A collaborative configuration method for microgrid units considering the mobility of phase change materials

Abstract

The present application relates to a method for collaborative configuration of microgrid cluster units that takes into account the mobility of phase change materials. Based on preset parameter constraints, the collaborative model of cooling and power supply equipment is optimized to obtain the minimum value of the collaborative model. The device capacity value of the cooling and power supply equipment corresponding to the minimum value of the collaborative model is used to determine the target device capacity of the cooling and power supply equipment in each park. The parameter constraints include transfer constraints that characterize the state of vehicle transfer of phase change materials. The collaborative model of cooling and power supply equipment includes the device capacity of cooling and power supply equipment in multiple parks. This method can reasonably configure the capacity of renewable energy generators and cold storage systems, thereby improving the park's surplus energy consumption rate.

Description

Technical Field

[0001] The present application relates to the field of energy planning, and in particular to a method for collaborative configuration of microgrid groups taking into account the mobility of phase change materials. Background Art

[0002] In order to promote industrial development and facilitate resource integration, large cities currently usually establish multiple industrial parks to develop the economy. Generally speaking, industrial parks have a large demand for electricity and are major electricity consumers in urban power grids. At the same time, due to the relatively high price of industrial load electricity, the electricity bills paid by the parks have always been high.

[0003] To reduce electricity costs, related technologies can be used to install small wind turbines, photovoltaic power generation units, and other renewable energy sources within the park, improving the economic efficiency of the park's electricity consumption through a "self-generated for self-use, with surplus energy connected to the grid." However, renewable energy generation is uncontrollable, and most of the time, the energy supply and demand within the park are out of balance. A considerable portion of renewable energy generation is connected to the grid at a lower price, requiring the park to coordinate the deployment of renewable energy generators and cold storage systems to achieve local consumption of surplus energy.

[0004] However, when realizing the coordinated configuration of the park, the capacity configuration of renewable energy generators and cold storage systems is not reasonable enough, resulting in a low absorption rate of surplus energy. Summary of the Invention

[0005] Based on this, it is necessary to provide a microgrid group unit collaborative configuration method that takes into account the mobility of phase change materials and can reasonably configure the capacity of renewable energy generators and cold storage systems to effectively consume the surplus energy in the park in response to the above technical problems.

[0006] In a first aspect, an embodiment of the present application provides a method for configuring installed capacity, the method comprising:

[0007] Based on preset parameter constraints, the cooling and power supply equipment collaborative model is optimized to obtain the minimum value of the cooling and power supply equipment collaborative model. The parameter constraints include transfer constraints, which represent the state of the vehicle transferring phase change materials. The cooling and power supply equipment collaborative model includes the installation capacity of the cooling and power supply equipment in multiple parks.

[0008] The target capacity of the cooling and power supply equipment in each park is determined by using the device capacity value of the cooling and power supply equipment corresponding to the minimum value of the cooling and power supply equipment coordination model.

[0009] In one embodiment, the parameter constraints further include phase change cold storage air conditioning operation constraints, phase change material energy storage constraints, and electric power exchange constraints; then, before optimizing the cold and electricity supply equipment collaborative model, the method further includes:

[0010] According to the spatial state characteristics of the vehicle when transferring phase change materials in each park, transfer constraints are established;

[0011] According to the working characteristics of the phase change cold storage air conditioner in each park, the operating constraints of the phase change cold storage air conditioner and the energy storage constraints of the phase change material are established;

[0012] According to the power exchange characteristics between the microgrid of each park and the external power grid, the power exchange constraint conditions are established;

[0013] Transfer constraints, phase change cold storage air conditioning operation constraints, phase change material energy storage constraints, and electric power exchange constraints are determined as parameter constraints.

[0014] In one embodiment, transfer constraints are constructed based on the spatial state characteristics of the vehicle when transferring phase change materials in each park, including:

[0015] Obtain vehicle location information when transferring phase change materials in various parks;

[0016] Based on the vehicle location information, analyze the spatial state characteristics of the vehicle when transferring phase change materials in each park;

[0017] According to the spatial state characteristics of the vehicle, transfer constraints are constructed.

[0018] In one embodiment, based on the operating characteristics of the phase change cold storage air conditioner in each park, operating constraints of the phase change cold storage air conditioner and energy storage constraints of the phase change material are established, including:

[0019] Obtaining operating parameters of the phase change cold storage air conditioner in each park; the operating parameters include at least one of the operating power of the phase change cold storage air conditioner, the electric cooling conversion efficiency of the operating power of the phase change cold storage air conditioner, the cooling load of each park, the energy storage of the phase change material in the phase change cold storage air conditioner, and the energy storage of the phase change material transferred by vehicles in each park within the park;

[0020] Based on the operating parameters of the phase-change cold storage air conditioners in each park, the operating characteristics of the phase-change cold storage air conditioners in each park are analyzed to obtain the cold supply balance relationship of each park; based on the operating parameters of the phase-change cold storage air conditioners in each park, the operating characteristics of the phase-change material energy storage in each park are analyzed to obtain the energy storage balance relationship of the phase-change material in each park;

[0021] Based on the cold supply balance relationship of each park, the operating constraints of phase change cold storage air conditioners are constructed; based on the energy storage balance relationship, the energy storage constraints of phase change materials are constructed.

[0022] In one embodiment, based on the power exchange characteristics between the microgrid of each park and the external power grid, power exchange constraints are established, including:

[0023] Obtaining electric power exchange parameters between the microgrid of each park and the external power grid; the electric power exchange parameters include at least one of the wind turbine power generation of each park, the photovoltaic power generation of each park, the phase change cold storage air conditioning operating power of each park, and the electric load of each park;

[0024] According to the electric power exchange parameters between the microgrid of each park and the external power grid, the electric power exchange characteristics of the microgrid of each park and the external power grid are analyzed to obtain the power supply balance relationship of each park;

[0025] Based on the power supply balance relationship of each park, the power exchange constraint conditions are constructed.

[0026] In one embodiment, obtaining the wind turbine power generation and photovoltaic power generation of each park includes:

[0027] Based on the wind turbine power generation formula and the wind speed values ​​of each park in the historical time period, the unit power generation of each wind turbine in each park is obtained; and based on the photovoltaic power generation formula and the sunshine intensity values ​​of each park in the historical time period, the unit power generation of each photovoltaic in each park is obtained;

[0028] Based on the preset initial installed capacity of wind turbines in each park and the unit power generation of each wind turbine in each park, the wind turbine power generation of each park is obtained; and based on the preset initial installed capacity of photovoltaic power in each park and the unit power generation of each photovoltaic in each park, the photovoltaic power generation of each park is obtained.

[0029] In one embodiment, the process of constructing a collaborative model for cooling and power supply equipment includes:

[0030] Based on the coordinated planning strategy of cooling and electricity supply equipment in each park, the average annual investment cost and operating cost of each park are determined; the average annual investment cost of each park includes the average annual investment cost of fans, photovoltaics, vehicles and phase change cold storage air conditioners in each park, and the average annual operating cost of each park includes electricity purchase cost, electricity sales cost and vehicle transfer cost.

[0031] Determine the cooling and electricity supply equipment coordination model based on the average annual investment cost and operating cost of each park.

[0032] In one embodiment, before determining the average annual operating cost of each park, the following steps are further included:

[0033] The unit power generation of each wind turbine in each park, the unit power generation of each photovoltaic unit in each park, the electric load in each park, and the cooling load in each park in the historical time period are reduced to the target time period through scenarios to obtain the corresponding reduction data in the target time period;

[0034] Determine the average annual operating cost of each park based on the reduction data.

[0035] In one embodiment, the parameter constraints also include phase change cold storage air conditioning operation constraints, phase change material energy storage constraints, and electric power exchange constraints. Accordingly, based on the preset parameter constraints, the cooling and electricity supply equipment collaborative model is optimized to obtain the minimum value of the cooling and electricity supply equipment collaborative model, including:

[0036] Obtain the initial installed capacity of cooling and power supply equipment in each park;

[0037] With transfer constraints and power exchange constraints as the constraints, the average annual operating cost of each park is obtained based on the initial installation capacity of the cooling and power supply equipment in each park and the power exchange cost between parks.

[0038] Taking the operation constraints of phase change cold storage air conditioner and the energy storage constraints of phase change materials as constraints, according to the initial installation capacity of the cooling and power supply equipment in each park and the average annual operation cost of each park, the genetic algorithm is used to solve the cooling and power supply equipment coordination model to obtain the minimum value of the cooling and power supply equipment coordination model.

[0039] In a second aspect, an embodiment of the present application provides an installed capacity configuration device, the device comprising:

[0040] An optimization module is used to optimize the cooling and power supply equipment collaborative model based on preset parameter constraints to obtain the minimum value of the cooling and power supply equipment collaborative model; the parameter constraints include transfer constraints, which represent the state of the vehicle transferring phase change materials; the cooling and power supply equipment collaborative model includes the device capacity of the cooling and power supply equipment in multiple parks;

[0041] The determination module is used to determine the target device capacity of the cooling and power supply equipment in each park by using the device capacity value of the cooling and power supply equipment corresponding to the minimum value of the cooling and power supply equipment coordination model.

[0042] In a third aspect, an embodiment of the present application provides a computer device comprising a memory and a processor, wherein the memory stores a computer program, and the processor implements the steps of the method provided in any embodiment of the first aspect when executing the computer program.

[0043] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the method provided in any embodiment of the first aspect above.

[0044] The embodiment of the present application provides a method for collaborative configuration of microgrid cluster units that takes into account the mobility of phase change materials. The method optimizes the collaborative model of cooling and power supply equipment based on preset parameter constraints to obtain the minimum value of the collaborative model of cooling and power supply equipment. The parameter constraints include transfer constraints, and the device capacity value of the cooling and power supply equipment corresponding to the minimum value of the collaborative model of cooling and power supply equipment is used to determine the target device capacity of the cooling and power supply equipment in each park. In this method, the transfer constraint represents the state of vehicle transfer of phase change materials. Since phase change materials can store surplus energy in a park, and the transfer of phase change materials by vehicles can transfer surplus energy within a park to other parks, energy sharing among multiple parks can be achieved, which can improve the absorption rate of surplus energy in the parks. By obtaining the minimum value of the collaborative model of cooling and power supply equipment, the target device capacity of cooling and power supply equipment in each park is determined, and the reasonable configuration of the capacity of renewable energy generators and cold storage systems is achieved. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] Figure 1 A diagram illustrating an application environment of an installed capacity configuration method in one embodiment;

[0046] Figure 2 A schematic flow chart of an installed capacity configuration method in one embodiment;

[0047] Figure 3 is a flow chart of an installed capacity configuration method in another embodiment;

[0048] Figure 4 is a flow chart of an installed capacity configuration method in another embodiment;

[0049] Figure 5 is a flow chart of an installed capacity configuration method in another embodiment;

[0050] Figure 6 is a flow chart of an installed capacity configuration method in another embodiment;

[0051] Figure 7 is a flow chart of an installed capacity configuration method in another embodiment;

[0052] Figure 8 is a flow chart of an installed capacity configuration method in another embodiment;

[0053] Figure 9 is a flow chart of an installed capacity configuration method in another embodiment;

[0054] Figure 10 A schematic diagram of data changes in an installed capacity configuration method in one embodiment;

[0055] Figure 11A schematic diagram of data changes in an installed capacity configuration method in another embodiment;

[0056] Figure 12 is a flow chart of an installed capacity configuration method in another embodiment;

[0057] Figure 13 A schematic diagram of data changes in an installed capacity configuration method in another embodiment;

[0058] Figure 14 A schematic diagram of data changes in an installed capacity configuration method in another embodiment;

[0059] Figure 15 A schematic diagram of data changes in an installed capacity configuration method in another embodiment;

[0060] Figure 16 is a flow chart of an installed capacity configuration method in another embodiment;

[0061] Figure 17 It is a structural block diagram of an installed capacity configuration device in one embodiment;

[0062] Figure 18 FIG. 1 is a diagram showing the internal structure of a computer device in one embodiment. DETAILED DESCRIPTION

[0063] In order to make the purpose, technical solutions and advantages of this application more clear, the following further describes this application in detail with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain this application and are not intended to limit this application.

[0064] The installed capacity configuration method provided in this application can be applied to computer devices, which can be devices in any field, such as various personal computers, laptops, tablet computers, wearable devices, terminal devices, etc. The embodiments of this application do not limit the type of computer devices. Figure 1 As shown, a schematic diagram of the internal structure of a computer device is provided. Figure 1 The processor is used to provide computing and control capabilities. The memory includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operation of the operating system and computer program in the non-volatile storage medium. The database is used to store data related to the table cell group interchange process. The network interface is used to communicate with other external devices via a network connection. When executed by the processor, the computer program implements a method for configuring installed capacity.

[0065] One approach involves synergizing renewable energy generators and energy storage batteries within a park to consume surplus energy locally. However, these batteries suffer from significant lifespan degradation while absorbing excess energy. Furthermore, their high price makes operating them in a park highly likely to be cost-prohibitive. Therefore, this strategy is unwise.

[0066] Another approach is to use cold / heat storage technology to absorb renewable energy generation energy. Industrial parks can optimize air-conditioning loads to absorb renewable energy generation energy, while storing excess cold / heat energy in building walls with lower enthalpy values. However, traditional cold / heat storage materials have a small specific heat capacity, and the energy storage capacity of the cold / heat storage systems developed based on them is extremely limited, making them less effective in absorbing excess energy from renewable energy generation.

[0067] There is another way. Phase change materials are applied to cold / heat storage systems due to their advantages such as low cost and large heat capacity. However, the existing technology is to fix the phase change materials in the composite phase change energy storage system inside the wall. Once the configuration is completed, the phase change material reserves cannot be adjusted. There is no direct connection between urban park microgrids. Any park microgrid can only independently configure the capacity of wind turbines, photovoltaics and phase change energy storage systems, and cannot cooperate with other park microgrids to coordinate the configuration of renewable energy generators and phase change cold storage system capacity.

[0068] Based on this, an embodiment of the present application provides a method for collaboratively configuring microgrid groups that takes into account the mobility of phase change materials, which can reasonably configure the capacity of renewable energy generators and cold storage systems, thereby improving the absorption rate of surplus energy in the park.

[0069] The following will explain in detail the technical solution of the present application and how the technical solution of the present application solves the above-mentioned technical problems through embodiments and in combination with the accompanying drawings. The following specific embodiments can be combined with each other, and the same or similar concepts or processes may not be repeated in some embodiments. It should be noted that the installed capacity configuration method provided by the present application can be executed by a computer device or an installed capacity configuration device, which can be implemented as part or all of the processor through software, hardware, or a combination of software and hardware. Obviously, the described embodiments are part of the embodiments of the present application, not all of the embodiments.

[0070] In one embodiment, Figure 2 As shown, a method for configuring installed capacity is provided. This embodiment involves optimizing a cooling and power supply equipment coordination model based on preset parameter constraints, obtaining a minimum value of the cooling and power supply equipment coordination model, and determining a target device capacity of cooling and power supply equipment in each park using the device capacity value of the cooling and power supply equipment corresponding to the minimum value of the cooling and power supply equipment coordination model. This embodiment includes the following steps:

[0071] S201, according to preset parameter constraints, optimize the cold and power supply equipment collaborative model to obtain the minimum value of the cold and power supply equipment collaborative model; the parameter constraints include transfer constraints, and the transfer constraints represent the state of the vehicle transferring phase change material; the cold and power supply equipment collaborative model includes the installation capacity of the cold and power supply equipment in multiple parks.

[0072] Cooling and power supply equipment includes renewable energy units and energy storage systems. Renewable energy units include coal-fired units, hydropower units, wind turbines, solar power units, and nuclear power units. Renewable energy refers to energy sources that can be continuously utilized and recycled in nature, such as solar energy, wind energy, hydropower, biomass energy, ocean energy, tidal energy, and geothermal energy. A renewable energy unit refers to a unit composed of several renewable energy sources that can collectively generate electricity. An energy storage system, also known as an energy storage system, acts like a giant "power bank," storing excess thermal, kinetic, electrical, potential, and chemical energy. This system can change the output capacity, location, and timing of energy, effectively utilizing energy and improving its efficiency. The fundamental task of an energy storage system is to overcome the temporal or local disparity between energy supply and demand. Energy storage systems include mechanical, electrical, electrochemical, thermal, and chemical storage.

[0073] Parameter constraints include transfer constraints, which represent the state of the vehicle's phase change material transfer. The cooling and power supply equipment coordination model includes the capacity of cooling and power supply equipment across multiple campuses. The capacity represents the total rated effective power of the installed generator sets.

[0074] In one embodiment, based on the planning strategy of cooling and electricity supply equipment in an urban park, parameter constraints and a cooling and electricity supply equipment collaborative model are established, and the model is optimized to obtain the minimum value of the cooling and electricity supply equipment collaborative model. The optimization method can be implemented through a pre-trained neural network model. For example, the parameter constraints and the cooling and electricity supply equipment collaborative model are used as inputs of the pre-trained neural network model, and the minimum value of the cooling and electricity supply equipment collaborative model can be directly output after passing through the neural network model.

[0075] Phase change materials (PCMs) are materials that change state while maintaining constant temperature and can generate latent heat. The process of changing physical properties is called a phase change, during which the PCM absorbs or releases a significant amount of latent heat. For example, when heated to its melting point, a phase change occurs from solid to liquid. During the melting process, the PCM absorbs and stores a significant amount of latent heat. When the PCM cools, this stored heat must be dissipated into the surrounding environment within a certain temperature range, undergoing the reverse phase change from liquid to solid. The energy stored or released during these two phase changes is called the latent heat of the phase change. During the physical state change, the material's temperature remains nearly constant until the phase change is complete, forming a wide temperature plateau. Despite the constant temperature, the latent heat absorbed or released is considerable. For example, water, a PCM, changes from liquid to solid (freezes) when the temperature drops to 0°C. When the temperature is above 0℃, water changes from solid to liquid (dissolves); it absorbs and stores a large amount of cold energy during the freezing process, and absorbs a large amount of heat energy during the melting process. The larger the amount (volume) of ice, the longer the melting process takes.

[0076] S202 , determining the target device capacity of the cooling and electricity supply equipment in each park using the device capacity value of the cooling and electricity supply equipment corresponding to the minimum value of the cooling and electricity supply equipment coordination model.

[0077] The device capacity of the cooling and electricity supply equipment corresponding to the minimum value of the cooling and electricity supply equipment coordination model obtained according to the above embodiment is determined as the target device capacity of the cooling and electricity supply equipment in each park.

[0078] In one embodiment, taking two parks A and B, where the cooling and power supply equipment is a wind turbine and an electrical energy storage device as an example, according to the above embodiment, the device capacity of the cooling and power supply equipment corresponding to the minimum value of the cooling and power supply equipment coordination model is determined to be 50KW and 40KW for the wind turbine and the electrical energy storage device of Park A, and 60KW and 45KW for the wind turbine and the electrical energy storage device of Park B. Then, the target device capacity of the cooling and power supply equipment in each park can be determined as follows: the wind turbine and the electrical energy storage device of Park A are 50KW and 40KW respectively, and the wind turbine and the electrical energy storage device of Park B are 60KW and 45KW respectively.

[0079] The embodiment of the present application provides a method for configuring installed capacity. According to preset parameter constraints, the cold power supply equipment coordination model is optimized to obtain the minimum value of the cold power supply equipment coordination model. The parameter constraints include transfer constraints, and the device capacity value of the cold power supply equipment corresponding to the minimum value of the cold power supply equipment coordination model is used to determine the target device capacity of the cold power supply equipment in each park. In this method, the transfer constraint represents the state of the vehicle transferring phase change material. Since the phase change material can store the surplus energy of the park, and the vehicle transfers the phase change material to transfer the surplus energy in the park to other parks, energy sharing among multiple parks is achieved, which can improve the consumption rate of the surplus energy in the park. By obtaining the minimum value of the cold power supply equipment coordination model, the target device capacity of the cold power supply equipment in each park is determined, and the reasonable configuration of the capacity of the renewable energy generator set and the cold storage system is achieved.

[0080] In one embodiment, the parameter constraints also include phase change cold storage air conditioning operation constraints, phase change material energy storage constraints, and electric power exchange constraints; then, before optimizing the cold and electricity supply equipment collaborative model, the following steps are also included:

[0081] S301: Construct transfer constraints based on the spatial state characteristics of the vehicle when transferring phase change materials in each park.

[0082] Phase change materials are actively used in cold / heat storage systems due to their low cost and large heat capacity. Among them, applying phase change materials to cold storage air conditioners to form phase change cold storage air conditioners not only realizes large-scale cold storage, but also can flexibly adjust the operating power, and has the potential for demand-side response.

[0083] In one embodiment, a phase change material-based cold storage air conditioner is installed in each park to form a phase change cold storage air conditioner, and vehicles are used to transfer the phase change materials in the phase change cold storage air conditioner in each park. Taking two parks A and B as an example, the spatial state characteristics of the vehicles when transferring the phase change materials in each park can be divided into four types: on the road from park A to park B, on the road from park B to park A, in park A and in park B. Based on these four characteristics, transfer constraints can be constructed.

[0084] S302: Constructing operation constraints of the phase change cold storage air conditioner and energy storage constraints of the phase change material according to the operating characteristics of the phase change cold storage air conditioner in each park.

[0085] Cold storage air conditioning is an energy storage device and the main component of the cold storage air conditioning system. The air conditioning refrigeration equipment uses the low point of night to cool the air and stores the cold energy in the form of cold water or solidified phase change materials. During the peak load period of air conditioning, the stored cold energy is partially or fully used to supply cooling to the air conditioning system, so as to achieve the purpose of reducing the installed capacity of the refrigeration equipment, reducing operating costs and shaving the peak and filling the valley of electricity load.

[0086] Phase-change materials are installed in a cold storage air conditioner to form a phase-change cold storage air conditioner. The phase-change cold storage air conditioner has the following operating characteristics: it includes refrigerator 1, refrigerator 2, and a cooler. Based on the operating characteristics of the phase-change cold storage air conditioner, operating constraints for the phase-change cold storage air conditioner and energy storage constraints for the phase-change materials are established.

[0087] S303: Construct power exchange constraint conditions based on the power exchange characteristics between the microgrid of each park and the external power grid.

[0088] A microgrid, also known as a microgrid, is a network consisting of multiple distributed power sources and their associated loads in a specific topological structure, connected to the conventional power grid via static switches. A microgrid is a small power generation and distribution system that integrates distributed power sources, energy storage devices, energy conversion devices, associated loads, and monitoring and protection devices. It is an autonomous system capable of self-control, protection, and management. It can operate in parallel with an external grid or in isolation, making it a key component of the smart grid.

[0089] In one embodiment, the microgrid of each park can represent a small power generation and distribution system composed of the cooling power supply equipment of each park, and the power exchange constraint conditions are constructed according to the power exchange characteristics between the microgrid of each park and the external power grid.

[0090] S304 , determining the transfer constraint conditions, the phase change cold storage air conditioner operation constraint conditions, the phase change material energy storage constraint conditions, and the electric power exchange constraint conditions as parameter constraint conditions.

[0091] The transfer constraints, phase change cold storage air conditioner operation constraints, phase change material energy storage constraints, and electric power exchange constraints obtained in the above embodiment are determined as parameter constraints.

[0092] The present application provides an installed capacity configuration method that constructs transfer constraints based on the spatial state characteristics of vehicles as they transfer phase-change materials within each park. It also constructs phase-change cold storage air conditioner operation constraints and phase-change material energy storage constraints based on the operating characteristics of the phase-change cold storage air conditioner within each park. It also constructs power exchange constraints based on the power exchange characteristics between each park's microgrid and the external power grid. The transfer constraints, phase-change cold storage air conditioner operation constraints, phase-change material energy storage constraints, and power exchange constraints are then determined as parameter constraints. In this method, determining the parameter constraints enables the rational configuration of renewable energy generators and cold storage system capacities, improving the absorption rate of surplus energy within the park.

[0093] Based on the spatial state characteristics of the vehicle when transferring phase change materials in each park in the previous embodiment, the transfer constraint condition is constructed, and this is described in detail through an embodiment below. In one embodiment, if Figure 4As shown, according to the spatial state characteristics of the vehicle when transferring phase change materials in each park, the transfer constraint conditions are constructed, including the following steps:

[0094] S401, obtaining vehicle position information when a vehicle is transferring phase change materials in each park.

[0095] The vehicle position information of the vehicle when transferring the phase change material in each park represents the spatiotemporal position information of the vehicle in each park. The vehicle can be within each park or on the road between parks.

[0096] In one embodiment, the method for obtaining the vehicle position information when the vehicle transfers the phase change material in each park can be to monitor the vehicle position in real time, or to obtain the vehicle position information when the vehicle transfers the phase change material in each park based on the position mark.

[0097] S402 , analyzing the spatial state characteristics of the vehicle when the vehicle transfers the phase change material in each park based on the vehicle position information.

[0098] Based on the vehicle position information of the above embodiment, the spatial state characteristics of the vehicle when the vehicle transfers the phase change material in each park are analyzed.

[0099] In one embodiment, taking two parks i and j as an example, the vehicle's location information includes: on the road from park i to j, on the road from park j to park i, in park i, and in park j. If the vehicle's travel time from park i to j is T, then the vehicle's spatial state characteristics when transferring phase change material in each park include: if the vehicle is in park i at time t, then the vehicle arrives at park j at time t+T, and during time t+T, the vehicle is on the road from park i to park j.

[0100] S403: Construct transfer constraints based on the spatial state characteristics of the vehicle.

[0101] Alternatively, taking two parks as an example, transfer constraints are constructed based on the spatial state characteristics of the vehicles in the above embodiment. The constructed constraints can be expressed as:

[0102]

[0103]

[0104] H ij,t+1 +H jj,t+1 ≥H ij,t (3)

[0105] H ii,T =H ii,0 (4)

[0106] Among them, H ij,t: vehicle spatiotemporal position flag, a value of 1 indicates that the vehicle is on the road from park i to park j, while a value of 0 indicates that the vehicle is not on the corresponding road; H ii,t =1: indicates that the vehicle is in the spatial position of park i, while 0 indicates that the vehicle is not in the corresponding park; T ij It represents the travel time of a vehicle from park i to park j; T is the scheduling cycle time.

[0107] Formula (1) indicates that no matter where the vehicle is in time and space, it can only be in one time and space position.

[0108] Formula (2) represents the time constraint of the vehicle in the park. If the vehicle is in park i at time t, H ii,t =1, then at t+T ij At this moment, the vehicle is in the park, If the vehicle is not in park i at time t, H ii,t = 0, then the vehicle may be on the road from park i to park j at time t, or on the road from park j to park i, or may be in park j at time t+T ij At this moment, the vehicle is in the park, or 0.

[0109] Formula (3) represents the constraints on the vehicle on the road to and from the park. If the vehicle is on the road from park i to park j at time t, then at time t+1, the vehicle may have arrived at park j or still be on the road from park i to park j. If the vehicle is not on the road from park i to park j at time t, the vehicle may be in park i, park j, or on the road from park j to park i. Then, at time t+1, the vehicle may be on the road from park i to park j, in park j, on the road from park j to park i, or in park i.

[0110] The present application provides a method for configuring installed capacity. This method obtains vehicle position information as it transfers phase-change materials between various industrial parks. Based on this information, it analyzes the spatial state characteristics of the vehicles as they transfer phase-change materials between the various industrial parks. Transfer constraints are then established based on these spatial state characteristics. This method, by establishing transfer constraints, enables the rational allocation of renewable energy generators and cold storage systems, improving the utilization rate of surplus energy within the industrial park.

[0111] Based on the previous implementation, according to the working characteristics of the phase change material air conditioner in each park, the phase change cold storage air conditioner operation constraints and the phase change material energy storage constraints are constructed. The following is a detailed description of this through an embodiment. In one embodiment, if Figure 5As shown, according to the working characteristics of the phase change cold storage air conditioner in each park, the operation constraints of the phase change cold storage air conditioner and the energy storage constraints of the phase change material are constructed, including the following steps:

[0112] S501, obtaining the operating parameters of the phase change cold storage air conditioner in each park; the operating parameters include at least one of the operating power of the phase change cold storage air conditioner, the electric cooling conversion efficiency of the operating power of the phase change cold storage air conditioner, the cooling load of each park, the energy storage of the phase change material in the phase change cold storage air conditioner, and the energy storage of the phase change material transferred by vehicles in each park within the park.

[0113] Obtain the operating parameters of the phase-change cold storage air conditioner in each park; the operating parameters include the operating power of the phase-change cold storage air conditioner, the electric-to-cold conversion efficiency of the phase-change cold storage air conditioner's operating power, the cooling load of each park, the energy stored in the phase-change material of the phase-change cold storage air conditioner, and the energy stored in the phase-change material of each park transferred by vehicles within the park. The operating power of the phase-change cold storage air conditioner includes the operating power of phase-change cold storage air conditioner refrigeration machine 1, the operating power of phase-change cold storage air conditioner refrigeration machine 2, and the operating power of the phase-change cold storage air conditioner's refrigeration release machine; the electric-to-cold conversion efficiency of the phase-change cold storage air conditioner's operating power includes the electric-to-cold conversion efficiency of phase-change cold storage air conditioner refrigeration machine 1, the electric-to-cold conversion efficiency of phase-change cold storage air conditioner refrigeration machine 2, and the electric-to-cold conversion efficiency of phase-change cold storage air conditioner's refrigeration release machine.

[0114] In one embodiment, the operating parameters of the phase-change cold storage air conditioner in each park are obtained. The operating power of the phase-change cold storage air conditioner can be obtained through sensors, and the electric-cooling conversion efficiency of the operating power of the phase-change cold storage air conditioner can be obtained based on historical data; the cooling load of each park can be obtained based on the local meteorological station or each park; the energy storage of the phase change material in the phase change cold storage air conditioner and the energy storage of the phase change material transferred by vehicles in each park within its respective park can be obtained through real-time data calculation.

[0115] S502: Analyze the operating characteristics of the phase change cold storage air conditioner in each park based on the operating parameters of the phase change cold storage air conditioner in each park to obtain the cold supply balance relationship of each park; analyze the operating characteristics of the phase change material energy storage in each park based on the operating parameters of the phase change cold storage air conditioner in each park to obtain the energy storage balance relationship of the phase change material in each park.

[0116] According to the operating parameters of the phase change cold storage air conditioners in each park, the working characteristics of the phase change material air conditioning operation in each park are analyzed, and the cold supply balance relationship of each park is obtained; according to the operating parameters of the phase change cold storage air conditioners in each park, the working characteristics of the phase change material energy storage in each park are analyzed, and the energy storage balance relationship of the phase change material in each park is obtained.

[0117] The working characteristics of the phase change material air conditioning in each park are that the refrigerator 1 in the phase change cold storage air conditioning directly supplies cold energy to the load, the refrigerator 2 can store the produced cold energy in the phase change material, and the refrigerator releases the stored energy of the phase change material to supply the load.

[0118] The operating power of a PCC AC is the sum of the operating power of chiller 1, chiller 2, and the cooling unit. Since chiller 1 directly cools the load, the cooling unit releases the energy stored in the phase-change material to supply the load. Therefore, the cooling load supplied by chiller 1, the energy supplied by the phase-change material to the cooling unit, and the cooling load of each park form a cooling supply balance.

[0119] The operating characteristics of the phase-change material energy storage in each park are that Chiller 2 stores the cold energy it produces in the phase-change material, while the refrigeration discharger releases the stored energy in the phase-change material. The phase-change material's energy storage also comes from energy transferred from the phase-change material via vehicles. Therefore, the phase-change material's current energy storage balance is formed by the remaining energy stored in the phase-change material at the previous moment, the cold energy produced by Chiller 2, the energy released by the refrigeration discharger, and the energy transferred from the phase-change material via vehicles.

[0120] S503, constructing the phase change cold storage air conditioner operation constraint conditions based on the cold supply balance relationship of each park; and constructing the phase change material energy storage constraint conditions based on the energy storage balance relationship.

[0121] In one embodiment, based on the cooling supply balance relationship of each park obtained above, operating constraints of the phase change cold storage air conditioner are constructed. The constraints can be expressed as:

[0122]

[0123]

[0124]

[0125]

[0126]

[0127] in, and are the operating power and rated power of refrigerator 1 respectively; and are the operating power and rated power of refrigerator 2 respectively; and are the operating power and rated power of the refrigeration machine respectively; η MC,c1 and η MC,d Respectively represent the electrical cooling conversion efficiency of refrigerator 1 and the electrical cooling conversion efficiency of refrigeration machine 1. MC,c1=2.8,η MC,d =42.5.

[0128] In one embodiment, based on the energy storage balance relationship of each park obtained above, energy storage constraints of the phase change material are constructed. The constraints can be expressed as:

[0129] -H ii,t Q N ≤Q i,t ≤H ii,t Q N (10)

[0130]

[0131]

[0132]

[0133] in, represents the phase change material energy storage of park i at time t; Q i,t represents the energy storage of the phase change material when the vehicle is loaded and unloaded at the park i at time t; Q N Indicates the maximum capacity of a vehicle for loading and unloading phase change materials at a single time; η MC,c2 represents the working efficiency of refrigerator 2; ξ MC It represents the cold storage retention rate of the phase change material considering the cold leakage factor; Indicates the rated energy storage of the phase change cold storage air conditioner, Usually half of the rated energy storage of the phase change cold storage air conditioner. MC,c2 =4.2,ξ MC =0.999.

[0134] An embodiment of the present application provides a method for configuring installed capacity. The method obtains the operating parameters of each park's phase-change cold storage air conditioner, analyzes the operating characteristics of the phase-change cold storage air conditioner in each park based on the operating parameters of the phase-change cold storage air conditioner in each park, and obtains the cooling supply balance relationship of each park. The method also analyzes the operating characteristics of the phase-change material energy storage in each park based on the operating parameters of the phase-change cold storage air conditioner in each park, and obtains the energy storage balance relationship of the phase-change material in each park. Based on the cooling supply balance relationship of each park, operating constraints for the phase-change cold storage air conditioner are constructed. Based on the energy storage balance relationship, energy storage constraints for the phase-change material are constructed. In this method, operating constraints for the phase-change cold storage air conditioner and energy storage constraints for the phase-change material are constructed using at least one of the operating power of the phase-change cold storage air conditioner, the electric-to-cooling conversion efficiency of the operating power of the phase-change cold storage air conditioner, the cooling load of each park, the energy storage of the phase-change material in the phase-change cold storage air conditioner, and the energy storage of the phase-change material in each park transferred by vehicles within the park. This method enables reasonable configuration of the capacity of renewable energy generators and cooling storage systems, thereby improving the absorption rate of surplus energy in the park.

[0135] Based on the power exchange characteristics of the microgrids of each park and the external power grid in the previous embodiment, the power exchange constraint conditions are constructed. The following is a detailed description of this through an embodiment. In one embodiment, Figure 6 As shown in FIG, based on the electric power exchange characteristics between the microgrid of each park and the external power grid, the electric power exchange constraint conditions are constructed, including the following steps:

[0136] S601, obtain the electric power exchange parameters between the microgrid of each park and the external power grid; the electric power exchange parameters include at least one of the wind turbine power generation power of each park, the photovoltaic power generation power of each park, the phase change cold storage air conditioning operating power of each park, and the electric load of each park.

[0137] Obtain electric power exchange parameters between the microgrid of each park and the external power grid; the electric power exchange parameters include at least one of the wind turbine power generation power of each park, the photovoltaic power generation power of each park, the air conditioning operating power of each park, and the electric load of each park.

[0138] In one embodiment, a data set D of wind speed, sunshine intensity, power load, and cooling load for the past 365 days is obtained from a local weather station and industrial park i (i=1, 2, ..., I), as shown in the following formula:

[0139]

[0140] Among them, u t and G t represent the wind speed and light intensity at time t (t=1,2,…,T) respectively; and They represent the electric load and cooling load of park i at time t respectively.

[0141] Optionally, the wind turbine power generation and photovoltaic power generation for each park can be obtained based on the wind speed and sunshine intensity of each park. This can be done by using a preset neural network model based on the wind speed and sunshine intensity of each park, with the wind speed and sunshine intensity of each park as input and the neural network model outputting the wind turbine power generation and photovoltaic power generation for each park. The air conditioning operating power for each park can be obtained by calculating the operating power of chiller 1, chiller 2, and the cooling unit of the phase change cold storage air conditioner in each park according to the above embodiment.

[0142] S602 , analyzing the power exchange characteristics of the microgrid of each park and the external power grid based on the power exchange parameters of the microgrid of each park and the external power grid, and obtaining the power supply balance relationship of each park.

[0143] According to the electric power exchange parameters between the microgrid of each park and the external power grid, the electric power exchange characteristics of the microgrid of each park and the external power grid are analyzed to obtain the power supply balance relationship of each park.

[0144] The power exchange characteristics between each park's microgrid and the external grid are as follows: each park generates electricity through wind turbines and photovoltaics, and the phase-change cold storage air conditioners consume electricity during operation. If the microgrid has excess or insufficient power, it can sell or purchase electricity from the external grid. Therefore, the power purchased or sold by each park's microgrid from the external grid, the power generated by the wind turbines and photovoltaics, the operating power of the phase-change cold storage air conditioners in each park, and the electrical load of each park constitute the balance of power supply for each park.

[0145] S603: Construct power exchange constraint conditions based on the power supply balance relationship of each park.

[0146] In one embodiment, based on the power supply balance relationship of each park in the above embodiment, the power exchange constraint conditions are constructed:

[0147]

[0148]

[0149]

[0150]

[0151] in, and They represent the purchased power and sold power of park i at time t respectively; represents the power generation of the wind turbine in park i at time t; represents the photovoltaic power generation power of park i at time t; represents the operating power of the phase change cold storage air conditioner in park i at time t; represents the electrical load of park i at time t; and They represent the maximum allowed power purchase and power sales of park i respectively; and They represent the electricity purchasing and selling signs of park i at time t respectively.

[0152] The present application provides an installed capacity configuration method, which obtains the electric power exchange parameters between the microgrid of each park and the external power grid, analyzes the electric power exchange characteristics between the microgrid of each park and the external power grid based on the electric power exchange parameters between the microgrid of each park and the external power grid, obtains the power supply balance relationship of each park, and constructs electric power exchange constraints based on the power supply balance relationship of each park. In this method, the electric power exchange parameters include at least one of the wind turbine power generation power of each park, the photovoltaic power generation power of each park, the phase change cold storage air conditioning operating power of each park, and the electric load of each park. By using the electric power exchange parameters between the microgrid of each park and the external power grid, the electric power exchange constraints can be constructed to achieve a balance between the microgrid of each park and the external power grid, thereby improving the consumption rate of the park's surplus energy and achieving a reasonable configuration of the capacity of renewable energy generators and cold storage systems.

[0153] In the previous embodiment, the electric power exchange parameters include the wind turbine power generation of each park and the photovoltaic power generation of each park. The following describes in detail how to obtain the wind turbine power generation of each park and the photovoltaic power generation of each park through an embodiment. In one embodiment, if Figure 7 As shown, obtaining the wind turbine power generation and photovoltaic power generation of each park includes the following steps:

[0154] S701, according to the wind turbine power generation formula and the wind force value of each park in the historical time period, obtain the unit power generation power of each wind turbine in each park; and according to the photovoltaic power generation formula and the sunshine intensity value of each park in the historical time period, obtain the unit power generation power of each photovoltaic in each park.

[0155] In one embodiment, the unit power generation of each wind turbine in each park is obtained based on the wind power values ​​of each park in the historical time period obtained in the above embodiment and the wind turbine power generation formula. t The unit wind power of each wind turbine at time t is:

[0156]

[0157] in, Indicates the fan cut-in wind speed; u r Indicates the rated wind speed of the fan; Indicates the fan cut-out wind speed; Indicates the rated generating power of a single wind turbine (1kW).

[0158] One is an embodiment, according to the sunshine intensity value of each park in the historical time period obtained in the above embodiment and the photovoltaic power generation formula, the unit power generation power of each photovoltaic in each park is obtained. t The unit power generation of each photovoltaic cell at time t is:

[0159]

[0160] Among them, G N represents the sunshine intensity under standard test conditions; ε represents the power temperature coefficient; T t Indicates the operating temperature of the solar panel at time t; T r Indicates the reference temperature; Indicates the rated photovoltaic power generation power per unit capacity (1kW).

[0161] S702, based on the preset initial installed capacity of the wind turbines in each park and the unit power generation power of each wind turbine in each park, obtain the wind turbine power generation power of each park; and based on the preset initial installed capacity of the photovoltaic power generation capacity of each park and the unit power generation power of each photovoltaic power generation in each park, obtain the photovoltaic power generation power of each park.

[0162] Based on the preset initial installed capacity of the wind turbines in each park and the unit power generation of each wind turbine in each park obtained in the above embodiment, the power generation of the wind turbines in each park is obtained; the power generation of the wind turbines in each park at time t is:

[0163]

[0164] in, represents the wind turbine power generation power in park i at time t; represents the installed capacity of wind turbines in park i; is the unit power generated by the wind turbine at time t.

[0165] Based on the preset initial installed capacity of photovoltaic power in each park and the unit power generation of each photovoltaic power in each park obtained in the above embodiment, the photovoltaic power generation of each park is obtained; the photovoltaic power generation of each park at time t is:

[0166]

[0167] in, represents the photovoltaic power generation power of park i at time t; represents the photovoltaic installed capacity of park i; is the unit power generated by photovoltaic at time t.

[0168] The embodiment of the present application provides a method for configuring installed capacity, which obtains the unit power generation of each wind turbine in each park according to the wind turbine power generation formula and the wind force value of each park in the historical time period, and obtains the unit power generation of each photovoltaic in each park according to the photovoltaic power generation formula and the sunshine intensity value of each park in the historical time period, obtains the wind turbine power generation of each park according to the preset initial installed capacity of the wind turbine in each park and the unit power generation of each wind turbine in each park, and obtains the photovoltaic power generation of each park according to the preset initial installed capacity of the photovoltaic in each park and the unit power generation of each photovoltaic in each park. In this method, according to the wind turbine power generation and the wind force value of each park, based on the wind turbine installed capacity of each park, the wind turbine power generation of each park at each moment is obtained, according to the photovoltaic power generation and the sunshine intensity of each park, based on the photovoltaic installed capacity of each park, the photovoltaic power generation of each park at each moment is obtained, and the wind and photovoltaic power generation of each park are obtained, which can achieve a reasonable configuration of the capacity of renewable energy generators and cold storage systems and improve the absorption rate of surplus energy in the park.

[0169] In one embodiment, Figure 8 As shown in FIG, the construction process of the cold and electricity supply equipment collaborative model includes the following steps:

[0170] S801. Determine the average annual investment cost and operating cost of each park based on the coordinated planning strategy for cooling and electricity supply equipment in each park. The average annual investment cost of each park includes the average annual investment cost of fans, photovoltaics, vehicles, and phase-change cold storage air conditioners in each park. The average annual operating cost of each park includes the electricity purchase cost, electricity sales cost, and vehicle transfer cost.

[0171] Based on the coordinated planning strategy for cooling and power supply equipment in each park, the average annual investment and operating costs of each park are determined. The coordinated planning strategy for cooling and power supply equipment in each park in this embodiment combines renewable energy units such as wind turbines and photovoltaics with an energy storage system using phase change materials for cold storage and air conditioning. The strategy uses vehicles to transfer excess energy from the phase change materials. This strategy aims to minimize the sum of the average annual investment and operating costs of each park and thereby determine the installed capacity of the energy storage system for wind turbines, photovoltaics, and other renewable energy units combined with the phase change materials for cold storage and air conditioning.

[0172] The average annual investment cost for each park is determined by the costs of its wind turbines, photovoltaics, vehicles, and phase-change thermal storage air conditioners. These costs are based on the installed capacity of these turbines, photovoltaics, and phase-change thermal storage air conditioners, their unit capacity investment costs and service lifespans, and the unit price and service lifespan of these vehicles. The average annual operating cost for each park is determined by its electricity purchase and sales costs, and vehicle transfer costs. These costs are based on its electricity purchase and sales power, electricity purchase and sales unit prices, and whether vehicles are transferred.

[0173] S802: Determine a cooling and electricity supply equipment coordination model based on the average annual investment cost and operating cost of each park.

[0174] According to the above embodiment, the cooling and electricity supply equipment coordination model is determined based on the average annual investment cost and operating cost of each park. The cooling and electricity supply equipment coordination model is determined by the sum of the average annual investment cost and the sum of the operating cost of each park.

[0175] In one embodiment, the sum of the average annual investment costs of the parks in the above embodiment can be expressed as:

[0176]

[0177] in, It represents the rated power of refrigerator 1, refrigerator 2, refrigeration unit and phase change material in the phase change cold storage air conditioner, i.e., installed capacity. MC,c1 、p MC,c2 and p MC,d and p MAC Represents the unit capacity investment cost of refrigerator 1, refrigerator 2, cooler and phase change material container in the phase change cold storage air conditioner; Represent the installed capacity of wind turbines and photovoltaics respectively, N MC Indicates the service life of phase change cold storage air conditioner; p Truck and N MC Represent the vehicle unit price and service life years respectively; p WT and p PV Represent the price of wind turbine and photovoltaic unit capacity respectively; N WT and N PV Respectively represent the service life of wind turbine and photovoltaic per unit capacity.

[0178] In one embodiment, the sum of the average annual operating costs of each park in the above embodiment can be expressed as:

[0179]

[0180] in, and They represent the purchased power and sold power of park i at time t respectively; represents the electricity purchase price of park i at time t; represents the electricity price of park i; is the hourly space transfer cost of the vehicle; H ii,t Indicates the spatial position of the vehicle in park i.

[0181] Based on the sum of the average annual investment costs and the sum of the operating costs of the above parks, the cooling and electricity supply equipment coordination model is determined. The model can be expressed as:

[0182] min(C I +C O ) (25)

[0183] Among them, C I and C O They represent the sum of annual investment costs and annual operating costs of each park respectively.

[0184] The embodiment of the present application provides a method for configuring installed capacity. Based on the collaborative planning strategy of the cooling and power supply equipment of each park, the average annual investment cost and operating cost of each park are determined. Based on the average annual investment cost and operating cost of each park, a collaborative model for cooling and power supply equipment is determined. In this method, the average annual investment cost of each park includes the average annual investment cost of each park's fans, photovoltaics, vehicles, and phase-change cold storage air conditioners. The average annual operating cost of each park includes the electricity purchase cost, electricity sales cost, and vehicle transfer cost. The collaborative model for cooling and power supply equipment is determined based on the average annual investment cost and operating cost of each park. Constructing this model can achieve a reasonable configuration of the capacity of renewable energy generators and cold storage systems, thereby improving the absorption rate of surplus energy in the park.

[0185] In one embodiment, if Figure 9 As shown, before determining the average annual operating cost of each park, it also includes:

[0186] S901, the unit power generation power of each wind turbine in each park, the unit power generation power of each photovoltaic in each park, the electric load of each park and the cooling load of each park in the historical time period are reduced to the target time period through the scenario to obtain the reduction data corresponding to the target time period.

[0187] The unit power generation power of each wind turbine in each park, the unit power generation power of each photovoltaic unit in each park, the electric load of each park, and the cooling load of each park in the historical time period are reduced to the target time period through scenarios to obtain the corresponding reduction data in the target time period.

[0188] One embodiment can obtain the unit power generation of each wind turbine, the unit power generation of each photovoltaic in each park, the electric load of each park and the cooling load of each park in the past year, reduce them to the target time period through a scenario reduction algorithm, and obtain the reduction data for the corresponding time period.

[0189] Optionally, the scenario reduction algorithm can adopt the typical day method within the cycle, replacing the original large-scale time series scenario with a small number of scenarios. The typical day method is to perform data analysis and processing on the original scenario within the cycle, and select a typical day scenario such as a certain day or a specific day for simulation calculation based on different research purposes or experience. For example, the scenario set corresponding to the time when the unit power generation of each wind turbine is large or the unit power generation of each photovoltaic in each park is large is taken as the typical day of the whole year. This embodiment reduces the data of the whole year to two typical days through the scenario reduction algorithm. Among them, the embodiment of the present application does not limit the specific implementation method of the scenario reduction algorithm.

[0190] Among them, such as Figure 10 As shown, Figure 10 are the electricity load and cooling load corresponding to two typical days. Figure 11 As shown, Figure 11 The corresponding changes in the unit power generation power of wind turbines and photovoltaic power generation for two typical days.

[0191] S902, determine the average annual operating cost of each park based on the reduction data.

[0192] The average annual operating cost of each park is determined based on the reduction data obtained according to the above embodiment. The reduction data is the data of two typical days for each park. Therefore, to calculate the average annual operating cost, 8760 hours (one year) is divided by 48 hours (two typical days), and then multiplied by the operating cost of two typical days for each park to obtain the average annual operating cost of each park.

[0193] The present application provides an installed capacity configuration method that reduces the unit power generation of each wind turbine in each park, the unit power generation of each photovoltaic unit in each park, the electrical load of each park, and the cooling load of each park in the historical time period to a target time period through scenario reduction, obtains the reduction data corresponding to the target time period, and determines the average annual operating cost of each park based on the reduction data. The scenario reduction algorithm reduces the data in the historical time period to the data in the target time period, thereby achieving the description of a large number of complex scenario features with a small number of representative scenarios, reducing similar scenarios within the cycle, reducing time complexity, and achieving reasonable configuration of the capacity of renewable energy generators and cold storage systems, thereby improving the absorption rate of surplus energy in the park.

[0194] In one embodiment, Figure 12As shown, the parameter constraints also include phase change cold storage air conditioning operation constraints, phase change material energy storage constraints, and electric power exchange constraints. Accordingly, according to the preset parameter constraints, the cold and electricity supply equipment collaborative model is optimized to obtain the minimum value of the cold and electricity supply equipment collaborative model, including the following steps:

[0195] S1201, obtaining the initial installation capacity of the cooling and power supply equipment in each park.

[0196] The installed capacity of the cooling and electricity supply equipment includes the installed capacity of fans, photovoltaics and refrigerator 1, refrigerator 2, cooling machines and phase change materials in each park's phase change cold storage air conditioner.

[0197] In one embodiment, the initial device capacity of the cooling and power supply equipment in each park is obtained by randomly initializing the device capacity of the cooling and power supply equipment in each park, or by directly giving an initial value to the initial device capacity of the cooling and power supply equipment in each park.

[0198] S1202 , using the transfer constraint and the electric power exchange constraint as constraints, and according to the initial installation capacity of the cooling and power supply equipment in each park and the electric power exchange cost between the parks, obtain the average annual operating cost of each park.

[0199] With the transfer constraints and the electric power exchange constraints as constraints, the annual average operating cost of each park is obtained based on the initial device capacity of the cooling power supply equipment of each park and the electric power exchange cost obtained in the above embodiment. With the above formulas (1)-(4) and the above formulas (15)-(18) as constraints, based on the initial device capacity of the cooling power supply equipment obtained above and the exchange cost between each park, the annual average operating cost of each park is obtained with the goal of minimizing the annual average operating cost formula (24). Among them, the electric power exchange cost between each park is the purchase cost or sales cost of electricity between the park microgrid and the external power grid.

[0200] In one embodiment, based on the initial installation capacity of the cooling and power supply equipment in each park and the electric power exchange cost between the parks, the method for obtaining the average annual operating cost of each park can be obtained through the commercial solver Gurobi. The specific method is to use the transfer constraints, the electric power exchange constraints and the average annual operating cost function of each park as input conditions, call the commercial solver Gurobi, and directly output the average annual operating cost of each park.

[0201] S1203, using the phase change cold storage air conditioning operation constraints and the phase change material energy storage constraints as constraints, according to the initial installation capacity of the cooling and power supply equipment in each park and the average annual operating cost of each park, using a genetic algorithm to solve the cooling and power supply equipment coordination model to obtain the minimum value of the cooling and power supply equipment coordination model.

[0202] Based on the average annual operating costs of each park obtained in the above embodiment, the sum of the average annual operating costs of each park is obtained. The phase change cold storage air conditioning operation constraints and the phase change material energy storage constraints are used as constraints. Based on the initial installation capacity of the cooling and power supply equipment in each park and the sum of the average annual operating costs of each park, a genetic algorithm is used to solve the cooling and power supply equipment coordination model to obtain the minimum value of the cooling and power supply equipment coordination model. Based on the installation capacity of the cooling and power supply equipment in each park and the average annual operating costs of each park, a genetic algorithm is used to solve the cooling and power supply equipment coordination model to obtain the minimum value of the cooling and power supply equipment coordination model. The cooling and power supply equipment coordination model aims to minimize the sum of the average annual investment costs and the sum of the average annual operating costs of each park, and is the objective function in the genetic algorithm.

[0203] One embodiment uses a two-layer algorithm to solve the cooling and power supply equipment collaborative model. The two-layer algorithm is divided into an outer layer and an inner layer. The outer layer and the inner layer each have their own objective function and constraints. The outer layer first gives an optimization variable. The lower layer uses this optimization variable as a parameter and, based on its own objective function and constraints, finds an optimal value within the possible range. The lower layer then feeds its optimal value back to the outer layer. The outer layer then finds the overall optimal solution within the possible range based on the optimal value of the inner layer. The specific steps of the two-layer algorithm for solving the cooling and power supply equipment collaborative model are as follows:

[0204] In the outer layer, the installed capacity of fans, photovoltaics and phase-change cold storage air conditioners is used as the optimization variable, and the installed capacity of fans, photovoltaics and phase-change cold storage air conditioners in the outer layer is input into the inner layer. In the inner layer, the operating power of the phase-change cold storage air conditioners and the exchange power between the parks are used as the optimization variables. According to the goal of minimizing the sum of the average annual operating costs of each park, the commercial solver Gurobi is used to solve the problem and obtain the sum of the average annual operating costs of each park. The outer layer then uses the installed capacity of fans, photovoltaics and phase-change cold storage air conditioners in each park and the sum of the average annual operating costs obtained in the inner layer, with the sum of the average annual investment cost and operating cost of each park as the objective function. The genetic algorithm is used to solve the objective function and obtain the installed capacity of fans, photovoltaics and phase-change cold storage air conditioners in each park.

[0205] The present application provides an installed capacity configuration method that obtains the initial installation capacity of the cooling and power supply equipment in each park, and uses transfer constraints and electric power exchange constraints as constraints. Based on the initial installation capacity of the cooling and power supply equipment in each park and the electric power exchange cost between the parks, the average annual operating cost of each park is obtained. Based on the initial installation capacity of the cooling and power supply equipment in each park and the average annual operating cost of each park, a genetic algorithm is used to solve the cooling and power supply equipment coordination model, and the minimum value of the cooling and power supply equipment coordination model is obtained. In this method, a two-layer algorithm is used to solve the cooling and power supply equipment coordination model, which improves the accuracy of the problem solution, can achieve a reasonable configuration of the capacity of renewable energy generators and cold storage systems, and improves the absorption rate of surplus energy in the park.

[0206] In one embodiment, the working efficiencies of the refrigerator 1, refrigerator 2, and cold release machine in the phase change cold storage air conditioner are 2.8, 4.2, and 42.5, respectively; the cold storage retention rate of the phase change material is 0.999; the unit capacity investment costs of the refrigerator 1, refrigerator 2, cold release machine, and phase change material container in the phase change cold storage air conditioner are 1,000 yuan / kW, 1,000 yuan / kW, 1,000 yuan / kW, and 50 yuan / kWh, respectively; the service life of the phase change cold storage air conditioner is 30 years; the unit price of the vehicle is 200,000 yuan, and the service life of the vehicle is 10 years; the unit capacity fan price is 4,000 yuan / kWh. The price of kW and unit capacity photovoltaic is 4,500 yuan / kW; the service life of unit capacity wind turbines and photovoltaics is 30 years; the park's electricity purchase price at different times is: 1.0 yuan / kW from 00:00 to 6:00 and 22:00 to 24:00, 1.5 yuan / kW from 6:00 to 9:00 and 12:00 to 17:00, and 1.8 yuan / kW from 9:00 to 12:00 and 17:00 to 22:00; the park's electricity sales price is always equal to 0.2 yuan; the vehicle space transfer fee per hour is 50 yuan; the park's maximum allowable power purchase and sales is 3,000kW.

[0207] Optionally, first, collect historical data on wind and sunshine intensity and the park's cooling / electricity load, as well as formulas for wind turbine and photovoltaic power generation; second, establish a vehicle-phase change material spatial transfer model, a phase change cold storage air conditioning operation model, and a phase change cold storage air conditioning energy storage model; then, use a scenario reduction algorithm to determine the appropriate number of renewable energy power generation and cooling / electricity load scenarios, and based on this, formulate a collaborative planning model for the microgrid group's cooling and electricity supply system; on this basis, introduce a two-layer algorithm to solve the optimization model; finally, determine the installed capacity of the park's fans, photovoltaics, and phase change cold storage air conditioning. Taking two parks as an example, the scenario reduction algorithm is used to reduce the data of wind turbine and photovoltaic power generation, cooling load and electric load for 8760 hours (365 days) to 48 hours (typical day 1 and typical day 2); the solution result based on the two-layer algorithm is: the annual comprehensive operating cost of the multi-microgrid combined power and cooling system is 36,665,000 yuan; the wind turbine, photovoltaic, refrigerator 1, refrigerator 2, refrigeration machine and phase change material container in Park 1 are configured with 5700kW, 100kW, 1513kW, 1360kW, 95kW and 28588kWh respectively; the wind turbine, photovoltaic, refrigerator 1, refrigerator 2, refrigeration machine and phase change material container in Park 2 are configured with 4000kW, 0kW, 756kW, 750kW, 72kW and 20787kWh respectively. Figure 13 Shows the spatial position of the vehicle on typical days 1 and 2. Figure 14 and Figure 15 The operating power of the campus microgrid on Typical Day 1 and Typical Day 2 is shown respectively. Figure 13 It can be seen that vehicles can transfer and exchange phase change energy storage materials in phase change cold storage air conditioners in different parks by moving in space, thereby realizing the energy flow of multiple park microgrids. Figure 14 and Figure 15 It can be seen that the phase-change cold storage air conditioners within the park microgrid can operate flexibly, reducing the amount of electricity purchased from the external grid. Therefore, under the guidance of the coordinated planning strategy for the cooling and power supply system of urban park microgrid clusters, the phase-change cold storage air conditioners, fans, and photovoltaics in the park microgrid cluster can be coordinated, significantly reducing system investment costs.

[0208] like Figure 16 As shown, in one embodiment, a method for configuring installed capacity is further provided, which includes:

[0209] S1601, obtain the data set of wind power, sunshine intensity, electricity load and cooling load in the past year;

[0210] S1602: Obtain the wind turbine and photovoltaic power generation power of each park based on the wind turbine and photovoltaic power generation formula per unit capacity and the installed capacity of wind turbines and photovoltaic power generation in each park;

[0211] S1603, based on the phase change materials transferred by vehicles in each park, determining the spatial transfer constraints of vehicles and phase change materials;

[0212] S1604: Determine the phase-change cold storage air conditioner operation constraints and the phase-change cold storage air conditioner energy storage constraints based on the operating characteristics of the phase-change cold storage air conditioner.

[0213] S1605: Determine exchange constraints between the campus microgrid and the external power grid based on exchange characteristics between the campus microgrid and the external power grid;

[0214] S1606: Based on the scenario reduction algorithm, the wind turbine and photovoltaic power generation, the electrical load, and the cooling load of each park are reduced to 48 hours, namely, typical day 1 and typical day 2.

[0215] S1607: With the goal of minimizing the sum of the average annual investment and operating costs of the campus microgrid units, determine a coordinated planning model for the cooling and electricity supply system of the microgrid cluster based on spatial transfer constraints, phase-change cold storage air conditioning operation constraints, phase-change cold storage air conditioning energy storage constraints, and exchange constraints between the campus microgrid and the external power grid.

[0216] S1608: Solve the microgrid cooling and power supply system collaborative planning model based on the two-layer algorithm to obtain the installed capacity of each park microgrid unit.

[0217] The implementation principles and technical effects of each step in the installed capacity configuration method provided in this embodiment are similar to those in the previous embodiments of the installed capacity configuration method, and will not be repeated here.

[0218] It should be understood that, although the various steps in the flowcharts of the above-described embodiments are shown in sequence as indicated by the arrows, these steps are not necessarily performed in the order indicated by the arrows. Unless otherwise specified herein, there is no strict order restriction on the execution of these steps, and these steps may be performed in other orders. Moreover, at least a portion of the steps in the flowcharts of the above-described embodiments may include multiple steps or multiple stages, and these steps or stages are not necessarily performed at the same time, but may be performed at different times. The execution order of these steps or stages is not necessarily to be performed in sequence, but may be performed in turn or alternately with other steps or at least a portion of steps or stages in other steps.

[0219] The embodiment of the present application provides a device for configuring installed capacity, such as Figure 17 As shown, in one embodiment, the installed capacity configuration device 1700 includes: an optimization module 1701 and a determination module 1702, wherein:

[0220] Optimization module 1701 is configured to optimize the cooling and power supply equipment coordination model based on preset parameter constraints to obtain a minimum value of the cooling and power supply equipment coordination model. The parameter constraints include transfer constraints, which represent the state of the vehicle transferring phase change materials. The cooling and power supply equipment coordination model includes the device capacity of the cooling and power supply equipment in multiple parks.

[0221] The determination module 1702 is configured to determine the target device capacity of the cooling and power supply equipment in each park by using the device capacity value of the cooling and power supply equipment corresponding to the minimum value of the cooling and power supply equipment coordination model.

[0222] In one embodiment, a device for configuring installed capacity is further provided, the device comprising:

[0223] The first constraint module is used to construct transfer constraint conditions based on the spatial state characteristics of the vehicle when the vehicle transfers the phase change material in each park;

[0224] The second constraint module is used to construct the phase change cold storage air conditioner operation constraint conditions and the phase change material energy storage constraint conditions according to the working characteristics of the phase change cold storage air conditioner in each park;

[0225] The third constraint module is used to construct power exchange constraint conditions based on the power exchange characteristics of the microgrid of each park and the external power grid;

[0226] The constraint module is used to determine transfer constraints, phase change cold storage air conditioning operation constraints, phase change material energy storage constraints, and electric power exchange constraints as parameter constraints.

[0227] In one embodiment, the first constraint module includes:

[0228] A location unit, used to obtain vehicle location information when transferring phase change materials in each park;

[0229] A state unit is used to analyze the spatial state characteristics of the vehicle when the vehicle transfers the phase change material in each park based on the vehicle position information;

[0230] The first constraint unit is used to construct a transfer constraint condition according to the spatial state characteristics of the vehicle.

[0231] In one embodiment, the second constraint module includes:

[0232] The first acquisition unit is used to obtain the operating parameters of the phase change cold storage air conditioner in each park; the operating parameters include at least one of the operating power of the phase change cold storage air conditioner, the electric cooling conversion efficiency of the operating power of the phase change cold storage air conditioner, the cooling load of each park, the energy storage of the phase change material in the phase change cold storage air conditioner, and the energy storage of the phase change material transferred by vehicles in each park within the park;

[0233] The first relationship unit is used to analyze the operating characteristics of the phase change cold storage air conditioner in each park based on the operating parameters of the phase change cold storage air conditioner in each park, and obtain the cold supply balance relationship of each park; based on the operating parameters of the phase change cold storage air conditioner in each park, analyze the operating characteristics of the phase change material energy storage in each park, and obtain the energy storage balance relationship of the phase change material in each park;

[0234] The second constraint unit is used to construct the phase change cold storage air conditioning operation constraint conditions according to the cold supply balance relationship of each park; and to construct the phase change material energy storage constraint conditions according to the energy storage balance relationship.

[0235] In one embodiment, the third constraint module includes:

[0236] The second acquisition unit is used to obtain the electric power exchange parameters between the microgrid of each park and the external power grid; the electric power exchange parameters include at least one of the wind turbine power generation power of each park, the photovoltaic power generation power of each park, the phase change cold storage air conditioning operating power of each park, and the electric load of each park;

[0237] The second relationship unit is used to analyze the power exchange characteristics of the microgrid of each park and the external power grid based on the power exchange parameters of the microgrid of each park and the external power grid, and obtain the power supply balance relationship of each park;

[0238] The third constraint unit is used to construct electric power exchange constraint conditions according to the power supply balance relationship of each park.

[0239] In one embodiment, the second acquiring unit includes:

[0240] The acquisition subunit is used to obtain the unit power generation of each wind turbine in each park based on the wind turbine power generation formula and the wind force value of each park in the historical time period; and to obtain the unit power generation of each photovoltaic unit in each park based on the photovoltaic power generation formula and the sunshine intensity value of each park in the historical time period;

[0241] A subunit is obtained, which is used to obtain the wind turbine power generation power of each park based on the preset initial installed capacity of the wind turbine in each park and the unit power generation power of each wind turbine in each park; and to obtain the photovoltaic power generation power of each park based on the preset initial installed capacity of the photovoltaic power plant in each park and the unit power generation power of each photovoltaic power plant in each park.

[0242] In one embodiment, a device for configuring installed capacity is further provided, the device comprising:

[0243] The first determination module is used to determine the average annual investment cost and operating cost of each park based on the collaborative planning strategy of the cooling and electricity supply equipment of each park; the average annual investment cost of each park includes the average annual investment cost of each park's fans, photovoltaics, vehicles and phase change cold storage air conditioners, and the average annual operating cost of each park includes the electricity purchase cost, electricity sales cost and vehicle transfer cost.

[0244] The second determination module is used to determine the cooling and electricity supply equipment coordination model based on the average annual investment cost and operation cost of each park.

[0245] In one embodiment, a device for configuring installed capacity is further provided, the device comprising:

[0246] The reduction module is used to reduce the unit power generation of each wind turbine in each park, the unit power generation of each photovoltaic unit in each park, the electric load of each park, and the cooling load of each park in the historical time period to the target time period through scenarios, and obtain the corresponding reduction data in the target time period;

[0247] The third determination module is used to determine the average annual operating cost of each park based on the reduction data.

[0248] In one embodiment, the optimization module 1701 includes:

[0249] Initial unit, used to obtain the initial installation capacity of cooling and power supply equipment in each park;

[0250] The third acquisition unit is configured to acquire the average annual operating cost of each park based on the initial device capacity of the cooling and power supply equipment in each park and the power exchange cost between the parks, with the transfer constraint and the power exchange constraint as constraints;

[0251] The third acquisition unit is used to use the phase change cold storage air conditioning operation constraints and the phase change material energy storage constraints as constraints, and use a genetic algorithm to solve the cold power supply equipment coordination model according to the initial installation capacity of the cold power supply equipment in each park and the average annual operating cost of each park to obtain the minimum value of the cold power supply equipment coordination model.

[0252] The specific definition of the installed capacity configuration device can be found in the definition of the installed capacity configuration method above and will not be repeated here. The various modules in the above-mentioned installed capacity configuration device can be implemented in whole or in part through software, hardware, or a combination thereof. The above-mentioned modules can be embedded in or independent of the processor in the computer device in hardware form, or can be stored in the memory of the computer device in software form, so that the processor can call and execute the corresponding operations of each of the above modules.

[0253] In one embodiment, a computer device is provided. The computer device may be a terminal, and its internal structure diagram may be as follows: Figure 18As shown. The computer device includes a processor, a memory, a communication interface, a display screen and an input device connected via a system bus. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The communication interface of the computer device is used to communicate with an external terminal in a wired or wireless manner, and the wireless manner can be achieved through WIFI, an operator network, NFC (near field communication) or other technologies. When the computer program is executed by the processor, a method for configuring installed capacity is implemented. The display screen of the computer device can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device can be a touch layer covering the display screen, or a button, trackball or touchpad provided on the computer device housing, or an external keyboard, touchpad or mouse.

[0254] Those skilled in the art will understand that Figure 18 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than shown in the figure, or combine certain components, or have a different component arrangement.

[0255] In one embodiment, a computer device is provided, including a memory and a processor, wherein a computer program is stored in the memory, and when the processor executes the computer program, the following steps are implemented:

[0256] Based on preset parameter constraints, the cooling and power supply equipment collaborative model is optimized to obtain the minimum value of the cooling and power supply equipment collaborative model. The parameter constraints include transfer constraints, which represent the state of the vehicle transferring phase change materials. The cooling and power supply equipment collaborative model includes the installation capacity of the cooling and power supply equipment in multiple parks.

[0257] The target capacity of the cooling and power supply equipment in each park is determined by using the device capacity value of the cooling and power supply equipment corresponding to the minimum value of the cooling and power supply equipment coordination model.

[0258] In one embodiment, the processor implements the following steps when executing the computer program:

[0259] According to the spatial state characteristics of the vehicle when transferring phase change materials in each park, transfer constraints are established;

[0260] According to the working characteristics of the phase change cold storage air conditioner in each park, the operating constraints of the phase change cold storage air conditioner and the energy storage constraints of the phase change material are established;

[0261] According to the power exchange characteristics between the microgrid of each park and the external power grid, the power exchange constraint conditions are established;

[0262] Transfer constraints, phase change cold storage air conditioning operation constraints, phase change material energy storage constraints, and electric power exchange constraints are determined as parameter constraints.

[0263] In one embodiment, the processor implements the following steps when executing the computer program:

[0264] Obtain vehicle location information when transferring phase change materials in various parks;

[0265] Based on the vehicle location information, analyze the spatial state characteristics of the vehicle when transferring phase change materials in each park;

[0266] According to the spatial state characteristics of the vehicle, transfer constraints are constructed.

[0267] In one embodiment, the processor implements the following steps when executing the computer program:

[0268] Obtaining operating parameters of the phase change cold storage air conditioner in each park; the operating parameters include at least one of the operating power of the phase change cold storage air conditioner, the electric cooling conversion efficiency of the operating power of the phase change cold storage air conditioner, the cooling load of each park, the energy storage of the phase change material in the phase change cold storage air conditioner, and the energy storage of the phase change material transferred by vehicles in each park within the park;

[0269] Based on the operating parameters of the phase-change cold storage air conditioners in each park, the operating characteristics of the phase-change cold storage air conditioners in each park are analyzed to obtain the cold supply balance relationship of each park; based on the operating parameters of the phase-change cold storage air conditioners in each park, the operating characteristics of the phase-change material energy storage in each park are analyzed to obtain the energy storage balance relationship of the phase-change material in each park;

[0270] Based on the cold supply balance relationship of each park, the operating constraints of phase change cold storage air conditioners are constructed; based on the energy storage balance relationship, the energy storage constraints of phase change materials are constructed.

[0271] In one embodiment, the processor implements the following steps when executing the computer program:

[0272] Obtaining electric power exchange parameters between the microgrid of each park and the external power grid; the electric power exchange parameters include at least one of the wind turbine power generation of each park, the photovoltaic power generation of each park, the phase change cold storage air conditioning operating power of each park, and the electric load of each park;

[0273] According to the electric power exchange parameters between the microgrid of each park and the external power grid, the electric power exchange characteristics of the microgrid of each park and the external power grid are analyzed to obtain the power supply balance relationship of each park;

[0274] Based on the power supply balance relationship of each park, the power exchange constraint conditions are constructed.

[0275] In one embodiment, the processor implements the following steps when executing the computer program:

[0276] Based on the wind turbine power generation formula and the wind speed values ​​of each park in the historical time period, the unit power generation power of each wind turbine in each park is obtained; and based on the photovoltaic power generation formula and the sunshine intensity values ​​of each park in the historical time period, the unit power generation power of each photovoltaic in each park is obtained;

[0277] Based on the preset initial installed capacity of wind turbines in each park and the unit power generation of each wind turbine in each park, the wind turbine power generation of each park is obtained; and based on the preset initial installed capacity of photovoltaic power in each park and the unit power generation of each photovoltaic in each park, the photovoltaic power generation of each park is obtained.

[0278] In one embodiment, the processor implements the following steps when executing the computer program:

[0279] Based on the coordinated planning strategy of cooling and electricity supply equipment in each park, the average annual investment cost and operating cost of each park are determined; the average annual investment cost of each park includes the average annual investment cost of fans, photovoltaics, vehicles and phase change cold storage air conditioners in each park, and the average annual operating cost of each park includes electricity purchase cost, electricity sales cost and vehicle transfer cost.

[0280] Determine the cooling and electricity supply equipment coordination model based on the average annual investment cost and operating cost of each park.

[0281] In one embodiment, the processor implements the following steps when executing the computer program:

[0282] The unit power generation of each wind turbine in each park, the unit power generation of each photovoltaic unit in each park, the electric load in each park, and the cooling load in each park in the historical time period are reduced to the target time period through scenarios to obtain the corresponding reduction data in the target time period;

[0283] Determine the average annual operating cost of each park based on the reduction data.

[0284] In one embodiment, the processor implements the following steps when executing the computer program:

[0285] Obtain the initial installed capacity of cooling and power supply equipment in each park;

[0286] With transfer constraints and power exchange constraints as the constraints, the average annual operating cost of each park is obtained based on the initial installation capacity of the cooling and power supply equipment in each park and the power exchange cost between parks.

[0287] Taking the operation constraints of phase change cold storage air conditioner and the energy storage constraints of phase change materials as constraints, according to the initial installation capacity of the cooling and power supply equipment in each park and the average annual operation cost of each park, the genetic algorithm is used to solve the cooling and power supply equipment coordination model to obtain the minimum value of the cooling and power supply equipment coordination model.

[0288] The above embodiment provides a computer-readable storage medium, whose implementation principle and technical effects are similar to those of the above method embodiment, and will not be repeated here.

[0289] Those skilled in the art will appreciate that all or part of the processes in the above-mentioned embodiment methods can be implemented by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application may include at least one of non-volatile and volatile memory. Non-volatile memory may include read-only memory (ROM), magnetic tape, floppy disk, flash memory or optical memory, etc. Volatile memory may include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM).

[0290] The technical features of the above embodiments can be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0291] The above-described embodiments merely represent several implementation methods of the present application. While the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the present invention. It should be noted that a person skilled in the art could make various modifications and improvements without departing from the spirit of the present application, all of which fall within the scope of protection of the present application. Therefore, the scope of protection of the present patent application shall be determined by the appended claims.

Claims

1. A method for configuring installed capacity, characterized in that: The method comprises: Optimizing the cooling and power supply equipment coordination model based on preset parameter constraints to obtain a minimum value of the cooling and power supply equipment coordination model; the parameter constraints include transfer constraints that characterize the state of the vehicle transferring phase change materials; the cooling and power supply equipment coordination model includes the device capacities of the cooling and power supply equipment in multiple parks; Determining the device capacity value of the cooling and power supply equipment corresponding to the minimum value of the cooling and power supply equipment coordination model as the target device capacity of the cooling and power supply equipment in each of the parks; The cooling and electricity supply equipment coordination model is expressed as min(C I +C O );C I and C O Respectively represent the sum of annual investment costs and annual operating costs of each park; represents the rated power, i.e. installed capacity, of chiller 1, chiller 2, refrigeration unit, and phase change material in the phase change cold storage air conditioner in park i, p MC,c1 、p MC,c2 、p MC,d and p MAC Represents the unit capacity investment cost of refrigerator 1, refrigerator 2, cooler and phase change material container in the phase change cold storage air conditioner; Represent the installed capacity of wind turbines and photovoltaics respectively, N MC1 Indicates the service life of phase change cold storage air conditioner; p Truck and N MC2 Represent the vehicle unit price and service life years respectively; p WT and p PV Represent the price of wind turbine and photovoltaic unit capacity respectively; N WT and N PV Respectively represent the service life of wind turbine and photovoltaic per unit capacity; and They represent the purchased power and sold power of park i at time t respectively; represents the electricity purchase price at time t; represents the electricity price of park i; is the hourly space transfer cost of the vehicle; H ii,t Indicates the spatial position of the vehicle in park i; I represents the total number of parks; T S Indicates the number of hours in the target time period to be reduced.

2. The method according to claim 1, characterized in that The parameter constraints also include phase change cold storage air conditioning operation constraints, phase change material energy storage constraints, and electric power exchange constraints; before optimizing the cold power supply equipment collaborative model, the method further includes: Constructing the transfer constraint conditions according to the spatial state characteristics of the vehicle when the vehicle transfers the phase change material in each of the parks; According to the working characteristics of the phase change cold storage air conditioner in each of the parks, the operating constraints of the phase change cold storage air conditioner and the energy storage constraints of the phase change material are established; Constructing the power exchange constraint conditions according to the power exchange characteristics between the microgrid of each park and the external power grid; The transfer constraint condition, the phase change cold storage air conditioner operation constraint condition, the phase change material energy storage constraint condition, and the electric power exchange constraint condition are determined as the parameter constraint conditions.

3. The method according to claim 2, characterized in that The transfer constraint condition is constructed according to the spatial state characteristics of the vehicle when the vehicle transfers the phase change material in each of the parks, including: Acquiring vehicle position information when transferring the phase change material in each of the parks; analyzing, based on the vehicle position information, spatial state characteristics of the vehicle when the vehicle transfers the phase change material in each of the parks; The transfer constraint condition is constructed according to the spatial state characteristics of the vehicle.

4. The method according to claim 2, characterized in that The phase change cold storage air conditioner operation constraint conditions and the phase change material energy storage constraint conditions are constructed based on the operating characteristics of the phase change cold storage air conditioner in each of the parks, including: Obtaining operating parameters of the phase-change cold storage air conditioner in each of the parks; the operating parameters include at least one of the operating power of the phase-change cold storage air conditioner, the electric-to-cooling conversion efficiency of the operating power of the phase-change cold storage air conditioner, the cooling load of each of the parks, the energy storage of the phase-change material in the phase-change cold storage air conditioner, and the energy storage of the phase-change material transferred by vehicles in each of the parks within the park; According to the operating parameters of the phase-change cold storage air conditioner in each park, the operating characteristics of the phase-change cold storage air conditioner in each park are analyzed to obtain the cold supply balance relationship of each park; according to the operating parameters of the phase-change cold storage air conditioner in each park, the operating characteristics of the phase-change material energy storage in each park are analyzed to obtain the energy storage balance relationship of the phase-change material in each park; According to the cold supply balance relationship of each park, the operating constraints of the phase change cold storage air conditioner are constructed; according to the energy storage balance relationship, the energy storage constraints of the phase change material are constructed.

5. The method according to claim 2, characterized in that The electric power exchange constraint condition is constructed according to the electric power exchange characteristics between the microgrid of each park and the external power grid, including: Obtaining electric power exchange parameters between the microgrid of each park and the external power grid; the electric power exchange parameters include at least one of the wind turbine power generation power of each park, the photovoltaic power generation power of each park, the phase change cold storage air conditioning operating power of each park, and the electric load of each park; Analyzing the power exchange characteristics of the microgrid and the external power grid of each park based on the power exchange parameters between the microgrid and the external power grid of each park to obtain the power supply balance relationship of each park; The electric power exchange constraint condition is constructed based on the power supply balance relationship of each of the parks.

6. The method according to claim 5, characterized in that The obtaining of the wind turbine power generation power and the photovoltaic power generation power of each of the parks includes: Obtain the unit power generation power of each wind turbine in each of the parks according to the wind turbine power generation power formula and the wind force value of each park in the historical time period; and obtain the unit power generation power of each photovoltaic in each of the parks according to the photovoltaic power generation power formula and the sunshine intensity value of each park in the historical time period; According to the preset initial installed capacity of the wind turbines in each park and the unit power generation power of each wind turbine in each of the parks, the wind turbine power generation power of each of the parks is obtained; and according to the preset initial installed capacity of the photovoltaic power generation capacity in each park and the unit power generation power of each photovoltaic power generation in each of the parks, the photovoltaic power generation power of each of the parks is obtained.

7. The method according to any one of claims 1 to 5, characterized in that The process of constructing the cold and electricity supply equipment collaborative model includes: Determine the average annual investment cost and operating cost of each park based on the coordinated planning strategy for cooling and electricity supply equipment in each park; the average annual investment cost of each park includes the average annual investment cost of wind turbines, photovoltaics, vehicles, and phase-change cold storage air conditioners in each park; and the average annual operating cost of each park includes the cost of electricity purchase, the cost of electricity sales, and the cost of vehicle transfer; The cooling and electricity supply equipment coordination model is determined based on the average annual investment cost and operating cost of each of the parks.

8. The method according to claim 7, characterized in that Before determining the average annual operating cost of each park, the method further includes: The unit power generation of each wind turbine in each park, the unit power generation of each photovoltaic unit in each park, the electric load of each park, and the cooling load of each park in the historical time period are reduced to the target time period through the scenario, and the reduction data corresponding to the target time period is obtained; The average annual operating cost of each of the parks is determined based on the reduction data.

9. The method according to any one of claims 1 to 5, characterized in that The parameter constraints also include phase change cold storage air conditioning operation constraints, the phase change material energy storage constraints, and electric power exchange constraints. Accordingly, the cooling and electricity supply equipment collaborative model is optimized according to the preset parameter constraints to obtain the minimum value of the cooling and electricity supply equipment collaborative model, including: Obtaining the initial installation capacity of the cooling and power supply equipment in each of the parks; Obtaining the average annual operating cost of each park based on the transfer constraint and the electric power exchange constraint, and according to the initial device capacity of the cooling and power supply equipment in each park and the electric power exchange cost between the parks; Taking the phase change cold storage air conditioner operation constraints and the phase change material energy storage constraints as constraints, according to the initial device capacity of the cold and electricity supply equipment in each park and the average annual operating cost of each park, a genetic algorithm is used to solve the cold and electricity supply equipment coordination model to obtain the minimum value of the cold and electricity supply equipment coordination model.

10. A device for configuring installed capacity, characterized in that: The device comprises: an optimization module configured to optimize the cooling and power supply equipment coordination model based on preset parameter constraints to obtain a minimum value of the cooling and power supply equipment coordination model; the parameter constraints include transfer constraints that characterize the state of a vehicle transferring phase change material; the cooling and power supply equipment coordination model includes the device capacities of cooling and power supply equipment in multiple parks; a determination module, configured to determine the device capacity value of the cooling and power supply equipment corresponding to the minimum value of the cooling and power supply equipment coordination model as the target device capacity of the cooling and power supply equipment in each of the parks; The cooling and electricity supply equipment coordination model is expressed as min(C I +C O );C I and C O Respectively represent the sum of annual investment costs and annual operating costs of each park; represents the rated power, i.e. installed capacity, of chiller 1, chiller 2, refrigeration unit, and phase change material in the phase change cold storage air conditioner in park i, p MC,c1 、p MC,c2 、p MC,d and p MAC Represents the unit capacity investment cost of refrigerator 1, refrigerator 2, cooler and phase change material container in the phase change cold storage air conditioner; Represent the installed capacity of wind turbines and photovoltaics respectively, N MC1 Indicates the service life of phase change cold storage air conditioner; p Truck and N MC2 Represent the vehicle unit price and service life years respectively; p WT and p PV Represent the price of wind turbine and photovoltaic unit capacity respectively; N WT and N PV Respectively represent the service life of wind turbine and photovoltaic per unit capacity; and They represent the purchased power and sold power of park i at time t respectively; represents the electricity purchase price at time t; represents the electricity price of park i; is the hourly space transfer cost of the vehicle; H ii,t Indicates the spatial position of the vehicle in park i; I represents the total number of parks; T S Indicates the number of hours in the target time period to be reduced.

Images