Method and system for capacity configuration and operation optimization of building photovoltaic heat pump energy storage system

Abstract

The invention discloses a method and system for capacity configuration and operation optimization of a building photovoltaic heat pump energy storage system, and the method comprises the steps: determining a working mode of an energy storage water tank in a corresponding time period according to time-of-use electricity price, and determining an operation strategy of the building photovoltaic heat pump energy storage system in each time period in combination with the working mode corresponding to the energy storage water tank; based on the determined operation strategy of the building photovoltaic heat pump energy storage system, the capacity of an energy storage water tank serves as an optimization object, the minimum annual total cost of the system and the maximum photovoltaic self-consumption rate serve as optimization objectives, and a non-dominated genetic algorithm is used for solving the dual-objective optimization problem to obtain the Pareto leading edge of the annual total cost of the system and the photovoltaic self-consumption rate; and selecting the capacity of the energy storage water tank corresponding to the Pareto frontier optimal solution set as the design capacity of the energy storage water tank in the building photovoltaic heat pump energy storage system by using an Euclidean distance method. The method aims at solving the problem that an existing building energy system is difficult in configuration and operation optimization solving, and the solving speed of the system configuration optimization problem is increased.

Description

Technical Field

[0001] The present invention relates to the technical field of building energy conservation, and in particular to a method and system for capacity configuration and operation optimization of a building photovoltaic heat pump energy storage system. Background Art

[0002] Building energy consumption accounts for more than 33% of the world's total energy consumption. In order to reduce building energy consumption and increase the flexibility of building electricity use, renewable energy technology, energy storage technology and building cold and heat source technology are combined, that is, building multi-energy complementary technology has been vigorously developed and applied in buildings. The building multi-energy complementary energy system mainly includes renewable energy systems, cold and heat source energy supply systems and cold, heat and electricity energy storage systems. Its main research contents include configuration optimization research and equipment control theory research. In order to promote the low-carbon and energy-saving development of buildings, it is necessary to continuously accelerate the application of renewable energy and energy storage technology in buildings to achieve the optimal configuration of building multi-energy complementary systems and building operation control optimization. However, at present, the energy storage facilities in the building multi-energy complementary energy system are still mainly concentrated on battery energy storage, and the research on water storage, a more economical energy storage method, is very lacking, especially the capacity configuration optimization of energy storage water tanks and its coordinated control theory. At present, there are many design optimization methods for building photovoltaic heat pump energy storage systems, mainly including optimization methods based on mathematical programming models and rule-based control logic. The optimization method based on mathematical programming model mainly establishes an optimization model for the building energy system and uses optimization software to solve it. This method has been successfully applied to various types of building energy system configurations; while the optimization method based on rule control logic mainly formulates optimization goals and corresponding system operation strategies for the building energy system and uses heuristic algorithms to solve it. The optimization of building energy systems based on mathematical programming models takes a long time to solve, while the optimization method based on rule control logic takes a short time to solve and is easy to combine with heat pump control, making it easier to promote and apply in actual projects. Summary of the invention

[0003] Technical problem to be solved by the present invention: In view of the above-mentioned problems in the prior art, a method and system for capacity configuration and operation optimization of a building photovoltaic heat pump energy storage system is provided. The present invention aims to solve the problem of difficulty in solving the configuration and operation optimization of the existing building energy system and to improve the speed of solving the system configuration optimization problem.

[0004] In order to solve the above technical problems, the technical solution adopted by the present invention is: A method for capacity configuration and operation optimization of a building photovoltaic heat pump energy storage system comprises the following steps: S1, determining the working mode of the energy storage water tank corresponding to the time period according to the time-sharing electricity price, wherein the working mode corresponding to the energy storage water tank is one of discharging energy, storing energy and not working; S2, determine the operation strategy of the building photovoltaic heat pump energy storage system in each time period in combination with the corresponding working mode of the energy storage water tank; S3, based on the determined operation strategy of the building photovoltaic heat pump energy storage system, the energy storage tank volume is taken as the optimization object, the minimum system annual total cost and the maximum photovoltaic self-consumption rate are taken as the optimization goals, and the non-dominated genetic algorithm is used to solve the dual-objective optimization problem to obtain the Pareto frontier of the system annual total cost and the photovoltaic self-consumption rate; S4, normalize the system annual total cost and photovoltaic self-consumption rate in the Pareto frontier, and use the Euclidean distance method to select the optimal system annual total cost and photovoltaic self-consumption rate. The energy storage tank volume corresponding to the optimal system annual total cost and photovoltaic self-consumption rate is used as the design volume of the energy storage tank in the building photovoltaic heat pump energy storage system.

[0005] Optionally, when determining the working mode of the energy storage water tank for the corresponding time period according to the time-of-use electricity price, the time-of-use electricity price includes valley electricity price, flat electricity price and peak electricity price, and each day includes one valley electricity price, two flat electricity prices and two peak electricity prices. The working mode of the energy storage water tank under the two peak electricity prices is energy release. The working mode of the energy storage water tank under the first flat electricity price is not working, and the working mode of the energy storage water tank under the second flat electricity price is energy release. The working mode of the energy storage water tank under the peak electricity price is energy release, and the working mode of the energy storage water tank under the valley electricity price is energy storage.

[0006] Optionally, in step S2, determining the operation strategy of the building photovoltaic heat pump energy storage system in each time period in combination with the working mode corresponding to the energy storage water tank refers to combining the working mode of the energy storage water tank, the total building power load consisting of equipment, lighting power and power used to drive the air source heat pump to meet the building air conditioning load , building electrical load consisting of equipment and lighting electrical load To determine the operation strategy of the building photovoltaic heat pump energy storage system in each time period, including: When the energy storage tank is not working, the operation strategy of the building photovoltaic heat pump energy storage system in each time period is determined as follows: Less than the total power load of the building , and photovoltaic power generation Less than building electrical load The operation strategy of the building photovoltaic heat pump energy storage system in each time period is determined according to the following formula: , , , In photovoltaic power generation Less than the total power load of the building , and photovoltaic power generation Greater than or equal to the building electrical load The operation strategy of the building photovoltaic heat pump energy storage system in each time period is determined according to the following formula: , , , In photovoltaic power generation Greater than or equal to the total power load of the building , and photovoltaic power generation Greater than or equal to the building electrical load The operation strategy of the building photovoltaic heat pump energy storage system in each time period is determined according to the following formula: , , , , in, The photovoltaic power generation used to meet the building electrical load, is the photovoltaic power generation of the photovoltaic power generation system, The grid electricity used to meet the building electrical load, The grid electricity used to meet the building air conditioning load, is the building air conditioning load, is the coefficient of performance of the air source heat pump; The amount of photovoltaic electricity used to meet the building's air conditioning load; To meet the total electricity load of the building, is the total electricity load of the building, is the amount of photovoltaic power generation connected to the grid, is the maximum limit of photovoltaic grid-connected power, The electricity consumed by photovoltaic power generation to drive the heat pump to store energy in the energy storage tank, is the maximum energy that can be stored in the energy storage tank, is the energy state of the energy storage tank at the previous moment, The amount of electricity wasted from photovoltaic power generation.

[0007] Optionally, in step S2, determining the operation strategy of the building photovoltaic heat pump energy storage system in each time period in combination with the working mode corresponding to the energy storage water tank refers to combining the working mode of the energy storage water tank, the total building power load consisting of equipment, lighting power and power used to drive the air source heat pump to meet the building air conditioning load , building electrical load consisting of equipment and lighting electrical load To determine the operation strategy of the building photovoltaic heat pump energy storage system in each time period, including: When the working mode of the energy storage tank is to release energy, the operation strategy of the building photovoltaic heat pump energy storage system in each time period is determined as follows: Less than the total power load of the building , and photovoltaic power generation Less than building electrical load The operation strategy of the building photovoltaic heat pump energy storage system in each time period is determined according to the following formula: , , , , In photovoltaic power generation Less than the total power load of the building , and photovoltaic power generation Greater than or equal to the building electrical load The operation strategy of the building photovoltaic heat pump energy storage system in each time period is determined according to the following formula: , , , , In photovoltaic power generation Greater than or equal to the total power load of the building , and photovoltaic power generation Greater than or equal to the building electrical load The operation strategy of the building photovoltaic heat pump energy storage system in each time period is determined according to the following formula: , , , , , , in, The photovoltaic power generation used to meet the building electrical load, is the photovoltaic power generation of the photovoltaic power generation system, The grid electricity used to meet the building electrical load, The energy released by the energy storage tank to meet the building air conditioning load, The energy released by the energy storage tank, is the building air conditioning load, The grid electricity used to meet the building air conditioning load, is the coefficient of performance of the air source heat pump; The amount of photovoltaic electricity used to meet the building's air conditioning load; is the amount of photovoltaic power generation connected to the grid, is the maximum limit of photovoltaic grid-connected power, The photovoltaic power generation consumed by the heat pump to store energy in the energy storage tank is is the maximum energy that can be stored in the energy storage tank, is the stored energy of the energy storage tank at the previous moment, The amount of electricity wasted from photovoltaic power generation.

[0008] Optionally, in step S2, determining the operation strategy of the building photovoltaic heat pump energy storage system in each time period in combination with the working mode corresponding to the energy storage water tank refers to combining the working mode of the energy storage water tank, the total building power load consisting of equipment, lighting power and power used to drive the air source heat pump to meet the building air conditioning load , building electrical load consisting of equipment and lighting electrical load To determine the operation strategy of the building photovoltaic heat pump energy storage system in each time period, including: When the working mode of the energy storage tank is energy storage, the operation strategy of the building photovoltaic heat pump energy storage system in each time period is determined as follows: Less than the total power load of the building , and photovoltaic power generation Less than building electrical load The operation strategy of the building photovoltaic heat pump energy storage system in each time period is determined according to the following formula: , , , , In photovoltaic power generation Less than the total power load of the building , and photovoltaic power generation Greater than or equal to the building electrical load The operation strategy of the building photovoltaic heat pump energy storage system in each time period is determined according to the following formula: , , , , In photovoltaic power generation Greater than or equal to the total power load of the building , and photovoltaic power generation Greater than or equal to the building electrical load When the building is in operation, the operation strategy of the photovoltaic heat pump energy storage system in each time period is first determined according to the following formula: , , , Then determine whether the energy storage state of the energy storage tank is less than the maximum storage capacity of the energy storage tank. If so, further determine the operation strategy of the building photovoltaic heat pump energy storage system in each time period according to the following formula: , Otherwise, the operation strategy of the building photovoltaic heat pump energy storage system in each time period is further determined according to the following formula: , , in, The photovoltaic power generation used to meet the building electrical load, is the photovoltaic power generation of the photovoltaic power generation system, The grid electricity used to meet the building electrical load, The grid electricity used to meet the building air conditioning load, is the building air conditioning load, is the coefficient of performance of the air source heat pump, The grid electricity is used to drive the air source heat pump to store energy in the energy storage tank. The energy stored in the energy storage tank, The maximum limit for power drawn from the grid; The amount of photovoltaic electricity used to meet the building's air conditioning load; The photovoltaic power generation consumed by the photovoltaic power generation to drive the heat pump to store energy in the energy storage tank; is the amount of photovoltaic power generation connected to the grid, The maximum limit of photovoltaic grid-connected power; Abandoned electricity from photovoltaic power generation.

[0009] Optionally, the function expression for minimizing the total annual cost of the system in step S3 is: , in, To minimize, is the total annual cost of the system, is the annual investment cost of the energy storage tank, is the annual operating cost, is the annual maintenance cost, is the replacement cost, and: , , in, is the volume of the energy storage tank, is the unit volume price of the energy storage tank, is the capital recovery rate, for The cost of purchasing electricity from the grid at all times, for Revenue from selling electricity to the grid at all times; The function expression for the maximum photovoltaic self-consumption rate in step S3 is: , in, represents maximization, is the photovoltaic self-consumption rate, The photovoltaic power generation used to meet the building electrical load, The photovoltaic power generation used to meet the building electrical load, The photovoltaic power generation consumed by the heat pump to store energy in the energy storage tank is is the photovoltaic power generation of the photovoltaic power generation system.

[0010] Optionally, in step S3, when the non-dominated genetic algorithm is used to solve the bi-objective optimization problem with the energy storage tank volume as the optimization object and the minimum system annual total cost and the maximum photovoltaic self-consumption rate as the optimization objectives to obtain the Pareto frontier of the system annual total cost and the photovoltaic self-consumption rate, the bi-objective optimization problem includes that the system satisfies the system power balance constraint and the energy storage tank operation constraint at each time step, and when the energy storage tank is storing energy, the function expression of the system power balance constraint is: , When the energy storage tank is discharged, the function expression of the system power balance constraint is: , The functional expression of the energy storage tank operation constraint is: , , , in, is the total electricity load of the building, The energy stored in the energy storage tank, is the coefficient of performance of the air source heat pump, The photovoltaic power generation used to meet the building electrical load, To meet the photovoltaic power generation of the building air conditioning load, The grid electricity used to meet the building electrical load, The grid electricity used to meet the building air conditioning load, The grid electricity is used to drive the air source heat pump to store energy in the energy storage tank. The energy released by the energy storage tank; is the maximum energy that can be stored in the energy storage tank, is the maximum energy that the energy storage tank can release, is the volume of the energy storage tank, It is the maximum volume limit of the energy storage tank.

[0011] In addition, the present invention also provides a system for capacity configuration and operation optimization of a building photovoltaic heat pump energy storage system, comprising an interconnected microprocessor and a memory, wherein the microprocessor is programmed or configured to execute the method for capacity configuration and operation optimization of the building photovoltaic heat pump energy storage system.

[0012] In addition, the present invention also provides a computer-readable storage medium, which stores a computer program or instruction, and the computer program or instruction is programmed or configured to execute the method for capacity configuration and operation optimization of the building photovoltaic heat pump energy storage system through a processor.

[0013] In addition, the present invention also provides a computer program product, including a computer program or instructions, which are programmed or configured to execute the method for capacity configuration and operation optimization of the building photovoltaic heat pump energy storage system through a processor.

[0014] Compared with the prior art, the present invention mainly has the following advantages: in order to solve the problem of difficult solution of existing building energy system configuration and operation optimization, the method of capacity configuration and operation optimization of building photovoltaic heat pump energy storage system of the present invention adopts a rule-based control strategy to simultaneously optimize the energy storage tank capacity configuration and operation of the building photovoltaic heat pump water storage system, with the minimum annual total cost of the system and the maximum photovoltaic self-consumption rate as the optimization goals, and uses a non-dominated genetic algorithm to solve the dual-objective optimization problem, which can obtain the optimal energy storage tank capacity, reduce the cost of the energy storage tank while meeting the operation of the building photovoltaic heat pump energy storage system, and can improve the speed of solving the system configuration optimization problem, and has strong versatility. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 Schematic diagram of the basic flow of the method of the embodiment of the present invention.

[0016] Figure 2 This is a flow chart of the energy storage tank capacity and operation optimization of the building photovoltaic heat pump energy storage system in an embodiment of the present invention.

[0017] Figure 3 This is a diagram of the first stage of the flat electricity price system operation strategy of the building photovoltaic heat pump energy storage system in an embodiment of the present invention.

[0018] Figure 4 This is a diagram of the peak electricity price and the second stage flat electricity price system operation strategy of the building photovoltaic heat pump energy storage system in an embodiment of the present invention.

[0019] Figure 5 This is a diagram of the valley electricity price system operation strategy of the building photovoltaic heat pump energy storage system in an embodiment of the present invention.

[0020] Figure 6 It is the annual load of the building in the embodiment of the present invention.

[0021] Figure 7 It is the annual power generation of the photovoltaic power generation system in the embodiment of the present invention.

[0022] Figure 8 The figure shows the time-of-use electricity price setting in the embodiment of the present invention.

[0023] Fig. 9 It is the Pareto frontier of the annual total cost and photovoltaic self-consumption rate of the building photovoltaic heat pump energy storage system in the embodiment of the present invention.

[0024] Fig.10 FIG. 4 is the flow of system electric power in an embodiment of the present invention.

[0025] Fig.11 This is the power flow of the energy storage water tank per hour in the embodiment of the present invention. DETAILED DESCRIPTION

[0026] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0027] like Figure 1 As shown, the method for capacity configuration and operation optimization of the building photovoltaic heat pump energy storage system in this embodiment includes the following steps: S1, determining the working mode of the energy storage water tank corresponding to the time period according to the time-sharing electricity price, wherein the working mode corresponding to the energy storage water tank is one of discharging energy, storing energy and not working; S2, determine the operation strategy of the building photovoltaic heat pump energy storage system in each time period in combination with the corresponding working mode of the energy storage water tank; S3, based on the determined operation strategy of the building photovoltaic heat pump energy storage system, the energy storage tank volume is taken as the optimization object, the minimum system annual total cost and the maximum photovoltaic self-consumption rate are taken as the optimization goals, and the non-dominated genetic algorithm is used to solve the dual-objective optimization problem to obtain the Pareto frontier of the system annual total cost and the photovoltaic self-consumption rate; S4, normalize the system annual total cost and photovoltaic self-consumption rate in the Pareto frontier, and use the Euclidean distance method to select the optimal system annual total cost and photovoltaic self-consumption rate. The energy storage tank volume corresponding to the optimal system annual total cost and photovoltaic self-consumption rate is used as the design volume of the energy storage tank in the building photovoltaic heat pump energy storage system.

[0028] As an optional implementation, the time-of-use electricity price structure used in this embodiment is valley electricity price: 23:00-7:00; flat electricity price: 7:00-11:00, 14:00-18:00; peak electricity price: 11:00-14:00, 18:00-23:00. In addition, some regions may also have a single valley electricity price, flat electricity price and peak electricity price, that is, there is only one valley electricity price, one flat electricity price and one peak electricity price in 24 hours a day. Figure 2 As shown, in this embodiment, when determining the working mode of the energy storage water tank corresponding to the time period according to the time-of-use electricity price, the time-of-use electricity price includes a valley electricity price, a flat electricity price and a peak electricity price. Every day includes one valley electricity price, two flat electricity prices and two peak electricity prices. The working mode of the energy storage water tank under the two peak electricity prices is energy release. Under the first flat electricity price (7:00-11:00), the working mode of the energy storage water tank is not working. Under the second flat electricity price (14:00-18:00), the working mode of the energy storage water tank is energy release. Under the peak electricity price (11:00-14:00), the working mode of the energy storage water tank is energy release. Under the valley electricity price (23:00-7:00), the working mode of the energy storage water tank is energy storage.

[0029] The building photovoltaic heat pump energy storage system mainly includes a photovoltaic power generation module, an air source heat pump and an energy storage water tank. In this embodiment, a simulation model is constructed for the building photovoltaic heat pump energy storage system, which mainly includes a building load model, a photovoltaic power generation model, an air source heat pump model, an energy storage water tank model and a power grid model. Among them, the building load model is established using the Type56 module in the TRNSYS software, and the photovoltaic power generation model is established using the Type94a module in the TRNSYS software.

[0030] Air source heat pump model: The air source heat pump model is simply described by the following formula: , in, is the coefficient of performance of the air source heat pump, is the heating capacity of the air source heat pump, kW; is the input power of the air source heat pump, kW; the performance coefficient of the air source heat pump is closely related to the ambient temperature. The following formulas describe the relationship between the performance coefficient of the air source heat pump and the ambient temperature under heating and cooling conditions respectively.

[0031] , , in, and are the performance coefficients of air source heat pumps under heating and cooling conditions, is the ambient temperature, °C; Energy storage tank model: A hybrid water tank model is used to model the energy storage tank. The storage energy of the energy storage tank is related to the current charging and discharging energy and the storage energy of the previous moment. The energy of the energy storage tank will dissipate over time. The energy storage balance of the energy storage tank is described by the following formula: , in, is the net energy storage tank ( time), is the energy storage efficiency of the hot water storage tank, which is 0.98 in this embodiment; is the net energy storage of the energy storage tank at the previous moment; and They are the energy storage efficiency and energy release efficiency of the energy storage tank, both of which are 0.95. and They are the storage energy and release energy of the energy storage tank respectively.

[0032] Grid model: The grid input power and grid-connected power of the grid-connected system should satisfy the following formula: , , Among them, the grid input limit The maximum power that users can draw from the grid for energy storage during off-peak electricity prices, and the online power limit The maximum power output from the user's photovoltaic power generation system to the grid. , and are the power flows (kW) from the grid to the building cooling and heating loads, building electrical loads and energy storage tanks, respectively. is the power flow from the photovoltaic power generation system to the grid (kW).

[0033] like Figure 3As shown, in step S2 of this embodiment, the operation strategy of the building photovoltaic heat pump energy storage system in each time period is determined in combination with the working mode corresponding to the energy storage water tank, which means that the total building power load composed of equipment, lighting power and power used to drive the air source heat pump to meet the building air conditioning load is determined in combination with the working mode of the energy storage water tank. , building electrical load consisting of equipment and lighting electrical load To determine the operation strategy of the building photovoltaic heat pump energy storage system in each time period, including: When the energy storage tank is not working, the operation strategy of the building photovoltaic heat pump energy storage system in each time period is determined as follows: Less than the total power load of the building , and photovoltaic power generation Less than building electrical load The operation strategy of the building photovoltaic heat pump energy storage system in each time period is determined according to the following formula: , , , In photovoltaic power generation Less than the total power load of the building , and photovoltaic power generation Greater than or equal to the building electrical load The operation strategy of the building photovoltaic heat pump energy storage system in each time period is determined according to the following formula: , , , In photovoltaic power generation Greater than or equal to the total power load of the building , and photovoltaic power generation Greater than or equal to the building electrical load The operation strategy of the building photovoltaic heat pump energy storage system in each time period is determined according to the following formula: , , , , in, The photovoltaic power generation used to meet the building electrical load, is the photovoltaic power generation of the photovoltaic power generation system, The grid electricity used to meet the building electrical load, The grid electricity used to meet the building air conditioning load, is the building air conditioning load, is the coefficient of performance of the air source heat pump; The amount of photovoltaic electricity used to meet the building's air conditioning load; To meet the total electricity load of the building, is the total electricity load of the building, is the amount of photovoltaic power generation connected to the grid, is the maximum limit of photovoltaic grid-connected power, The electricity consumed by photovoltaic power generation to drive the heat pump to store energy in the energy storage tank, is the maximum energy that can be stored in the energy storage tank, is the energy state of the energy storage tank at the previous moment, The amount of electricity wasted from photovoltaic power generation.

[0034] like Figure 4 As shown, in step S2 of this embodiment, the operation strategy of the building photovoltaic heat pump energy storage system in each time period is determined in combination with the working mode corresponding to the energy storage water tank, which means that the total building power load composed of equipment, lighting power and power used to drive the air source heat pump to meet the building air conditioning load is determined in combination with the working mode of the energy storage water tank. , building electrical load consisting of equipment and lighting electrical load To determine the operation strategy of the building photovoltaic heat pump energy storage system in each time period, including: When the working mode of the energy storage tank is to release energy, the operation strategy of the building photovoltaic heat pump energy storage system in each time period is determined as follows: Less than the total power load of the building , and photovoltaic power generation Less than building electrical load The operation strategy of the building photovoltaic heat pump energy storage system in each time period is determined according to the following formula: , , , , In photovoltaic power generation Less than the total power load of the building , and photovoltaic power generation Greater than or equal to the building electrical load The operation strategy of the building photovoltaic heat pump energy storage system in each time period is determined according to the following formula: , , , , In photovoltaic power generation Greater than or equal to the total power load of the building , and photovoltaic power generation Greater than or equal to the building electrical load The operation strategy of the building photovoltaic heat pump energy storage system in each time period is determined according to the following formula: , , , , , , in, The photovoltaic power generation used to meet the building electrical load, is the photovoltaic power generation of the photovoltaic power generation system, The grid electricity used to meet the building electrical load, The energy released by the energy storage tank to meet the building air conditioning load, The energy released by the energy storage tank, is the building air conditioning load, The grid electricity used to meet the building air conditioning load, is the coefficient of performance of the air source heat pump; The amount of photovoltaic electricity used to meet the building's air conditioning load; is the amount of photovoltaic power generation connected to the grid, is the maximum limit of photovoltaic grid-connected power, The photovoltaic power generation consumed by the heat pump to store energy in the energy storage tank is is the maximum energy that can be stored in the energy storage tank, is the stored energy of the energy storage tank at the previous moment, The amount of electricity wasted from photovoltaic power generation.

[0035] like Figure 5 As shown, in step S2 of this embodiment, the operation strategy of the building photovoltaic heat pump energy storage system in each time period is determined in combination with the working mode corresponding to the energy storage water tank, which means that the total building power load composed of equipment, lighting power and power used to drive the air source heat pump to meet the building air conditioning load is determined in combination with the working mode of the energy storage water tank. , building electrical load consisting of equipment and lighting electrical load To determine the operation strategy of the building photovoltaic heat pump energy storage system in each time period, including: When the working mode of the energy storage tank is energy storage, the operation strategy of the building photovoltaic heat pump energy storage system in each time period is determined as follows: Less than the total power load of the building , and photovoltaic power generation Less than building electrical load The operation strategy of the building photovoltaic heat pump energy storage system in each time period is determined according to the following formula: , , , , In photovoltaic power generation Less than the total power load of the building , and photovoltaic power generation Greater than or equal to the building electrical load The operation strategy of the building photovoltaic heat pump energy storage system in each time period is determined according to the following formula: , , , , In photovoltaic power generation Greater than or equal to the total power load of the building , and photovoltaic power generation Greater than or equal to the building electrical load When the building is in operation, the operation strategy of the photovoltaic heat pump energy storage system in each time period is first determined according to the following formula: , , , Then determine whether the energy storage state of the energy storage tank is less than the maximum storage capacity of the energy storage tank. If so, further determine the operation strategy of the building photovoltaic heat pump energy storage system in each time period according to the following formula: , Otherwise, the operation strategy of the building photovoltaic heat pump energy storage system in each time period is further determined according to the following formula: , , in, The photovoltaic power generation used to meet the building electrical load, is the photovoltaic power generation of the photovoltaic power generation system, The grid electricity used to meet the building electrical load, The grid electricity used to meet the building air conditioning load, is the building air conditioning load, is the coefficient of performance of the air source heat pump, The grid electricity is used to drive the air source heat pump to store energy in the energy storage tank. The energy stored in the energy storage tank, The maximum limit for power drawn from the grid; The amount of photovoltaic electricity used to meet the building's air conditioning load; The photovoltaic power generation consumed by the photovoltaic power generation to drive the heat pump to store energy in the energy storage tank; is the amount of photovoltaic power generation connected to the grid, The maximum limit of photovoltaic grid-connected power; Abandoned electricity from photovoltaic power generation.

[0036] The decision variable in this embodiment is the capacity of the energy storage tank. , and the power flow of the system during the whole year , , , , , , , , , , ,in: : Photovoltaic power generation used to meet the total power load of the building, kW; : Photovoltaic power generation, kW; : The amount of electricity consumed by photovoltaic power generation to drive the heat pump to store energy in the energy storage tank, kW; : The photovoltaic power generation used to meet the building electrical load (lighting, equipment electrical load), kW; : Photovoltaic power generation used to meet the building's electrical load, kW; : Grid power used to meet the building air conditioning load, kW; : Grid power used to meet the building electrical load (lighting, equipment load), kW; : Grid power used to drive the air source heat pump to store energy in the energy storage tank, kW; : The power released by the energy storage tank to meet the building air conditioning load, kW; : Energy stored in the energy storage tank, kW; : Energy released by the energy storage tank, kW.

[0037] The function expression for minimizing the total annual cost of the system in step S3 of this embodiment is: , in, To minimize, is the total annual cost of the system, is the annual investment cost of the energy storage tank, is the annual operating cost, is the annual maintenance cost, The replacement cost is assumed to be the same as the annual maintenance cost, assuming that the performance of the energy storage tank remains unchanged during its life cycle. and replacement costs , the annual maintenance cost and replacement costs Set to 0, with: , , in, is the volume of the energy storage tank, is the unit volume price of the energy storage tank, is the capital recovery rate, for The cost of purchasing electricity from the grid at all times, for The income from selling electricity to the grid at all times; and: , , , in, is the annual interest rate, which is 5% in this embodiment; is the life cycle of the project, which is 20 years in this embodiment. The grid electricity is used to drive the air source heat pump to store energy in the energy storage tank. The grid electricity is used to meet the building electrical load (lighting, equipment load), The grid electricity used to meet the building air conditioning load, To calculate the step length, in this embodiment, it is set to one hour. is the electricity purchase price (CNY), The electricity sales price (CNY).

[0038] The photovoltaic self-consumption rate SCR uses the photovoltaic self-consumption rate to reflect the local consumption capacity of photovoltaic power generation, which is defined as the ratio of the photovoltaic power generation directly used to the total power generation of the photovoltaic system. The maximization of the photovoltaic self-consumption rate is another objective function in this embodiment. The function expression of the maximum photovoltaic self-consumption rate in step S3 of this embodiment is: , in, represents maximization, is the photovoltaic self-consumption rate, The photovoltaic power generation used to meet the building electrical load, The photovoltaic power generation used to meet the building electrical load, The photovoltaic power generation consumed by the heat pump to store energy in the energy storage tank is is the photovoltaic power generation of the photovoltaic power generation system.

[0039] In step S3 of this embodiment, when the non-dominated genetic algorithm is used to solve the dual-objective optimization problem with the energy storage tank volume as the optimization object and the minimum system annual total cost and the maximum photovoltaic self-consumption rate as the optimization objectives to obtain the Pareto frontier of the system annual total cost and the photovoltaic self-consumption rate, the dual-objective optimization problem includes that the system satisfies the system power balance constraint and the energy storage tank operation constraint at each time step, and when the energy storage tank is storing energy, the function expression of the system power balance constraint is: , When the energy storage tank is discharged, the function expression of the system power balance constraint is: , Through the above system power balance constraint, it is possible to ensure that the energy supply and energy consumption of the building energy system are balanced, and the energy supply side and demand side of the building energy system are balanced. In this embodiment, the function expression of the energy storage tank operation constraint is: , , , in, is the total electricity load of the building, The energy stored in the energy storage tank, is the coefficient of performance of the air source heat pump, The photovoltaic power generation used to meet the building electrical load, To meet the photovoltaic power generation of the building air conditioning load, The grid electricity used to meet the building electrical load, The grid electricity used to meet the building air conditioning load, The grid electricity is used to drive the air source heat pump to store energy in the energy storage tank. The energy released by the energy storage tank; is the maximum energy that can be stored in the energy storage tank, is the maximum energy that the energy storage tank can release, is the volume of the energy storage tank, is the maximum volume limit of the energy storage tank. The system annual total operating cost is minimized and the system photovoltaic self-consumption rate is maximized as the optimization objectives. The capacity configuration and operation optimization of the building photovoltaic heat pump water storage system are optimized by dual objectives, and the non-dominated genetic algorithm (NSGA-Ⅱ) is used to solve the dual objective optimization problem to obtain the Pareto frontier of the system annual total cost and photovoltaic self-consumption rate. When carrying out multi-objective optimization, due to the conflict and incomparability between multiple objectives, a solution is the best in a certain objective, but may be the worst in other objectives. While improving any objective function, it is inevitable to weaken the solution of at least one other objective function to become a non-dominated solution or Pareto solution. A set of optimal solutions of a set of objective functions is called a Pareto optimal set, and the surface formed by the optimal set in space is called a Pareto frontier. In this embodiment, the non-dominated genetic algorithm is used to solve the dual objective optimization problem, and the optimal solution set of the two optimization objective functions of the minimum system annual total cost and the maximum photovoltaic self-consumption rate and the corresponding optimized volume of the energy storage tank can be obtained. The optimal solution set of the two optimization objective functions forms a Pareto frontier in space.

[0040] In step S4 of this embodiment, the annual system total cost and photovoltaic self-consumption rate in the Pareto front are normalized, and the optimal annual system total cost and photovoltaic self-consumption rate are selected using the Euclidean distance method. Normalization refers to changing a column of data to a fixed interval range, usually a decimal between [0,1] or (-1,1). It is mainly for the convenience of data processing, mapping the data to the range of 0-1 for processing, which is more convenient and faster. The conversion formula is: , in, x is the normalized value; For the first i Number; is the minimum value in the array; In this embodiment, the optimal solutions of the two optimization objective functions of minimizing the total annual system cost and maximizing the photovoltaic self-consumption rate are converted into dimensionless values ​​by normalization processing, so as to facilitate weighting and comparison of indicators in different units.

[0041] Euclidean distance is a commonly used distance definition, which refers to the real distance between two points in m-dimensional space, or the natural length of a vector (that is, the distance from the point to the origin). ) to the origin ( ) is calculated as: , in is the Euclidean distance from a point in two-dimensional space to the origin, is the horizontal coordinate value of the point, is the ordinate value of the point. A two-dimensional space is established based on the optimal solutions of the two optimization objective functions of the normalized total system cost and the photovoltaic self-consumption rate, with the photovoltaic self-consumption rate as the horizontal coordinate and the system annual total cost as the vertical coordinate. The optimal solutions of each group of system total cost and photovoltaic self-consumption rate are calculated respectively ( ) to the origin of the coordinate system ( ), the optimal solution combination of system total cost and photovoltaic self-consumption rate with the smallest Euclidean distance is selected as the optimal system annual total cost and photovoltaic self-consumption rate of the building photovoltaic energy storage system. The energy storage tank volume corresponding to the optimal solution combination is the design volume of the energy storage tank in this example.

[0042] In order to verify the capacity configuration and operation optimization method of the building photovoltaic heat pump energy storage system in this embodiment, a three-story office building in Changsha is used as a simulation case in this embodiment. The total building area is 1439.1m 2 , the main parameters of the building envelope are shown in Table 1. The Type56 module of TRNSYS software is used to calculate the building air-conditioning load. The input data includes meteorological data, building HVAC system design parameters, fresh air volume, indoor personnel, lighting and equipment use schedule, etc. The meteorological data are typical meteorological data of Changsha. The relevant parameters such as building HVAC system design parameters, fresh air volume, indoor personnel, building lighting, equipment power load, etc. refer to the "Public Building Energy Saving Design Standard" (GB 50189-2015). The building power load, such as lighting and equipment power load, is calculated using the unit area method, and the relevant setting parameters refer to the "Public Building Energy Saving Design Standard" (GB50189-2015). In this simulation case, the annual hourly power load and building air-conditioning load of the three-story office building are as follows Figure 6 The building envelope parameters are shown in Table 1.

[0043] Table 1 Building envelope parameters

[0044] In this simulation case, the photovoltaic power generation system of the three-story office building is installed on the roof of the building. The area of ​​the photovoltaic array is 476m 2 The Type94a module in TRNSYS software is used to calculate the annual power generation of the photovoltaic power generation system. The simulation results are as follows: Figure 7 As shown in Figure 2. Both retail electricity prices and on-grid electricity prices are time-of-use electricity prices, such as Figure 8 shown.

[0045] In this simulation case, the capacity configuration and operation optimization method of the building photovoltaic heat pump energy storage system of this embodiment is adopted. The energy storage tank volume is taken as the optimization object, and the minimum system annual total cost and the maximum photovoltaic self-consumption rate are taken as the optimization goals. The non-dominated genetic algorithm is used to solve the dual-objective optimization problem to obtain the Pareto frontier of the system annual total cost and the photovoltaic self-consumption rate. The system annual total cost and the photovoltaic self-consumption rate in the Pareto frontier are normalized, and the energy storage tank volume corresponding to the optimal system annual total cost and the photovoltaic self-consumption rate is selected by the Euclidean distance method as the design volume of the energy storage tank in the building photovoltaic heat pump energy storage system. Fig. 9 is the Pareto frontier of the annual total cost and photovoltaic self-consumption rate of the building photovoltaic heat pump energy storage system. Point P in the figure is the optimal system annual total cost and photovoltaic self-consumption rate selected by the Euclidean distance method. The corresponding energy storage tank capacity is the optimal energy storage tank capacity of the building photovoltaic heat pump energy storage system. The detailed data are: the optimal capacity of the energy storage tank is 15.9m 3 The total annual cost of the system is 54,858.7 yuan, and the system photovoltaic self-consumption rate is 78.3%.

[0046] Fig.10 The electric power flow of the building from August 1 to August 3 is shown below. The energy released by the energy storage tank to meet the building air conditioning load is converted into electrical power; The photovoltaic power generation system drives the air source heat pump to operate the electrical power to meet the building air conditioning load; The power required for photovoltaic power generation to meet the building's electrical load; The electric power taken from the grid to drive the air source heat pump to store energy in the energy storage tank; To draw electricity from the grid to drive the air source heat pump to meet the building air conditioning load; The electrical power taken from the power grid to meet the electrical load of the building. Fig.11 It is the power flow of the energy storage tank per hour. The energy stored in the energy storage tank, The energy released by the energy storage tank. The effectiveness of the method for capacity configuration and operation optimization of the building photovoltaic heat pump energy storage system in this embodiment is confirmed. It can be seen that the method for capacity configuration and operation optimization of the building photovoltaic heat pump energy storage system in this embodiment adopts a rule-based control strategy to simultaneously optimize the capacity configuration and operation of the building photovoltaic heat pump water energy storage system, with the minimum annual total cost of the system and the maximum photovoltaic self-consumption rate as the optimization goals, and uses a non-dominated genetic algorithm to solve the dual-objective optimization problem, which can obtain the optimal energy storage tank volume, reduce the cost of the energy storage tank while meeting the operation of the building photovoltaic heat pump energy storage system, and can improve the speed of solving the system configuration optimization problem, and has strong versatility.

[0047] In addition, this embodiment also provides a system for capacity configuration and operation optimization of a building photovoltaic heat pump energy storage system, including an interconnected microprocessor and a memory, wherein the microprocessor is programmed or configured to execute the method for capacity configuration and operation optimization of the building photovoltaic heat pump energy storage system.

[0048] In addition, this embodiment also provides a computer-readable storage medium, which stores a computer program or instruction, and the computer program or instruction is programmed or configured to execute the method for capacity configuration and operation optimization of the building photovoltaic heat pump energy storage system through a processor.

[0049] In addition, this embodiment also provides a computer program product, including a computer program or instructions, which are programmed or configured to execute the method for capacity configuration and operation optimization of the building photovoltaic heat pump energy storage system through a processor.

[0050] Those skilled in the art should understand that the technical solutions provided by the embodiments of the present application may be in the form of methods, systems, or computer program products. Therefore, the present application may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present application may take the form of a computer program product implemented on one or more computer-readable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program codes. The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the process Figure 1 A process or multiple processes and / or boxes Figure 1 These computer program instructions can also be stored in a computer-readable memory that can guide a computer or other programmable data processing device to work in a specific way, so that the instructions stored in the computer-readable memory produce a product including an instruction device, which implements the functions specified in the process. Figure 1 A process or multiple processes and / or boxes Figure 1These computer program instructions can also be loaded onto a computer or other programmable data processing device, so that a series of operation steps are executed on the computer or other programmable device to produce a computer-implemented process, so that the instructions executed on the computer or other programmable device provide for implementing the process in the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0051] The above is only a preferred embodiment of the present invention, and the protection scope of the present invention is not limited to the above embodiments. All technical solutions under the concept of the present invention belong to the protection scope of the present invention. It should be pointed out that for ordinary technicians in this technical field, some improvements and modifications without departing from the principle of the present invention should also be regarded as the protection scope of the present invention.

Claims

1. A method for capacity configuration and operation optimization of a building photovoltaic heat pump energy storage system, characterized in that: The steps include: S1, determining the working mode of the energy storage water tank corresponding to the time period according to the time-sharing electricity price, wherein the working mode corresponding to the energy storage water tank is one of discharging energy, storing energy and not working; S2, determine the operation strategy of the building photovoltaic heat pump energy storage system in each time period in combination with the corresponding working mode of the energy storage water tank; S3, based on the determined operation strategy of the building photovoltaic heat pump energy storage system, the energy storage tank volume is taken as the optimization object, the minimum system annual total cost and the maximum photovoltaic self-consumption rate are taken as the optimization goals, and the non-dominated genetic algorithm is used to solve the dual-objective optimization problem to obtain the Pareto frontier of the system annual total cost and the photovoltaic self-consumption rate; S4, normalize the system annual total cost and photovoltaic self-consumption rate in the Pareto frontier, and use the Euclidean distance method to select the optimal system annual total cost and photovoltaic self-consumption rate. The energy storage tank volume corresponding to the optimal system annual total cost and photovoltaic self-consumption rate is used as the design volume of the energy storage tank in the building photovoltaic heat pump energy storage system.

2. The method for capacity configuration and operation optimization of a building photovoltaic heat pump energy storage system according to claim 1, characterized in that: When determining the working mode of the energy-storage water tank for the corresponding time period according to the time-of-use electricity price, the time-of-use electricity price includes valley electricity price, flat electricity price and peak electricity price. Each day includes one valley electricity price, two flat electricity prices and two peak electricity prices. The working mode of the energy-storage water tank under the two peak electricity prices is to release energy. The working mode of the energy-storage water tank under the first flat electricity price is not to work, and the working mode of the energy-storage water tank under the second flat electricity price is to release energy. The working mode of the energy-storage water tank under the peak electricity price is to release energy, and the working mode of the energy-storage water tank under the valley electricity price is to store energy.

3. The method for capacity configuration and operation optimization of a building photovoltaic heat pump energy storage system according to claim 2, characterized in that: In step S2, the operation strategy of the building photovoltaic heat pump energy storage system in each time period is determined in combination with the working mode of the energy storage water tank. It refers to the total building power load composed of equipment, lighting power and power used to drive the air source heat pump to meet the building air conditioning load in combination with the working mode of the energy storage water tank. , building electrical load consisting of equipment and lighting electrical load To determine the operation strategy of the building photovoltaic heat pump energy storage system in each time period, including: When the energy storage tank is not working, the operation strategy of the building photovoltaic heat pump energy storage system in each time period is determined as follows: Less than the total power load of the building , and photovoltaic power generation Less than building electrical load The operation strategy of the building photovoltaic heat pump energy storage system in each time period is determined according to the following formula: ， ， ， In photovoltaic power generation Less than the total power load of the building , and photovoltaic power generation Greater than or equal to the building electrical load The operation strategy of the building photovoltaic heat pump energy storage system in each time period is determined according to the following formula: ， ， ， In photovoltaic power generation Greater than or equal to the total power load of the building , and photovoltaic power generation Greater than or equal to the building electrical load The operation strategy of the building photovoltaic heat pump energy storage system in each time period is determined according to the following formula: ， ， ， ， in, The photovoltaic power generation used to meet the building electrical load, is the photovoltaic power generation of the photovoltaic power generation system, The grid electricity used to meet the building electrical load, The grid electricity used to meet the building air conditioning load, is the building air conditioning load, is the coefficient of performance of the air source heat pump; The amount of photovoltaic electricity generated to meet the building's air conditioning load; To meet the total electricity load of the building, is the total electricity load of the building, is the amount of photovoltaic power generation connected to the grid, is the maximum limit of photovoltaic grid-connected power, The electricity consumed by photovoltaic power generation to drive the heat pump to store energy in the energy storage tank, is the maximum energy that can be stored in the energy storage tank, is the energy state of the energy storage tank at the previous moment, The amount of electricity wasted from photovoltaic power generation.

4. The method for capacity configuration and operation optimization of a building photovoltaic heat pump energy storage system according to claim 2, characterized in that: In step S2, the operation strategy of the building photovoltaic heat pump energy storage system in each time period is determined in combination with the working mode of the energy storage water tank. It refers to the total building power load composed of equipment, lighting power and power used to drive the air source heat pump to meet the building air conditioning load in combination with the working mode of the energy storage water tank. , building electrical load consisting of equipment and lighting electrical load To determine the operation strategy of the building photovoltaic heat pump energy storage system in each time period, including: When the working mode of the energy storage tank is to release energy, the operation strategy of the building photovoltaic heat pump energy storage system in each time period is determined as follows: Less than the total power load of the building , and photovoltaic power generation Less than building electrical load The operation strategy of the building photovoltaic heat pump energy storage system in each time period is determined according to the following formula: ， ， ， ， In photovoltaic power generation Less than the total power load of the building , and photovoltaic power generation Greater than or equal to the building electrical load The operation strategy of the building photovoltaic heat pump energy storage system in each time period is determined according to the following formula: ， ， ， ， In photovoltaic power generation Greater than or equal to the total power load of the building , and photovoltaic power generation Greater than or equal to the building electrical load The operation strategy of the building photovoltaic heat pump energy storage system in each time period is determined according to the following formula: ， ， ， ， ， ， in, The photovoltaic power generation used to meet the building electrical load, is the photovoltaic power generation of the photovoltaic power generation system, The grid electricity used to meet the building electrical load, The energy released by the energy storage tank to meet the building air conditioning load, The energy released by the energy storage tank, is the building air conditioning load, The grid electricity used to meet the building air conditioning load, is the coefficient of performance of the air source heat pump; The amount of photovoltaic electricity generated to meet the building's air conditioning load; is the amount of photovoltaic power generation connected to the grid, is the maximum limit of photovoltaic grid-connected power, The photovoltaic power generation consumed by the heat pump to store energy in the energy storage tank is is the maximum energy that can be stored in the energy storage tank, is the stored energy of the energy storage tank at the previous moment, The amount of electricity wasted from photovoltaic power generation.

5. The method for capacity configuration and operation optimization of a building photovoltaic heat pump energy storage system according to claim 2, characterized in that: In step S2, the operation strategy of the building photovoltaic heat pump energy storage system in each time period is determined in combination with the working mode of the energy storage water tank. It refers to the total building power load composed of equipment, lighting power and power used to drive the air source heat pump to meet the building air conditioning load in combination with the working mode of the energy storage water tank. , building electrical load consisting of equipment and lighting electrical load To determine the operation strategy of the building photovoltaic heat pump energy storage system in each time period, including: When the working mode of the energy storage tank is energy storage, the operation strategy of the building photovoltaic heat pump energy storage system in each time period is determined as follows: Less than the total power load of the building , and photovoltaic power generation Less than building electrical load The operation strategy of the building photovoltaic heat pump energy storage system in each time period is determined according to the following formula: ， ， ， ， In photovoltaic power generation Less than the total power load of the building , and photovoltaic power generation Greater than or equal to the building electrical load The operation strategy of the building photovoltaic heat pump energy storage system in each time period is determined according to the following formula: ， ， ， ， In photovoltaic power generation Greater than or equal to the total power load of the building , and photovoltaic power generation Greater than or equal to the building electrical load When the building is in operation, the operation strategy of the photovoltaic heat pump energy storage system in each time period is first determined according to the following formula: ， ， ， Then determine whether the energy storage state of the energy storage tank is less than the maximum storage capacity of the energy storage tank. If so, further determine the operation strategy of the building photovoltaic heat pump energy storage system in each time period according to the following formula: ， Otherwise, the operation strategy of the building photovoltaic heat pump energy storage system in each time period is further determined according to the following formula: ， ， in, The photovoltaic power generation used to meet the building electrical load, is the photovoltaic power generation of the photovoltaic power generation system, The grid electricity used to meet the building electrical load, The grid electricity used to meet the building air conditioning load, is the building air conditioning load, is the coefficient of performance of the air source heat pump, The grid electricity is used to drive the air source heat pump to store energy in the energy storage tank. The energy stored in the energy storage tank, The maximum limit for power drawn from the grid; The amount of photovoltaic electricity generated to meet the building's air conditioning load; The photovoltaic power generation consumed by the photovoltaic power generation to drive the heat pump to store energy in the energy storage tank; is the amount of photovoltaic power generation connected to the grid, The maximum limit of photovoltaic grid-connected power; Abandoned electricity from photovoltaic power generation.

6. The method for capacity configuration and operation optimization of a building photovoltaic heat pump energy storage system according to claim 2, characterized in that: The function expression for minimizing the total annual cost of the system in step S3 is: ， in, To minimize, is the total annual cost of the system, is the annual investment cost of the energy storage tank, is the annual operating cost, is the annual maintenance cost, is the replacement cost, and: ， ， in, is the volume of the energy storage tank, is the unit volume price of the energy storage tank, is the capital recovery rate, for The cost of purchasing electricity from the grid at all times, for Revenue from selling electricity to the grid at all times; The function expression for the maximum photovoltaic self-consumption rate in step S3 is: ， in, represents maximization, is the photovoltaic self-consumption rate, The photovoltaic power generation used to meet the building electrical load, The photovoltaic power generation used to meet the building electrical load, The photovoltaic power generation consumed by the heat pump to store energy in the energy storage tank is is the photovoltaic power generation of the photovoltaic power generation system.

7. The method for capacity configuration and operation optimization of a building photovoltaic heat pump energy storage system according to claim 6, characterized in that: In step S3, when the non-dominated genetic algorithm is used to solve the bi-objective optimization problem with the energy storage tank volume as the optimization object and the minimum system annual total cost and the maximum photovoltaic self-consumption rate as the optimization objectives to obtain the Pareto frontier of the system annual total cost and the photovoltaic self-consumption rate, the bi-objective optimization problem includes that the system satisfies the system power balance constraint and the energy storage tank operation constraint at each time step, and when the energy storage tank is storing energy, the function expression of the system power balance constraint is: ， When the energy storage tank is discharged, the function expression of the system power balance constraint is: ， The functional expression of the energy storage tank operation constraint is: ， ， ， in, is the total electricity load of the building, The energy stored in the energy storage tank, is the coefficient of performance of the air source heat pump, The photovoltaic power generation used to meet the building electrical load, To meet the photovoltaic power generation of the building air conditioning load, The grid electricity used to meet the building electrical load, The grid electricity used to meet the building air conditioning load, The grid electricity is used to drive the air source heat pump to store energy in the energy storage tank. The energy released by the energy storage tank; is the maximum energy that can be stored in the energy storage tank, is the maximum energy that the energy storage tank can release, is the volume of the energy storage tank, It is the maximum volume limit of the energy storage tank.

8. A system for capacity configuration and operation optimization of a building photovoltaic heat pump energy storage system, comprising an interconnected microprocessor and a memory, characterized in that: The microprocessor is programmed or configured to execute the method for capacity configuration and operation optimization of a building photovoltaic heat pump energy storage system as described in any one of claims 1 to 7.

9. A computer-readable storage medium having a computer program or instruction stored therein, characterized in that: The computer program or instruction is programmed or configured to execute the method for capacity configuration and operation optimization of a building photovoltaic heat pump energy storage system as described in any one of claims 1 to 7 through a processor.

10. A computer program product comprising a computer program or instructions, characterized in that The computer program or instruction is programmed or configured to execute the method for capacity configuration and operation optimization of a building photovoltaic heat pump energy storage system as described in any one of claims 1 to 7 through a processor.

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