Source network load storage integrated planning method and system

Abstract

The invention relates to a source network load storage integrated planning method and system. The method comprises the following steps: constructing a load model, an energy system model and a comprehensive energy station site selection model of a target area; based on the load model, the energy system model and the comprehensive energy station site selection model, constructing an energy system configuration model of the target area; and with maximum new energy consumption and minimum system operation cost as targets, performing simulation optimization on the energy system configuration model, and generating a source network load storage optimal planning scheme of the target area based on an optimization result. The method can be combined with the actual industrial base of the park, the multi-energy form, the multi-load demand and the like in the park are fused to the maximum extent, the cooperative promotion of the industry is enhanced, the comprehensive efficiency of the energy is effectively improved, the localized maximum consumption of renewable energy is promoted, and the system configuration is reasonable.

Description

Technical Field

[0001] The present application relates to the technical field of power systems, and in particular to a source-grid-load-storage integrated planning method and a source-grid-load-storage integrated planning system. Background Art

[0002] The integration of power grid, load and storage is a new power system operation mode that takes power source, power grid, load and energy storage as the overall planning. Deepening the reform of the power system, promoting the integration of power grid, load and storage, and building a new power system with new energy as the main body are the key links in building a new energy system.

[0003] At present, domestic and foreign research and demonstration promotion of the source-grid-load-storage integrated planning system have been carried out, but the results are not ideal. This is mainly manifested in the lack of a complete planning system and technical system, and the limited integration of the system with the actual industrial base characteristics of the park itself, resulting in unreasonable system configuration and insufficient release of regional energy potential, thus limiting the effect of promoting industry synergy. Summary of the invention

[0004] Based on this, it is necessary to provide a source-grid-load-storage integrated planning method and a source-grid-load-storage integrated planning system to address the above technical problems.

[0005] In a first aspect, the present application provides a source-grid-load-storage integrated planning method, the method comprising: constructing a load model, an energy system model and an integrated energy station site selection model for a target area; based on the load model, the energy system model and the integrated energy station site selection model, constructing an energy system configuration model for the target area; with the goal of maximizing new energy consumption and minimizing system operating costs, simulating and optimizing the energy system configuration model, and generating an optimal source-grid-load-storage planning scheme for the target area based on the optimization results.

[0006] In some embodiments, the step of constructing a load model of the target area includes: respectively constructing a basic load curve and a flexible load curve of the target load of the target energy unit in the target area; the target load is cold, hot, electric, and gas load; superimposing the basic load curve and the flexible load curve to obtain a total load curve; based on the total load curve and the flexible load curve, generating a total load model and an optimal flexible load model of the target load of the target energy unit.

[0007] In some embodiments, the types of energy consuming units include social buildings and industrial buildings; when the energy consuming unit is a social building, the step of constructing a flexible load curve of the electric load of the energy consuming unit includes: separately constructing the load curve of each adjustable electric load of the energy consuming unit; superimposing the load curves of all adjustable electric loads to obtain the flexible load curve of the electric load of the energy consuming unit; when the energy consuming unit is an industrial building, the step of constructing a flexible load curve of the electric load of the energy consuming unit includes: separately constructing the load curve of each adjustable electric load of the energy consuming unit; constructing the load curve of the translatable electric load of the energy consuming unit with the goal of achieving the highest degree of fit between the load curve after translation and the target load curve; superimposing the load curves of all the adjustable electric loads and the translatable electric load to obtain the flexible load curve of the electric load of the energy consuming unit.

[0008] In some embodiments, based on the total load curve and the flexible load curve, the steps of generating a total load model and an optimal flexible load model of the electric load of the target energy consumption unit include: taking the total flexible load not exceeding the total load at any time and each single flexible load not exceeding the adjustment range of the equipment or system as constraints, and taking stable flexible load fluctuation and maximum total load adjustment space as goals, constructing an objective function based on the flexible load curve and the total load curve; solving the objective function to obtain the total load model and the optimal flexible load model of the electric load of the target energy consumption unit.

[0009] In some embodiments, the energy system model includes an output characteristic model of a new energy power supply system; the step of constructing the output characteristic model of the new energy power supply system in the target area includes: determining the type and system scale of the new energy power supply in the target area; determining the original output characteristic model of each new energy power supply system according to the type and system scale, as well as the unit characteristics of each new energy power supply system; and determining the final output characteristic model of each new energy power supply system by comparing the existing power supply data of the target area with the original output characteristic model and correcting the original output characteristic model.

[0010] In some embodiments, the energy system model also includes an energy supply characteristic model, an energy efficiency characteristic model and a regulation characteristic model of the public service energy system; the steps of constructing the energy supply characteristic model, the energy efficiency characteristic model and the regulation characteristic model of the public service energy system in the target area include: determining the type and configuration form of the public service energy system in the target area; according to the type and configuration form, combined with the system performance parameters in the equipment database corresponding to each public service energy system, determining the energy supply characteristic model and the energy efficiency characteristic model of each public service energy system; according to the system performance parameters, generating a regulation quantity model of the energy storage body in each public service energy system; combining the regulation quantity model and the corresponding regulation strategy, constructing the regulation characteristic models of various types of public service energy systems.

[0011] In some embodiments, when the type of the energy storage body is a cold storage or heat storage system, the regulation strategy includes one or more of a pipeline energy storage regulation strategy, a temperature difference control strategy, a partition regulation strategy, and a compensation regulation strategy; when the type of the energy storage body is a gas storage system, the regulation strategy includes a gas tank regulation strategy; when the type of the energy storage body is an electric storage system, the regulation strategy includes a constant power charging and discharging, and a constant voltage and frequency regulation strategy.

[0012] In some embodiments, the step of constructing an integrated energy station site selection model for the target area includes: determining all energy-consuming units corresponding to each integrated energy station in the target area; obtaining the location coordinates of each energy-consuming unit corresponding to each integrated energy station; obtaining load data of the corresponding load of each energy-consuming unit corresponding to each integrated energy station; and determining the location coordinate model of each integrated energy station through a load moment algorithm or an equivalent load moment algorithm based on the location coordinates and the load data.

[0013] In some embodiments, the step of constructing the energy system configuration model of the target area based on the load model, the energy system model and the integrated energy station site selection model includes: based on the load model, obtaining the total load model of the target load of all energy-consuming units in the target area; constructing the original load curve of the target load of the target area; the original load curve is obtained by superimposing the total load models of the target loads of all energy-consuming units; arranging the original load curves in descending order from large to small according to the load data to generate a load descending curve; the load descending curve and the coordinate axis are enclosed to form a load fitting space band; the load fitting space band is divided into an upper subspace band, a middle subspace band and a lower subspace band in turn; based on the energy system model and the integrated energy station site selection model, an energy system configuration strategy for the loads corresponding to the upper subspace band, the middle subspace band and the lower subspace band is generated as the energy system configuration model of the target area.

[0014] In some embodiments, the step of dividing the load fitting space band into an upper subspace band, a middle subspace band and a lower subspace band includes: determining a first percentage and a second percentage for the load fitting space band; based on the first percentage, dividing an upper subspace band within the load fitting space band; the first percentage is the area ratio of the upper subspace band to the load fitting space band; based on the second percentage, dividing a lower subspace band within the load fitting space band; the second percentage is the area ratio of the lower subspace band to the load fitting space band; determining a middle subspace band; the middle subspace band is located between the upper subspace band and the lower subspace band.

[0015] In some embodiments, the step of generating an energy system configuration strategy for the loads corresponding to the upper subspace band, the neutron space band and the lower subspace band based on the energy system model and the integrated energy station site selection model includes: constructing an operating cost model and an energy supply model of the energy system in the target area based on the energy system model and the integrated energy station site selection model; constructing an objective function based on the operating cost model and the energy supply model of the energy system with the goal of optimizing unit energy economy; and configuring corresponding energy systems and their operating priorities for the loads corresponding to the upper subspace band, the neutron space band and the lower subspace band based on the solution of the objective function.

[0016] In some embodiments, the optimal planning scheme for source, grid, load and storage includes the selection and scale of the energy system, the optimal location of the integrated energy station, the optimal layout scheme of the energy supply network, the optimal configuration scheme of the energy system, and the optimal operation strategy of source, grid, load and storage.

[0017] In some embodiments, with the goal of optimizing unit energy economy, an objective function is constructed based on the pipeline cost model and pipeline energy supply model of the integrated energy station, and the constraints of the objective function are set based on the constraint parameters of the benchmark object of the integrated energy station or the loss rate of the transmission and distribution network; the pipeline cost model and the pipeline energy supply model are both constructed based on the energy system model and the site selection model of the integrated energy station; based on the solution result of the objective function, the target constraints are obtained in combination with the actual scenario to determine the optimal site for the integrated energy station; wherein the types of the integrated energy stations include cooling systems, heating systems, power supply systems and gas supply systems, the benchmark objects of the cooling systems include VRV systems, the benchmark objects of the heating systems include gas boiler systems, the benchmark objects of the gas supply systems include compressed air systems, and the power supply systems use the loss rate of the transmission and distribution network as the constraints of the objective function.

[0018] On the second aspect, the present application also provides an integrated planning system for source, grid, load and storage, including a load analysis module for constructing a load model of a target area; an energy system analysis module for constructing an energy system model of the target area; an integrated energy station site selection module for constructing an integrated energy station site selection model of the target area; an energy system configuration module for constructing an energy system configuration model of the target area based on the load model, the energy system model and the integrated energy station site selection model; a target optimization module for simulating and optimizing the energy system configuration model with the goal of maximizing new energy consumption and minimizing system operating costs, and generating an optimal planning scheme for source, grid, load and storage of the target area based on the optimization results.

[0019] One of the above technical solutions has the following advantages or beneficial effects: by constructing the characteristics and relationship models of multiple load characteristics, multiple energy forms, multiple systems and networks, the integrity of the entire planning process is guaranteed; among them, by constructing load models and energy system models, especially taking the comprehensive energy station site selection model into consideration, it is helpful to combine with the actual industrial base of the park itself, laying a solid and reliable foundation for energy system configuration and energy network optimization; this application closely revolves around the policies and demonstration intentions of the national source-grid-load-storage system, maximizes the integration of multiple energy forms and multiple load demands within the park, strengthens the coordinated promotion of industries, and can effectively improve the overall energy efficiency, promote the localized maximum consumption of renewable energy, and make the system configuration reasonable. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] Figure 1 A schematic diagram of a flow chart of a source-grid-load-storage integrated planning method in an embodiment;

[0021] Figure 2 A schematic diagram of the type of load model of a target area in one embodiment;

[0022] Figure 3 A schematic diagram of the type of energy system model of a target area in one embodiment;

[0023] Figure 4 A schematic diagram of the position coordinates of each energy consumption unit corresponding to the integrated energy station (circular mark) in one embodiment;

[0024] Figure 5 A schematic diagram of generating an upper limit of an adjustable energy storage space in one embodiment;

[0025] Figure 6 Schematic diagram of the relationship between the hourly characteristic coefficient of the heat load of the target area and time (h) in one embodiment;

[0026] Figure 7 for Figure 6 Schematic diagram after descending processing;

[0027] Figure 8 is a schematic diagram of a cost database of an energy system in one embodiment;

[0028] Fig. 9 is a schematic diagram of an upper subspace band, a middle subspace band, and a lower subspace band in one embodiment;

[0029] Fig.10 A schematic diagram of an optimal configuration scheme for an energy system in one embodiment;

[0030] Fig.11 Schematic diagram of the structure of a source-grid-load-storage integrated planning system in one embodiment. DETAILED DESCRIPTION

[0031] 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.

[0032] Reference to "embodiments" herein means that a particular feature, structure, or characteristic described in conjunction with the embodiments may be included in at least one embodiment of the present application. The appearance of the phrase in various locations in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0033] The source-grid-load-storage integrated planning method proposed in this application can be understood as a source-grid-load-storage integrated planning method that takes into account both demand response and energy supply economy.

[0034] Demand response, or demand-side response, can be understood as a power management strategy that aims to balance power supply and demand through the behavior of power users to ensure the stable operation of the power grid. It can be further understood as a source-grid-load-storage park or corporate user, under the premise of ensuring power quality and reliability, according to the increase or decrease of electricity prices and energy production prices, actively adjust their own electricity, cooling, heating and other needs (specific adjustment methods may include staggered production, adjustment of air conditioning and lighting start-up time, energy storage, etc.), reduce or increase the use of electricity and other energy, change energy habits and behaviors, and achieve the purpose of reducing costs. Among them, demand response can be associated with the load-side regulation characteristics. The load side may include indoor air conditioning and lighting in buildings, interruptible and shiftable loads in production, etc., and also self-contained generator sets.

[0035] Energy supply economics mainly involves the cost-benefit analysis of energy supply, that is, evaluating whether the investment in the energy supply system is reasonable and whether such investment can bring the expected economic return. Energy supply economics includes considering many factors, such as energy production cost, transmission efficiency, demand-side management, and energy utilization efficiency. This application mainly considers various types of energy, such as cold water, hot water, steam, compressed air, electricity, etc., and their corresponding economic energy supply distances.

[0036] This application provides a source-grid-load-storage integrated planning method, such as Figure 1 As shown, a source-grid-load-storage integrated planning method is provided, comprising the following steps:

[0037] S202, constructing a load model, energy system model and integrated energy station site selection model for the target area.

[0038] The target area may be an area where a source-grid-load-storage system is to be planned, which may be an existing area or a new area, or may be an integrated area of ​​multiple areas, which is not limited here.

[0039] The load model can be understood as the overall basic load and flexible load curves of the process production, office, living and other building categories in the target area.

[0040] The energy system model can be understood as the energy system in the target area, such as the output characteristic model, energy efficiency characteristic model, adjustable characteristic model, etc. of photovoltaic, wind power, thermal power generation, hydrogen production, chillers, boilers, etc.

[0041] The integrated energy station site selection model can be understood as a model for site selection for an integrated energy station. An integrated energy station can be understood as a new type of energy station with two or more facilities such as refueling, gas filling, hydrogen filling, charging / battery replacement, photovoltaic power generation, etc. It is a multifunctional integrated station for multiple energy and non-energy services. The integrated energy station in this article includes but is not limited to cooling systems, heating systems, power supply systems, and gas supply systems. It should be noted that the energy type of the gas supply system is compressed air.

[0042] S204: construct an energy system configuration model for the target area based on the load model, the energy system model and the integrated energy station site selection model.

[0043] In the embodiment of the present application, the energy system configuration model of the target area can be understood as the optimal design state system configuration model of the target area, which can indicate the configuration of different types of energy systems for different types of loads to meet energy needs.

[0044] S206, with the goal of maximizing the consumption of new energy and minimizing the system operating cost, the energy system configuration model is simulated and optimized, and the optimal planning scheme for source, grid, load and storage in the target area is generated based on the optimization results.

[0045] The new energy here can also be understood as renewable resources; this application has formulated an optimal planning scheme for source, grid, load and storage by taking into account both demand response and energy supply economy.

[0046] The source-grid-load-storage integrated planning method proposed in this application ensures the integrity of the entire planning process by constructing characteristics and relationship models of multiple loads, multiple energy forms, multiple systems and networks; among them, by constructing load models and energy system models, especially taking the integrated energy station site selection model into consideration, it helps to combine with the actual industrial base of the park itself, laying a solid and reliable foundation for energy system configuration and energy network optimization; this application closely revolves around the policies and demonstration intentions of the national source-grid-load-storage system, maximizes the integration of multiple energy forms and multiple load demands within the park, strengthens the coordinated promotion of the industry, can effectively improve the overall energy efficiency, promote the localized maximum consumption of renewable energy, and make the system configuration reasonable.

[0047] In some embodiments, Figure 2 As shown, the steps of constructing the load model of the target area include: respectively constructing the basic load curve and the flexible load curve of the target load of the target energy unit in the target area; the target load is the cold, heat, electricity and gas load; superimposing the basic load curve and the flexible load curve to obtain the total load curve; based on the total load curve and the flexible load curve, generating the total load model and the optimal flexible load model of the target load of the target energy unit.

[0048] In this embodiment, the load model can be understood as the total load model and the optimal flexible load model of the target load of the target energy unit; the target energy unit can be various buildings in the target area, such as office buildings, residential buildings, production workshops, etc. It should be noted that the target load can be cooling load, heating load, electric load and compressed air load, and each load can correspond to multiple types of equipment, such as electric load, which can correspond to photovoltaic power generation, wind power generation, thermal power generation, etc., and thermal load can correspond to boilers, heat pumps, waste heat utilization, etc.

[0049] Among them, flexible loads can be divided into three categories: adjustable loads, interruptible loads and shiftable loads. Interruptible loads can be understood as the load part that can be interrupted by the user load center during the peak period of the power grid or in an emergency situation; shiftable loads can be understood as loads whose load power supply time can be changed according to plan. Taking the automobile production load as an example, the shell part can be produced in the daytime without going to the next process, but the process can be shifted to the evening when there is off-peak electricity or new energy is generated for centralized production; adjustable loads can be understood as loads that adjust the output according to demand and economic conditions. For example, air conditioning can adjust the temperature, that is, adjust the power of the fan disk, thereby affecting the output of the chiller and adjusting the power consumption; lighting, for example, can adjust the illumination according to the light conditions. All of the above are adjustable loads.

[0050] In some embodiments, you may continue to refer to Figure 2, because the load characteristics of the building types corresponding to the process production, office, and life in the park are different, the park buildings are classified to classify the park load accordingly; the types of energy-consuming units can include social buildings and industrial buildings. Social buildings can include office, residential, and living buildings, and industrial buildings refer to buildings related to industrial production. Accordingly, the load curve of the park load can be classified into the basic load curve and flexible load curve of each load (cooling load, heating load, electricity load, and compressed air load) of social buildings, and the basic load curve and flexible load curve of each load (cooling load, heating load, electricity load, and compressed air load) of industrial buildings.

[0051] In this embodiment, when the energy consumption unit is a social building, the construction of the flexible load curve can be based on the construction of the curve of the adjustable load, and the step of constructing the flexible load curve of the electric load of the energy consumption unit includes: constructing the load curve of each adjustable electric load of the energy consumption unit respectively; wherein, the load that can be used as the adjustable electric load includes the flexible air conditioning load, the flexible lighting load and the flexible charging pile load; superimposing the load curves of all the adjustable electric loads to obtain the flexible load curve of the electric load of the energy consumption unit. When the energy consumption unit is an industrial building, the construction of the flexible load curve can be based on the construction of the curve of the adjustable load and the translatable load, and the step of constructing the flexible load curve of the electric load of the energy consumption unit includes: constructing the load curve of each adjustable electric load of the energy consumption unit respectively; wherein, the load that can be used as the adjustable electric load here can also include the flexible air conditioning load, the flexible lighting load and the flexible charging pile load; with the goal of the highest degree of fit between the load curve after translation and the target load curve, constructing the load curve of the translatable electric load of the energy consumption unit; superimposing the load curves of all the adjustable electric loads and the translatable electric load to obtain the flexible load curve of the electric load of the energy consumption unit. This embodiment is described by taking electric load as an example. The flexible load curves of load curves of other loads can be constructed by referring to the above method, which will not be described in detail here.

[0052] In some embodiments, based on the total load curve and the flexible load curve, the steps of generating the total load model and the optimal flexible load model of the electric load of the target energy consumption unit include: taking the total flexible load not exceeding the total load at any time and each individual flexible load not exceeding the adjustment range of the equipment or system as the constraint condition, taking the stable fluctuation of the flexible load and the maximum adjustment space of the total load as the goal, constructing the objective function based on the flexible load curve and the total load curve; solving the objective function to obtain the total load model and the optimal flexible load model of the electric load of the target energy consumption unit. The total flexible load does not exceed the total load at any time. It can be understood that when establishing the constraint condition, it should be considered that any flexible load at that moment should be superimposed and then not exceed the total load. The total load is the superposition result of all loads including the basic load and the flexible load at that moment. Each individual flexible load does not exceed the adjustment range of the equipment or system. It can be understood that each of the adjustable load, the translatable load, and the interruptible load cannot exceed the adjustment range of the corresponding equipment or system. For example, the adjustment parameters of the air-conditioning temperature cannot exceed the adjustment range of the air-conditioning equipment. In some embodiments, such as Figure 3 As shown, the energy system model includes an output characteristic model of a new energy power supply system; the steps of constructing the output characteristic model of the new energy power supply system in the target area include: determining the type and system scale of the new energy power supply in the target area; determining the original output characteristic model of each new energy power supply system according to the type and system scale, as well as the unit characteristics of each new energy power supply system; and determining the final output characteristic model of each new energy power supply system by comparing the existing power supply data of the target area with the original output characteristic model and correcting the original output characteristic model.

[0053] In this embodiment, determining the type and system scale of renewable energy power supply in the target area can be understood as evaluating the potential of renewable energy (or new energy) in the park; the type of renewable energy power supply can include photovoltaic, wind power and other power supply types. When determining the scale of the renewable energy power supply system, it can be considered based on multiple factors; for example, when determining the installation conditions of distributed photovoltaics, it can be obtained by analyzing the lighting conditions of the park. The analysis of lighting conditions can be further converted into analyzing the geographical information of the park, the orientation and shading of buildings, the installation method of photovoltaic components, etc.; when determining the installed scale of distributed photovoltaics, the available roof area, roof form and load-bearing conditions can be analyzed to calculate the maximum installable scale of distributed photovoltaics. For example, when evaluating the potential of wind power generation, the installation conditions, installed quantity and scale of wind turbines can be preliminarily determined in combination with the wind resource conditions and site conditions in and around the park.

[0054] It should be explained that the unit characteristics of the new energy power supply system can be understood as the unit data or energy efficiency characteristic curve provided by the manufacturer of the new energy unit (generally recorded in the equipment manual or instruction manual), or can be obtained by referring to the operating data of the actual system of the same type and scenario; the unit characteristic data can be stored in the equipment database for subsequent steps. Existing power supply data can be understood as historical data related to power supply, which may include data related to existing local projects or wind towers.

[0055] The method of constructing the output characteristic model of the new energy power supply system in the target area in the above embodiment is applicable to the construction of the existing new energy power supply system in the park, and is also applicable to the acquisition of the final output characteristic model of the typical day and the whole year of the newly introduced external energy system.

[0056] In some embodiments, see Figure 3 The energy system model also includes an energy supply characteristic model, an energy efficiency characteristic model and a regulation characteristic model of the public service energy system; the steps of constructing the energy supply characteristic model, energy efficiency characteristic model and regulation characteristic model of the public service energy system in the target area include: determining the type and configuration form of the public service energy system in the target area; according to the type and configuration form, combined with the system performance parameters in the equipment database corresponding to each public service energy system, determining the energy supply characteristic model and energy efficiency characteristic model of each public service energy system; according to the system performance parameters, generating a regulation quantity model of the energy storage body in each public service energy system; combining the regulation quantity model and the corresponding regulation strategy, constructing the regulation characteristic models of various types of public service energy systems.

[0057] It should be noted that the energy supply characteristic model and energy efficiency characteristic model of the public service energy system under different working conditions can be determined based on the system performance parameters, and the system performance parameters can be obtained from the equipment database generated by the product manual statistics provided by each public service energy system manufacturer. The determination of the adjustment characteristic model should take into account both the characteristics of the public service energy system itself and the actual operation strategy of the public service energy system. The adjustment characteristic model of the public service energy system itself can be an upper limit value, and the adjustment strategy can be formulated within its range according to the actual constraints.

[0058] In some embodiments, continue to refer to Figure 3 When the type of energy storage body is a cold storage or heat storage system, the regulation strategy includes one or more of the pipeline energy storage regulation strategy, the temperature difference control strategy, the partition regulation strategy and the compensation regulation strategy; when the type of energy storage body is a gas storage system, the regulation strategy includes the gas tank regulation strategy; when the type of energy storage body is an electric storage system, the regulation strategy includes the charging and discharging constant power and constant voltage and frequency regulation strategy.

[0059] Temperature difference control can be adjusted by adding a temperature difference control system, adopting a large temperature difference and small flow design, interlocking the water pump and unit control, and building temperature, flow and other parameters into the equipment controller, which can learn and adjust autonomously according to the working conditions. Specifically, if the inlet and return water temperature difference is increased, the original 6°C inlet and 12°C return can be changed to 5°C inlet and 15°C return. This can achieve flexible switching of the unit, especially under partial load conditions, without significantly reducing the unit's efficiency, while reducing transmission and distribution losses and improving the economy of the system. It should be pointed out that temperature difference control is an important means to achieve the adjustment and optimization of cold and heat storage capacity.

[0060] Zoning regulation and compensation regulation can be used as important means to optimize the regulation of air-conditioning terminal fans, chillers, and boilers. Zoning regulation refers to dividing a building into different areas for regulation. For example, if an area is unoccupied during a certain period of time, or if an area such as a leader's office has high environmental requirements, it can be regulated by zoning. Compensation regulation can be understood as the unit making corresponding adjustments in advance according to climatic conditions (such as temperature, weather forecast, etc.), and the control target can be the supply and return water temperature difference or flow.

[0061] Gas tank adjustment can be understood as adjustment based on electricity prices, gas demand, etc. For example, gas can be compressed and stored at night when electricity is off-peak, and then released in an orderly manner during the day when electricity consumption is at its peak and electricity prices are at their peak, thereby reducing costs.

[0062] In some embodiments, the step of constructing the integrated energy station site selection model of the target area includes: determining all energy consumption units corresponding to each integrated energy station in the target area; obtaining the location coordinates of each energy consumption unit corresponding to each integrated energy station, such as Figure 4 As shown; obtain the load data of each type of load for each energy-consuming unit corresponding to each integrated energy station; based on the position coordinates and load data, determine the position coordinate model of the integrated energy station corresponding to each type of load through the load moment algorithm or the equivalent load moment algorithm.

[0063] It should be explained that the load moment of the integrated energy station can be calculated by multiplying the corresponding load of the energy-consuming unit by the location coordinates of the energy-consuming unit (used to characterize the distance from the energy-consuming unit to the energy supply unit) and dividing it by the total load of the corresponding load. The corresponding load can be understood as follows: if the integrated energy station is a power supply system, the corresponding load is the electric load; if the integrated energy station is a heating system, the corresponding load is the thermal load, and so on. After determining the energy station location coordinate model corresponding to each type of load, the optimal integrated energy station location coordinate model is determined in combination with target constraints such as scenarios. For details, please refer to the introduction of the steps for determining the optimal location of the integrated energy station later.

[0064] In some embodiments, the step of constructing an energy system configuration model of a target area based on a load model, an energy system model and an integrated energy station site selection model includes: based on the load model, obtaining a total load model of the target loads of all energy consuming units in the target area; constructing an original load curve of the target load of the target area; the original load curve is obtained by superimposing the total load models of the target loads of all energy consuming units; arranging the original load curves in descending order from large to small according to the load data to generate a load descending curve; the load descending curve and the coordinate axis are enclosed to form a load fitting space band; the load fitting space band is divided into an upper subspace band, a neuter space band and a lower subspace band in turn; based on the energy system model and the integrated energy station site selection model, an energy system configuration strategy for the loads corresponding to the upper subspace band, the neuter space band and the lower subspace band is generated as the energy system configuration model of the target area.

[0065] In some embodiments, Fig. 9 As shown, the steps of dividing the load fitting space band into an upper subspace band, a middle subspace band and a lower subspace band include: determining a first percentage and a second percentage for the load fitting space band; based on the first percentage, dividing the upper subspace band within the load fitting space band; the first percentage is the area ratio of the upper subspace band to the load fitting space band; based on the second percentage, dividing the lower subspace band within the load fitting space band; the second percentage is the area ratio of the lower subspace band to the load fitting space band; determining the middle subspace band; the middle subspace band is located between the upper subspace band and the lower subspace band.

[0066] In some embodiments, based on the energy system model and the integrated energy station site selection model, the steps of generating energy system configuration strategies for the loads corresponding to the upper subspace belt, the middle subspace belt, and the lower subspace belt include: constructing the operating cost model and the energy supply model of the energy system in the target area based on the energy system model and the integrated energy station site selection model; constructing the objective function based on the operating cost model and the energy supply model of the energy system with the goal of optimizing the unit energy economy; and configuring the corresponding energy system and its operation priority for the loads corresponding to the upper subspace belt, the middle subspace belt, and the lower subspace belt, respectively, based on the solution of the objective function. Specifically, the priority order of the energy system can be determined according to the unit economic target model of the energy system, so as to serve as the basis for the hierarchical configuration of the energy system.

[0067] In some embodiments, the optimal planning scheme for source, grid, load and storage includes but is not limited to the selection and scale of the energy system, the optimal location of the integrated energy station, the optimal layout scheme of the energy supply network, the optimal configuration scheme of the energy system, and the optimal operation strategy for source, grid, load and storage.

[0068] In some embodiments, the step of determining the optimal location of the integrated energy station includes: taking the optimal unit energy economy as the goal, constructing an objective function based on the pipeline cost model and the pipeline energy supply model of the integrated energy station, and the constraints of the objective function are based on the constraint parameters of the benchmark object of the integrated energy station or the transmission and distribution network loss rate setting; the pipeline cost model and the pipeline energy supply model are both constructed based on the energy system model and the integrated energy station site selection model; based on the solution result of the objective function, the target constraint condition is obtained in combination with the actual scenario to determine the optimal location of the integrated energy station. In other words, based on the solution result of the objective function, it can be used as a part of the target constraint condition, and specifically, it can also be combined with information such as the actual scenario to form the final target constraint condition, so as to determine the optimal location coordinate model of the integrated energy station; wherein the types of integrated energy stations include cooling systems, heating systems, power supply systems and gas supply systems, the benchmark object of the cooling system includes the VRV system, the benchmark object of the heating system includes the gas boiler system, the benchmark object of the gas supply system includes the compressed air system, and the power supply system uses the above-mentioned transmission and distribution network loss rate as the constraint condition of the objective function.

[0069] On the second aspect, the present application also provides an integrated planning system for source, grid, load and storage, including a load analysis module for constructing a load model of a target area; an energy system analysis module for constructing an energy system model of a target area; an integrated energy station site selection module for constructing an integrated energy station site selection model of a target area; an energy system configuration module for constructing an energy system configuration model of a target area based on the load model, the energy system model and the integrated energy station site selection model; a target optimization module for simulating and optimizing the energy system configuration model with the goal of maximizing the absorption of new energy and minimizing the system operating cost, and generating an optimal planning scheme for source, grid, load and storage of a target area based on the optimization results.

[0070] In a specific implementation, the source-grid-load-storage integrated planning method proposed in this application solves the problem of collaborative planning of the full-process source-grid-load-storage integrated planning system based on industrial production characteristics, which may specifically include:

[0071] 1. Construct basic load and flexible load curves for process production, office, life, etc. in the park.

[0072] 1. Model construction for social building foundation loads:

[0073] Specifically, the building business parameters (including business type, area, etc.) can be used as input, and the load index method can be used to output the load curves of cooling, heating, electricity, and gas on a typical day. Of course, the input can also be imported into software such as DEST and eQUEST for simulation to output the load curve, which is not the only limitation here.

[0074] Taking the building business parameters as input and the load index method as an example, the model construction process of the basic load of social buildings is explained, that is, refer to the following formula:

[0075] P i =p i (t)×A i ×ε i

[0076] Where P i is the load of the i-th type of building at a certain moment, W; p i (t) is the load index of the i-th building type at time t, w / m 2 (It can be understood as the electricity, cooling and heating consumption per square meter of the i-th building type at time t, and it is divided by the area A i The total energy consumption of the building can be obtained by multiplying i is the air-conditioned area of ​​the i-th type of building, m 2 , generally 80%-90% of the building area; ε i is the load factor of the i-th type building at time t, 1≥ε i ≥0. If it is an average load system, the cooling and heating systems are simultaneous coefficients, which are generally 0.6-0.7, and the electrical system is generally 0.9-1.0.

[0077] The above formula can ultimately determine the typical daily 24-hour load curve of the basic load of social buildings, which may include cooling load curve, heating load curve, and electrical load curve.

[0078] 2. Model construction for flexible loads of social buildings:

[0079] When constructing the flexible load curve of the electric load, the objective function is to ensure the stability of the building load fluctuation and the maximization of the adjustment space under the premise of ensuring the indoor comfort level of the building. For details, please refer to the following formula:

[0080]

[0081] Where P d (t) is the total load of social buildings at time t, kW. It should be noted that the total load of social buildings at time t is the superposition of basic load and flexible load; P dr (t) is the flexible load of social buildings at time t, kW; t0 is the response start time, min; t max The response end time, min.

[0082] The corresponding constraints for the flexible and adjustable loads of this social building are:

[0083] P dr (t) = PAC (t)+P V (t)+P Li (t)≤P d (t)

[0084] Where P AC (t) is the flexible air conditioning load of social buildings at time t, kW; P V (t) is the flexible charging pile load of social buildings at time t, kW; P Li (t) is the flexible lighting load of social buildings at time t, kW.

[0085] 2.1. Flexible air conditioning load P for social buildings at time t aC (t):

[0086] Usually, the main electrical equipment for cooling conditions of air-conditioning systems include chillers, fan coils, chilled water pumps, cooling water pumps and cooling towers. The heating conditions are mainly circulating water pumps, gas or electric boilers or heat pump systems, terminal fan coils or radiation heat exchange devices, such as radiators. If it is municipal thermal heating, the main equipment is circulating water pumps, heat exchangers, etc. From the perspective of adjustability, the above 5 parts can all be considered as adjustable loads. Therefore, the control and cooling input of these devices depend on the fluctuation of the indoor cooling load of the building. In order to simplify the model, constraints such as air supply volume design based on the indoor cooling demand of the building and the temperature requirements of the zone are not considered, and the adjustment characteristics of the valve are not considered. Under the condition of meeting the comfort requirements, the goal is to obtain the maximum adjustable capacity of the air-conditioning system at each moment.

[0087] The maximum adjustable capacity objective function is:

[0088]

[0089] Where P d (t) is the total load of the building at time t, kW; t0 is the response start time, min; t max The response end time, min.

[0090] The maximum adjustable capacity function of the air conditioning system (cooling condition) is composed of:

[0091]

[0092] P fan (t,f)=P fan0 -s f (t)P fan0

[0093] P pump (t) = (1-η n )*P pump0

[0094] P coolingpump (t) = (1-η m )*P coolingpump0

[0095] P tower (t) = (1-η k )*P tower0

[0096] P chiller (t) = (1-η e )*P chiller0

[0097] Where P fan (t, f) is the flexible load of the f-th fan coil unit of the building at time t, kW; P pimp (t, n) is the flexible load of the nth cooling water pump of the building at time t, kW; P chiller 9t, e) is the flexible load of the e-th chiller in the building at time t, kW, P tower (t, k) is the flexible load of the kth cooling tower of the building at time t, kW; P coolingpump (t, m) is the flexible load of the mth chilled water pump at time t, kW. η n , η k , η m , η e The load rates of the nth circulating water pump, kth cooling tower, mth chilled water pump, and eth chiller, respectively, %; s f (t) is the gear position or switch state corresponding to the f-th fan coil unit; f, n, k, m, e are the number of fan coil units, circulating water pumps, cooling towers, chilled water pumps, and chillers participating in flexible regulation, respectively; f max , n max , k max , m max , e max are the total number of fan coil units, circulating water pumps, cooling towers, chilled water pumps, and chillers, respectively; P fan0 , P pump0 , P coolingpump0 , P chiller0 , P tower0 They are the rated powers of fan coil units, circulating water pumps, chilled water pumps, chillers and cooling towers, in kW.

[0098] The maximum adjustable capacity function of the air conditioning system (heating condition) is composed of:

[0099]

[0100] P fan (t,f)=P fan0 -sf (t)P fan0

[0101] P circlepump (t) = (1-η c )*P circlepump0

[0102] P boiler (t) = (1-η l )*P boiler0

[0103] Where P fan (t, f) is the flexible adjustable capacity of the f-th fan coil unit in the building at time t, kW; P circlepump (t,c) is the flexible adjustable capacity of the cth circulating water pump of the building at time t, kW; P boiler (t,l) is the flexible adjustable capacity of the building's lth chiller at time t, kW. η c , η l The load rate of the cth circulating water pump, the lth boiler or the heat pump, %; s f (t) is the gear position or switch state corresponding to the f-th fan coil unit; f, c, l are the number of fan coil units, circulating water pumps, boilers or heat pumps participating in flexible regulation, respectively; f max , c max , l max are the total number of fan coil units, circulating water pumps, boilers or heat pumps, respectively; P fan0 , P circlepump0 , ,P boiler0 They are the rated power of fan coil units, circulating water pumps, boilers or heat pumps, in kW. If the above is municipal heating, the adjustable capacity does not include boilers or heat pump systems.

[0104] For the adjustable capacity analysis of air conditioning cooling or hot water supply pipe network as energy storage, its adjustable capacity

[0105]

[0106] In the formula, Q g (t) is the energy storage capacity of the air conditioning system network, kwh; C is the specific heat capacity of chilled water or hot water, kJ / kg·k; R is the radius of the i-th chilled water or hot water network, m; L is the length of the i-th network, m; ρ is the density of chilled water or hot water, kg / m3; △T t is the inlet and return water temperature difference of the pipe network, K. In order to simplify the calculation, it can also be considered according to the inlet and return water temperature difference of the entire pipe network system.

[0107] The flexible constraints are:

[0108] Cooling conditions

[0109] △T t =T h -T c ≤10℃

[0110] t c ≤5℃

[0111] T h ≤20℃

[0112] Heating conditions

[0113] △T t =T h -T c ≤30℃

[0114] T c ≤90℃

[0115] T h ≥23℃

[0116] Where, T h T is the return water temperature of the air conditioning system chilled water or hot water pipe network, ℃; c It is the supply temperature of chilled water or hot water network of air conditioning system, ℃.

[0117] 2.2 Flexible lighting load P for social buildings at time t Li (t):

[0118] The soft load constraints for lighting equipment are:

[0119] P Li (t) = nP0-k i (t)P0

[0120] k i (t)≤n / 3

[0121] P z (t)≥P z0

[0122] Where, P0 is the power of a single lighting device in a social building, assuming the same power model, kW; n is the number of lighting devices in a social building, pieces; k i (t) is the number of lighting devices turned off at time t in social buildings; P z (t) is the indoor illumination of social buildings at time t, W / m 2 ;P z0 The minimum illumination requirement for social buildings is 9-11W / m 2 According to the national standard "Architectural Lighting Design Standard" GB50034-2004, the illumination for ordinary offices is 300lx, and the illumination for high-end offices is 500lx.

[0123] 2.3. Flexible charging pile load P for social buildings at time t AC (t):

[0124] The interactive behavior constraints of electric vehicles are:

[0125]

[0126] In the formula, the total charging capacity of the electric vehicle should meet its power demand, △t is the charging time at a certain power, min;

[0127] Q V0 is the total electricity demand of electric vehicles.

[0128] P V (t) = k V (t)P V0

[0129] In the formula, k V (t) represents the number of electric vehicles being charged at time t, which is an integer;

[0130] P V0 is the charging power of each electric vehicle, kW.

[0131] 0≤k V (t)≤k Vmax

[0132] In the formula, k Vmax Represents the number of electric vehicles being charged, as an integer.

[0133] 3. Model construction for foundation loads of industrial buildings:

[0134] For the basic load of industrial buildings, if the enterprise engaged in process production is an existing enterprise and has already carried out production, the load curves of cold, hot, electric and gas for typical days, years and months can be generated through historical production data; if it is a newly built enterprise, the unit area method, the reference method of similar process enterprises or the equipment nameplate power evaluation method can be used to generate its load curves of cold, hot, electric and gas.

[0135] Taking the unit area method as an example, the calculation can be carried out based on the unit area electricity and steam indicators of the corresponding types of industries:

[0136] Pe=pe*Al*Ee

[0137] Where Pe is the peak load of the process production, W; pe is the load index at a certain moment, MW / km 2 (Electricity) or t / km 2 (steam); Al is the building area of ​​the process plant, m 2; Ee is the simultaneous use coefficient, 1≥Ee≥0. If it is electricity, it needs to be multiplied by the demand coefficient in the above formula.

[0138] 4. Model construction for flexible loads of industrial buildings:

[0139] For the model construction of process production and flexible adjustable loads, such as lighting, air conditioning, and charging piles, please refer to the method of model construction of flexible loads of social buildings in the above point 2, which will not be elaborated here.

[0140] The construction method of the process production translatable load model is as follows:

[0141] The goal of the translatable load is to maximize the fit between the translated load curve and the target load curve. The formula is:

[0142]

[0143] P t =P foret +P int -P outt

[0144] Where T is the scheduling period; P t is the load in the period t after translation; P obt is the target load during period t; P foret P is the load in period t predicted by the current dispatch; int , P outt They are the load transferred into period t and the load transferred out of period t respectively. The load transferred in and out is the sum of the product of the number of movable load units Δt=tt′ in the corresponding time period and the power of the corresponding k-type load in this time period. The least squares method is used to solve it, which is not expanded here.

[0145] In the above calculation formula:

[0146]

[0147] In the formula, m SL1 is the total number of types of loads that can be translated; m SL2 The number of load types that can be shifted when the power supply duration is greater than one scheduling period; h max is the maximum duration of power supply for the movable load unit. If one hour is used as a scheduling period, then h max ≥2; x ktt′ is the number of k-type load units that can be translated from time period t to time period t′; p 1k is the power of the kth type of movable load unit in the first working period; p (h+1)k It is the power of the kth type movable load unit in the h+1th working period during its power supply duration.

[0148] The translation period constraints are:

[0149] Δt kt

[0150] Δt>(s kt +d kt )

[0151] x ktt′ =0

[0152] In the formula, s kt The earliest possible transfer period; d kt is the translation margin of the kth type of translatable load.

[0153] The translation constraint is:

[0154] x ktt′ ≥0

[0155]

[0156] In the formula, x kt The number of units of k types of shiftable loads that supply power to the original t period. The characteristics of the shiftable loads must ensure that the total load in the entire scheduling cycle remains unchanged before and after the shift.

[0157] like Figure 2 As shown, based on the above determination of the optimal opening time, opening strategy and adjustment capacity of lighting, air-conditioning equipment and process energy-consuming equipment, such as water pumps, fans, drying processes, etc., a flexible load adjustment characteristic model can be formed, which is superimposed on the basic load curve to truly reflect the demand and response capacity of the load side. Specifically, after the basic load curve of each load (cold, hot, electric, gas) is obtained, it is superimposed with the later generated flexible load curve to generate a superimposed load curve for subsequent steps.

[0158] 2. Based on regional resource conditions, construct an energy system model (such as photovoltaic, wind power, thermal power generation, hydrogen production, chillers, boilers, etc.). The energy system model may include an output characteristic model and a regulation characteristic model.

[0159] 1. For renewable energy (or new energy), the specific method of constructing the final output characteristic model is:

[0160] First, the renewable energy potential within the park is assessed.

[0161] Secondly, based on the evaluation results of renewable energy potential and combined with the characteristics of each renewable energy unit, the original output characteristic model of each energy system on a typical day and throughout the year can be determined, such as Figure 3 shown.

[0162] ​Finally, we can refer to the data of existing local projects or wind towers, compare them with the original output characteristic model, and then modify the original output characteristic model to determine the final output characteristic model of the energy system that meets the planning conditions. The planning conditions here can refer to the boundary conditions of the project planning, such as park load demand, declaration conditions, power access conditions, energy network conditions, and the needs of all parties.

[0163] The following will take wind power and photovoltaic power generation as examples to introduce the construction process of their original output characteristic models:

[0164] ① For photovoltaic power generation, its output is affected by solar radiation and can be calculated using the following formula.

[0165] P PV =A c CI T η PV f PV #

[0166] Where P PV is the photovoltaic power generation power, kW; A c is the light receiving area of ​​the photovoltaic panel, m 2 GI T is the total irradiance including direct irradiance and diffuse irradiance, W·m -2 ; η PV is the actual efficiency; f PV is the derating factor.

[0167] Among them, η PV It is related to ambient temperature, wind speed, etc. and can be expressed as:

[0168]

[0169] Where η PV,ref is the reference efficiency; λ is the temperature coefficient, K -1 ; T a is the ambient temperature, K; T c,ref is the photovoltaic cell temperature under standard test conditions (STC), K; τα is the transmission-absorption coefficient; v1 is the measured wind speed, m·s -1 .

[0170]

[0171] In the formula, is the minimum output of the photovoltaic power generation system, kW; is the maximum output of the photovoltaic power generation system, kW; is the actual output value of the photovoltaic power generation system, kW.

[0172] ②For wind power generation, its actual output power can be expressed as:

[0173]

[0174] Where P WT is the actual output power of the wind farm, kW; k(v) is the normalized power generation under different wind speeds; is the rated output power of the wind farm, kW; η t is the transmission efficiency; η g For power generation efficiency.

[0175] Among them, v can be calculated by the formula:

[0176]

[0177] Where v is the wind speed at the hub center, m·s -1 , wind speed as a function of time t; v r Meteorological rated wind speed for h1 = 10m, m·s -1 ; h2 is the hub center height, m; h1 is the anemometer height, m; α is the wind shear index.

[0178] Wind power generation constraints:

[0179] P WT =0, v <v c , v>v f

[0180]

[0181] In the formula, v c is the wind turbine cut-in wind speed, m·s -1 ;v r is the rated wind speed, m·s -1 ;v f is the fan cut-out wind speed, m·s -1 .

[0182]

[0183] In the formula, is the minimum power output of the wind power generation system, kW; The maximum power output of the wind power generation system, kW; It is the actual power output of the wind power generation system, kW.

[0184] 1.2. For various energy public service systems, the specific method of constructing the regulation characteristic model is as follows:

[0185] First, evaluate the characteristics of energy public service systems such as cooling, heating, and air compression (including but not limited to chillers, heat pump systems, boiler systems, trigeneration systems, air compression systems, air separation systems, etc.); secondly, determine the possible system forms of the energy public service system based on the evaluation results, and screen the possible system forms based on the actual conditions of the planned project to obtain the target energy system form that meets the project requirements or meets the project conditions; finally, obtain the energy efficiency characteristics, output characteristics, and constraints of various equipment and systems under the target energy system form (energy efficiency characteristics and constraints can be obtained from the equipment database), and then determine the regulation characteristic model of the energy public service system.

[0186] The following will take two types of energy storage systems as examples to introduce the construction process of their regulation characteristic models:

[0187] ① For cold and heat storage systems using water as the energy storage medium:

[0188] For the adjustable capacity analysis of the air-conditioning chilled water network as an energy storage body, its adjustable capacity is:

[0189]

[0190] In the formula, Q g (t) is the cooling capacity of the chilled water network of the air conditioning system, kw·h; C is the specific heat capacity of chilled water, kJ / (kg·K); R i is the radius of the i-th chilled water network, m; L i is the length of the i-th pipe network, m; ρ is the density of chilled water, kg / m3; △T t is the inlet and return water temperature difference of the chilled water network, K, which can be considered according to the inlet and return water temperature difference of the entire system.

[0191] The flexible constraints for this item are:

[0192] △T t =T h -T c ≤10℃

[0193] T c ≤5℃

[0194] T h ≤20℃

[0195] Where, T h is the return water temperature of the chilled water network of the air conditioning system, ℃; T c The water supply temperature of the chilled water network of the air-conditioning system, ℃.

[0196] The method for constructing the regulation characteristic model of the heat storage system is the same as that of the cold storage system in the above point ①, that is, the construction principles of the hot water network and the cold water network models are the same, only the parameter values ​​are different.

[0197] ②For heat storage systems using flue gas and exhaust gas as heat sources:

[0198] For thermoelectric conversion, such as solid heat storage, lava heat storage and other power conversion, it is also necessary to consider factors such as the heat source form, heat storage method, thermal power generation system configuration, and the interaction with the existing power generation system. Taking system-level solid heat storage with flue gas as the heat source as an example, the heat storage system includes a heat storage body, a generator set, an induced draft fan and supporting management and control systems.

[0199] The heat storage capacity is:

[0200]

[0201] Where, Qc is the heat storage capacity of the heat storage body, kJ; Qy is the heat taken away by flue gas or high-temperature exhaust gas, kJ; is the heat exchange efficiency between the heat storage body and the flue gas or high-temperature exhaust gas, %; m is the mass of the heat storage body, kg; C is the specific heat capacity of the heat storage body, kJ / kg·K; ΔT is the temperature difference increase of the heat storage body, K.

[0202] Among them, power generation capacity:

[0203] Qf=Qc*θ*μ

[0204] Where Qf is the power generation capacity, kWh; θ is the system efficiency, which is the product of the efficiency of heat storage and water heat exchange to produce steam and the pipeline transmission efficiency, %; μ is the power generation efficiency of the steam generator set, %.

[0205] 3. Construct energy network optimization, comprehensive energy site selection and network loss model.

[0206] This step mainly involves using the method of economic energy supply radius, load moment or equivalent load moment to determine the economic energy supply distance of electricity, cooling, heat, gas, etc., and then determine the site selection of the comprehensive energy station that meets the requirements of the actual scenario. The specific determination method is:

[0207] 1. Construct network loss models for cooling, heating, electricity and gas systems:

[0208] 1.1. For the cold and hot systems, the calculation formula for the resistance along the way is:

[0209]

[0210] In the formula, l represents the pipe length; d represents the pipe diameter; v represents the flow velocity; λ represents the resistance coefficient along the way, which is related to the roughness of the pipe; and g represents the acceleration due to gravity.

[0211] The calculation formula of local resistance is: dynamic pressure = local resistance coefficient * ρ * V * V * 1 / 2, which is the ratio of the local resistance generated by the fluid flowing through the equipment and pipeline accessories to the corresponding dynamic pressure, and its value is a dimensionless number; among them, ρ is the density, unit is kg / m3; V is the flow velocity, m / s.

[0212] Usually the approximate calculation can be used:

[0213]

[0214] Where p1 is the pressure at the front section of the local pipeline, p; p2 is the pressure at the rear section of the local pipeline, p; g is the acceleration of gravity, m / s2; z1 and z2 are the heights of the pipeline inlet and outlet, m; ρ is the liquid density, kg / m3.

[0215] 1.2. For electricity, network losses mainly include transformation losses, transmission and distribution losses, etc.

[0216] 2. System operation strategy based on benchmarking planning:

[0217] First, a model that meets the economic energy supply radius is constructed. The economic energy supply radius usually refers to the effective distance from the energy supply source (such as thermal power plants, substations, etc.) to the farthest user in the energy supply field. This distance is determined after considering multiple factors such as economic cost, technical feasibility, and energy efficiency.

[0218] 2.1. Select reference objects for the model of economic energy supply radius of cooling and heating systems; the cooling system can refer to the VRV (variable refrigerant flow system) system, and the heating system can refer to the gas boiler. The general cost objective function is:

[0219] F=T c +T o

[0220] Where, F is the comprehensive cost of the system network, RMB; T c is the initial investment in the pipeline network, yuan; T o is the network operation and maintenance cost, RMB.

[0221] The energy supply function is:

[0222]

[0223] In the formula, Q g is the energy supply of the system throughout the year, cold and hot are kWh; m is the mass flow rate, kg / s; c is the specific heat capacity, kJ / (kg·K); ΔT is the temperature difference between the supply and return fluids, K; n is the operating time of a certain energy system throughout the year, s; ω i is the loss coefficient of cold and hot water transmission; ω i =ω z +ω t ,ωz is the resistance along the way and the local resistance coefficient, ω t It is the heat loss coefficient between the pipe network wall and the environment. The loss coefficient is the ratio of the energy loss of a pipe network to the total energy delivery.

[0224] 2.2. The energy supply function of the compressed air system is:

[0225]

[0226] Where V is the volume flow rate, m3 / s, Q v is the total flow rate of compressed air, m3; ω fk is the loss coefficient of compressed air transportation.

[0227] 2.3. The energy supply function of the power supply system is:

[0228]

[0229] Where q(t) is the power delivered at time t, kWh, Q d is the cumulative power delivered, kWh; ω e is the loss coefficient of the transmission and distribution system.

[0230] 2.4. The optimal objective function of unit energy economy is:

[0231] minf l =F l / Q gl

[0232] minf r =F r / Q gr

[0233] minf d =F d / Q d

[0234] minf k =F k / Q v

[0235] In the formula, f l , f r , f d , f k They represent the unit energy transmission and distribution costs of cold, heat, electricity, compressed air, etc.; Q gl , Q gr , Q d , Q v The annual energy supply of cooling, heating, electricity and gas systems, kwh; F l 、F r 、Fd 、F k They are the comprehensive costs of the cooling network, heating network, power transmission and distribution network, and compressed air network, RMB.

[0236] The constraints are:

[0237] minf l ≤fl VRV

[0238] minfr≤fr gl

[0239] ω e ≤5%

[0240] ΔP fk ≤30%

[0241] ω fk ≤3%

[0242] Where fl VRV is the unit cooling distribution cost of the variable refrigerant flow (VRV) system, RMB / kwh; fr gl is the unit heat supply and distribution cost of the gas boiler system, RMB / kwh; ΔP fk is the delivery pressure drop of the compressed air system, pa.

[0243] 2.5. Operation strategy planning:

[0244] Based on the results of the above calculations, the cooling system, heating system, power supply system, and compressed air system can all use their respective reference objects (benchmarking objects) as reference systems, and combined with corresponding constraints, plan and select different pipeline paths, and continuously optimize and determine the pipeline layout plan that meets the actual conditions of the project and is closer to the reference object.

[0245] Specifically, Figure 8 As shown, after determining the energy supply costs of various systems, the costs can be ranked. Systems with low unit energy supply costs can be operated with priority and for a long time. Systems with high unit energy supply costs can be operated as peak loaders or auxiliary systems to reduce operating time.

[0246] like Fig.10 As shown in the figure, taking gas boilers and trigeneration as examples, trigeneration can realize the supply of three types of energy: electricity, heat and cold. The input is gas, and the input of the gas boiler is also gas. However, trigeneration is a one-time investment and outputs three types of energy. The unit energy supply cost is lower. Therefore, when planning and operating, it is used as the basic energy output as much as possible to ensure an operating time of more than 3,500 hours, which is more economical; and the boiler is mainly operated for peak regulation.

[0247] 3. Selection and optimization of energy station sites:

[0248] This application innovatively applies the load moment assessment method to the selection of energy station sites in the integrated energy system, that is, to various energy systems including cold, heat, electricity, and gas. The specific application is as follows:

[0249] For cooling, heating, electricity, gas systems, etc., please refer to the following methods for calculation:

[0250] Energy station location: X-axis coordinate = ∑Pi*Xi / ∑Pi

[0251] Energy station location: Y-axis coordinate = ∑Pi*Yi / ∑P

[0252] Where Pi is the load of the i-th energy consumption unit, kW; Xi is the X-axis coordinate of the i-th energy consumption unit; Yi is the Y-axis coordinate of the i-th energy consumption unit; specifically, Figure 4 shown.

[0253] Of course, in order to further accurately select the energy station as the load center, the equivalent load moment method can also be used for calculation and site selection, that is, the actual route along the load center to each load point is used as the equivalent load moment to calculate and determine the location of the load center. By transferring the load moment or equivalent load moment method used in the power field to multiple energy fields such as cold, heat, and gas, it is helpful to determine the optimal site selection plan for energy stations (such as power stations, etc.), laying the foundation for the subsequent steps to find the suboptimal energy station site selection location. The subsequent step five can be combined with actual land use, safety and other conditions, such as the impact of underground garages, green spaces, pipeline networks or roads, etc., for comprehensive consideration to determine the optimal site selection plan for energy stations that better meet actual needs.

[0254] 4. Based on load demand and energy system characteristics, determine the design system configuration and network layout plan.

[0255] This step is mainly to integrate the above models and optimization algorithms (i.e. the load model, energy system model and energy station site selection model obtained in the previous steps, etc.) to construct an energy system configuration model for the target area, which will be used in step five. Combined with the actual situation of the planning project, the final load curve, energy system selection, energy system configuration, energy station site selection and network planning scheme are formed.

[0256] Taking the target load (cold, hot, electric, gas load) in a certain target area as an example, a specific implementation method of this step may be:

[0257] 1. Determine the load model of the target load in the target area according to step 1, and obtain the typical annual load curve of the target load ( Figure 6 The typical annual load curve of heat load is shown) and arranged in descending order (see Figure 7), and obtain the load fitting space band, which is used to provide a basis for the energy system configuration selection and function customization of the target load. The role of descending order is to explore the load ratio of various loads such as cold, hot, electric, and gas. Taking the heat load as an example, the proportion of loads above 80%, the proportion of loads above 30%, etc., can be analyzed, and then the proportion range of loads with high proportions can be determined, thereby providing a basis for efficient and low-cost energy system scale design and operation time design.

[0258] 2. Analyze the energy storage scale corresponding to each target load.

[0259] Taking the electric load as an example, the electric load is mainly composed of two parts: electric load = terminal electric load + public service system electric load (including flexible electric load). The terminal electric load here refers to the electric load of the target load itself, including air-conditioning terminals, lighting, power equipment, etc.

[0260] The spatial band formed by the fitting difference between the output characteristic curve and the load curve (base + flexibility) of the power system is used as the upper limit of the adjustable space of energy storage, such as Figure 5 As shown; and combined with the electricity price model, peak-valley characteristics, and energy storage charging and discharging characteristics, a reasonable energy storage scale (including electricity storage and heat storage type thermoelectric conversion) is configured; among them, the electricity price model and peak-valley electricity price characteristics can be obtained from the regional resource conditions in the above step 2, and can be specifically determined based on the local municipal electricity price characteristic curve of the planned project obtained from the power supply bureau.

[0261] The above-mentioned adjustable space may refer to the difference between the electric load curve obtained in the above step one and the output characteristic curve of the power system energy obtained in the above step two, which can be adjusted or supplemented by energy storage; however, when the actual energy storage system is configured, it is necessary to reconfigure it according to the actual site, installation conditions, etc., but its total adjustable power is not recommended to be higher than the difference.

[0262] 3. Combined with the unit energy cost economic accounting method, evaluate the economic indicators of the energy system corresponding to the target load, and establish a cost database based on the initial investment, operation and maintenance costs of the energy system.

[0263] The specific implementation of this step can be: Evaluate the economic indicators of each energy system:

[0264] Fs=Tcs+Tys

[0265] Where Fs is the comprehensive cost of a certain energy system, RMB; Tcs is the initial investment of a certain energy system; Tys is the operation and maintenance cost of a certain energy system, RMB.

[0266] Then, based on the initial investment, operation and maintenance costs of each energy system, a cost database is established, such as Figure 8 shown.

[0267] 4. Solve the unit energy cost of each energy system to evaluate the economic level of each energy system.

[0268] The specific implementation of this step can be to calculate the energy supply function:

[0269] Qg=∑mcΔT*ti*ω

[0270] In the formula, Qg is the system's annual energy supply, cold and hot is kWh; m is mass flow, kg / s; c is specific heat, kJ / kgK; ΔT is the temperature difference between the supply and return fluids, K; ti is a time point corresponding to a certain energy supply; if it is compressed air, the calculation formula changes to: Qv = ∑V*ti, V is the volume flow, m3, Qv is the total flow of compressed air, m3. If it is power supply, the calculation formula is: Qd = ∑q*ti, q is the power delivered at a certain moment, kWh, Qd is the cumulative power delivered, kWh, ω is the transmission and distribution loss coefficient.

[0271] The optimal objective function of unit energy economy is:

[0272] minf lj =(F l +C lj ) / Q gl

[0273] minf ri =(F r +C ri ) / Q gr

[0274] minf dn =(F d +C dn ) / Q d

[0275] minf km =(F k +C km ) / Q v

[0276] In the formula, f lj , f ri , f dn , f km They are the unit energy transmission and distribution costs of the jth cooling system, the ith heating system, the nth power generation system, and the mth compressed air system (including the comprehensive cost of equipment and pipeline network. In a certain category, if they are all heating systems, the pipeline network cost is the same). Q gl and Q gr The annual energy supply of the cooling and heating systems respectively, kwh. l 、F r 、F d 、F kare the comprehensive costs of the cooling network, heating network, power transmission and distribution network, and compressed air network, respectively, in yuan. lj , C ri , C dn , C km They are the comprehensive costs (including initial investment and operation and maintenance costs) of the jth type of cooling, the ith type of heating, the nth type of power generation, and the mth type of compressed air system equipment.

[0277] The constraints are:

[0278] ω e ≤5%

[0279] ΔP fk ≤309%

[0280] ω fk ≤3%

[0281] In the formula, ΔP fk is the delivery pressure drop of the compressed air system, pa.

[0282] 5. Configure the design energy system for the target load.

[0283] A specific implementation of this step is: based on the first percentage and the second percentage, the load fitting space band can be divided into three sub-space bands: upper, middle and lower. Fig. 9 shown.

[0284] Among them, the area of ​​the upper subspace band = the area of ​​the load fitting space band * the first percentage, the area of ​​the lower subspace band = the area of ​​the load fitting space band * the second percentage, and the area of ​​the middle subspace band = the area of ​​the load fitting space band - the area of ​​the upper subspace band - the area of ​​the lower subspace band. Optionally, the first percentage and the second percentage are both empirical parameters, the first percentage is 10%-20%, the second percentage is 30%-50%, and the second percentage is preferably 40%. It should be noted that the first percentage and the second percentage can also be set according to the solution results obtained in the above steps 1-4, and of course, other settings can be made in combination with actual conditions, and are not limited here.

[0285] For the peak part and the upper subspace band part, the energy storage can be adjusted according to the energy storage scale obtained in step 2.

[0286] The long-term stable lower subspace band can be understood as the basic load, and it is necessary to find equipment or systems that meet the requirements of stable load operation and high operating efficiency to undertake the basic load supply. Therefore, according to the cost database and unit energy cost obtained in steps 3 and 4, as well as the efficiency characteristics of each energy system equipment in step 2 above, a system with low operation and maintenance cost, longer operation time, better economy, and high efficiency can be selected to ensure its long-term operation.

[0287] For the neutron space belt in the middle transition part, the cost database and unit energy cost obtained in steps 3 and 4, as well as the efficiency characteristics of each energy system equipment mentioned in the above step 2, can be used to sort out the equipment and systems with slightly lower operating time requirements and relatively higher efficiency compared to the lower subspace belt, and meet the energy needs of the park in a graded and layered manner.

[0288] The above method is suitable for selecting and configuring energy systems with operating priorities for loads such as cold, hot, electricity, and compressed air; the above method can determine the optimal design system configuration and network layout plan of the energy system under various loads of the target load, and then the design energy system configuration and network layout can be carried out for all building formats corresponding to process production, office, and life in the park.

[0289] 5. Combine various constraints, implant optimized operation priority, operation time and strategy, simulate and emulate, reversely optimize the design state system configuration, and ensure the output of the optimal source-grid-load-storage integrated planning system solution.

[0290] Based on the energy network topology and system design configuration formed in step 4 above, various constraints will be implanted at this time, including photovoltaic, wind power, chillers, boilers, air compressors, current, voltage and other constraints, including upper and lower limits of the capacity or power of the energy medium, wind and solar abandonment rate constraints, and simultaneous power constraints of various equipment. Implant the scheduling optimization strategy, and give priority to the above-mentioned systems with low operation and maintenance costs, good economy, and high operating time requirements, participate in the auxiliary operation of the regulation system, and set the system operation priority. The adjustable load is modified based on the cost price model and the process requirements according to the optimal operation mode, such as Fig.10 shown.

[0291] For example, according to the target indicator requirements of the planning scheme of the original source, grid, load and storage, the new energy consumption rate is not less than 70%, and the comprehensive cost is reduced by 30% as constraints. At this time, it is necessary to adjust the flexible load (process production, office and residence, etc.), energy system regulation capacity and energy system configuration and output, and use the constraints of each system, pipeline transmission and distribution constraints, electricity price constraints, etc. as constraints, continuously perform convergence optimization, and determine the optimal source, grid, load and storage integrated planning system solution under the above constraints, that is, the optimal energy system scale configuration and operation strategy requirements.

[0292] Specifically, the objective function can be to maximize the consumption of new energy and optimize the economic efficiency of system operation. Through simulation (such as MATLAB), iterative convergence optimization, reverse optimization of the design state system configuration and network layout, and output the optimized system configuration and solution.

[0293] Among them, the construction of the new energy consumption model can, on the one hand, effectively evaluate the new energy consumption performance of the source-grid-load-storage integrated planning system; on the other hand, through the comparison of performance indicators, it can adjust the system operation strategy or optimize the system configuration of new energy such as chillers, boilers or photovoltaics in step four, thereby further improving the new energy consumption level.

[0294] When constructing, it is necessary to follow the principle of giving priority to new energy and maximizing consumption, specifically:

[0295]

[0296] In the formula, Q n is the cumulative consumption of new energy, kWh; P(i,j) is the basic load of the i-th time and the j-th category of process production, life, office, etc., kW; P r (i,j) is the flexible and adjustable load of the process production, life, office and energy public service system at the i-th moment and the j-th category, kW; Q si is the amount of electricity unloaded from the grid during time period i, kW.

[0297] If P V (i)+P W (i)< <P(i,j)+P r (i,j), the maximum consumption of new energy is:

[0298]

[0299] Where: P V and P W are the wind power and photovoltaic power generation output at the i-th moment, kW.

[0300] In other scenarios:

[0301] The maximum consumption of new energy is:

[0302]

[0303] The above constraints are:

[0304]

[0305]

[0306] In addition, the comprehensive cost minimum model will take electricity as the core and consider the overall economic efficiency of the project. It mainly includes the power generation cost and operating cost of thermal power units, the power generation cost and operating cost of rotating standby units, the power generation cost and operating cost of wind power, the power generation cost and operating cost of photovoltaic power, the energy storage cost and operating cost, the power distribution and other energy network operating costs, the dispatching operation platform cost and operating service cost, and the cost of purchased electricity.

[0307]

[0308] In the formula, are the power generation cost and operation cost of thermal power unit m respectively; is the power generation of the thermal power unit, kwh; are the power generation cost and operation cost of adjustable thermal power unit u respectively; is the power generation of the adjustable thermal power unit, kwh; are the power generation cost and operation cost of photovoltaic power generation g respectively; is the power generation of photovoltaic power g, kWh; are the power generation cost and operation cost of wind power generation f respectively; is the power generation of wind power f, kwh; are the storage cost and operation cost of the energy storage system respectively. is the exchange power of the energy storage system, kwh; C j is the operation and maintenance cost of the jth energy network, including transmission lines of various voltage levels, heating networks, cooling networks, compressed air networks, etc.; T j is the operating cost of the public service equipment included in the corresponding j-th energy system (excluding thermal power units, wind power generation, photovoltaic power generation and energy storage systems); is the transmission loss rate of thermal power units, adjustable thermal power units, photovoltaic power generation, wind power generation, etc., %; p(i) is the off-grid electricity price corresponding to the i-th moment, RMB / kwh; p f (i) is the on-grid electricity price corresponding to the i-th moment. Generally, for new energy projects, this electricity price is the local desulfurized coal benchmark on-grid electricity price, which is a fixed value of RMB / kwh; F PO is the operating cost of the scheduling and operation management platform, RMB; Q si Q is the amount of electricity purchased from the power grid during the i-th time period, kWh. e The annual input or usage of the energy of category e, such as natural gas, heat, coal, etc., is determined according to the energy settlement unit; e is the input unit price of the energy of type e, which is generally a fixed price. If it is a fluctuating price, then Q e and p e It is the input or usage of the e-th type of energy at a certain moment and the corresponding price at that moment.

[0309] The constraints are:

[0310] The constraints on the output and capacity of the power storage system are:

[0311]

[0312] SOC min ≤SOC t ≤SOC max

[0313]

[0314] In the formula, SOC min is the minimum state of charge of the energy storage device; is the rated power of energy storage device i; t is the time period; SOC t-1 S is the state of charge in time period t-1; max The upper limit of the energy storage device capacity; is the charging and discharging power of energy storage device i in time period t; t it is the charging and discharging time of energy storage device i in time period t. When it is negative, the condition is that the amount of energy storage equipment discharged in time period t is less than the amount of electricity stored in the previous stage; When is positive, this condition is the charge capacity constraint of the energy storage device within time period t.

[0315] The constraints for photovoltaic power generation and wind power generation are:

[0316]

[0317] In the formula, is the minimum output of the photovoltaic power generation system, kW; is the maximum output of the photovoltaic power generation system, kW; is the actual output value of the photovoltaic power generation system, kW.

[0318]

[0319] In the formula, is the minimum power output of the wind power generation system, kW; The maximum power output of the wind power generation system, kW; It is the actual power output of the wind power generation system, kW.

[0320] Similarly, the constraints of thermal power units and thermal power generation regulating units are also between their maximum output and minimum output. Usually, the lower limit of thermal power condition units is set at 50% of the rated load.

[0321] Power balance constraints, with electricity as the main consideration.

[0322]

[0323] In the formula, They are the power generation capacities of photovoltaic power generation, wind power generation, thermal power generating units, and thermal power regulating units, kW.

[0324] This step realizes the feedback of the operating state to the design state to further optimize the system configuration and improve the system operation efficiency and economy.

[0325] Through the above five steps of planning and design, a collaborative planning solution that conforms to the integrated source, grid, load and storage planning system can be output in the end.

[0326] The focus of this application is to protect any of the above-mentioned source-grid-load-storage integrated planning methods, which can be understood as a full-process planning and design method from load forecasting, energy system design, site optimization, network design, economic evaluation, to reverse optimization. This method integrates multiple forms of energy (not just electricity), with the maximum absorption of new energy and the optimal system operating cost as the objective function. It can be used as an evaluation of the effectiveness of the planning system, and can also be used to reversely optimize the configuration and operation strategy of the aforementioned planning system through the effect evaluation. The present application is more systematic, with higher requirements for collaborative innovation of various systems, a wider scope, and more obvious implementation effects. Specific beneficial effects may include:

[0327] 1) The present invention constructs the characteristics and relationship models of multiple load characteristics, multiple energy forms, multiple systems and networks, ensuring the integrity of the entire planning process;

[0328] 2) The present invention innovatively couples optimization configuration methods such as flexible load regulation, load reduction optimization, load moment site selection, and operation state feedback design state into the entire process of the system, providing a guarantee for the output of the most optimized solution.

[0329] 3) The present invention closely revolves around the policy and demonstration intention of the national integrated planning system of source, grid, load and storage, maximizes the integration of multiple energy forms and multiple load demands within the park, can effectively improve the overall energy efficiency, and promote the localization and maximum consumption of renewable energy; at the same time, by analyzing the flexible load and the flexible adjustable capabilities of the energy system, it can reduce dependence on the large power grid, reduce the backup of the large power grid, and have its own adjustment capabilities; and can provide auxiliary service capabilities for the large power grid, and ultimately achieve friendly interaction with the large power grid through the integrated management system of source, grid, load and storage.

[0330] It should be understood that, for the aforementioned various method embodiments, although the various steps in the flow chart 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 description in this article, the execution of these steps does not have a strict order restriction, and these steps can be executed in other orders. Moreover, at least a portion of the steps in the flow chart of the method embodiment may include a plurality of sub-steps or a plurality of stages, and these sub-steps or stages are not necessarily executed at the same time, but can be executed at different times, and the execution order of these sub-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 portion of the sub-steps or stages of other steps.

[0331] Based on the same inventive concept, the embodiment of the present application also provides a source-grid-load-storage integrated planning system for implementing the source-grid-load-storage integrated planning method involved above, such as Fig.11 As shown. The source-grid-load-storage integrated planning system is an operating system that assists in the source-grid-load-storage integrated planning, including a load analysis module, an energy system analysis module, an integrated energy station site selection module, an energy system configuration module and a target optimization module, and finally outputs a systematic plan for source-grid-load-storage integrated planning. The implementation scheme for solving the problem provided by the system is similar to the implementation scheme recorded in the above method, so the specific limitations in one or more source-grid-load-storage integrated planning system embodiments provided below can refer to the limitations of the source-grid-load-storage integrated planning method in the above text, and will not be repeated here. This source-grid-load-storage integrated planning system may include: a load analysis module for constructing a load model of the target area; an energy system analysis module for constructing an energy system model of the target area; an integrated energy station site selection module for constructing an integrated energy station site selection model of the target area; an energy system configuration module for constructing an energy system configuration model of the target area based on the load model, the energy system model and the integrated energy station site selection model; a target optimization module for simulating and optimizing the energy system configuration model with the goal of maximizing the consumption of new energy and minimizing the system operating cost, and generating the optimal planning scheme for source-grid-load-storage of the target area based on the optimization results.

[0332] Each module in the above-mentioned source-grid-load-storage integrated planning system can be implemented in whole or in part by software, hardware, or a combination thereof. Each of the above-mentioned modules can be embedded in or independent of a processor in a computer device in the form of hardware, or can be stored in a memory in a computer device in the form of software, so that the processor can call and execute operations corresponding to each of the above modules.

[0333] In addition, in the implementation of the above-mentioned example of the integrated planning system for source, grid, load and storage, the logical division of each program module is only an example. In actual applications, the above-mentioned functions can be assigned to different program modules as needed, for example, for the configuration requirements of the corresponding hardware or the convenience of software implementation. That is, the internal structure of the integrated planning system for source, grid, load and storage is divided into different program modules to complete all or part of the functions described above.

[0334] 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.

[0335] It should be noted that in the embodiments of the present application, certain software, components, models and other existing solutions in the industry may be mentioned, and they should be regarded as exemplary. Their purpose is only to illustrate the feasibility of implementing the technical solution of the present application, but it does not mean that the applicant has or will necessarily use the solution.

[0336] The technical features of the above embodiments can be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification. In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, please refer to the relevant description of other embodiments.

[0337] The terms "including" and "having" and any variations thereof in the embodiments herein are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device comprising a series of steps or (module) units is not limited to the listed steps or units, but may optionally include steps or units not listed, or may optionally include other steps or units inherent to these processes, methods, products or devices.

[0338] The term "multiple" as used herein refers to two or more than two. "And / or" describes the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can mean: A exists alone, A and B exist at the same time, and B exists alone. The character " / " generally indicates that the related objects are in an "or" relationship.

[0339] The "first\second" mentioned in this article is only to distinguish similar objects, and does not represent a specific order for the objects. It is understandable that the "first\second" can be interchanged with the specific order or sequence where permitted. It should be understood that the objects distinguished by "first\second" can be interchanged where appropriate, so that the embodiments described herein can be implemented in an order other than those illustrated or described herein.

[0340] The above-mentioned 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 invention patent. 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 patent of the present application shall be subject to the attached claims.

Claims

1. A source-grid-load-storage integrated planning method, the method comprising: Construct load models, energy system models and integrated energy station site selection models for the target area; Based on the load model, energy system model and integrated energy station site selection model, construct an energy system configuration model for the target area; With the goal of maximizing the consumption of new energy and minimizing the system operating cost, the energy system configuration model is simulated and optimized, and the optimal planning scheme for source, grid, load and storage in the target area is generated based on the optimization results.

2. The method according to claim 1, characterized in that The steps to construct the load model for the target area include: Constructing basic load curves and flexible load curves of target loads of target energy consumption units in target areas respectively; the target loads are cooling, heating, electricity and gas loads; Superimposing the basic load curve and the flexible load curve to obtain a total load curve; Based on the total load curve and the flexible load curve, a total load model and an optimal flexible load model of the target load of the target energy consuming unit are generated.

3. The method according to claim 2, characterized in that The types of energy-consuming units include social buildings and industrial buildings; When the energy consumption unit is a social building, the step of constructing a flexible load curve of the electric load of the energy consumption unit includes: constructing load curves for each adjustable electrical load of the energy-consuming unit respectively; Superimposing the load curves of all adjustable electric loads to obtain a flexible load curve of the electric load of the energy-consuming unit; When the energy consumption unit is an industrial building, the step of constructing a flexible load curve of the electric load of the energy consumption unit includes: constructing load curves for each adjustable electrical load of the energy-consuming unit respectively; With the goal of achieving the highest degree of agreement between the load curve after translation and the target load curve, a load curve of the translatable electric load of the energy-consuming unit is constructed; The load curves of all the adjustable electric loads and the shiftable electric loads are superimposed to obtain a flexible load curve of the electric load of the energy-consuming unit.

4. The method according to claim 2, characterized in that: The step of generating a total load model and an optimal flexible load model of the electric load of the target energy consumption unit based on the total load curve and the flexible load curve comprises: Taking the total flexible load not exceeding the total load at any time and each single flexible load not exceeding the adjustment range of the equipment or system as the constraint conditions, taking the stable fluctuation of the flexible load and the maximum adjustment space of the total load as the goal, constructing the objective function based on the flexible load curve and the total load curve; The objective function is solved to obtain the total load model and the optimal flexible load model of the electric load of the target energy-consuming unit.

5. The method according to claim 2, characterized in that: The energy system model includes an output characteristic model of a new energy power supply system; The steps of constructing the output characteristic model of the new energy power supply system in the target area include: Determine the type and system scale of renewable energy power supply in the target area; Determine the original output characteristic model of each renewable energy power supply system according to the type and system scale, as well as the unit characteristics of each renewable energy power supply system; By comparing the existing power supply data of the target area with the original output characteristic model, the original output characteristic model is corrected to determine the final output characteristic model of each new energy power supply system.

6. The method according to claim 5, characterized in that The energy system model also includes an energy supply characteristic model, an energy efficiency characteristic model and a regulation characteristic model of the public service energy system; The steps of constructing the energy supply characteristic model, energy efficiency characteristic model and regulation characteristic model of the public service energy system in the target area include: Determine the type and configuration of the public service energy system in the target area; According to the type and configuration form, combined with the system performance parameters in the equipment database corresponding to each public service energy system, determine the energy supply characteristic model and energy efficiency characteristic model of each public service energy system; Generate a regulation quantity model of energy storage bodies in each public service energy system according to the system performance parameters; In combination with the regulation quantity model and the corresponding regulation strategy, regulation characteristic models of various public service energy systems are constructed.

7. The method according to claim 6, characterized in that When the type of the energy storage body is a cold storage or heat storage system, the regulation strategy includes one or more of a pipeline network energy storage regulation strategy, a temperature difference control strategy, a partition regulation strategy, and a compensation regulation strategy; When the type of the energy storage body is a gas storage system, the regulation strategy includes a gas storage tank regulation strategy; When the type of the energy storage body is an electric storage system, the regulation strategy includes a constant power charging and discharging and a constant voltage and frequency regulation strategy.

8. The method according to claim 1, characterized in that The steps to construct a comprehensive energy station site selection model for the target area include: Determine all energy-consuming units corresponding to each integrated energy station in the target area; Obtain the location coordinates of each energy consumption unit corresponding to each integrated energy station; Obtain load data of each type of load of each energy-consuming unit corresponding to each integrated energy station; Based on the position coordinates and the load data, the position coordinate model of the integrated energy station corresponding to each type of load is determined by a load moment algorithm or an equivalent load moment algorithm.

9. The method according to claim 6, characterized in that The step of constructing the energy system configuration model of the target area based on the load model, the energy system model and the integrated energy station site selection model includes: Based on the load model, obtaining a total load model of target loads of all energy consuming units in the target area; Constructing an original load curve of the target load of the target area; the original load curve is obtained by superimposing a total load model of the target loads of all energy-consuming units; Arrange the original load curve in descending order according to the load data from large to small to generate a load descending curve; the load descending curve and the coordinate axis are combined to form a load fitting space band; Sequentially dividing the load fitting space band into an upper subspace band, a middle subspace band and a lower subspace band; Based on the energy system model and the integrated energy station site selection model, an energy system configuration strategy for the loads corresponding to the upper subspace band, the middle subspace band and the lower subspace band is generated as the energy system configuration model of the target area.

10. The method according to claim 9, characterized in that The step of dividing the load fitting space band into an upper subspace band, a middle subspace band and a lower subspace band comprises: determining a first percentage and a second percentage for the load-fitting spatial band; Based on the first percentage, an upper subspace band is divided in the load fitting space band; the first percentage is an area ratio of the upper subspace band to the load fitting space band; Based on the second percentage, a lower subspace band is divided in the load fitting space band; the second percentage is an area ratio of the lower subspace band to the load fitting space band; A neutron subspace band is determined; the neutron subspace band is located between the upper subspace band and the lower subspace band.

11. The method according to claim 9, characterized in that The step of generating an energy system configuration strategy for the loads corresponding to the upper subspace band, the middle subspace band, and the lower subspace band based on the energy system model and the integrated energy station site selection model comprises: Based on the energy system model and the integrated energy station site selection model, construct an operation cost model and an energy supply model of the energy system in the target area; Taking the optimization of unit energy economy as the goal, constructing an objective function based on the operation cost model and energy supply model of the energy system; Based on the solution result of the objective function, corresponding energy systems and their operation priorities are configured for the loads corresponding to the upper subspace band, the middle subspace band and the lower subspace band, respectively.

12. The method according to any one of claims 1 to 11, characterized in that The optimal planning scheme for sources, grids, loads and storage includes the selection and scale of the energy system, the optimal location of the integrated energy station, the optimal layout scheme of the energy supply network, the optimal configuration scheme of the energy system, and the optimal operation strategy of sources, grids, loads and storage.

13. The method according to claim 12, characterized in that The step of determining the optimal location of the integrated energy station comprises: Taking the optimization of unit energy economy as the goal, an objective function is constructed based on the pipeline network cost model and pipeline network energy supply model of the integrated energy station. The constraint conditions of the objective function are set based on the constraint parameters of the benchmark object of the integrated energy station or the loss rate of the transmission and distribution network; the pipeline network cost model and the pipeline network energy supply model are both constructed based on the energy system model and the integrated energy station site selection model; Based on the solution result of the objective function, the objective constraint conditions are obtained in combination with the actual scenario to determine the optimal location of the integrated energy station; Among them, the types of integrated energy stations include cooling systems, heating systems, power supply systems and gas supply systems. The benchmarking objects of the cooling system include VRV systems, the benchmarking objects of the heating system include gas boiler systems, the benchmarking objects of the gas supply system include compressed air systems, and the power supply system uses the transmission and distribution network loss rate as the constraint condition of the objective function.

14. A source-grid-load-storage integrated planning system, characterized in that: include: Load analysis module, used to build the load model of the target area; An energy system analysis module, used to construct an energy system model of the target area; An integrated energy station site selection module, used to construct an integrated energy station site selection model for the target area; An energy system configuration module, used to construct an energy system configuration model of the target area based on the load model, the energy system model and the integrated energy station site selection model; The target optimization module is used to simulate and optimize the energy system configuration model with the goal of maximizing the consumption of new energy and minimizing the system operation cost, and generate the optimal planning scheme of source, grid, load and storage in the target area based on the optimization results.

Images