Optical storage direct flexible park adjustable load orderly energy using method and device and computer equipment

Abstract

The invention relates to an optical storage direct flexible park adjustable load orderly energy using method and device and computer equipment. The method comprises the following steps: constructing a micro-grid architecture model of the optical storage direct-current flexible park according to equipment power utilization characteristics and power resource scheduling information of the optical storage direct-current flexible park; constructing an equipment operation model corresponding to each piece of power equipment according to the equipment operation characteristics of each piece of power equipment in the optical storage direct flexible park; according to the micro-grid architecture model and each equipment operation model, constructing an adjustable load ordered energy use objective function of the optical storage direct flexible park and park equipment operation constraint conditions; the park equipment operation constraint condition is used as a limit, an adjustable load ordered energy use target function is solved, and adjustable load ordered energy use adjustment information of the optical storage direct flexible park is obtained; the adjustable load orderly energy utilization adjustment information is used for adjusting the power resource distribution condition of the optical storage direct flexible park. By adopting the method, the satisfaction degree of the user on the regulation and control means of the adjustable load can be improved.

Description

Technical Field

[0001] The present application relates to the field of photovoltaic, storage, direct and flexible technologies, and in particular to a method, device and computer equipment for orderly energy use of adjustable loads in a photovoltaic, storage, direct and flexible park. Background Art

[0002] The photovoltaic storage direct-flexible technology integrates advanced technologies such as photovoltaic power generation, energy storage system, DC power distribution and flexible power consumption to adapt to environmental protection requirements, technological development, policy incentives and changes in user needs, and promote the development of smart grids and clean energy. In the photovoltaic storage direct-flexible park, the main power generation equipment is rooftop distributed photovoltaics. Through the large-scale construction of photovoltaics, the power demand of user loads can be met; the excess photovoltaic power generation can be stored through distributed energy storage, and the power can be released and supplied to users when the photovoltaic power generation is low or no power generation; inside the buildings of the park, through the DC power distribution system, the DC power generated by photovoltaics can be directly supplied to DC loads through voltage reduction, reducing the loss of AC-DC conversion; flexible power consumption is that the load users change their own power consumption by accepting the regulation of the dispatching center, reducing the power consumption of users during peak power consumption periods, encouraging more power consumption during low power consumption periods, and promoting peak shaving and valley filling.

[0003] At present, the operation method of the photovoltaic storage direct flexible park microgrid is generally to produce electricity through distributed photovoltaic power generation, power grid purchase and other methods in the park, and the electricity is directly supplied to the power load. Due to the access to new energy power generation, there will be surplus electricity when it is generated in large quantities, and the excess electricity is stored in the park through power storage equipment (batteries, large capacitors, etc.). The park is usually optimized with the goal of minimizing the comprehensive operating cost (new energy power generation cost, equipment operating cost, power purchase cost, etc.) and the best peak shaving and valley filling effect. For the photovoltaic storage direct flexible park with traditional technology, the park usually only considers the reduction of operating costs and the improvement of peak shaving and valley filling effects. The means of regulating the adjustable load are relatively rigid. The adjustable load is only regulated by means of time-of-use electricity prices, price compensation and other means, and the user satisfaction is often ignored, resulting in low user satisfaction with the means of regulating the adjustable load. Summary of the invention

[0004] Based on this, it is necessary to provide a method, device, computer equipment, computer-readable storage medium and computer program product for orderly energy use of adjustable loads in a photovoltaic storage direct and flexible park, which can improve user satisfaction with the means of regulating adjustable loads, in response to the above-mentioned technical problems.

[0005] In a first aspect, the present application provides a method for orderly energy use of adjustable loads in a photovoltaic storage direct and flexible park, comprising:

[0006] According to the power consumption characteristics of the equipment in the photovoltaic, storage, direct and flexible park and the power resource scheduling information, a microgrid architecture model of the photovoltaic, storage, direct and flexible park is constructed;

[0007] According to the equipment operation characteristics of each power equipment in the solar-storage-direct-flexible park, construct an equipment operation model corresponding to each power equipment;

[0008] According to the microgrid architecture model and the operation models of each device, an adjustable load orderly energy utilization objective function and park equipment operation constraint conditions of the photovoltaic storage direct-flexible park are constructed;

[0009] Taking the operation constraints of the park equipment as the limitation, the objective function of the adjustable load orderly energy consumption is solved to obtain the adjustable load orderly energy consumption adjustment information of the photovoltaic, storage, direct and flexible park; the adjustable load orderly energy consumption adjustment information is used to adjust the power resource allocation of the photovoltaic, storage, direct and flexible park.

[0010] In the second aspect, the present application also provides a photovoltaic storage direct-flexible park load-adjustable orderly energy use device, including:

[0011] A model building module, used to build a microgrid architecture model of the photovoltaic storage direct and flexible park according to the equipment power consumption characteristics and power resource scheduling information of the photovoltaic storage direct and flexible park;

[0012] The model building module is also used to build a device operation model corresponding to each power device according to the device operation characteristics of each power device in the solar-storage-direct-flexible park;

[0013] A condition determination module, used to construct an adjustable load orderly energy utilization objective function and park equipment operation constraint conditions of the photovoltaic storage direct and flexible park according to the microgrid architecture model and each of the equipment operation models;

[0014] The function solving module is used to solve the adjustable load orderly energy consumption objective function based on the operation constraints of the park equipment, and obtain the adjustable load orderly energy consumption adjustment information of the photovoltaic, storage, direct and flexible park; the adjustable load orderly energy consumption adjustment information is used to adjust the power resource allocation of the photovoltaic, storage, direct and flexible park.

[0015] In a third aspect, the present application further provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the following steps are implemented:

[0016] According to the power consumption characteristics of the equipment in the photovoltaic, storage, direct and flexible park and the power resource scheduling information, a microgrid architecture model of the photovoltaic, storage, direct and flexible park is constructed;

[0017] According to the equipment operation characteristics of each power equipment in the solar-storage-direct-flexible park, an equipment operation model corresponding to each power equipment is constructed;

[0018] According to the microgrid architecture model and the operation models of each device, an adjustable load orderly energy utilization objective function and park equipment operation constraint conditions of the photovoltaic storage direct-flexible park are constructed;

[0019] Taking the operation constraints of the park equipment as the limitation, the objective function of the adjustable load orderly energy consumption is solved to obtain the adjustable load orderly energy consumption adjustment information of the photovoltaic, storage, direct and flexible park; the adjustable load orderly energy consumption adjustment information is used to adjust the power resource allocation of the photovoltaic, storage, direct and flexible park.

[0020] In a fourth aspect, the present application further provides a computer-readable storage medium having a computer program stored thereon, wherein when the computer program is executed by a processor, the following steps are implemented:

[0021] According to the power consumption characteristics of the equipment in the photovoltaic, storage, direct and flexible park and the power resource scheduling information, a microgrid architecture model of the photovoltaic, storage, direct and flexible park is constructed;

[0022] According to the equipment operation characteristics of each power equipment in the solar-storage-direct-flexible park, an equipment operation model corresponding to each power equipment is constructed;

[0023] According to the microgrid architecture model and the operation models of each device, an adjustable load orderly energy utilization objective function and park equipment operation constraint conditions of the photovoltaic storage direct-flexible park are constructed;

[0024] Taking the operation constraints of the park equipment as the limitation, the objective function of the adjustable load orderly energy consumption is solved to obtain the adjustable load orderly energy consumption adjustment information of the photovoltaic, storage, direct and flexible park; the adjustable load orderly energy consumption adjustment information is used to adjust the power resource allocation of the photovoltaic, storage, direct and flexible park.

[0025] In a fifth aspect, the present application further provides a computer program product, including a computer program, which implements the following steps when executed by a processor:

[0026] According to the power consumption characteristics of the equipment in the photovoltaic, storage, direct and flexible park and the power resource scheduling information, a microgrid architecture model of the photovoltaic, storage, direct and flexible park is constructed;

[0027] According to the equipment operation characteristics of each power equipment in the solar-storage-direct-flexible park, an equipment operation model corresponding to each power equipment is constructed;

[0028] According to the microgrid architecture model and the operation models of each device, an adjustable load orderly energy utilization objective function and park equipment operation constraint conditions of the photovoltaic storage direct-flexible park are constructed;

[0029] Taking the operation constraints of the park equipment as the limitation, the objective function of the adjustable load orderly energy consumption is solved to obtain the adjustable load orderly energy consumption adjustment information of the photovoltaic, storage, direct and flexible park; the adjustable load orderly energy consumption adjustment information is used to adjust the power resource allocation of the photovoltaic, storage, direct and flexible park.

[0030] The above-mentioned method, device, computer equipment, storage medium and computer program product for orderly energy use of adjustable loads in a photovoltaic, storage, direct and flexible park constructs a microgrid architecture model of the photovoltaic, storage, direct and flexible park based on the equipment power consumption characteristics of the photovoltaic, storage, direct and flexible park and the power resource scheduling information; constructs the equipment operation model corresponding to each power equipment based on the equipment operation characteristics of each power equipment in the photovoltaic, storage, direct and flexible park; constructs the adjustable load orderly energy use objective function and park equipment operation constraints of the photovoltaic, storage, direct and flexible park based on the microgrid architecture model and each equipment operation model; solves the adjustable load orderly energy use objective function with the park equipment operation constraints as the limitation, and obtains the adjustable load orderly energy use adjustment information of the photovoltaic, storage, direct and flexible park; the adjustable load orderly energy use adjustment information is used to adjust the power resource allocation of the photovoltaic, storage, direct and flexible park.

[0031] By constructing the microgrid architecture model of the photovoltaic storage direct flexible park and the operation model of each power equipment, it is possible to accurately capture the power consumption characteristics and dynamic changes of various power equipment in the park, and optimize the operation mode of the power equipment in combination with the power resource dispatch information. By setting up the objective function of orderly energy consumption of adjustable loads and optimizing the solution with the equipment operation constraints as the boundary, this method can improve the user's satisfaction with the means of regulating and controlling adjustable loads, and effectively coordinate the balance between power generation and consumption of renewable energy (such as photovoltaic and energy storage systems), thereby maximizing the utilization rate of self-generation and reducing the demand for power purchases from the power grid. In addition, it can also enhance the park's ability to adapt to power fluctuations, reduce peak load pressure, reduce operating costs, and improve the stability and reliability of the system by dynamically adjusting load distribution, which not only improves the energy efficiency of the park, but also provides an important technical reference for the development of future smart microgrids. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the related technologies, the drawings required for use in the embodiments or the related technical descriptions are briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0033] Figure 1 This is an application environment diagram of a method for orderly energy use of adjustable loads in a photovoltaic storage direct and flexible park in one embodiment;

[0034] Figure 2A schematic diagram of a flow chart of an adjustable load orderly energy use method in a photovoltaic storage direct and flexible park in one embodiment;

[0035] Figure 3 A schematic diagram of a flow chart of a method for constructing an adjustable load orderly energy utilization objective function in one embodiment;

[0036] Figure 4 It is a flowchart of a method for setting target information of orderly energy consumption of adjustable loads in one embodiment;

[0037] Figure 5 A schematic diagram of a flow chart of a method for constructing park equipment operation constraint conditions in one embodiment;

[0038] Figure 6 It is a flowchart of a method for obtaining information on orderly energy use adjustment of adjustable loads in one embodiment;

[0039] Figure 7 A schematic diagram of a process of building a device operation model in one embodiment;

[0040] Figure 8 It is a structural block diagram of an adjustable load orderly energy use device for a photovoltaic storage direct and flexible park in one embodiment;

[0041] Fig. 9 FIG. 4 is a diagram showing the internal structure of a computer device in one embodiment. DETAILED DESCRIPTION

[0042] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0043] The embodiment of the present application provides a method for orderly energy use of adjustable loads in a photovoltaic storage and direct flexible park, which can be applied to Figure 1In the application environment shown. Among them, the terminal 102 communicates with the server 104 through the network. The data storage system can store data that the server 104 needs to process. The data storage system can be integrated on the server 104, or it can be placed on the cloud or other network servers. The server 104 constructs a microgrid architecture model of the photovoltaic storage direct and flexible park according to the equipment power consumption characteristics of the photovoltaic storage direct and flexible park and the power resource scheduling information; according to the equipment operation characteristics of each power equipment in the photovoltaic storage direct and flexible park, the corresponding equipment operation model of each power equipment is constructed; according to the microgrid architecture model and each equipment operation model, the adjustable load orderly energy consumption objective function and the park equipment operation constraints of the photovoltaic storage direct and flexible park are constructed; with the park equipment operation constraints as the limitation, the adjustable load orderly energy consumption objective function is solved to obtain the adjustable load orderly energy consumption adjustment information of the photovoltaic storage direct and flexible park; the adjustable load orderly energy consumption adjustment information is used to adjust the power resource allocation of the photovoltaic storage direct and flexible park. The terminal 102 may be, but is not limited to, various personal computers, laptops, smart phones, tablet computers, IoT devices, and portable wearable devices. The IoT devices may be smart speakers, smart TVs, smart air conditioners, smart car-mounted devices, etc. The portable wearable devices may be smart watches, smart bracelets, head-mounted devices, etc. The server 104 may be implemented as an independent server or a server cluster consisting of multiple servers.

[0044] In an exemplary embodiment, Figure 2 As shown, a method for orderly energy use of loads in a photovoltaic storage and direct-flexible park is provided, and this method is applied to Figure 1 The server in the example is used to illustrate, including the following steps 202 to 208. Among them:

[0045] Step 202, construct a microgrid architecture model of the photovoltaic, storage, direct and flexible park based on the equipment power consumption characteristics and power resource scheduling information of the photovoltaic, storage, direct and flexible park.

[0046] Among them, the photovoltaic storage direct and flexible park can be a park with a comprehensive energy system that integrates photovoltaic power generation (photovoltaic), energy storage system (storage), DC transmission and distribution (direct), flexible load management (flexible) and other technologies. It uses photovoltaic system power generation and energy storage system to adjust the balance of power supply and demand, and combines intelligent scheduling and flexible load control to achieve self-sufficiency and efficient use of electricity in the park.

[0047] Among them, equipment power consumption characteristics can refer to the power demand and consumption characteristics of various power equipment in the park during operation, including power demand, start and stop time, load changes, and energy consumption characteristics. These characteristics can help formulate power dispatch plans to ensure the stability and efficiency of power supply.

[0048] Among them, power resource dispatch information may refer to the allocation and management data of power resources inside and outside the park, including information such as photovoltaic power generation, energy storage system power, load demand and power supply capacity of the power grid.

[0049] Among them, the microgrid architecture model can be a systematic modeling of the power system in the park, including the connection between the photovoltaic power generation system, energy storage system, various load equipment and power dispatching system. This model is used to describe the flow and dispatching mode of electricity in the park to ensure efficient and reliable operation of the power system.

[0050] Specifically, according to the power consumption characteristics of the equipment in the photovoltaic, storage, direct and flexible park and the power resource scheduling information, it is necessary to classify the power consumption equipment in the park and understand the power consumption requirements and operating characteristics of various types of equipment. Combined with the power generation characteristics of the photovoltaic power generation and energy storage system in the park, a microgrid architecture model that can coordinate the management of various types of power resources is constructed. Specifically, the main components of the photovoltaic, storage, direct and flexible park are distributed photovoltaics, energy storage and power loads. The distributed photovoltaic equipment in the photovoltaic, storage, direct and flexible park is mainly used by users in the photovoltaic, storage, direct and flexible park; energy storage is mainly used to absorb excess photovoltaics and excess electricity generated in the photovoltaic, storage, direct and flexible park, and can use time-of-use electricity prices to purchase and store electricity at a lower price during valley hours, and release electricity for load use or sell electricity during peak hours to achieve energy arbitrage; power loads can be divided into adjustable loads and non-adjustable loads according to their flexibility. Some power loads cannot be interrupted for safety and technical reasons, such as life-sustaining equipment in hospitals, equipment in data centers, basic lighting, etc. Such loads are set as non-adjustable loads; some power loads, such as electric vehicles, air conditioning equipment, and some power equipment of household users, can be dispatched by the power grid and can increase or decrease power consumption in a short period of time to assist in balancing the supply and demand of the power grid. Such loads are adjustable loads. In the specific implementation process, electric vehicles and air conditioning equipment can be used as adjustable loads to obtain a microgrid architecture model.

[0051] Step 204: construct an equipment operation model corresponding to each power equipment according to the equipment operation characteristics of each power equipment in the solar-storage-direct-flexible park.

[0052] Among them, equipment operation characteristics can refer to the behavior of each power equipment in the park under different working conditions, including startup time, operating power, working cycle, and load change law, etc. These characteristics help to establish an accurate equipment operation model for better energy management and scheduling.

[0053] The equipment operation model can be a mathematical model built for each power equipment based on its operating characteristics, which is used to simulate the operating status of the equipment under different conditions. The model can predict the energy consumption, load fluctuation of the equipment and its impact on the power system, thereby providing support for the power dispatching of the park.

[0054] Specifically, a detailed power consumption analysis is performed on each power device in the photovoltaic storage direct and flexible park to obtain its energy consumption characteristics under different operating conditions, such as peak power, stable operating power, starting current, etc. Since the equipment operation model also needs to reflect its operating cycle and load change pattern, especially for equipment that starts and stops periodically or needs to be scheduled on time, such as air conditioners, cooling equipment, etc. Therefore, in constructing the equipment operation model, the impact of environmental factors (such as weather, temperature, etc.) on equipment operation should also be considered, especially for photovoltaic systems and energy storage systems. Weather conditions have a direct impact on their power generation and charging and discharging capabilities. In addition, the equipment operation model needs to integrate the equipment failure prediction mechanism to pre-judge the possible failure state of the equipment and avoid instability of the power system due to equipment abnormalities during the load scheduling process. The above three points are combined to construct the final equipment operation model.

[0055] Step 206, based on the microgrid architecture model and the operation models of each device, construct the adjustable load orderly energy consumption objective function of the photovoltaic storage direct-flexible park and the park equipment operation constraint conditions.

[0056] Among them, the objective function of orderly energy use of adjustable loads can be an optimization objective function for load scheduling of all equipment in the park, which aims to achieve the lowest operating cost, the smallest net load variance and the maximum satisfaction of various adjustable load energy use through reasonable allocation of photovoltaic power generation, energy storage system and grid power.

[0057] Among them, the park equipment operation constraints can refer to the technical and operational restrictions that need to be followed during equipment scheduling and load optimization, including the safe operating range of the equipment (such as power limit, start and stop frequency, etc.), the charging and discharging constraints of the energy storage system, and the power supply and demand balance conditions, etc. The constraints ensure that the technical limits of the equipment or system are not exceeded during the optimization scheduling process.

[0058] Specifically, when constructing the objective function of orderly energy use of adjustable loads, we must first clarify the optimization goal, that is, to maximize the energy efficiency of the park and minimize the electricity cost by reasonably dispatching the energy distribution between photovoltaics, energy storage and the power grid. This objective function is usually set to minimize the total electricity consumption cost or maximize the utilization rate of renewable energy. The objective function should comprehensively consider the electricity demand of different equipment, the power generation of renewable energy, the power of the energy storage system, and the fluctuation of the power price of the power grid. When constructing the objective function, it is expressed as a multi-objective optimization problem to balance the equipment operation efficiency, energy consumption and cost to obtain the objective function.

[0059] Regarding the construction of some constraints for the photovoltaic storage direct-flexible park, the first is the physical constraints of the electrical equipment. For example, the rated power of each electrical equipment cannot exceed its safe operating range. Some electrical equipment may have fixed start and stop time windows and cannot be adjusted at will. The second is that the charging and discharging rates of the energy storage system cannot exceed its technical specifications; the battery power cannot be overcharged or over-discharged. The third is to consider the limitations of the power supply of the power grid, such as the maximum power supply capacity of the power grid or the impact of peak and valley electricity prices. For some key equipment, its operation must be guaranteed and cannot be completely shut down. The fourth is to consider environmental constraints, such as the impact of weather changes on photovoltaic power generation, especially when photovoltaic power is insufficient and energy needs to be supplemented by energy storage or the power grid. Finally, multiple park equipment operation constraints are obtained.

[0060] Step 208, using the park equipment operation constraints as limitations, solve the adjustable load orderly energy consumption objective function to obtain the adjustable load orderly energy consumption adjustment information of the solar-storage-direct-flexible park.

[0061] Among them, the orderly energy adjustment information of adjustable loads can be a power dispatching plan obtained through an optimization algorithm, including information such as load distribution, start-stop strategy, and charging and discharging plan of the energy storage system for each device. These adjustment information is used to guide the power dispatching system of the park to minimize the park's operating costs, minimize the net load variance, and maximize the energy satisfaction of various adjustable loads.

[0062] Specifically, after setting the operating constraints of the park equipment as the limitation for solving the objective function of orderly energy consumption of adjustable loads, an appropriate optimization algorithm (such as dynamic programming, genetic algorithm, particle swarm optimization, etc.) is used to solve the objective function of orderly energy consumption of adjustable loads; the solution process requires real-time acquisition of dynamic information such as the operating status of power equipment, power demand, renewable energy generation, and energy storage device power, to perform global load optimization. During the calculation process, the system needs to evaluate the operating status of each power equipment in real time, and reasonably plan the start and stop sequence, operating power, and charging and discharging strategy of the energy storage system for each device to ensure the balance of power supply and demand. After the optimization is completed, the adjustable load orderly energy consumption adjustment information of the photovoltaic storage direct and flexible park is output. The adjustment information will be used to guide the park's power dispatching system to perform intelligent control of equipment, including dynamically adjusting equipment power, starting backup equipment, and executing the discharge operation of the energy storage system, thereby achieving efficient utilization of power resources.

[0063] In the above-mentioned method for orderly energy use of adjustable loads in a photovoltaic, storage, direct and flexible park, a microgrid architecture model of the photovoltaic, storage, direct and flexible park is constructed according to the power consumption characteristics of the equipment in the photovoltaic, storage, direct and flexible park and the power resource scheduling information; according to the equipment operation characteristics of each power equipment in the photovoltaic, storage, direct and flexible park, an equipment operation model corresponding to each power equipment is constructed; according to the microgrid architecture model and each equipment operation model, an adjustable load orderly energy use objective function and park equipment operation constraints of the photovoltaic, storage, direct and flexible park are constructed; with the park equipment operation constraints as limitations, the adjustable load orderly energy use objective function is solved to obtain the adjustable load orderly energy use adjustment information of the photovoltaic, storage, direct and flexible park; the adjustable load orderly energy use adjustment information is used to adjust the power resource allocation situation of the photovoltaic, storage, direct and flexible park.

[0064] By constructing the microgrid architecture model of the photovoltaic storage direct flexible park and the operation model of each power equipment, it is possible to accurately capture the power consumption characteristics and dynamic changes of various power equipment in the park, and optimize the operation mode of the power equipment in combination with the power resource dispatch information. By setting up the objective function of orderly energy consumption of adjustable loads and optimizing the solution with the equipment operation constraints as the boundary, this method can improve the user's satisfaction with the means of regulating and controlling adjustable loads, and effectively coordinate the balance between power generation and consumption of renewable energy (such as photovoltaic and energy storage systems), thereby maximizing the utilization rate of self-generation and reducing the demand for power purchases from the power grid. In addition, it can also enhance the park's ability to adapt to power fluctuations, reduce peak load pressure, reduce operating costs, and improve the stability and reliability of the system by dynamically adjusting load distribution, which not only improves the energy efficiency of the park, but also provides an important technical reference for the development of future smart microgrids.

[0065] In an exemplary embodiment, Figure 3 As shown, according to the microgrid architecture model and the operation models of each device, the adjustable load orderly energy use objective function of the photovoltaic storage direct-flexible park is constructed, including steps 302 to 306. Among them:

[0066] Step 302, according to the microgrid architecture model and the operation models of each device, the adjustable load orderly energy consumption target information of the objective function is set.

[0067] Among them, the adjustable load orderly energy consumption target information can be the information of the target direction that needs to be optimized according to the microgrid architecture and the operating characteristics of each device in the park, which is used to optimize the scheduling of equipment loads.

[0068] Specifically, based on the microgrid architecture model and equipment operation model, the time distribution of photovoltaic power generation in the park, the power generation curve, the charging and discharging strategy of the energy storage system, and the power requirements, start and stop time, operation cycle and other detailed information of each device are comprehensively analyzed. At the same time, the grid power purchase strategy must also be considered to prepare for timely replenishment when photovoltaic power generation is insufficient to ensure the continuity of the overall power supply in the park. Taking into account the volatility of renewable energy and the flexibility of each device, and setting a strategy of giving priority to the use of renewable energy and reasonably allocating loads, all the above information is combined to set the target information of the adjustable load orderly energy use of the objective function, that is, to clarify the adjustable load demand and the availability of power generation resources of the equipment in each time period.

[0069] Step 304, constructing the initial orderly energy consumption target function of the PV-storage-direct-flexible park based on the orderly energy consumption target information of the adjustable load.

[0070] Among them, the initial orderly energy consumption objective function can be a preliminary mathematical model constructed on the basis of the orderly energy consumption objective information of the adjustable load, aiming to optimize the load distribution of power equipment and the scheduling of power resources in the park.

[0071] Specifically, after setting detailed adjustable load and energy supply target information, the power demand and dispatchability of all equipment are modeled, and the association between each device and the coupling relationship between the equipment and the power supply source (such as photovoltaic power generation, energy storage system, and power grid) are established. Combined with the flexibility and constraints of equipment start and stop; for example, some equipment may have high scheduling flexibility and can be delayed or run in advance, while other key equipment must be operated during a specific time period and cannot be interrupted. At the same time, the charging and discharging strategy of the energy storage system should also be included in the design of the objective function to ensure that energy storage plays a buffering role when photovoltaic power generation fluctuates and the electricity price of the external power grid changes. After determining to maximize the use of renewable energy in the park and reduce the demand for electricity purchases from the external power grid by optimizing load distribution, it is necessary to consider reducing power losses while ensuring the normal operation of equipment, and construct the initial orderly energy use objective function.

[0072] Step 306, normalize the initial orderly energy consumption objective function to obtain the adjustable load orderly energy consumption objective function.

[0073] Specifically, each objective function is normalized, and the processing formula is as follows:

[0074]

[0075] F=c1F1+c2F2+c3F3

[0076] c1+c2+c3=1

[0077] Where: F nis the normalized value of the nth objective function, f n,min 、f n,max is the minimum and maximum value of the nth objective function, F is the normalized total objective function value, c1, c2, c3 are the weight coefficients set for each objective function. Through the above formulas, the objective function of orderly energy use of adjustable load is obtained.

[0078] In this embodiment, by setting the orderly energy consumption target information of the adjustable load according to the microgrid architecture model and the operation model of each device, and constructing the initial orderly energy consumption target function of the photovoltaic storage direct flexible park based on this, and then normalizing the target function, the energy consumption coordination and resource utilization efficiency of each device in the park can be significantly improved. The normalization process optimizes the optimization targets of different devices and loads on a unified scale, thereby ensuring that the system minimizes the overall electricity cost and optimizes the allocation of energy scheduling under the premise of meeting the power demand and various constraints.

[0079] In an exemplary embodiment, Figure 4 As shown, according to the microgrid architecture model and the operation model of each device, the adjustable load orderly energy consumption target information of the objective function is set, including steps 402 to 412. Among them:

[0080] Step 402: Define the distributed photovoltaic operation resource consumption according to the microgrid architecture model and the distributed photovoltaic equipment operation model.

[0081] Among them, the distributed photovoltaic equipment operation model can be a model used to simulate the operation of distributed photovoltaic equipment under different environmental conditions (such as light intensity, temperature, etc.). It takes into account the rated power and operating conditions of the equipment to evaluate and predict the performance of photovoltaic power generation in actual operation and provide support for power dispatching.

[0082] Among them, the distributed photovoltaic operating resource consumption can refer to the operating cost of photovoltaic equipment within a specific period of time, which is used to measure the contribution of photovoltaic power generation to the overall electricity consumption of the park and ensure the maximum utilization of photovoltaic energy to reduce dependence on the external power grid.

[0083] Specifically, according to the microgrid architecture model and the distributed photovoltaic equipment operation model, the power generation, power generation time and equipment power consumption of the photovoltaic system are analyzed. By evaluating the power generation efficiency of the photovoltaic equipment, the duration and angle of sunlight exposure, the energy output of the photovoltaic system in different time periods is calculated, and the operating cost of the distributed photovoltaic equipment is determined as the distributed photovoltaic operation resource consumption in combination with the distributed photovoltaic operation unit price.

[0084] Step 404 , defining the energy storage device operation source consumption according to the microgrid architecture model and the energy storage device operation model.

[0085] The energy storage device operating source consumption may refer to the cost of the energy storage device during operation. This value is used to measure the energy efficiency and operating cost of the energy storage device, and to help optimize the scheduling of the energy storage device in the power system to improve energy utilization and reduce consumption.

[0086] Specifically, the charging rate, energy storage capacity, and power loss of the energy storage device during discharge are evaluated based on the charging and discharging efficiency and power consumption of the energy storage device. Under different power supply and demand conditions, the charging and discharging strategies of the energy storage device will affect the scheduling of the overall power resources. Therefore, it is also necessary to consider the dynamic adjustment of the energy storage device operating source consumption, and determine the operating cost of the energy storage device as the energy storage device operating source consumption in combination with the unit price of energy storage device charging and discharging.

[0087] Step 406 , based on the microgrid architecture model and the power equipment operation model, define the power consumption of the power equipment operation source, the load power of the power equipment and each power consumption impact coefficient.

[0088] Among them, the equipment operation source consumption may refer to the operating cost of the electrical equipment during operation, including power consumption, heat dissipation loss, etc.

[0089] The load power of the electrical equipment refers to the actual power demand of the electrical equipment at a certain moment, reflecting the power load required by the equipment during operation. The load power is used for power dispatching and resource allocation to ensure that the power supply can meet the power demand of the equipment.

[0090] The power consumption impact coefficient refers to the degree of influence of power-consuming equipment on the overall power system, which is usually determined based on factors such as the power demand and operating status of the equipment. This coefficient is used to evaluate the priority of equipment in load scheduling, help optimize energy distribution, and ensure efficient use of power resources.

[0091] Specifically, based on the microgrid architecture model and the operation model of the power-consuming equipment, the operation cost of the power-consuming equipment is determined as the operation source consumption of each device according to the power resources consumed by each device during operation, combined with the time-of-use electricity price, the unit price of electric vehicle charging, and the unit price of air conditioning operation. At the same time, the load power of the power-consuming equipment is defined as the actual power demand of each device during operation, which is calculated based on information such as the working cycle of the equipment and the power demand curve. In addition, the power consumption impact coefficient of each device is defined to indicate the impact of the load regulation of the equipment on the overall system. For example, the start and stop of some equipment may cause large fluctuations in the system. The impact coefficient reflects the load balance impact of the equipment on the entire microgrid system.

[0092] Step 408, constructing the park operation resource consumption according to the distributed photovoltaic operation resource consumption, the energy storage equipment operation source consumption and the power equipment operation source consumption.

[0093] Specifically, the various defined parameters from step 402 to step 406 are integrated to form the park operation resource consumption, that is, the park operation cost f1, which includes the distributed photovoltaic power generation operation cost, the energy storage equipment operation cost, the external power purchase and sale cost, the electric vehicle charging cost, and the air conditioning equipment operation cost:

[0094]

[0095] L t =(MW)-3.05[5.733-0.007(MW)-P a ]-0.42(MW-58.15)-1.73×10 -2 M(5.867-P a )-1.4×10 -3 M(34-T in,t )-3.96×10 -8 f cl [(t cl +273) 4 -(t r +273) 4 ]-f cl h c (t cl -T in,t )

[0096] Where: r pv 、r ES 、r e,t 、r ev 、r ac is the unit price of distributed photovoltaic operation, the unit price of energy storage equipment charging and discharging, the time-of-use electricity price at time t, the unit price of electric vehicle charging, and the unit price of air conditioning operation. buy,t , P sel；,t is the power purchased and sold from the external power grid at time t. t The expression of L t is the heat load of the user's body at time t, W is the mechanical work done by the human body, P a is the partial pressure of water vapor around the human body, T in,t is the indoor temperature at time t, f cl is the clothing area coefficient, t cl is the average temperature of the outer surface of the garment, t r is the average radiation temperature of the environment, h c is the convective heat transfer coefficient.

[0097] Step 410: construct a net load variance according to the load power of the electrical equipment.

[0098] Among them, net load variance can be an indicator to measure the difference fluctuation between actual load and predicted load in the power system. The smaller the variance, the more accurate the load forecast and the more efficient the system scheduling and allocation. It is used to evaluate the load balance of the power system and help optimize the power scheduling strategy.

[0099] Specifically, the net load variance f2 describes the fluctuation degree of the park's optimized operation, and is also an indicator of the adjustable load's participation in regulation. The smaller the net load variance, the more stable the park's operation.

[0100]

[0101] Where: P Load,t is the actual load power at time t, is the total load after the adjustable load participates in regulation, P Load,plan,t is the total load power consumption of the day-ahead dispatch plan at time t, which is predicted from historical data.

[0102] Step 412: constructing adjustable load energy evaluation information based on each power consumption impact coefficient and the load power of the power-consuming equipment.

[0103] The load adjustment energy consumption evaluation information may be satisfaction information on the adjustable load. The higher the satisfaction, the more it conforms to the interests of the user.

[0104] Specifically, the adjustable load energy evaluation information f3 includes the electric vehicle charging benefit satisfaction f ev Thermal comfort satisfaction of air-conditioning users ac The higher the satisfaction, the more it conforms to the interests of users.

[0105] f3=f ev +f ac

[0106]

[0107] As mentioned above, each electricity consumption impact coefficient can be expressed by the following formula:

[0108] L t =(MW)-3.05[5.733-0.007(MW)-P a ]-0.42(MW-58.15)-1.73×10 -2 M(5.867-P a )-1.4×10 -3 M(34-T in,t )-3.96×10 -8 f cl [(t cl +273) 4 -(t r +273)4 ]-f cl h c (t cl -T in,t )

[0109] Where: a, b are the electric vehicle charging preference coefficients, M is the human energy metabolism rate, L t is the heat load of the user's body at time t, W is the mechanical work done by the human body, P a is the partial pressure of water vapor around the human body, T in,t is the indoor temperature at time t, f cl is the clothing area coefficient, t cl is the average temperature of the outer surface of the garment, t r is the average radiation temperature of the environment, h c is the convective heat transfer coefficient.

[0110] In this embodiment, by defining the operating resource consumption of distributed photovoltaic, energy storage equipment and power equipment based on the microgrid architecture model, and combining the load power and influence coefficient of the power equipment to construct the overall operating resource consumption and net load variance of the park, the energy consumption evaluation and optimization scheduling accuracy of various equipment in the park can be effectively improved. By comprehensively considering the consumption characteristics and load power of each device, the system can more accurately predict and optimize energy consumption distribution, thereby achieving a more balanced and efficient energy use strategy among different devices, maximizing the energy utilization of the park and reducing operating costs.

[0111] In an exemplary embodiment, Figure 5 As shown, based on the microgrid architecture model and the operation models of each device, the operation constraints of the equipment in the photovoltaic storage direct-flexible park are constructed, including steps 502 to 508. Among them:

[0112] Step 502: setting photovoltaic power generation constraints according to power limitation information in the photovoltaic equipment operation model.

[0113] The power limit information may refer to the limit conditions on the maximum power output or input of the photovoltaic equipment. These limits may come from the rated power of the equipment, line capacity, safe operation standards, etc., and are used to ensure the stable operation of the power system and avoid overload.

[0114] Among them, photovoltaic power generation constraints can refer to the limiting factors that the photovoltaic system is subject to during the power generation process, including weather conditions (such as sunlight intensity, temperature, etc.), equipment power generation capacity, grid connection requirements, etc. These factors will affect the power generation output of the photovoltaic system.

[0115] Specifically, the constraint for distributed photovoltaic power generation is that the distributed photovoltaic power generation power is not greater than the maximum power. Therefore, according to the power limit information in the photovoltaic equipment operation model, the photovoltaic power generation constraint can be given. The specific expression is as follows:

[0116] 0≤P pv,t ≤P pv,max

[0117] Where: P pv,max It is the maximum value of photovoltaic power generation.

[0118] Step 504 : setting a power resource interaction power constraint according to the power reserve and power interaction power of the energy storage device operation model at different times.

[0119] Among them, power interaction power can refer to the power exchange or transmission between different power systems or different devices of energy storage devices. It is usually used to describe the power dispatch and power flow between parks, regions or power grids to achieve energy optimization and power balance.

[0120] Among them, the power resource interaction power constraint may refer to the restrictive conditions that the energy storage device must follow when exchanging power between power systems or microgrids, which may involve the capacity of the energy storage device, the load capacity of the energy storage device, the power carrying capacity of the transmission line, etc.

[0121] Specifically, the power of the energy storage device is limited by its capacity, and the charging and discharging power is related to the power in the previous period. Therefore, the shock capacity and the charging and discharging power are limited for the energy storage device at the same time. Therefore, according to the reserve power and power interaction power of the energy storage device operation model at different times, the power resource interaction power constraint can be obtained. The specific expression is as follows:

[0122] 0≤S ES,t ≤S ES,max

[0123] 0≤P dis,t+1 ≤S ES,t

[0124] 0≤P cha,t+1 ≤SES,t ES,max

[0125] Where: S ES,max is the maximum storage capacity of the energy storage device, P dis,t+1 , P cha,t+1 are the discharge power and charging power at time t+1.

[0126] Step 506 : according to the power information and temperature information of the electric equipment in the operation model of the electric equipment, the charging constraint of the electric equipment, the temperature constraint of the electric equipment and the capacity constraint of the electric equipment are set.

[0127] The power information of the electrical equipment may refer to the power data of the electrical equipment during operation, including instantaneous power and cumulative power, which is used to monitor the energy consumption and efficiency of the equipment for energy management and optimization.

[0128] The temperature information of the electrical equipment may refer to the real-time monitoring data of the equipment temperature, the equipment cavity temperature, and the equipment external environment temperature during the operation of the equipment. These data can be used to prevent the equipment from overheating, ensure the normal operation of the equipment, extend the service life of the equipment, and ensure safety.

[0129] Among them, the charging constraints of the electric device may refer to the rules and restrictions that must be followed when charging the electric device, such as charging speed, charging current, charging time, etc., to ensure safety, extend battery life, and prevent overcharging or overheating.

[0130] The temperature constraint of the electrical device may refer to that during the operation or charging of the electrical device, the device temperature, the device cavity temperature and the device external environment temperature cannot exceed the set upper and lower limits.

[0131] The capacity constraint of the power-consuming device may refer to the maximum capacity limit that the power-consuming device can carry. When the device is actually running, it cannot exceed its capacity limit to prevent the device from being overloaded or damaged.

[0132] Specifically, since the electrical equipment needs to meet a certain power range during the charging process, and the electrical equipment needs to reflect certain constraints during use according to the use environment and the power range during use to ensure and utilize electricity; therefore, based on the electrical equipment power information and electrical equipment temperature information of the electrical equipment operation model, the electrical equipment charging constraints, electrical equipment temperature constraints and electrical equipment capacity constraints can be set.

[0133] Among them, setting the charging constraints of power-consuming equipment, that is, setting the charging constraints of electric vehicles:

[0134] 0≤P ev,t ≤H×P ev,fast

[0135] Where: H is the number of charging piles in the park.

[0136] Set the temperature constraint of the electrical equipment, that is, the air conditioner operation is subject to the temperature range set indoors; set the capacity constraint of the electrical equipment, that is, the air conditioner installed capacity constraint:

[0137] T in,min ≤T in,t ≤T in,max

[0138] 0≤P ac,t ≤P ac,max

[0139] Where: T in,min , T in,max The minimum and maximum values ​​for the indoor temperature setting, P ac,max It is the maximum installed capacity of the air conditioner.

[0140] Step 508, setting the park power balance constraint according to the photovoltaic equipment operation model, the energy storage equipment operation model and the power equipment operation model.

[0141] The park power balance constraint refers to the balance constraint between power supply and power demand in the park, requiring the park's total power generation, energy storage power, and external power supply to be balanced with the power demand of all power-consuming devices to ensure stable operation of the power system.

[0142] Specifically, the power supply in the park should be greater than the power demand. Therefore, under the corresponding constraints of the photovoltaic equipment operation model, the energy storage equipment operation model and the power consumption equipment operation model, the power balance constraints of the park are as follows:

[0143] P pv,t +P dis,t +P buy,t ≥P ev,t +P ac,t +P un,t +P cha,t +P sell,t

[0144] In this embodiment, by setting photovoltaic power generation constraints according to the power limit information of photovoltaic equipment, setting power resource interaction power constraints according to the reserve power and power interaction power of energy storage equipment, and setting charging, temperature and capacity constraints in combination with the power, temperature and capacity information of power-consuming equipment, it is possible to ensure that the entire park power system can achieve safe and efficient power distribution under various equipment operating conditions. Through the precise setting of these constraints, the system can not only optimize energy use on the basis of ensuring stable operation of equipment, but also ensure the balance of power supply and demand in the entire park through power balance constraints, maximize energy utilization and reduce unnecessary power waste.

[0145] In an exemplary embodiment, Figure 6 As shown, taking the operation constraint of the park equipment as a limitation, solving the objective function of the orderly energy use of the adjustable load, and obtaining the orderly energy use adjustment information of the adjustable load of the solar-storage-direct-flexible park, including steps 602 to 606. Among them:

[0146] Step 602, using the predicted electric load data corresponding to any period of the PV-storage-direct-flexible park and the time-sharing power resource interaction information, define the application parameters of the adjustable load orderly energy utilization objective function to obtain the defined load orderly energy utilization objective function.

[0147] Among them, the predicted electricity load data can be an estimate of the electricity demand in a specific period of time in the future based on historical electricity consumption, weather changes, production plans and other factors.

[0148] Among them, time-sharing power resource interaction information can refer to the power exchange between the park and external power resources in different time periods, which is usually related to the time-sharing electricity price. This information includes the input, output and price changes of power resources in a certain period of time, which is used to optimize the power consumption decision and resource scheduling of the park.

[0149] Among them, defining the load orderly energy utilization objective function may refer to constructing a mathematical model for optimizing equipment power output and load distribution based on actual power demand, equipment characteristics and related constraints.

[0150] Specifically, the power demand and resource supply of each time period are evaluated by using the predicted electric load data corresponding to each time period and the interactive information of electric power resources (such as the power exchange with the external power grid). The application parameters of the orderly energy use objective function of the adjustable load are defined, including adjustable and non-adjustable loads, start and stop time, load distribution weight, priority of interaction with other electric power resources, input of time-of-use electricity price, input of capacity parameters, operation parameters, cost parameters of each device, etc. By constructing the load orderly energy use objective function, the intelligent scheduling of the adjustable load is realized to ensure that the adjustable load is used first when the electricity price is low or the resources are abundant, so as to maximize cost savings and improve the utilization efficiency of electric power resources on the basis of ensuring the power demand. In an application example, the 24-hour predicted electric load data of a solar storage direct and flexible park is input, including adjustable loads and non-adjustable loads; the time-of-use electricity price is input, and the capacity parameters, operation parameters, and cost parameters of each device are input.

[0151] Step 604, based on photovoltaic power generation constraints, power resource interaction power constraints, power equipment charging constraints, power equipment temperature constraints, power equipment capacity constraints and park power balance constraints, determine the boundary ranges of the load orderly energy utilization objective function to be solved, and obtain the load orderly energy utilization objective function to be solved.

[0152] The boundary range may be a computational constraint condition for the objective function.

[0153] Among them, the objective function for solving the orderly energy consumption of loads may be an objective function with defined boundary conditions, and an optimization algorithm (such as linear programming or mixed integer programming) may be used to find a solution that optimizes the objective function value within the constraints.

[0154] Specifically, through various constraints (such as photovoltaic power generation constraints, power resource interaction power constraints, power equipment charging constraints, power equipment temperature constraints, power equipment capacity constraints, and park power balance constraints, etc.), the output range of each power equipment and the adjustment range of the adjustable load are determined. These boundary ranges not only define the physical limits of the equipment, but also ensure the safety and stability of the system during operation. For example, the output of photovoltaic power generation equipment is subject to weather conditions and cannot exceed the rated power generation capacity of the equipment; when charging energy storage equipment, the power must not exceed the maximum allowable charging rate, and the temperature needs to be controlled within a safe range to prevent overheating and damage to the equipment.

[0155] Based on these boundary ranges, the real-time power demand and time-of-use electricity prices are dynamically evaluated, and the power output and load adjustment order of the equipment are intelligently adjusted. For example, during periods of low electricity prices, the system may give priority to increasing the power consumption of adjustable loads and reducing power consumption during periods of high electricity prices; conversely, the system may reduce unnecessary load output when electricity prices are high, give priority to the use of energy storage equipment, or adjust equipment operation strategies. The goal of the entire process is to maximize the economic benefits of electricity consumption and equipment operation efficiency within the park while meeting all constraints, while avoiding problems such as equipment overload, overheating, or imbalance in the power system. Finally, on this basis, a load orderly energy consumption objective function to be solved is generated.

[0156] Step 606, use the power resource solver of the photovoltaic storage direct-flexible park to solve the load orderly energy consumption objective function to be solved, and obtain the adjustable load orderly energy consumption adjustment information.

[0157] Among them, the power resource solver can be a mathematical optimization tool for handling complex power scheduling problems, which can efficiently solve optimization problems involving power load, equipment output and constraints.

[0158] Specifically, the load orderly energy consumption objective function is normalized to ensure that different variables and constraints have a unified dimension for optimization and solution. Use a power resource solver (such as a large-scale mathematical programming optimization solver) as a power resource optimization tool, and input the processed objective function and its constraints. The large-scale mathematical programming optimization solver uses efficient mathematical optimization algorithms (such as linear programming, mixed integer programming, etc.) to calculate and solve the optimal output plan for each device based on the real-time power demand of the park, the output range of the equipment, the adjustable load power adjustment range, and other constraints (such as photovoltaic power generation constraints, power resource interaction power, etc.), and finally obtains the adjustable load orderly energy consumption adjustment information in each time period.

[0159] In this embodiment, by combining the predicted electric load data of the photovoltaic storage direct-flexible park and the time-sharing power resource interaction information, the application parameters of the adjustable load orderly energy use objective function are defined, and the boundary range of the objective function is determined according to the photovoltaic power generation constraints, the power resource interaction power constraints, the charging, temperature and capacity constraints of the power-consuming equipment, and the power balance constraints of the park. Finally, the power resource solver is used for optimization and solution, which can not only significantly improve the energy management efficiency in the park, but also dynamically adjust the power output in each time period, ensuring the optimal scheduling and allocation of energy on the basis of meeting all constraints, reducing energy waste, optimizing electricity costs, and ensuring the safe and stable operation of equipment.

[0160] In an exemplary embodiment, Figure 7 As shown, the power equipment includes a distributed photovoltaic power generation model, a charging and discharging power model, and a power load dynamic model; according to the equipment operation characteristics of each power equipment in the photovoltaic storage direct and flexible park, the equipment operation model corresponding to each power equipment is constructed, including steps 702 to 706. Among them:

[0161] Step 702: construct a distributed photovoltaic power generation model according to the rated value of the photovoltaic power generation equipment, the light intensity and the ambient temperature.

[0162] Among them, the equipment's own rated value may refer to the rated or maximum power or capacity that the photovoltaic power generation equipment can continuously output or process under normal operating conditions. This is a safe operating parameter specified by the equipment manufacturer based on its design and testing, and is used to ensure that the equipment can operate for a long time at this rated value without damage or failure.

[0163] Specifically, since the distributed photovoltaic power generation power is related to the rated value of the equipment itself, the light intensity and the ambient temperature, the expression of the distributed photovoltaic power generation model constructed according to the rated value of the photovoltaic power generation equipment itself, the light intensity and the ambient temperature is as follows:

[0164]

[0165] Where: P pv is the actual power of photovoltaic power generation, P pv,test is the maximum power generation of the photovoltaic device under standard test conditions, I out is the actual outdoor light intensity, I test The light intensity under standard test environment is generally 1kW / m 2 ;k p is the power temperature coefficient of photovoltaic power generation, generally taken as 0.004, T out is the actual outdoor temperature, T test It is the temperature under standard test environment, usually 25℃.

[0166] Step 704, constructing a charging and discharging power model according to the inherent capacity of the energy storage device, the equipment operating efficiency, the relationship between the energy storage capacity and time.

[0167] The inherent capacity of the device may refer to the maximum available capacity or storage capacity determined during the design and manufacturing process of the energy storage device.

[0168] Among them, the equipment operating efficiency can be the effectiveness ratio of the energy storage device in converting input energy into output power during operation, usually expressed as a percentage. A higher operating efficiency means that the device can effectively convert more input energy into useful output and reduce energy loss.

[0169] The relationship between energy storage capacity and time reflects the change of energy over time during the charging and discharging process of the energy storage device, which is usually determined by the charging rate, discharging rate, energy storage capacity and time of the device. This relationship can be used to evaluate the energy storage status and usage of energy storage devices in different time periods to ensure the reasonable scheduling and optimal utilization of the energy storage system.

[0170] Specifically, since the charging and discharging power of the energy storage device is affected by its own capacity and equipment efficiency, and in actual operation, the amount of energy stored at a certain moment is related to the previous moment, the expression of the charging and discharging power model constructed based on the relationship between the inherent capacity of the energy storage device, the equipment operation efficiency, the energy storage amount and time is as follows:

[0171]

[0172] Where: S ES,t+1 , S ES,t is the power of the energy storage device at time t+1 and time t, P cha,t , P dis,t is the charging and discharging power of the energy storage device at time t; η cha , η dis Charging and discharging efficiency of energy storage devices.

[0173] Step 706, constructing a dynamic model of power load according to the fast charging power, slow charging power, and power consumption of the power-consuming equipment.

[0174] Specifically, since the power load dynamic model is related to the fact that the power load can be divided into adjustable load and non-adjustable load, the charging of electric vehicles is mainly divided into fast charging and slow charging modes, and the power consumption of air conditioners affected by outdoor and indoor temperatures, the power load dynamic model constructed based on the fast charging power, slow charging power, and equipment power consumption of the power equipment includes the following formulas:

[0175] Among them, the power load can be divided into adjustable load and non-adjustable load:

[0176] P Load,t =P un,t +(P ev,t +P ac,t )

[0177] Where: P Load,t , P un,t , P ev,t , P ac,t It is the total power of power load, power of non-adjustable load, power of electric vehicle charging and power of air conditioner at time t.

[0178] Among them, electric vehicle charging is mainly divided into fast charging and slow charging modes:

[0179]

[0180] Where: N is the number of electric vehicles connected to the charging station at time t, P ev,fast , P ev,slow Fast charging and slow charging power of electric vehicles, X ev,n is the fast charging mark of the nth electric vehicle, X ev,n When it is 1, the current time is fast charging mode, X ev,n When it is 0, the current moment is in slow charging mode.

[0181] Among them, the air conditioning load provides cooling capacity through electric refrigeration. The park can issue dispatching instructions to regulate the air conditioning load through air conditioning load aggregators and other channels to increase or reduce the power consumption of air conditioning. Generally, when the outdoor temperature is higher than the indoor temperature, the air conditioning starts to run. The power consumption of the air conditioning is mainly related to the outdoor and indoor temperatures:

[0182]

[0183] Where: T out,t , T set,t is the outdoor temperature at time t and the indoor set temperature, λ is the air conditioning energy efficiency coefficient, and R is the equivalent thermal resistance of the building.

[0184] In this embodiment, by constructing a distributed photovoltaic power generation model based on the rated value, light intensity and ambient temperature of the photovoltaic power generation equipment, and combining the inherent capacity, operating efficiency and the relationship between the energy storage capacity and time of the energy storage equipment to construct a charging and discharging power model, and then constructing a power load dynamic model based on the fast charging power, slow charging power and power consumption of the power equipment, it is possible to achieve accurate power prediction and dynamic load management for various types of equipment in the park. The beneficial effect of this process is that the system can optimize the power scheduling of photovoltaic power generation and energy storage equipment according to real-time conditions, flexibly adjust the charging strategy of power equipment, improve energy utilization efficiency, reduce electricity costs, and ensure the overall balance and stable operation of the power system.

[0185] It should be understood that, although the steps in the flowcharts involved in the above embodiments are displayed in sequence according to the indication of the arrows, these steps are not necessarily executed in sequence according to the order indicated by the arrows. Unless there is a clear explanation in this article, the execution of these steps is not strictly limited in order, and these steps can be executed in other orders. Moreover, at least a part of the steps in the flowcharts involved in the above embodiments may include multiple steps or multiple stages, and these steps or stages are not necessarily executed at the same time, but can be executed at different times, and the execution order of these steps or stages is not necessarily carried out in sequence, but can be executed in turn or alternately with other steps or at least a part of the steps or stages in other steps.

[0186] Based on the same inventive concept, the embodiment of the present application also provides a photovoltaic storage direct and flexible park adjustable load orderly energy use device for realizing the photovoltaic storage direct and flexible park adjustable load orderly energy use method involved in the above. The implementation scheme for solving the problem provided by the device is similar to the implementation scheme recorded in the above method, so the specific limitations in one or more photovoltaic storage direct and flexible park adjustable load orderly energy use device embodiments provided below can refer to the above limitations on a photovoltaic storage direct and flexible park adjustable load orderly energy use method, which will not be repeated here.

[0187] In an exemplary embodiment, Figure 8 As shown, a photovoltaic storage direct-flexible park load adjustable orderly energy use device is provided, including: a model building module 802, a condition determination module 804 and a function solving module 806, wherein:

[0188] Model building module 802, used to build a microgrid architecture model of the photovoltaic storage direct and flexible park according to the equipment power consumption characteristics and power resource scheduling information of the photovoltaic storage direct and flexible park;

[0189] The model building module 802 is also used to build a device operation model corresponding to each power device according to the device operation characteristics of each power device in the photovoltaic storage direct and flexible park;

[0190] The condition determination module 804 is used to construct the adjustable load orderly energy use objective function and the park equipment operation constraint conditions of the photovoltaic storage direct and flexible park according to the microgrid architecture model and the operation model of each device;

[0191] The function solving module 806 is used to solve the objective function of the orderly energy consumption of the adjustable load with the operation constraints of the park equipment as the limitation, and obtain the orderly energy consumption adjustment information of the adjustable load of the photovoltaic, storage, direct and flexible park; the orderly energy consumption adjustment information of the adjustable load is used to adjust the power resource allocation situation of the photovoltaic, storage, direct and flexible park.

[0192] In one embodiment, the condition determination module 804 is also used to set the adjustable load orderly energy consumption target information of the objective function according to the microgrid architecture model and the operation models of each device; construct the initial orderly energy consumption target function of the photovoltaic storage direct and flexible park according to the adjustable load orderly energy consumption target information; normalize the initial orderly energy consumption target function to obtain the adjustable load orderly energy consumption target function.

[0193] In one embodiment, the condition determination module 804 is also used to define the distributed photovoltaic operation resource consumption according to the microgrid architecture model and the distributed photovoltaic equipment operation model; define the energy storage equipment operation source consumption according to the microgrid architecture model and the energy storage equipment operation model; define the power equipment operation source consumption, the power equipment load power and each power consumption impact coefficient according to the microgrid architecture model and the power equipment operation model; construct the park operation resource consumption according to the distributed photovoltaic operation resource consumption, the energy storage equipment operation source consumption and the power equipment operation source consumption; construct the net load variance according to the power equipment load power; and construct the adjustable load energy consumption evaluation information according to each power consumption impact coefficient and the power equipment load power.

[0194] In one embodiment, the condition determination module 804 is also used to set photovoltaic power generation constraints based on the power limit information in the photovoltaic equipment operation model; set power resource interaction power constraints based on the reserve power and power interaction power of the energy storage equipment operation model at different times; set power equipment charging constraints, power equipment temperature constraints and power equipment capacity constraints based on the power equipment power information and power equipment temperature information of the power equipment operation model; set park power balance constraints based on the photovoltaic equipment operation model, the energy storage equipment operation model and the power equipment operation model.

[0195] In one embodiment, the function solving module 806 is also used to use the predicted electric load data corresponding to any time period of the photovoltaic storage direct and flexible park and the time-sharing power resource interaction information to define the application parameters of the adjustable load orderly energy utilization objective function, and obtain the defined load orderly energy utilization objective function; determine the boundary ranges of the defined load orderly energy utilization objective function based on photovoltaic power generation constraints, power resource interaction power constraints, power consumption equipment charging constraints, power consumption equipment temperature constraints, power consumption equipment capacity constraints and park power balance constraints, and obtain the load orderly energy utilization objective function to be solved; use the power resource solver of the photovoltaic storage direct and flexible park to solve the load orderly energy utilization objective function to be solved, and obtain the adjustable load orderly energy utilization adjustment information.

[0196] In one embodiment, the model building module 802 is also used to build a distributed photovoltaic power generation model based on the equipment rating, light intensity and ambient temperature of the photovoltaic power generation equipment; to build a charging and discharging power model based on the equipment inherent capacity, equipment operating efficiency, and the relationship between the energy storage device and time; and to build a dynamic model of power load based on the fast charging power, slow charging power and power consumption of the power-consuming equipment.

[0197] Each module in the above-mentioned photovoltaic storage direct-flexible park adjustable load orderly energy use device can be fully or partially implemented by software, hardware and their combination. The above-mentioned modules can be embedded in or independent of the processor in the computer device in the form of hardware, or can be stored in the memory of the computer device in the form of software, so that the processor can call and execute the corresponding operations of the above modules.

[0198] In an exemplary embodiment, a computer device is provided. The computer device may be a server, and its internal structure diagram may be as shown in FIG. Fig. 9 As shown. The computer device includes a processor, a memory, an input / output interface (Input / Output, referred to as I / O) and a communication interface. The processor, the memory and the input / output interface are connected through a system bus, and the communication interface is connected to the system bus through the input / output interface. 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, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store server data. The input / output interface of the computer device is used to exchange information between the processor and an external device. The communication interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, a method for orderly energy use of adjustable loads in a photovoltaic storage direct and flexible park is implemented.

[0199] Those skilled in the art will understand that Fig. 9 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 those shown in the figure, or combine certain components, or have a different arrangement of components.

[0200] In one embodiment, a computer device is further provided, including a memory and a processor, wherein a computer program is stored in the memory, and the processor implements the steps in the above method embodiments when executing the computer program.

[0201] In one embodiment, a computer-readable storage medium is provided, storing a computer program, which implements the steps in the above method embodiments when executed by a processor.

[0202] In one embodiment, a computer program product or computer program is provided, the computer program product or computer program includes computer instructions, the computer instructions are stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium, and the processor executes the computer instructions, so that the computer device performs the steps in the above-mentioned method embodiments.

[0203] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with relevant regulations.

[0204] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed 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 the memory, database or other medium used in the embodiments provided in the present application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetoresistive random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. 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). The database involved in each embodiment provided in this application may include at least one of a relational database and a non-relational database. Non-relational databases may include distributed databases based on blockchains, etc., but are not limited to this. The processor involved in each embodiment provided in this application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, etc., but are not limited to this.

[0205] The technical features of the above embodiments may 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.

[0206] The above-described embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the present application. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the attached claims.

Claims

1. A method for orderly energy use of adjustable loads in a photovoltaic storage direct and flexible park, characterized in that: The method comprises: According to the power consumption characteristics of the equipment in the photovoltaic, storage, direct and flexible park and the power resource scheduling information, a microgrid architecture model of the photovoltaic, storage, direct and flexible park is constructed; According to the equipment operation characteristics of each power equipment in the solar-storage-direct-flexible park, construct an equipment operation model corresponding to each power equipment; According to the microgrid architecture model and the operation models of each device, an adjustable load orderly energy utilization objective function and park equipment operation constraint conditions of the photovoltaic storage direct-flexible park are constructed; Taking the operation constraints of the park equipment as the limitation, the objective function of the adjustable load orderly energy consumption is solved to obtain the adjustable load orderly energy consumption adjustment information of the photovoltaic, storage, direct and flexible park; the adjustable load orderly energy consumption adjustment information is used to adjust the power resource allocation of the photovoltaic, storage, direct and flexible park.

2. The method according to claim 1, characterized in that According to the microgrid architecture model and the operation models of each device, the adjustable load orderly energy use objective function of the photovoltaic storage direct-flexible park is constructed, including: According to the microgrid architecture model and the operation models of each device, setting the adjustable load orderly energy consumption target information of the objective function; According to the orderly energy consumption target information of the adjustable load, constructing the initial orderly energy consumption target function of the solar-storage direct-flexible park; The initial orderly energy consumption objective function is normalized to obtain the adjustable load orderly energy consumption objective function.

3. The method according to claim 2, characterized in that The equipment operation model includes a distributed photovoltaic equipment operation model, an energy storage equipment operation model, and an electrical equipment operation model; the adjustable load orderly energy consumption target information includes park operation resource consumption, net load variance, and adjustable load energy consumption evaluation information; The step of setting the adjustable load orderly energy consumption target information of the objective function according to the microgrid architecture model and each of the equipment operation models includes: Defining the distributed photovoltaic operation resource consumption according to the microgrid architecture model and the distributed photovoltaic equipment operation model; Defining energy storage device operation source consumption according to the microgrid architecture model and the energy storage device operation model; According to the microgrid architecture model and the power equipment operation model, define the power equipment operation source consumption, power equipment load power and each power consumption impact coefficient; Constructing the park operation resource consumption according to the distributed photovoltaic operation resource consumption, the energy storage device operation source consumption and the power equipment operation source consumption; Constructing the net load variance according to the load power of the electrical equipment; The adjustable load energy evaluation information is constructed according to each of the electricity consumption impact coefficients and the load power of the electrical equipment.

4. The method according to claim 1, characterized in that: The equipment operation model includes a distributed photovoltaic equipment operation model, an energy storage equipment operation model and an electric equipment operation model; the equipment operation constraint conditions include photovoltaic power generation constraint conditions, power resource interaction power constraint conditions, electric equipment charging constraint conditions, electric equipment temperature constraint conditions, electric equipment capacity constraint conditions and park power balance constraint conditions; The park equipment operation constraint conditions of the solar-storage direct-flexible park are constructed according to the microgrid architecture model and each of the equipment operation models, including: Setting the photovoltaic power generation constraint according to the power limitation information in the photovoltaic equipment operation model; According to the reserve power and the power interaction power of the energy storage device operation model at different times, setting the power resource interaction power constraint; According to the power information of the electric device and the temperature information of the electric device of the operation model of the electric device, setting the charging constraint of the electric device, the temperature constraint of the electric device and the capacity constraint of the electric device; The park power balance constraint is set according to the photovoltaic equipment operation model, the energy storage equipment operation model and the power consumption equipment operation model.

5. The method according to claim 4, characterized in that The method of solving the objective function of orderly energy use of the adjustable load by taking the operation constraint condition of the park equipment as a limitation and obtaining the orderly energy use adjustment information of the adjustable load of the solar-storage direct-flexible park includes: Using the predicted electric load data corresponding to any period of the solar-storage-direct-flexible park and the time-sharing electric power resource interaction information, the application parameters of the adjustable load orderly energy utilization objective function are defined to obtain the defined load orderly energy utilization objective function; Determine the boundary ranges of the load orderly energy utilization objective function defined by the photovoltaic power generation constraint, the electric power resource interaction power constraint, the electric equipment charging constraint, the electric equipment temperature constraint, the electric equipment capacity constraint and the park power balance constraint, and obtain the load orderly energy utilization objective function to be solved; The power resource solver of the photovoltaic storage direct-flexible park is used to solve the load orderly energy utilization objective function to be solved and obtain the adjustable load orderly energy utilization adjustment information.

6. The method according to any one of claims 1 to 5, characterized in that: The power equipment includes a distributed photovoltaic power generation model, a charging and discharging power model, and a power load dynamic model; according to the equipment operation characteristics of each power equipment in the photovoltaic storage direct and flexible park, the equipment operation model corresponding to each power equipment is constructed, including: Constructing the distributed photovoltaic power generation model according to the rated value of the photovoltaic power generation equipment, the light intensity and the ambient temperature; Constructing the charging and discharging power model according to the inherent capacity of the energy storage device, the equipment operating efficiency, the energy storage capacity and the relationship between time; The power load dynamic model is constructed according to the fast charging power, slow charging power and power consumption of the power consuming equipment.

7. A photovoltaic storage direct and flexible park load adjustable orderly energy use device, characterized in that: The device comprises: A model building module, used to build a microgrid architecture model of the photovoltaic storage direct and flexible park according to the equipment power consumption characteristics and power resource scheduling information of the photovoltaic storage direct and flexible park; The model building module is also used to build a device operation model corresponding to each power device according to the device operation characteristics of each power device in the solar-storage-direct-flexible park; A condition determination module, used to construct an adjustable load orderly energy utilization objective function and park equipment operation constraint conditions of the photovoltaic storage direct and flexible park according to the microgrid architecture model and each of the equipment operation models; The function solving module is used to solve the adjustable load orderly energy consumption objective function based on the operation constraints of the park equipment, and obtain the adjustable load orderly energy consumption adjustment information of the photovoltaic, storage, direct and flexible park; the adjustable load orderly energy consumption adjustment information is used to adjust the power resource allocation of the photovoltaic, storage, direct and flexible park.

8. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 6 are implemented.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

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