A method for optimizing configuration of an electricity-hydrogen-heat coupled multi-energy complementary microgrid considering hydrogen transaction

Abstract

The application provides an optimization configuration method of an electric-hydrogen-thermal coupled multi-energy complementary microgrid considering hydrogen transaction. The method comprises the following steps: analyzing the actual situation of new energy resources at the microgrid construction site; investigating or obtaining the local or nearby electric power load data, hot water demand data and hydrogen demand situation, and installation conditions, equipment capacity upper limit and other requirements of the construction site; determining the topological structure and energy flow relationship of the microgrid, taking the minimum comprehensive cost of the whole life cycle of the microgrid and the wind and light consumption rate and energy efficiency factor as the objective function; establishing a comprehensive constraint set, and a double-layer configuration-operation optimization model with the objective function; and solving the optimization model to obtain an optimized configuration scheme. The application can effectively reduce the energy storage configuration capacity and cost of the hybrid microgrid, effectively improve the comprehensive energy efficiency and wind and light consumption rate of the multi-energy complementary microgrid system, and provide technical support for the construction and promotion of the microgrid.

Description

TECHNICAL FIELD

[0001] The application relates to an optimization configuration method of an electric-hydrogen-heat coupled multi-energy complementary micro-grid considering hydrogen transaction, and belongs to the technical field of micro-grid planning optimization configuration. BACKGROUND

[0002] In recent years, with the gradual depletion of fossil energy and the increasing climate problems, developing clean renewable energy to reduce carbon dioxide emissions has become an important development trend. However, the high dependence of renewable energy such as photovoltaic and wind turbine on the environment leads to strong uncertainty on the power generation side, which brings great challenges to the stable operation and dispatching of the power grid. As a new networking form, the micro-grid can be compatible with multiple new energy sources and has strong regional networking capability, which is conducive to local consumption and management of new energy and has been widely concerned and developed. The optimization configuration and energy selection of the micro-grid are important problems in the construction and operation of the micro-grid, and the configuration of the energy storage is crucial. Selecting appropriate energy storage type and capacity can effectively improve the economy and reliability of the micro-grid operation. At present, battery energy storage is widely used as a relatively mature energy storage method. However, due to the limitations of operation constraints and capacity, a large-scale battery configuration is needed to meet the reliable operation of the micro-grid, which is not conducive to the safe and economic operation of the micro-grid.

[0003] With the development of hydrogen production and fuel cell technology, hydrogen energy storage as a new type of energy storage has developed rapidly. Its zero-carbon emission and pollution-free characteristics meet the demand for environmental protection and cleanliness of the micro-grid. Hydrogen energy storage is not limited by the upper limit of capacity because of the storage and transportation characteristics of gas. At the same time, with the development of hydrogen storage technology, high-pressure hydrogen storage technology can ensure the safe and space-saving storage of hydrogen. However, in the optimization configuration of the hydrogen-containing micro-grid, the low efficiency of the hydrogen equipment is often ignored, resulting in a large amount of energy waste and increasing the operation cost of the micro-grid. At the same time, the short service life and high cost of the hydrogen equipment make it difficult to be configured on a large scale, that is, it cannot be compared with the configuration of large-scale power equipment such as batteries. Reasonable allocation of the hydrogen storage and electric storage ratio of the micro-grid can effectively improve the reliability and economy of the micro-grid by taking advantage of their respective capacity and power response. SUMMARY

[0004] In order to overcome the efficiency and cost problems of hydrogen storage, the application combines electric energy storage and hydrogen equipment heat recovery technology and proposes an optimization configuration method of an electric-hydrogen-heat coupled multi-energy complementary micro-grid considering hydrogen transaction, which can effectively improve the reliability, economy, renewable energy consumption rate and system energy efficiency of the micro-grid.

[0005] The application adopts the following technical scheme:

[0006] A method for optimizing configuration of an electricity-hydrogen-heat coupled multi-energy complementary microgrid considering hydrogen transaction, the method comprising the following steps:

[0007] Step one: collect and analyze the actual situation of new energy resources in the microgrid construction area, analyze and determine the installation parameters of new energy equipment, and obtain the total available amount of new energy;

[0008] Step two: investigate or obtain the local or nearby power load data, hot water demand data and hydrogen demand situation, as well as the installation conditions and equipment capacity upper limit of the construction site;

[0009] Step three: determine the topology structure of the microgrid, the energy flow relationship of various energy subject forms, and the overall energy supply and operation mode of the microgrid based on the data obtained in steps one and two; the microgrid is composed of distributed power supply, electric heating device, electrolytic hydrogen production device, load and energy storage device; the distributed power supply at least includes hydrogen fuel cell, the energy storage device at least includes electric storage device, hydrogen storage device and heat storage device; the load includes electric load, thermal load and gas load; wherein the distributed power supply, the electric storage device and the load are connected to the DC bus, and the DC network is connected to the external AC power grid through the power electronic inverter device;

[0010] Step four: taking the minimum comprehensive cost of the microgrid in the whole life cycle and the wind and light consumption rate and energy efficiency factor as the objective function, establishing a comprehensive constraint set meeting the reliable, economic and efficient operation requirements of the microgrid, and constructing a double-layer configuration-operation optimization model with the objective function; wherein the objective function is expressed as follows:

[0011] min F=(F ty1 +F sup +F rep )·CRF+F ty2 +βF p

[0012] Wherein, F ty1 is the initial investment cost of the equipment, F sup is the investment cost of the auxiliary equipment, F rep is the replacement cost of the equipment in the whole life cycle, F ty2 is the operation cost of the equipment, F p is the consumption rate and energy efficiency penalty term, β is the penalty coefficient, and CRF is the capital recovery factor;

[0013] The comprehensive constraint set includes the configuration capacity upper limit constraint of the microgrid determined according to step two and the lower layer operation constraint; the lower layer operation constraint includes power balance constraint, electric storage device operation constraint, hydrogen production-fuel cell equipment operation constraint and heat balance related constraint, main network power interaction and demand side response constraint and equipment power upper and lower limit constraint;

[0014] Step five: solving the optimization model to obtain the optimal configuration scheme of the micro-grid.

[0015] Further, in the step one, the new energy resources include wind and light resources, and the actual situation of the wind and light resources mainly refers to climate observation data, including hourly sunlight intensity, air temperature, solar direct angle, annual effective light time, and wind distribution and direction; the new energy equipment includes photovoltaic equipment and wind turbine, and the installation parameters include the installation angle of the photovoltaic equipment, the cut-in and cut-out wind speed of the wind turbine, and the orientation.

[0016] Further, in the step two, the power load data, hot water demand data and hydrogen demand situation include the power consumption of government, industry and residents near the construction area, as well as the load characteristic data of holidays, weekends and weekdays; the demand data and quality requirement situation of hot water of industrial and residential hot water near the construction area; the operation data and gas consumption parameters of hydrogen fuel cell vehicles in the construction area, and the hydrogen demand data of hydrogen industry and hydrogen marketers.

[0017] Further, in the step two, the installation conditions and the upper limit of the equipment capacity refer to the layout area of the new energy equipment in the construction area, the relevant land use standard of the government and the hydrogen safety distance, so as to obtain the maximum installation capacity and quantity of various equipment.

[0018] Further, in the step three, the energy flow relationship of various energy main forms determines the overall energy supply and operation mode of the micro-grid as follows: the distributed power supply generates electric energy by using new energy to supply the electric load, the excess electric energy will be stored in the electric storage device, or hydrogen will be produced by using electrolytic hydrogen production device and stored in the hydrogen storage device, or heat will be produced by using electric heating device and stored in the heat storage device or sold to the main grid, when the electric load supply is insufficient, electricity will be purchased from the main grid or demand side load response will be performed; the hydrogen produced by the electrolytic hydrogen production device is used for gas load supply, when the gas load supply is insufficient, demand side response will be performed, and when the gas load supply is sufficient, excess hydrogen will be sold, the electric heating device further includes heat produced by using heat recovery of hydrogen fuel cell and stored in the heat storage device, and the stored heat energy is used for heat load supply.

[0019] Further, in the step four, the cost expression of each cost in the objective function is:

[0020]

[0021] Wherein: k i is the unit power cost of the distributed power supply except the hydrogen fuel cell and the electric heating device, P i is the corresponding installed capacity i, which represents the type and number of the distributed power supply except the hydrogen fuel cell and the electric heating device; g j is the unit capacity cost of the energy storage device, C jj represents the type and number of energy storage devices; k m P represents the unit power cost of hydrogen-related equipment m-rate n represents the life cycle of the microgrid, LC m m represents the type and number of hydrogen-related equipment, including electrolytic hydrogen production devices and hydrogen fuel cells; α1 and α2 are auxiliary cost coefficients, indicating the proportion of auxiliary cost to purchase cost; P represents the real-time electricity price at time t, P represents the interaction power between the microgrid and the main grid; m gas P represents the hydrogen price, P represents the hydrogen trading volume at time t; p d P represents the demand-side response cost, P represents the demand-side response power at time t, P and P represent the electrical and thermal load demand at time t, respectively, P and P represent the photovoltaic and wind power output at time t, respectively, 总 P represents the optimization time.

[0022] Further, the capacity upper limit constraint in step four includes: the installed capacity of each distributed power source is greater than or equal to zero and less than or equal to its maximum configurable installed capacity, the rated power of the hydrogen fuel cell and the electrolytic hydrogen production device is greater than or equal to zero and less than or equal to its maximum configurable rated power, and the rated capacity of the energy storage device is greater than or equal to zero and less than or equal to its maximum configurable capacity;

[0023] The power balance constraint is that the sum of the distributed power output, the electrolytic hydrogen production device power, the energy storage device power, the electrical load demand, the heating device power, the main grid exchange power, and the demand-side response power at time t is zero.

[0024] The energy storage device operation constraint is:

[0025]

[0026] wherein SOC represents the state of charge of the energy storage device, SOC min SOC represents the lower limit of the SOC of the energy storage device, SOC max SOC represents the upper limit of the SOC of the energy storage device, SOC t P represents the SOC state at time t, P represents the output power of the energy storage device at time t. t0 represents the optimization start time, λ s C represents the initial SOC state quantity, bat P represents the rated capacity of the energy storage device, η bat η represents the charge and discharge efficiency of the energy storage device;

[0027] The operation constraints of hydrogen production-hydrogen fuel cell equipment are:

[0028]

[0029] where ES t represents the hydrogen storage device capacity state at time t, m pro , con are the electricity-gas conversion coefficients of the electrolytic hydrogen production device and the hydrogen fuel cell, respectively, C hyd is the hydrogen storage device capacity, λ e is the initial hydrogen storage device capacity state; represent the electrolytic hydrogen production power and the hydrogen fuel cell output at time t, respectively;

[0030] The heat balance related constraints are:

[0031]

[0032] where tw t is the temperature of the heat storage device at time t, C is the heat load water consumption in the t period, C water is the volume of the heat storage device, is the heating power of the electric heating device in the t period, represents the hydrogen fuel cell heat recovery power, γ1 and γ2 are the heat transfer efficiencies of the hydrogen fuel cell and the electric heating device, respectively, T is the ambient temperature, c s and ρ s are the specific heat capacity and density of water, respectively, tw min and tw max are the upper and lower limits of water temperature, λ th is the initial water temperature;

[0033] The main grid power interaction and demand side response constraints are:

[0034]

[0035] where P pmin , P pmax are the upper and lower limits of the microgrid and main grid interaction power, P drmax is the upper limit of the demand side response power; is the microgrid and main grid interaction power; is the demand side response power at time t;

[0036] The equipment power upper and lower limit constraints are:

[0037]

[0038] where P batmax is the maximum output / charging power of the electricity storage device, and α is the overload operation coefficient of the electrolytic hydrogen production device, Pel-rate , P fc-rate are the rated power of hydrogen fuel cell and electrolytic hydrogen production device respectively, P is the power of electrolytic hydrogen production device at time t, boilermax is the power upper limit of electrolytic hydrogen production device, the minimum operating point is not 0 when electrolytic hydrogen production device and hydrogen fuel cell are started, and is 0 when they are shut down.

[0039] Further, the step five comprises the following steps:

[0040] 1) reading new energy, various load data and electricity price information data;

[0041] 2) randomly initializing the position and speed of each particle in the population of particle swarm algorithm, the population comprises upper layer configuration capacity variables and upper and lower limit constraint values as lower layer operating constraints;

[0042] 3) based on the upper layer configuration variable values represented by the population of particle swarm algorithm, solving the mixed integer programming problem constituted by the lower layer operating constraints by using a solver to obtain the optimal operating cost or no solution information under the values;

[0043] 4) calculating the overall objective function value, evaluating the fitness of each particle, and storing the position and fitness of each particle at present;

[0044] 5) updating the speed and displacement of particles;

[0045] 6) updating the algorithm weight by using a nonlinear dynamic inertia weight coefficient formula:

[0046]

[0047] wherein, ω max , ω min are the maximum and minimum values of particle weight, F is the current objective function value of particles, F avg , F min respectively represent the average objective value and the minimum objective value of all particles at present.

[0048] 7) updating the position and fitness of the current optimal individual;

[0049] If the stop condition (preset operating precision or iteration number) is met, the search is stopped, and the optimal capacity configuration result is output, otherwise returning to 3).

[0050] Compared with the prior art, the application has the following advantages:

[0051] (1) The optimization configuration method of the present application fully taps the application potential of hydrogen equipment, including the fast response capability of hydrogen electrolysis tank and fuel cell equipment based on proton exchange membrane technology, the waste heat recovery capability of hydrogen fuel cell, and the flexible selling capability of hydrogen, so that the use efficiency of hydrogen equipment is improved, and the configuration capacity of battery energy storage is reduced by using the flexible capacity characteristics of hydrogen equipment, and the charge and discharge state of the battery is optimized, thereby improving the economy, reliability and comprehensive efficiency of the microgrid.

[0052] (2) The adaptive weight particle swarm and commercial solver combined algorithm proposed in the present application ensures the accuracy of small time scale planning, improves the convergence and optimization speed of the particle swarm algorithm by using the adaptive weight function, and ensures the error between the approximate search solution and the global optimal solution based on the commercial solver, so that fast and accurate optimization is realized. BRIEF DESCRIPTION OF DRAWINGS

[0053] Figure 1 It is an electric hydrogen heat coupled multi-energy complementary microgrid structure and energy flow relationship diagram containing photovoltaic equipment and a fan;

[0054] Figure 2 It is the light condition of Ningbo area in a year;

[0055] Figure 3 It is the wind speed data of Ningbo area in a year;

[0056] Figure 4 It is the load data of Ningbo area in a year;

[0057] Figure 5 It is the typical annual hot water consumption data;

[0058] Figure 6 It is an optimization solution algorithm block diagram;

[0059] Figure 7 It is a running result. DETAILED DESCRIPTION

[0060] The present application will be further explained in combination with an actual optimization configuration case and the accompanying drawings.

[0061] The electric hydrogen heat coupling multi-energy complementary micro-grid structure mainly comprises a distributed power supply, an electric heating device, an electrolytic hydrogen production device, a load and an energy storage device, the distributed power supply at least comprises a hydrogen fuel cell, the energy storage device at least comprises an electricity storage device, a hydrogen storage device and a heat storage device, and the load comprises an electric load, a heat load and a gas load; wherein the distributed power supply, the electricity storage device and the load are connected to a direct current bus, and the direct current network is connected to an external alternating current network through a power electronic inverter device; the distributed power supply can further comprise other new energy equipment, combined with new energy resources in different places, such as common photovoltaic equipment and wind turbines, the energy storage device is generally a storage battery, the heat load is mainly hot water, and the electric heating device can adopt an electric heating boiler; correspondingly, the heat storage device is a heat storage tank, the electrolytic hydrogen production device is generally an electrolytic tank, and correspondingly, the hydrogen storage device is a hydrogen storage tank, and the electrolytic tank, the hydrogen fuel cell and the hydrogen storage tank form an electrolytic tank-fuel cell system. Figure 1 As shown in the electric hydrogen heat coupling multi-energy complementary micro-grid structure and energy flow relationship diagram comprising photovoltaic equipment and wind turbines, the electric load can be powered by the main grid, the storage battery, the hydrogen fuel cell and wind and light, the excess electric energy will be stored in the storage battery, electrolytic hydrogen or sold to the main grid, and when the electric energy is insufficient, the electric energy can be purchased from the main grid or demand side load response can be performed; the gas load is mainly composed of hydrogen fuel cell vehicles, and hydrogen gas generated by the electrolytic tank is provided, when the hydrogen gas is insufficient, the hydrogen fuel cell vehicle can reduce the hydrogen gas demand, and when the hydrogen gas is sufficient, the hydrogen fuel cell vehicle can sell hydrogen gas to make a profit; the heat load is mainly hot water, which is mainly provided by an electric heating boiler and a fuel cell heat recovery, and when the electric power is insufficient, the fuel cell can effectively supply the heat load, and the demand side response is not considered for the heat load temporarily. The micro-grid construction of a certain area in Ningbo is taken as an example to illustrate the specific implementation manner of the present application.

[0062] In the embodiment of the present application, in the first step, the new energy situation of the micro-grid construction area is analyzed, the new energy of Ningbo area mainly comprises wind and light resources, including hourly sunlight intensity, air temperature, solar direct angle, annual effective illumination time, wind distribution and wind direction and the like, the climate observation data from the China Meteorological Administration, the installation angle of the photovoltaic equipment, the cut-in and cut-out wind speed of the wind turbine and the like basic parameters are determined through the data set analysis, and the total amount of available new energy is evaluated, and the construction feasibility evaluation result of the micro-grid installation area is obtained, as shown in Figure 2 , 3 As shown in the load and wind and light natural resource situation of Ningbo area, the cut-in wind speed of the wind power is 3 m / s, and the cut-out wind speed is 10 m / s;

[0063] In the embodiment of the present application, in the second step, the local or nearby power load data, hot water demand data and hydrogen demand situation of the construction site are investigated or obtained, and the installation conditions, equipment capacity upper limit and other requirements are obtained, including the government, industrial and residential electricity consumption near the construction area, and the load characteristic data of holidays, weekends and weekdays; the demand data and hot water quality requirement situation of industrial hot water and residential hot water near the construction area; the hydrogen fuel cell vehicle operation data and gas consumption parameters in the construction area, and the hydrogen demand data of hydrogen industry and hydrogen marketers, as shown in Figure 4 、 5

[0064] In the embodiment of the present application, in the third step, the topology of the microgrid, the energy flow relationship of various energy body forms, and the overall energy supply and operation mode of the microgrid are determined, including the connection relationship between the loads and power supplies in the microgrid, including the AC and DC structure design of the microgrid; the energy flow relationship of various energy body forms refers to the energy conversion relationship between the energies, the main mode of different energy supply and consumption; the operation mode refers to the interaction rules of the microgrid with the outside world during operation, such as hydrogen sales, switching between off-grid and on-grid, and demand side response strategy, and finally the determined structure and energy flow relationship are as shown in Figure 1 .

[0065] In the embodiment of the present application, in the fourth step, the overall cost of the microgrid in the whole life cycle is taken as the objective function, a comprehensive constraint set meeting the reliable, economic and efficient operation requirements of the microgrid is established, and a double-layer configuration-operation optimization model is constructed with the objective function:

[0066] minF=(F ty1 +F sup +F rep )·CRF+F ty2 +βF p

[0067] Wherein, F ty1 is the one-time investment cost of the equipment, F sup is the investment cost of the auxiliary equipment, F rep is the replacement cost of the equipment in the whole life cycle, F ty2 is the operation cost of the equipment, F p is the consumption rate and energy efficiency penalty term, β is the penalty coefficient, and CRF is the capital recovery factor.

[0068] Taking 1 year as the optimization time, the cost expression is:

[0069]

[0070] Wherein: k i is the unit power cost of the distributed power supply except the hydrogen fuel cell, and P​i Ci represents the installed capacity of the hydrogen-related equipment, i represents the type and number of distributed power sources other than hydrogen fuel cells, including photovoltaic devices, wind turbines, and electric heating boilers in this embodiment; g j Ci represents the installed capacity of the hydrogen-related equipment, i represents the type and number of distributed power sources other than hydrogen fuel cells, including photovoltaic devices, wind turbines, and electric heating boilers in this embodiment; g j Ci represents the installed capacity of the hydrogen-related equipment, i represents the type and number of distributed power sources other than hydrogen fuel cells, including photovoltaic devices, wind turbines, and electric heating boilers in this embodiment; g m Ci represents the installed capacity of the hydrogen-related equipment, i represents the type and number of distributed power sources other than hydrogen fuel cells, including photovoltaic devices, wind turbines, and electric heating boilers in this embodiment; g m-rate Ci represents the installed capacity of the hydrogen-related equipment, i represents the type and number of distributed power sources other than hydrogen fuel cells, including photovoltaic devices, wind turbines, and electric heating boilers in this embodiment; g m Ci represents the installed capacity of the hydrogen-related equipment, i represents the type and number of distributed power sources other than hydrogen fuel cells, including photovoltaic devices, wind turbines, and electric heating boilers in this embodiment; g Ci represents the installed capacity of the hydrogen-related equipment, i represents the type and number of distributed power sources other than hydrogen fuel cells, including photovoltaic devices, wind turbines, and electric heating boilers in this embodiment; g Ci represents the installed capacity of the hydrogen-related equipment, i represents the type and number of distributed power sources other than hydrogen fuel cells, including photovoltaic devices, wind turbines, and electric heating boilers in this embodiment; g gas Ci represents the installed capacity of the hydrogen-related equipment, i represents the type and number of distributed power sources other than hydrogen fuel cells, including photovoltaic devices, wind turbines, and electric heating boilers in this embodiment; g Ci represents the installed capacity of the hydrogen-related equipment, i represents the type and number of distributed power sources other than hydrogen fuel cells, including photovoltaic devices, wind turbines, and electric heating boilers in this embodiment; g d Ci represents the installed capacity of the hydrogen-related equipment, i represents the type and number of distributed power sources other than hydrogen fuel cells, including photovoltaic devices, wind turbines, and electric heating boilers in this embodiment; g Ci represents the installed capacity of the hydrogen-related equipment, i represents the type and number of distributed power sources other than hydrogen fuel cells, including photovoltaic devices, wind turbines, and electric heating boilers in this embodiment; g Ci represents the installed capacity of the hydrogen-related equipment, i represents the type and number of distributed power sources other than hydrogen fuel cells, including photovoltaic devices, wind turbines, and electric heating boilers in this embodiment; g Ci represents the installed capacity of the hydrogen-related equipment, i represents the type and number of distributed power sources other than hydrogen fuel cells, including photovoltaic devices, wind turbines, and electric heating boilers in this embodiment; g Ci represents the installed capacity of the hydrogen-related equipment, i represents the type and number of distributed power sources other than hydrogen fuel cells, including photovoltaic devices, wind turbines, and electric heating boilers in this embodiment; g Ci represents the installed capacity of the hydrogen-related equipment, i represents the type and number of distributed power sources other than hydrogen fuel cells, including photovoltaic devices, wind turbines, and electric heating boilers in this embodiment; g

[0071] Ci represents the installed capacity of the hydrogen-related equipment, i represents the type and number of distributed power sources other than hydrogen fuel cells, including photovoltaic devices, wind turbines, and electric heating boilers in this embodiment; g Ci represents the installed capacity of the hydrogen-related equipment, i represents the type and number of distributed power sources other than hydrogen fuel cells, including photovoltaic devices, wind turbines, and electric heating boilers in this embodiment; g

[0072] Ci represents the installed capacity of the hydrogen-related equipment, i represents the type and number of distributed power sources other than hydrogen fuel cells, including photovoltaic devices, wind turbines, and electric heating boilers in this embodiment; g Ci represents the installed capacity of the hydrogen-related equipment, i represents the type and number of distributed power sources other than hydrogen fuel cells, including photovoltaic devices, wind turbines, and electric heating boilers in this embodiment; g Ci represents the installed capacity of the hydrogen-related equipment, i represents the type and number of distributed power sources other than hydrogen fuel cells, including photovoltaic devices, wind turbines, and electric heating boilers in this embodiment; g

[0073] Ci represents the installed capacity of the hydrogen-related equipment, i represents the type and number of distributed power sources other than hydrogen fuel cells, including photovoltaic devices, wind turbines, and electric heating boilers in this embodiment; g STC Ci represents the installed capacity of the hydrogen-related equipment, i represents the type and number of distributed power sources other than hydrogen fuel cells, including photovoltaic devices, wind turbines, and electric heating boilers in this embodiment; g WT Ci represents the installed capacity of the hydrogen-related equipment, i represents the type and number of distributed power sources other than hydrogen fuel cells, including photovoltaic devices, wind turbines, and electric heating boilers in this embodiment; g fc-rate Ci represents the installed capacity of the hydrogen-related equipment, i represents the type and number of distributed power sources other than hydrogen fuel cells, including photovoltaic devices, wind turbines, and electric heating boilers in this embodiment; g el-rate Ci represents the installed capacity of the hydrogen-related equipment, i represents the type and number of distributed power sources other than hydrogen fuel cells, including photovoltaic devices, wind turbines, and electric heating boilers in this embodiment; g bat Ci represents the installed capacity of the hydrogen-related equipment, i represents the type and number of distributed power sources other than hydrogen fuel cells, including photovoltaic devices, wind turbines, and electric heating boilers in this embodiment; g water Ci represents the installed capacity of the hydrogen-related equipment, i represents the type and number of distributed power sources other than hydrogen fuel cells, including photovoltaic devices, wind turbines, and electric heating boilers in this embodiment; g hydThese represent the installed capacity of photovoltaic and wind power, the rated power of fuel cells and electrolyzers, and the rated capacity of batteries, hot water storage tanks, and hydrogen storage tanks in the microgrid, respectively. STCmax P WTCmax P fcmax P elmax C batmax C wmax C hmax These represent, in turn, the maximum installable capacity of photovoltaic and wind power, the maximum configurable rated power of fuel cells and electrolyzers, the maximum configurable capacity of batteries, and the maximum configurable capacity of water tanks and hydrogen storage tanks in a microgrid.

[0074] Lower-level operational constraints include:

[0075] Power balance constraint: At time t, the sum of the distributed power output, the power of the electrolysis hydrogen production unit, the power of the energy storage unit, the electrical load demand, the power of the heating unit, the main grid switching power, and the demand-side response power is zero; in this embodiment, the specifics are as follows:

[0076]

[0077] in, These represent the photovoltaic power output, wind power output, electrolyzer power, battery power, fuel cell output, electrical load demand, electric boiler power, grid switching power, and demand-side response power at time t.

[0078] Battery operating constraints

[0079]

[0080] Here, SOC represents the state of charge and discharge of the battery. min The lower limit of the allowable state of charge (SOC) for the battery. max The maximum allowable SOC for the battery. t This represents the state of soc at time t. Let λ be the battery power at time t. t0 is the initial optimization time, and λ is the power at time t. s It is the initial SOC state variable, C bat Indicates the rated capacity of the battery, η bat This refers to the charging and discharging efficiency of the battery.

[0081] Operating constraints of hydrogen production-fuel cell equipment

[0082]

[0083] Among them, ES t This represents the hydrogen storage tank capacity state at time t, equivalent to the state of charge (SOC) of a battery, m pr o,m conElectrical conversion coefficient of electrolyzer and fuel cell, respectively, C hyd Storage tank capacity, λ e Initial storage tank capacity state.

[0084] Thermal balance related constraints

[0085]

[0086] Where, tw t The temperature of the thermal storage water tank at t, Hot water consumption of thermal load at t, C water The volume of the hot water tank, The heating power of the electric boiler at t, Indicates the hydrogen fuel cell heat recovery power, γ1 and γ2 are the heat transfer efficiencies of the fuel cell and the electric boiler, respectively, T is the ambient temperature, c s , ρ s The specific heat capacity and density of water, respectively, tw min And tw max The upper and lower limits of water temperature, λ th The water temperature at the initial moment.

[0087] Main grid power interaction and demand side response constraints

[0088]

[0089] Where P pmin , P pmax The upper and lower limits of the main grid interaction power, P drmax The upper limit of the demand side response power.

[0090] Equipment power upper and lower limit constraints

[0091]

[0092] In the formula, P batmax The maximum output / charge power of the battery, α is the overloading operation coefficient of the electrolyzer, P boilermax The power upper limit of the electric heating device, subject to equipment safety constraints The electrolyzer and fuel cell run at a non-zero minimum operating point, or are in shutdown state (zero).

[0093] In the embodiments of the present application, the fifth step, the improved particle swarm algorithm and the commercial solver are combined to solve the optimization model, and the optimal configuration scheme is obtained, as shown in Figure 6 The method comprises the following steps:

[0094] 1) Read wind power, photovoltaic, various load data and electricity price information data;

[0095] 2) Randomly initialize the position and velocity of each particle in the population, which includes the upper layer configuration variables, as the upper and lower limit constraint values of the lower layer operation constraints;

[0096] 3) Based on the upper layer configuration variable values represented by the population of the particle swarm algorithm, use the solver to solve the mixed integer programming problem constituted by the lower layer operation constraints, to obtain the optimal operation cost or no solution information under the values;

[0097] 4) Calculate the overall objective function value, by which the fitness of each particle is evaluated, and the current position and fitness of each particle are stored;

[0098] 5) Update the velocity and displacement of the particles;

[0099] 6) Update the algorithm weight using the nonlinear dynamic inertia weight coefficient formula:

[0100]

[0101] Wherein, ω max ,ω min is the maximum and minimum value of the particle weight, F is the current objective function value of the particle, F avg , F min respectively represent the average objective value and the minimum objective value of all particles.

[0102] 7) Update the position and fitness of the current optimal individual;

[0103] 8) If the stop condition (preset operation accuracy or iteration number) is met, the search is stopped, and the optimal capacity configuration result is output, as shown in the following formula: Figure 7

[0104] The optimization configuration result in the embodiment is shown in Table 1:

[0105] Table 1 Optimization configuration capacity result

[0106]

[0107] Obviously, the above embodiments are only examples for clear illustration, and do not limit the embodiments. Based on the above description, other different forms of changes or variations can be made by those skilled in the art. Here, it is not necessary and impossible to enumerate all the embodiments. The obvious changes or variations derived therefrom are still within the protection scope of the present application.​

Claims

1. An optimized configuration method for an electro-hydrogen-thermal coupled multi-energy complementary microgrid considering hydrogen trading, characterized in that, The method includes the following steps: Step 1: Collect and analyze the actual situation of local new energy resources in the microgrid construction area, analyze and determine the installation parameters of new energy equipment, and obtain the total amount of new energy that can be utilized; Step 2: Investigate or obtain local or nearby electricity load data, hot water demand data, hydrogen demand, installation conditions, and equipment capacity limits for the construction site; Step 3: Combining the data obtained in Step 1 and Step 2, determine the microgrid topology, the energy flow relationships of various energy sources, and the overall power supply and operation mode of the microgrid. The microgrid consists of distributed power sources, electric heating devices, electrolytic hydrogen production devices, loads, and energy storage devices. The distributed power sources include at least hydrogen fuel cells, and the energy storage devices include at least electric energy storage devices, hydrogen storage devices, and thermal energy storage devices. The loads include electrical loads, thermal loads, and gas loads. The distributed power sources, energy storage devices, and loads are all connected to the DC bus, and the DC network is then connected to the external AC grid through a power electronic inverter. Step 4: Using the lowest overall cost over the entire lifecycle of the microgrid, the wind and solar grid integration rate, and the energy efficiency factor as objective functions, establish a comprehensive set of constraints that meets the requirements for reliable, economical, and efficient operation of the microgrid. This set of constraints, along with the objective function, constitutes a two-layer configuration-operation optimization model. The objective function is expressed as follows: minF=(F ty1 +F sup +F rep )·CRF+F ty2 +βF p Among them, F ty1 For the one-time investment cost of the equipment, F sup To cover the investment costs of supporting auxiliary equipment, F rep For equipment replacement costs throughout its entire lifecycle, F ty2 For equipment operating costs, F p For the absorption rate and energy efficiency penalty terms, β is the penalty coefficient, and CRF is the capital recovery coefficient; The comprehensive constraint set includes the upper limit constraint of the microgrid configuration capacity and the lower-level operation constraints determined in step two; the lower-level operation constraints include power balance constraints, energy storage device operation constraints, hydrogen production-fuel cell equipment operation constraints and heat balance related constraints, main grid power interaction and demand-side response constraints, and equipment power upper and lower limit constraints. Step 5: Solve the optimization model to obtain the optimal configuration scheme of the microgrid, specifically: Step five includes the following steps: 1) Read data on new energy sources, various loads, and electricity prices; 2) Randomly initialize the position and velocity of each particle in the particle swarm algorithm. This swarm includes the upper-level configuration capacity variable, which serves as the upper and lower limit constraint values ​​for the lower-level running constraints. 3) Based on the upper-level configuration variable value represented by the particle swarm algorithm population, the solver is used to solve the mixed integer programming problem composed of the lower-level running constraints, and the optimal running cost or no-solution information under this value is obtained; 4) Calculate the overall objective function value, evaluate the fitness of each particle, and store the current position and fitness value of each particle; 5) Update the particle's velocity and displacement; 6) Update the algorithm weights using the nonlinear dynamic inertia weight coefficient formula: Where, ω max ,ω min Let F be the maximum and minimum values ​​of the particle weights, and F be the current objective function value of the particle. avg ,F min These represent the average target value and the minimum target value of all current particles, respectively. 7) Update the position and fitness of the current best individual; If the stopping condition is met (the preset computational precision or number of iterations), the search stops and the optimal capacity configuration result is output; otherwise, return 3).

2. The optimized configuration method for an electro-hydrogen-thermal coupled multi-energy complementary microgrid considering hydrogen trading, as described in claim 1, is characterized in that... In step one, new energy resources include wind and solar resources. The actual situation of wind and solar resources mainly refers to climate observation data, including hourly solar intensity, air temperature, direct sunlight angle, annual effective sunshine duration, wind distribution and wind direction. New energy equipment includes photovoltaic equipment and wind turbines. Installation parameters include the installation angle of photovoltaic equipment, the cut-in and cut-out wind speeds of wind turbines and their orientation.

3. The optimized configuration method for an electro-hydrogen-thermal coupled multi-energy complementary microgrid considering hydrogen trading, as described in claim 1, is characterized in that... In step two, the electricity load data, hot water demand data, and hydrogen demand data include the electricity consumption of governments, industries, and residents near the construction area, as well as load characteristic data for holidays, weekends, and weekdays; the demand data for industrial and residential hot water near the construction area and the hot water quality requirements; the operating data and gas consumption parameters of hydrogen fuel cell vehicles in the construction area, and the hydrogen demand data of the hydrogen industry and hydrogen marketers.

4. The optimized configuration method for an electro-hydrogen-thermal coupled multi-energy complementary microgrid considering hydrogen trading, as described in claim 1, is characterized in that... In step two, the installation conditions and equipment capacity limits refer to the layout area of ​​new energy equipment in the construction area, relevant government land use standards, and hydrogen safety distance, thereby obtaining the maximum installation capacity and quantity of various equipment.

5. The optimized configuration method for an electro-hydrogen-thermal coupled multi-energy complementary microgrid considering hydrogen trading, as described in claim 1, is characterized in that... In step three, the energy flow relationships of the various energy sources determine the overall energy supply and operation mode of the microgrid as follows: Distributed power sources use new energy sources to generate electricity to supply the electrical load. Excess electricity will be stored in an energy storage device, or hydrogen will be produced using an electrolytic hydrogen production device and stored in a hydrogen storage device, or heat will be generated using an electric heating device and stored in a thermal storage device, or sold to the main grid. When the electricity load supply is insufficient, electricity will be purchased from the main grid or demand-side load response will be implemented. The hydrogen produced by the electrolytic hydrogen production device is used to supply the gas load. When the gas load supply is insufficient, demand-side response will be implemented. When the gas load supply is sufficient, excess hydrogen will be sold. The electric heating device also includes heat generated using the heat recovery of the hydrogen fuel cell and stored in a thermal storage device. The stored heat energy is used to supply the heat load.

6. The optimized configuration method for an electro-hydrogen-thermal coupled multi-energy complementary microgrid considering hydrogen trading, as described in claim 1, is characterized in that... In step four, the cost expressions in the objective function are as follows: Where: k i For distributed power sources and electric heating devices other than hydrogen fuel cells, P i For the corresponding installed capacity, i represents the type and number of distributed power sources and electric heating devices other than hydrogen fuel cells; g j C represents the unit capacity cost of the energy storage device. j Its capacity, j represents the type and number of the energy storage device; k m For the unit power cost of hydrogen-related equipment, P m-rate Let LC be the rated capacity of hydrogen-related equipment, n be the lifespan of the microgrid, and LC be the rated capacity of the hydrogen-related equipment. m The lifespan of hydrogen-related equipment is denoted by m, which represents the type and number of the hydrogen-related equipment, including electrolytic hydrogen production devices and hydrogen fuel cells; α1 and α2 are auxiliary cost coefficients, representing the proportion of auxiliary costs to purchase costs. Let be the real-time electricity price at time t. For the interaction power between the microgrid and the main grid; m gas For the price of hydrogen, Let p be the hydrogen trading volume at time t; d For demand-side response costs, Let be the demand-side response power at time t. Let represent the electrical load demand and heat load demand at time t, respectively. Let t represent the photovoltaic power output and wind power output at time t, respectively. 总 To optimize time.

7. The optimized configuration method for an electro-hydrogen-thermal coupled multi-energy complementary microgrid considering hydrogen trading, as described in claim 1, is characterized in that... The upper limit constraint of the configuration capacity in step four includes: the installed capacity of each distributed power source other than hydrogen fuel cells is greater than or equal to zero and less than or equal to its maximum configurable installed capacity; the rated power of hydrogen fuel cells and electrolysis hydrogen production devices is greater than or equal to zero and less than or equal to its maximum configurable rated power; and the rated capacity of energy storage devices is greater than or equal to zero and less than or equal to its maximum configurable capacity. The power balance constraint is: the sum of the output of distributed power sources, the power of electrolytic hydrogen production unit, the power of energy storage unit, the electrical load demand, the power of heating unit, the main grid switching power, and the demand-side response power at time t is zero. The operating constraints of the energy storage device are: Where SOC represents the charge / discharge state of the energy storage device, SOC min The lower limit of the allowable SOC for energy storage devices, SOC max The SOC (State of Charge) is the upper limit allowed for energy storage devices. t This represents the SOC state at time t. λ is the output power of the energy storage device at time t; t0 is the optimization start time, λ s It is the initial SOC state variable, C bat Indicates the rated capacity of the energy storage device, η bat The charging and discharging efficiency of the energy storage device; The operating constraints for hydrogen production and hydrogen fuel cell equipment are: Among them, ES t m represents the capacity status of the hydrogen storage device at time t. pro ,m con The electro-to-gas conversion coefficients for the electrolysis hydrogen production unit and the hydrogen fuel cell, respectively, are C. hyd For the capacity of the hydrogen storage device, λ e This is the initial capacity status of the hydrogen storage device; These represent the hydrogen production power by electrolysis and the output power of the hydrogen fuel cell at time t, respectively. The thermal equilibrium constraints are: Among them, tw t The temperature of the thermal storage device at time t. C represents the hot water consumption during the heat load period t. water The volume of the thermal storage device, The heating power of the electric heating device during time period t. The heat recovery power of the hydrogen fuel cell is represented by γ1 and γ2, which are the heat transfer efficiencies of the hydrogen fuel cell and the electric heating device, respectively. T is the ambient temperature, and c is the heat recovery power of the hydrogen fuel cell. s ρ s These are the specific heat capacity and density of water, respectively. min and tw max These are the upper and lower limits of water temperature, respectively, λ th The initial water temperature; The main grid power interaction and demand-side response constraints are: Where P pmin ,P pmax P represents the upper and lower limits of the power interaction between the microgrid and the main grid. drmax This represents the upper limit of demand-side response power. This refers to the power exchanged between the microgrid and the main grid. Let t be the demand-side response power; The upper and lower limits of equipment power are constrained as follows: In the formula, P batmax P represents the maximum output / charging power of the energy storage device, α is the overload operating coefficient of the electrolytic hydrogen production device, and P is the maximum output / charging power of the energy storage device. el-rate P fc-rate These are the rated power of the hydrogen fuel cell and the electrolysis hydrogen production unit, respectively. Let P be the power of the electric heating device at time t. boilermax It represents the upper limit of the power of the electric heating device. The electrolytic hydrogen production device and the hydrogen fuel cell have a non-zero minimum operating point when they are turned on, and the value is zero when they are turned off.

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