power flow; V is the node voltage; I is the branch current; P buy P is the amount of electricity purchased; sell is the electricity sold; r represents resistance; x represents reactance, P jm is the active power flowing from node j to node m, Q jm is the reactive power flowing from node j to node m;

[0051] General constraints:

[0052]

[0053]

[0054] Where:

[0055] Specifically, in step S3, the distribution network operation model is converted into a second-order cone programming model; The distribution network operation model is converted to the following formula:

[0056]

[0057] The present invention has the following advantages:

[0058] 1. By establishing fuel cell hydrogen-to-electricity and heat and electrolyzer electricity-to-hydrogen and heat models, introducing heat storage tanks to store heat, analyzing the operating characteristics of photovoltaic, wind turbine power generation systems, electric boilers, and gas boilers, and the complementary characteristics of electric energy storage systems and hydrogen energy storage systems, fine-tuning modeling of each component is carried out to study the wind and solar absorption capacity of microgrids when working independently; then introduce it into the distribution network for research. By aggregating renewable energy such as solar energy and wind energy to access the distribution network and absorbing and utilizing it locally, the consumption of fossil energy can be effectively reduced, and the distribution network can be promoted to develop in a clean and low-carbon direction.

[0059] 2. The microgrid can be connected to the grid or run independently off the grid. When connected to the grid, it can support and interact flexibly with the large grid to improve the operational stability of the large grid. When powered independently, it is not affected by failures or power outages in the large grid. In an emergency, it can achieve continuous power supply to important loads and ensure the reliability of power supply.

[0060] When the distribution network fails or is under maintenance, the microgrid can quickly switch to island mode to ensure the power supply of key loads, thereby greatly improving the power supply reliability of the distribution network. By aggregating renewable energy such as solar energy and wind energy to access the distribution network and consuming it locally, the consumption of fossil energy can be effectively reduced, and the distribution network can be promoted to develop in a clean and low-carbon direction. In the future, the power grid will form a development pattern dominated by the transmission and distribution network and supplemented by microgrids. Promoting the integrated development of large power grids and microgrids will be conducive to the stable operation of new power systems, help upgrade the power system form, promote clean and efficient new energy to play its industrial advantages, and promote the transformation of energy structure. BRIEF DESCRIPTION OF THE DRAWINGS

[0061] Figure 1 It is a schematic diagram of the process of the present invention;

[0062] Figure 2 It is a system grid structure diagram of the present invention;

[0063] Figure 3 This is a schematic diagram of wind and solar power output of the microgrid before coupling;

[0064] Figure 4 This is a schematic diagram of wind and solar power output of the coupled microgrid;

[0065] Figure 5 Schematic diagram of the power of the distribution network reference point before and after coupling. DETAILED DESCRIPTION

[0066] In order to make the purpose, technical solutions and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention, that is, the embodiments described are only part of the embodiments of the present invention, rather than all of the embodiments. The components of the embodiments of the present invention described and shown in the drawings herein can be arranged and designed in various different configurations.

[0067] Therefore, the following detailed description of the embodiments of the present invention provided in the accompanying drawings is not intended to limit the scope of the invention claimed for protection, but merely represents selected embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without making creative work are within the scope of protection of the present invention.

[0068] It should be noted that relational terms such as "first" and "second" are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the sentence "including a..." do not exclude the existence of other identical elements in the process, method, article or device including the elements.

[0069] The present invention is further described below in conjunction with the accompanying drawings, but the protection scope of the present invention is not limited to the following description. Figures 1 to 5 As shown, a method for optimizing the coordinated operation of a hydrogen energy microgrid and a distribution network includes the following steps:

[0070] Step S1: input all equipment parameters of the hydrogen energy microgrid, including wind power, photovoltaic output forecast values, load forecast values, maximum charging and discharging power of the storage tank, maximum working power of the electrolyzer, maximum heat storage and release power of the heat storage tank and hydrogen storage tank capacity, and construct a microgrid operation model, which includes operation constraints and a total operation cost function;

[0071] Step S2: input the distribution network node parameters and build a distribution network operation model based on the IEEE-33 node distribution model;

[0072] Step S3: Using coupling variables, the microgrid operation model is coupled with the distribution network operation model to form a mixed integer second-order cone programming model. The model is solved by a solver to analyze the peak-to-valley difference change of the distribution network after coupling and the wind and solar power consumption of the microgrid; Step S4: Taking the total operation cost function as the objective function, the mixed integer linear programming method is used to achieve optimal scheduling:

[0073] F=min{C OM +C fuel +C gas} (1)

[0074] Among them, C OM is the operation and maintenance cost, C fuel is the fuel cost, C gas The cost of polluted gas treatment.

[0075] The calculation formula of the operation and maintenance cost is as follows:

[0076]

[0077] Where T is the scheduling period; P hss (t) is the charging and discharging power of the hydrogen energy storage system at time t; ρ w , pv , hss , bat , eb , gb , tst are the unit operation and maintenance costs (yuan / kW·h) of wind turbines, photovoltaics, hydrogen energy storage system batteries, electric boilers, gas boilers, and heat storage tanks; P w (t) is the power generated by the wind turbine in the microgrid at time t; P pv (t) PV power of the microgrid at time t; P eb (t) is the charge and discharge power of the energy storage system at time t; P gb (t) is the amount of gas consumed by the gas boiler at time t; P tst (t) is the heat storage and release power of the heat storage tank at time t.

[0078] The calculation formula of the fuel cost is as follows:

[0079]

[0080] Among them, T is the scheduling period, R gas is the unit price of natural gas (yuan / m 3 );L H is the calorific value of natural gas (kWh / m 3 );H gb (t) is the heat generated by the gas boiler at time t.

[0081] The calculation formula of the pollution gas treatment cost is:

[0082]

[0083] Where T is the scheduling period, and They are the emission coefficients and treatment costs of the pollutants SO2, CO2 and NO2 generated by gas boilers.

[0084] The electric power balance constraint condition of the microgrid operation model is:

[0085] P w (t)+P buy (t)+P pv (t)+P fc (t) = P load (t)+P eb (t)+P el (t)+P sell (t)+P bat(t) (5)

[0086] Where: P w is the output power of the wind turbine; P buy is the output power of the grid to the load side. When the microgrid cannot meet the load power, it needs to purchase electricity from the grid. Similarly, P sell is the output power of the microgrid to the grid; P pv is the output power of the photovoltaic generator; P fc is the electrical power; P load is the load power; P bat P is the battery charging and discharging power. When it is negative, it is considered as discharging, otherwise it is charging. el P is the electric power obtained by the electrolyzer from the electric bus; eb is the charging and discharging power of the battery;

[0087] The thermal power balance constraint condition of the microgrid operation model is:

[0088] H load (t)+H tst-ch (t) = H gb (t)+H eb (t)+H tst-dis (t)+H el (t)+H fc (t) (6)

[0089] Where: H load (t) is the heat load at time t; H tst-ch (t), H tst-dis (t) is the heat storage and release of the heat storage tank at time t; H gb (t) is the heat generated by the gas boiler at time t; H eb (t) is the heat generated by the electric boiler at time t; H el (t) is the power used by the electrolytic cell to generate heat at time t; H fc (t) is the remaining heat power at time t;

[0090] The operation-related constraints of the battery in the microgrid operation model are:

[0091] P batmin ≤P bat (t)≤P batmax (7)

[0092] S OCmin ≤S OC (t)≤S OCmax (8)

[0093] Where: P batmin , P batmaxThey are the upper and lower limits of battery charge and discharge power respectively; S OCmin , S OCmax They are the upper and lower limits of the battery state of charge respectively;

[0094] The constraints related to the thermal energy storage system in the microgrid operation model are:

[0095] H tstmin ≤H tst (t)≤H tstmax (9)

[0096] H OCmin ≤H OC (t)≤H OCmax (10)

[0097] Where: H tstmin , H tstmax are the upper and lower limits of the heat storage and release power of the heat storage tank; H OCmin , H OCmax They are the upper and lower limits of the heat storage state of the heat storage tank respectively;

[0098] The constraints related to the hydrogen energy system in the microgrid operation model are:

[0099] P fcmin ≤P fc (t)≤P fcmax (11)

[0100] P elmin ≤P el (t)≤P elmax (12)

[0101] S OHCmin ≤S OHC (t)≤S OHCmax (13)

[0102] P hy (t) = a fc P fc (t)+a el P el (t) (14)

[0103] a fc +a el ≤1 (15)

[0104] Among them, P fcmin , P fcmax are the upper and lower limits of fuel cell power respectively; P elmin , P elmax are the upper and lower limits of the electrolytic cell power respectively; S OHCmin and S OHCmax They are respectively hydrogen storage state S OHC(t) upper and lower limits; P hy (t) is the operating power of the hydrogen energy system at time t; a fc 、a el They are the working flags of the fuel cell and the battery respectively, and their values ​​are 0 or 1, 0 means not working, and 1 means working.

[0105] Considering the safety and economy of the power grid, optimizing the operation of the power system, and building a distribution network operation model, the basic model of the optimal power flow includes the objective function, control variables and state variables, as well as equality and inequality constraints. The objective function is usually to minimize the power generation cost or the system active network loss. The control variables can be the active output of the generator, the voltage modulus of the generator node and the node with adjustable reactive compensation equipment, etc. The state variables include the voltage phase angle and modulus of all nodes except the balancing node. The objective function of the distribution network operation model is:

[0106] minf(p,q,P,Q,V,I)(16)

[0107] Where p and q are the node injection powers, P and Q are the branch currents, V is the node voltage, and I is the branch current.

[0108] When studying the 33-node power distribution model, the peak-to-valley difference f1 of the reference point is as follows:

[0109] f1=maxp1-minp1 (17)

[0110] Indicates maximum load - minimum load;

[0111] The constraints of the distribution network operation model include:

[0112] Injection power constraint:

[0113]

[0114] Where: p, q are the injected powers of the nodes, ij indicates that the positive direction of the power flow is from node i to node j; δ(j) is the set of branch end nodes with j as the head node, π(j) is the set of branch head nodes with j as the end node; (P, Q) is the branch power flow; V is the node voltage; I is the branch current; P buy P is the amount of electricity purchased; sell is the electricity sold; r represents resistance; x represents reactance, P jm is the active power flowing from node j to node m, Q jm is the reactive power flowing from node j to node m;

[0115] General constraints:

[0116]

[0117]

[0118] Where:

[0119] It can be seen that the optimization variables of the distribution network operation model include node injection power (p, q), branch power flow (P, Q), node voltage (V) and branch current (I), and the substation node voltage is not used as an optimization variable; Formula (1) is the objective function, which can be the minimum network loss, the minimum substation node power purchase, etc.; Formulas (2)-(6) are general constraints, that is, the optimal power flow of all radial networks is consistent, including power flow balance constraints and safety constraints;

[0120] The above distribution network operation model is a nonlinear programming model. In step S3, the distribution network operation model is converted into a second-order cone programming model. The distribution network operation model is converted to the following formula:

[0121]

[0122] The above formula constitutes the basic form of the relaxed static optimal power flow. When the objective function is a convex function and a strictly increasing function, it is strictly accurate for most distribution network structures.

[0123] The distribution system is mainly composed of distributed power storage equipment, energy supply equipment and loads, mainly photovoltaic power generation and wind power generation. Among them, the energy storage equipment includes electrical energy storage system, hydrogen energy storage system and thermal energy storage system. The load includes electrical load and thermal load. The electric boiler is a thermoelectric coupling element, and the fuel cell.

[0124] When the hydrogen energy microgrid works alone, the following can be obtained: Figure 3 As shown in the wind and solar output bar chart, it can be seen that from 7:00 to 18:00, the wind power output is almost 0 and the photovoltaic output is mostly maintained in the range of 100-250kW. When the hydrogen energy microgrid is connected to the grid, Figure 4 The wind and solar power output is shown; it can be seen that after connecting the hydrogen energy microgrid to the distribution network, the system's wind and solar power absorption capacity has been significantly improved, the overall photovoltaic output has increased by about 50%, and the wind power output has been achieved from scratch in a period of time.

[0125] like Figure 5 The power changes of the reference points before and after coupling are shown. It is not difficult to see that when the hydrogen energy microgrid is connected to the distribution network, it plays a role in peak shaving and valley filling. The peak-to-valley difference is reduced from 0.1796 to 0.1063, with an overall reduction of about 40.8%.

[0126] The above is only a preferred embodiment of the present invention and does not limit the present invention in any form. Any technician familiar with the art can make many possible changes and modifications to the technical solution of the present invention by using the above-mentioned technical content without departing from the scope of the technical solution of the present invention, or modify it into an equivalent embodiment of equivalent changes. Therefore, any changes, modifications, equivalent changes and modifications made to the above embodiments based on the technology of the present invention without departing from the content of the technical solution of the present invention belong to the protection scope of the present technical solution.

Claims

1. A method for optimizing the coordinated operation of a hydrogen energy microgrid and a distribution network, characterized in that: The following steps are involved: Step S1: constructing a microgrid operation model according to the equipment parameters of the grid-connected hydrogen energy microgrid, wherein the microgrid operation model includes operation constraints and a total operation cost function; Step S2: constructing a distribution network operation model based on the IEEE-33 node distribution model; Step S3: using coupling variables, coupling the microgrid operation model with the distribution network operation model to form a mixed integer second-order cone programming model, using a solver to solve the model, and analyzing the peak-to-valley difference change of the distribution network after coupling and the wind and solar power consumption of the microgrid; Step S4: Taking the total operating cost function as the objective function, the mixed integer linear programming method is used to achieve optimal scheduling: F=min{C OM +C fuel +C gas } (1) Among them, C OM is the operation and maintenance cost, C fuel is the fuel cost, C gas The cost of polluted gas treatment.

2. According to claim 1, a method for optimizing the coordinated operation of a hydrogen energy microgrid and a distribution network is characterized in that: The calculation formula of the operation and maintenance cost is as follows: Where T is the scheduling period; P hss (t) is the charging and discharging power of the hydrogen energy storage system at time t; ρ w , pv , hss , bat , eb , gb , tst are the unit operation and maintenance costs (yuan / kW·h) of wind turbines, photovoltaics, hydrogen energy storage system batteries, electric boilers, gas boilers, and heat storage tanks; P w (t) is the power generated by the wind turbine in the microgrid at time t; P pv (t) PV power of the microgrid at time t; P eb (t) is the charge and discharge power of the energy storage system at time t; P gb (t) is the amount of gas consumed by the gas boiler at time t; P tst (t) is the heat storage and release power of the heat storage tank at time t.

3. The method for optimizing the coordinated operation of a hydrogen energy microgrid and a distribution network according to claim 1 is characterized in that: The calculation formula of the fuel cost is as follows: Among them, T is the scheduling period, R gas is the unit price of natural gas (yuan / m 3 );L H is the calorific value of natural gas (kWh / m 3 );H gb (t) is the heat generated by the gas boiler at time t.

4. The method for optimizing the coordinated operation of a hydrogen energy microgrid and a distribution network according to claim 3 is characterized in that: The calculation formula of the pollution gas treatment cost is: Where T is the scheduling period, and They are the emission coefficients and treatment costs of the pollutants SO2, CO2 and NO2 generated by gas boilers.

5. The method for optimizing the coordinated operation of a hydrogen energy microgrid and a distribution network according to claim 4 is characterized in that: The electric power balance constraint condition of the microgrid operation model is: P w (t)+P buy (t)+P pv (t)+P fc (t)=P load (t)+P eb (t)+P el (t)+P sell (t)+P bat (t) (5) Where: P w is the output power of the wind turbine; P buy is the output power of the grid to the load side. When the microgrid cannot meet the load power, it needs to purchase electricity from the grid. Similarly, P sell is the output power of the microgrid to the grid; P pv is the output power of the photovoltaic generator; P fc is the electrical power; P load is the load power; P bat P is the battery charging and discharging power. When it is negative, it is considered as discharging, otherwise it is charging. el P is the electric power obtained by the electrolyzer from the electric bus; eb is the charging and discharging power of the battery; The thermal power balance constraint condition of the hydrogen energy microgrid is: H load (t)+H tst-ch (t)=H gb (t)+H eb (t)+H tst-dis (t)+H el (t)+H fc (t) (6) Where: H load (t) is the heat load at time t; H tst-ch (t), H tst-dis (t) is the heat storage and release of the heat storage tank at time t; H gb (t) is the heat generated by the gas boiler at time t; H eb (t) is the heat generated by the electric boiler at time t; H el (t) is the power used by the electrolytic cell to generate heat at time t; H fc (t) is the residual heat power at time t.

6. The method for optimizing the coordinated operation of a hydrogen energy microgrid and a distribution network according to claim 5 is characterized in that: The operation-related constraints of the battery in the microgrid operation model are: P batmin ≤P bat (t)≤P batmax (7) S OCmin ≤S OC (t)≤S OCmax (8) Where: P batmin , P batmax They are the upper and lower limits of battery charge and discharge power respectively; S OCmin , S OCmax They are the upper and lower limits of the battery state of charge respectively; The constraints related to the thermal energy storage system in the microgrid operation model are: H tstmin ≤H tst (t)≤H tstmax (9) H OCmin ≤H OC (t)≤H OCmax (10) Where: H tstmin , H tstmax are the upper and lower limits of the heat storage and release power of the heat storage tank; H OCmin , H OCmax They are the upper and lower limits of the heat storage state of the heat storage tank respectively; The constraints related to the hydrogen energy system in the microgrid operation model are: P fcmin ≤P fc (t)≤P fcmax (11) P elmin ≤P el (t)≤P elmax (12) S OHCmin ≤S OHC (t)≤S OHCmax (13) P hy (t)=a fc P fc (t)+a el P el (t) (14) a fc +a el ≤1 (15) Among them, P fcmin , P fcmax are the upper and lower limits of fuel cell power respectively; P elmin , P elmax are the upper and lower limits of the electrolytic cell power respectively; S OHCmin and S OHCmax They are respectively hydrogen storage state S OHC (t) upper and lower limits; P hy (t) is the operating power of the hydrogen energy system at time t; a fc 、a el They are the working flags of the fuel cell and battery respectively, and their values ​​are 0 or 1, 0 means not working and 1 means working.

7. The method for optimizing the coordinated operation of a hydrogen energy microgrid and a distribution network according to claim 1 is characterized in that: The objective function of the distribution network operation model in step S2 is: min f(p,q,P,Q,V,I) (16) Where p and q are the node injection powers, P and Q are the branch currents, V is the node voltage, and I is the branch current. Based on the IEEE-33 node power distribution model, the peak-to-valley difference f1 of the reference point is as follows: f1=max p1-min p1 (17).

8. The method for optimizing the coordinated operation of a hydrogen energy microgrid and a distribution network according to claim 7 is characterized in that: The constraints of the distribution network operation model include: Injection power constraint: Where: p, q are the injected powers of the nodes, ij indicates that the positive direction of the power flow is from node i to node j; δ(j) is the set of branch end nodes with j as the head node, π(j) is the set of branch head nodes with j as the end node; (P, Q) is the branch power flow; V is the node voltage; I is the branch current; P buy P is the amount of electricity purchased; sell is the electricity sold; r is resistance; x is reactance; g is conductance, P jm is the active power flowing from node j to node m, Q jm is the reactive power flowing from node j to node m; General constraints: Where: ij indicates that the positive direction of the power flow is from node i to node j; δ(j) is the set of branch end nodes with j as the head node, π(j) is the set of branch head nodes with j as the end node; (P, Q) is the branch power flow; V is the node voltage; I is the branch current; r is the resistance; and x is the reactance.

9. The method for optimizing the coordinated operation of a hydrogen energy microgrid and a distribution network according to claim 8 is characterized in that: In step S3, the distribution network operation model is converted into a second-order cone programming model; The distribution network operation model is converted to the following formula:

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