Optimal configuration method for distributed energy storage position and capacity of power grid

Abstract

The invention relates to a power grid distributed energy storage position and capacity optimal configuration method, which comprises the following steps of: establishing a simulation model of a distributed energy storage application scene, conveniently acquiring configuration demand information of a preparation power distribution building through an information acquisition module by utilizing the simulation model, analyzing the configuration demand information through a configuration analysis module, and analyzing the configuration demand information through a configuration analysis module. The power distribution requirement of the prepared power distribution building is obtained; then, the power investment income and the power investment cost are respectively and sequentially calculated by using the power distribution demand, finally, a distributed energy storage site selection and capacity optimization configuration model is established, and the power distribution demand parameter, the power investment income and the power investment cost are iterated into the model to complete the scientific configuration and access of the distributed energy storage capacity; the method has the advantages of being safe, reasonable and high in economic benefit.

Description

Technical Field

[0001] The present invention belongs to the technical field of power grid energy storage optimization, and in particular relates to a method for optimizing the location and capacity of distributed power grid energy storage. Background Art

[0002] At present, with the rapid development of renewable energy, people's pursuit of energy efficiency, and the rapid development of distributed power generation technology and DC technology, a large number of distributed photovoltaics have begun to be connected to the distribution network on a large scale, which has a profound impact on the line flow, short-circuit current, operation economy and reliability of the distribution network. In the distribution network with high penetration rate of distributed photovoltaics, the power of distributed photovoltaic power generation is affected by natural environmental conditions, has large volatility and uncertainty, and cannot provide stable power supply. The output power quality is generally poor, and due to its high penetration rate, it is very easy to abandon light, resulting in resource waste. In recent years, with the rapid development of advanced energy storage technology, a large number of energy storage systems have begun to be built in the distribution network, which can improve the reliability of power supply and reduce electricity costs by storing and releasing electric energy to achieve energy transfer. However, how to achieve the optimal scheduling and control of distributed energy storage systems to simultaneously meet multiple goals such as the economy, stability and sustainability of the power grid is an important challenge currently faced. Therefore, in order to solve the above problems, it is necessary to develop a safe, reasonable and economically efficient method for optimizing the location and capacity of distributed energy storage in the power grid. Summary of the invention

[0003] The purpose of the present invention is to overcome the deficiencies of the prior art and to provide a safe, reasonable and economically efficient method for optimizing the location and capacity of distributed energy storage in a power grid.

[0004] The object of the present invention is achieved by: a method for optimizing the location and capacity of distributed energy storage in a power grid, comprising the following steps: Step 1: Divide the area to be planned into multiple sub-power supply areas according to each main power supply equipment, and obtain basic information data of the wind power generation system, photovoltaic power generation system and energy storage system; Step 2: Combined with the distributed energy storage application scenarios actually given in the power supply area, taking into account the different grid structures faced by wind power generation and photovoltaic power generation in different locations, a simulation model of the distributed energy storage application scenario is established; Step 3: According to the simulation model of the distributed energy storage application scenario, the configuration requirement information of the reserve power distribution building is collected through the information collection module, and the configuration requirement information is sent to the configuration analysis module through the server. After that, the configuration requirement information is analyzed by the configuration analysis module to obtain the power distribution requirement of the reserve power distribution building; Step 4: Based on the power distribution demand and the power price information, the power investment income is obtained; Step 5: Calculate the energy storage conversion rate from the grid to the energy storage device based on the grid output power and the energy storage power of the energy storage device, and obtain the power investment cost based on the power investment income in step 4; Step 6: Based on the grid structure, voltage data, load data, PV user access location, charging facilities, PV access capacity, voltage fluctuation range, PV typical output and other data information, with the voltage stability, energy storage cost and active network loss of the grid as the objective function, considering the active balance constraint, energy storage power and capacity constraints, a distributed energy storage site selection and capacity optimization configuration model is established, and then the distribution demand parameters, power investment income and power investment cost are iterated into the model to achieve scientific configuration and access of distributed energy storage capacity.

[0005] Furthermore, the basic information data in step 1 includes load data, constraints of decision variables and state variables, wind power forecast data, forecast errors, energy storage configuration constraints, energy storage energy transfer formulas, and energy storage charging and discharging constraints.

[0006] Furthermore, in step 2, the wind power generation can establish an output power simulation model of the wind farm based on the observation data of the wind tower and the wind speed of the wind turbines in the wind farm; the photovoltaic power generation can establish an output power simulation model of the photovoltaic power generation system based on the hourly radiation observation data of the meteorological station.

[0007] Furthermore, the configuration analysis module in step 3 may obtain the power distribution demand of the standby power distribution building by means of power flow calculation.

[0008] Beneficial effects of the present invention: The present invention establishes a simulation model of a distributed energy storage application scenario. The simulation model can be used to collect configuration demand information of a reserve distribution building through an information collection module, and the configuration analysis module can be used to analyze the configuration demand information, thereby obtaining the distribution demand of the reserve distribution building; thereafter, the power investment income and the power investment cost are calculated in turn using the distribution demand, and finally, a distributed energy storage site selection and capacity optimization configuration model is established, and the distribution demand parameters, power investment income and power investment cost are iterated into the model to complete the scientific configuration and access of the distributed energy storage capacity; in general, the present invention has the advantages of being safe, reasonable and economically efficient. DETAILED DESCRIPTION

[0009] The present invention is further described below.

[0010] Embodiment: A method for optimizing the location and capacity of distributed energy storage in a power grid comprises the following steps: Step 1: Divide the area to be planned into multiple sub-power supply areas according to each main power supply equipment, and obtain basic information data of the wind power generation system, photovoltaic power generation system and energy storage system, where the basic information data includes load data, constraints of decision variables and state variables, wind power forecast data, forecast error, energy storage configuration constraints, energy storage energy transfer formula and energy storage charging and discharging constraints; Step 2: Combined with the distributed energy storage application scenarios actually given in the power supply area, the different grid structures faced by wind power generation and photovoltaic power generation in different locations are comprehensively considered to establish a simulation model for the distributed energy storage application scenarios. For wind power generation, the output power simulation model of the wind farm can be established based on the observation data of the wind tower and the wind speed of the wind turbines in the wind farm. For photovoltaic power generation, the output power simulation model of the photovoltaic power generation system can be established based on the hourly radiation observation data of the meteorological station. Step 3: According to the simulation model of the distributed energy storage application scenario, the configuration demand information of the reserve power distribution building is collected through the information collection module, and the configuration demand information is sent to the configuration analysis module through the server. After that, the configuration demand information is analyzed and the power flow is calculated by the configuration analysis module to obtain the power distribution demand of the reserve power distribution building; Step 4: Based on the power distribution demand and the power price information, the power investment income is obtained; Step 5: Calculate the energy storage conversion rate from the grid to the energy storage device based on the grid output power and the energy storage power of the energy storage device, and obtain the power investment cost based on the power investment income in step 4; Step 6: Based on the grid structure, voltage data, load data, PV user access location, charging facilities, PV access capacity, voltage fluctuation range, PV typical output and other data information, with the voltage stability, energy storage cost and active network loss of the grid as the objective function, considering the active balance constraint, energy storage power and capacity constraints, a distributed energy storage site selection and capacity optimization configuration model is established, and then the distribution demand parameters, power investment income and power investment cost are iterated into the model to achieve scientific configuration and access of distributed energy storage capacity.

[0011] When the present invention is used, first, the area to be planned is divided into multiple sub-power supply areas according to each main power supply equipment, and basic information data of the wind power generation system, the photovoltaic power generation system and the energy storage system are obtained, wherein the basic information data includes load data, constraints of decision variables and state variables, wind power prediction data, prediction errors, energy storage configuration constraints, energy storage energy transfer formulas and energy storage charging and discharging constraints. Then, combined with the distributed energy storage application scenarios actually given in the sub-power supply areas, the different power grid structure facts faced by wind power generation and photovoltaic power generation in different locations are comprehensively considered to establish a simulation model of the distributed energy storage application scenario. Then, according to the simulation model of the distributed energy storage application scenario, the configuration requirement information of the reserve distribution building is collected through the information collection module, and the configuration requirement information is sent to the configuration analysis module via the server. After that, the configuration requirement information is analyzed by the configuration analysis module to obtain the distribution demand of the reserve distribution building. Then, based on the distribution demand, the power investment income and the power investment cost are calculated in turn. Finally, according to the power grid structure, voltage data, load data, photovoltaic users, The data information such as access location, charging facilities, photovoltaic access capacity, voltage fluctuation range, typical photovoltaic output, etc., takes the voltage stability of the power grid, energy storage cost and active network loss as the objective function, considers the active balance constraint, energy storage power and capacity constraint, establishes a distributed energy storage site selection and capacity optimization configuration model, after completing the above operations, iterates the distribution demand parameters, power investment income and power investment cost into the model, so as to complete the scientific configuration and access of the distributed energy storage capacity; the present invention establishes a simulation model of the distributed energy storage application scenario, and uses the simulation model to facilitate the collection of configuration demand information of the prepared distribution building through the information collection module, and uses the configuration analysis module to analyze the configuration demand information, so as to obtain the distribution demand of the prepared distribution building; thereafter, using the distribution demand, respectively calculates the power investment income and the power investment cost in turn, and finally, establishes a distributed energy storage site selection and capacity optimization configuration model, and iterates the distribution demand parameters, power investment income and power investment cost into the model, so as to complete the scientific configuration and access of the distributed energy storage capacity; in general, the present invention has the advantages of safety, rationality and high economic benefit.

[0012] The above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit the same. Although the present invention has been described in detail with reference to the above embodiments, a person skilled in the art should understand that the specific implementation modes of the present invention can still be modified or replaced by equivalents, and any modification or equivalent replacement that does not depart from the spirit and scope of the present invention should be included in the scope of the claims of the present invention.

Claims

1. A method for optimizing the location and capacity of distributed energy storage in a power grid, characterized in that: The following steps are involved: Step 1: Divide the area to be planned into multiple sub-power supply areas according to each main power supply equipment, and obtain basic information data of the wind power generation system, photovoltaic power generation system and energy storage system; Step 2: Combined with the distributed energy storage application scenarios actually given in the power supply area, taking into account the different grid structures faced by wind power generation and photovoltaic power generation in different locations, a simulation model of the distributed energy storage application scenario is established; Step 3: According to the simulation model of the distributed energy storage application scenario, the configuration requirement information of the reserve power distribution building is collected through the information collection module, and the configuration requirement information is sent to the configuration analysis module through the server. After that, the configuration requirement information is analyzed by the configuration analysis module to obtain the power distribution requirement of the reserve power distribution building; Step 4: Based on the power distribution demand and the power price information, the power investment income is obtained; Step 5: Calculate the energy storage conversion rate from the grid to the energy storage device based on the grid output power and the energy storage power of the energy storage device, and obtain the power investment cost based on the power investment income in step 4; Step 6: Based on the grid structure, voltage data, load data, PV user access location, charging facilities, PV access capacity, voltage fluctuation range, PV typical output and other data information, with the voltage stability, energy storage cost and active network loss of the grid as the objective function, considering the active balance constraint, energy storage power and capacity constraints, a distributed energy storage site selection and capacity optimization configuration model is established, and then the distribution demand parameters, power investment income and power investment cost are iterated into the model to achieve scientific configuration and access of distributed energy storage capacity.

2. A method for optimizing the location and capacity of distributed energy storage in a power grid according to claim 1, characterized in that: The basic information data in step 1 includes load data, constraints of decision variables and state variables, wind power forecast data, forecast errors, energy storage configuration constraints, energy storage energy transfer formulas, and energy storage charging and discharging constraints.

3. A method for optimizing the location and capacity of distributed energy storage in a power grid according to claim 1, characterized in that: In step 2, the wind power generation can be based on the observation data of the wind tower and the wind speed of the wind turbines in the wind farm, so as to establish an output power simulation model of the wind farm; the photovoltaic power generation can be based on the hourly radiation observation data of the meteorological station, so as to establish an output power simulation model of the photovoltaic power generation system.

4. A method for optimizing the location and capacity of distributed energy storage in a power grid according to claim 1, characterized in that: The configuration analysis module in step 3 can obtain the power distribution demand of the reserve power distribution building by means of power flow calculation.