Power supply optimal configuration method, system and equipment based on source network load coordination interaction

Abstract

The invention provides a power supply optimization configuration method, system and equipment based on source network load coordination interaction, and the method comprises the steps: carrying out the distribution of the total installation increment of new energy based on the limitation of the power grid bearing capability and the load prediction amount; carrying out weighted summation on the installation capacity goodness, the power grid bearing capacity coefficient and the growth coefficient of the load prediction quantity of the installation project in the sub-period, and calculating the development suitability; taking the total installation limit quantity of the sub-period and the installation limit quantity of the sub-region in which each installation project is located as constraints, and selecting at least one installation project in the sub-period according to the development suitability degree to carry out power supply optimization configuration; according to the method and system, through collaborative planning of the new energy, the power grid and the load, new energy output consumption is guaranteed, safe and reliable operation of the power grid is guaranteed to the maximum extent, meanwhile, influences of volatility, randomness and intermittency of the new energy are fully considered, and through limitation of the power grid bearing capacity and the load predictive quantity, the load predictive quantity is optimized. And the development scale and the development time sequence of the installed project are suggested, so that the practicability is higher.

Description

Technical Field

[0001] The present invention belongs to the technical field of electric power energy, and particularly relates to a power source optimization configuration method, system and device based on coordinated interaction of power sources, grid and load. Background Art

[0002] There are a rich variety of power sources in the power system, covering renewable new energies such as wind power and photovoltaic power, as well as non-renewable energies such as thermal power. With the advancement of the construction of a new power system, the proportion of new energy power generation represented by wind and light new energies has been steadily increasing. The development plan of wind and light resources needs to consider the grid carrying capacity, the developable situation of wind and light resources, the situation of traditional thermal power generation, the current load and the load forecast situation at the same time, involving different entities in multiple industries. Currently, each entity often starts from its own considerations and lacks overall coordinated interaction, resulting in the lack of practical value of the configuration plan. Ultimately, it is generally decided manually according to research information and considerations such as economic development, relying on planners to subjectively consider the matching relationship between power sources, grid and load, without specific quantitative methods, resulting in increased configuration costs and affecting the stability of system operation. Summary of the Invention

[0003] To overcome the deficiencies of the above-mentioned prior art, the present invention proposes a power source optimization configuration method based on coordinated interaction of power sources, grid and load, including: Obtaining the total incremental installed capacity of new energy suitable for the area to be configured during the period to be configured and all installation projects; Dividing the area to be configured into several sub-areas, and dividing the period to be configured into several sub-periods. Based on the grid carrying capacity of each sub-area in each sub-period and the limitation of the load forecast quantity in each sub-period, distributing the total incremental installed capacity of new energy to obtain the installed capacity limit of each sub-area in each sub-period and the total installed capacity limit of the area to be configured in each sub-period; Based on each installation project, in each sub-period, weighted summation is performed on the goodness of the installed capacity of the installation project in the sub-period, the grid carrying capacity coefficient of the sub-area where the installation project is located in the sub-period, and the growth coefficient of the load forecast quantity, and the development suitability of the installation project in the sub-period is calculated; Taking the total installed capacity limit of the sub-period and the installed capacity limits of the sub-areas where each installation project is located as constraints, at least one installation project is selected in the sub-period for power source optimization configuration according to the development suitability of each installation project in the sub-period.

[0004] Preferably, the step of based on each installation project, in each sub-period, weighted summation is performed on the goodness of the installed capacity of the installation project in the sub-period, the grid carrying capacity coefficient of the sub-area where the installation project is located in the sub-period, and the growth coefficient of the load forecast quantity, and the development suitability of the installation project in the sub-period is calculated, includes: Based on each installed capacity project, in each sub-period, calculate the difference between the installed capacity limit of the sub-region where the installed capacity project is located in the sub-period and the installed capacity of the installed capacity project to obtain the installed capacity configuration deviation; When the installed capacity configuration deviation is negative, set the installed capacity goodness of the installed capacity project in the sub-period to zero; When the installed capacity configuration deviation is non-negative, set the installed capacity goodness of the installed capacity project in the sub-period to be inversely proportional to the installed capacity configuration deviation; Perform a weighted sum of the installed capacity goodness of the installed capacity project in the sub-period, the grid carrying capacity coefficient of the sub-region where the installed capacity project is located in the sub-period, and the growth coefficient of the load forecast amount to calculate the development suitability of the installed capacity project in the sub-period.

[0005] Preferably, the process of obtaining the growth coefficient of the load forecast amount of the sub-region where the installed capacity project is located in the sub-period includes: Obtain the load forecast amount of the sub-region where the installed capacity project is located in the sub-period and the actual load amount of the sub-region where the installed capacity project is located; Calculate the difference between the load forecast amount of the sub-region where the installed capacity project is located in the sub-period and the actual load amount of the sub-region where the installed capacity project is located to obtain the load forecast growth amount; After coefficientizing the load forecast growth amount, obtain the growth coefficient of the load forecast amount of the sub-region where the installed capacity project is located in the sub-period.

[0006] Preferably, obtaining the total suitable installed capacity increment of new energy in the area to be configured during the period to be configured includes: Based on the historical operation data of the source, grid, and load of the area to be configured, predict the load forecast amount of the last sub-period of the area to be configured during the period to be configured through a load forecast model; Take the pre-obtained new energy development boundary as a constraint condition, and construct an objective function with the goal of minimizing the total output difference between the power output of the area to be configured and the load forecast amount of the last sub-period; the power output is the sum of the new energy output and the non-new energy output; Assuming that the non-new energy output does not increase, solve the objective function to obtain the optimal new energy output and the total suitable installed capacity increment of new energy corresponding to the optimal new energy output.

[0007] Preferably, the process of obtaining the new energy development boundary includes: Based on the geographical information of the area to be configured, determine the installed capacity per unit area of new energy and the available area of new energy in the area to be configured; Calculate the product of the installed capacity per unit area of the new energy and the available area of the new energy in the area to be configured to obtain the maximum new energy development potential; Take the maximum new energy development potential as the upper limit value of the new energy development boundary, and take the existing new energy installed capacity in the area to be configured as the lower limit value of the new energy development boundary to obtain the new energy development boundary.

[0008] Preferably, after obtaining the total suitable installed capacity increment of the new energy in the area to be configured during the period to be configured, it further includes: Based on the total suitable installed capacity increment of the new energy, use the clustering algorithm to obtain the total non-new energy installed capacity increment required for peak regulation of the power grid system.

[0009] Preferably, the step of using the clustering algorithm to obtain the total non-new energy installed capacity increment required for peak regulation of the power grid system based on the total suitable installed capacity increment of the new energy includes: Calculate the sum of the total suitable installed capacity increment of the new energy and the existing new energy installed capacity to obtain the final installed capacity in the area to be configured; Based on the final installed capacity, use the clustering algorithm to determine the moment when the difference between the hourly output of the final installed capacity and the load forecast value in the last sub-period during the period to be configured is the largest, and obtain the output difference at the moment when the difference is the largest; Perform non-new energy output efficiency conversion on the output difference to obtain the total non-new energy installed capacity increment.

[0010] Based on the same inventive concept, the present invention further provides a power source optimization configuration system based on source-network-load coordinated interaction, including: A data acquisition module for acquiring the total suitable installed capacity increment of the new energy and all installed projects in the area to be configured during the period to be configured; A grid-based allocation module for dividing the area to be configured into several sub-areas, dividing the period to be configured into several sub-periods, and allocating the total installed capacity increment of the new energy based on the grid carrying capacity of each sub-area in each sub-period and the limit of the load forecast value in each sub-period, to obtain the installed capacity limit of each sub-area in each sub-period and the total installed capacity limit of the area to be configured in each sub-period; A development suitability calculation module for, based on each installed project, in each sub-period, performing weighted summation of the installation quantity goodness of the installed project in the sub-period, the grid carrying capacity coefficient of the sub-area where the installed project is located in the sub-period, and the growth coefficient of the load forecast value, to calculate the development suitability of the installed project in the sub-period; A power optimization configuration module is used to select at least one installation project for power optimization configuration in the sub-period according to the development suitability of each installation project in the sub-period, with the total installed capacity limit of the sub-period and the installed capacity limits of each sub-region where the installation projects are located as constraints.

[0011] Preferably, the development suitability calculation module is specifically used for: Based on each installation project, in each sub-period, calculate the difference between the installed capacity limit of the sub-region where the installation project is located in the sub-period and the installed capacity of the installation project to obtain the installed capacity configuration deviation. When the installed capacity configuration deviation is negative, set the installed capacity goodness of the installation project in the sub-period to zero. When the installed capacity configuration deviation is non-negative, make the installed capacity goodness of the installation project in the sub-period inversely proportional to the installed capacity configuration deviation. Perform a weighted sum of the installed capacity goodness of the installation project in the sub-period, the grid carrying capacity coefficient of the sub-region where the installation project is located in the sub-period, and the growth coefficient of the load forecast quantity to calculate the development suitability of the installation project in the sub-period.

[0012] Preferably, the development suitability calculation module is specifically used for: Obtain the load forecast quantity of the sub-region where the installation project is located in the sub-period and the actual load quantity of the sub-region where the installation project is located. Calculate the difference between the load forecast quantity of the sub-region where the installation project is located in the sub-period and the actual load quantity of the sub-region where the installation project is located to obtain the load forecast growth quantity. After coefficientizing the load forecast growth quantity, obtain the growth coefficient of the load forecast quantity of the sub-region where the installation project is located in the sub-period.

[0013] Preferably, the data acquisition module is specifically used for: Based on the historical operation data of the source, grid, and load in the area to be configured, predict the load forecast quantity of the last sub-period within the period to be configured of the area to be configured through a load forecast model. Take the pre-acquired new energy development boundary as a constraint condition, and construct an objective function with the goal of minimizing the total output difference between the power output of the area to be configured and the load forecast quantity of the last sub-period; the power output is the sum of the new energy output and the non-new energy output. Assuming that the non-new energy output does not increase, solve the objective function to obtain the optimal new energy output and the corresponding total installed capacity increment of the suitable new energy.

[0014] Preferably, the data acquisition module is specifically used for: Based on the geographical information of the area to be configured, determine the installed capacity per unit area of new energy and the available area of new energy in the area to be configured; Calculate the product of the installed capacity per unit area of new energy and the available area of new energy in the area to be configured to obtain the maximum new energy development potential; Use the maximum new energy development potential as the upper limit value of the new energy development boundary, and use the existing new energy installed capacity in the area to be configured as the lower limit value of the new energy development boundary to obtain the new energy development boundary.

[0015] Preferably, after obtaining the total installed capacity increment of new energy suitable for the area to be configured during the period to be configured, it further includes: A non-new energy increment acquisition module, configured to use a clustering algorithm to obtain the total non-new energy installed capacity increment required for peak shaving of the power grid system based on the total installed capacity increment of new energy suitable.

[0016] Preferably, the non-new energy increment acquisition module is specifically configured to: Calculate the sum of the total installed capacity increment of new energy suitable and the existing new energy installed capacity to obtain the final installed capacity in the area to be configured; Based on the final installed capacity, use a clustering algorithm to determine the moment when the difference between the hourly output of the final installed capacity and the load prediction value in the last sub-period during the period to be configured is the largest, and obtain the output difference at the moment when the difference is the largest; Perform non-new energy output efficiency conversion on the output difference to obtain the total non-new energy installed capacity increment.

[0017] Based on the same inventive concept, the present invention also provides a computer device, including: one or more processors; A memory for storing one or more programs; When the one or more programs are executed by the one or more processors, the power optimization configuration method based on the coordinated interaction of the source, grid, and load as described above is implemented.

[0018] Based on the same inventive concept, the present invention also provides a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed, the power optimization configuration method based on the coordinated interaction of the source, grid, and load as described above is implemented.

[0019] Compared with the closest prior art, the beneficial effects of the present invention are as follows: The present invention provides a method and system for optimizing the power source configuration based on the coordinated interaction of the power source, grid, and load, including obtaining the total incremental installed capacity of new energy suitable for the area to be configured during the period to be configured and all installation projects; dividing the area to be configured into several sub-areas, dividing the period to be configured into several sub-periods, and allocating the total incremental installed capacity of new energy based on the grid carrying capacity of each sub-area in each sub-period and the limitation of the load prediction quantity in each sub-period, so as to obtain the installed capacity limit of each sub-area in each sub-period and the total installed capacity limit of the area to be configured in each sub-period; based on each installation project, in each sub-period, calculating the development suitability of the installation project in the sub-period by weighted summing the goodness of the installed capacity of the installation project in the sub-period, the grid carrying capacity coefficient of the sub-area where the installation project is located in the sub-period, and the growth coefficient of the load prediction quantity; taking the total installed capacity limit of the sub-period and the installed capacity limits of the sub-areas where each installation project is located as constraints, and selecting at least one installation project for optimizing the power source configuration in the sub-period according to the development suitability of each installation project in the sub-period; through the coordinated planning of new energy, grid, and load, on the one hand, it ensures the consumption of new energy output, on the other hand, it maximally ensures the safe and reliable operation of the grid, and at the same time fully considers the impact of the volatility, randomness, and intermittency of new energy on the safe and stable operation of the grid. By restricting the grid carrying capacity and load prediction quantity, the planned installed capacity suitable for new energy, that is, the installed capacity limit, is quantitatively determined, and finally suggestions on the development scale and development time sequence of the installation project are given, with stronger practicability. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] Figure 1 It is a schematic flow chart of a method for optimizing the power source configuration based on the coordinated interaction of the power source, grid, and load provided by the present invention; Figure 2 It is a schematic flow chart of obtaining the total installed capacity limit of each sub-period provided by the present invention; Figure 3 It is a schematic structural diagram of a system for optimizing the power source configuration based on the coordinated interaction of the power source, grid, and load provided by the present invention; Figure 4 It is a schematic structural diagram of an electronic device provided by the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0021] The following further elaborates on the specific embodiments of the present invention with reference to the accompanying drawings.

[0022] Embodiment 1: A method for optimizing the power source configuration based on the coordinated interaction of the power source, grid, and load provided by the present invention, as Figure 1 shown, includes: S1. Obtain the total incremental installed capacity of new energy suitable for the area to be configured during the period to be configured and all installation projects; S2. Mesh the area to be configured into several sub - areas, divide the period to be configured into several sub - periods, and allocate the total installed capacity increment of new energy based on the grid - bearing capacity of each sub - area in each sub - period and the limit of the predicted load in each sub - period, so as to obtain the installed capacity limit of each sub - area in each sub - period and the total installed capacity limit of the area to be configured in each sub - period; S3. Based on each installation project, in each sub - period, calculate the development suitability of the installation project in the sub - period by weighted summing the goodness of the installed capacity of the installation project in the sub - period, the grid - bearing capacity coefficient of the sub - area where the installation project is located in the sub - period, and the growth coefficient of the predicted load; S4. Taking the total installed capacity limit of the sub - period and the installed capacity limits of the sub - areas where each installation project is located as constraints, select at least one installation project for power optimization configuration in the sub - period according to the development suitability of each installation project in the sub - period.

[0023] Considering that there is a lack of a planning method for the new - energy development time sequence that simultaneously considers the coordinated interaction of the power source, grid, and load in the existing technology. It only relies on planners to subjectively consider the matching relationship between the power source, grid, and load, without a specific quantification method. For the construction of a new - type power system with new energy as the main body, it is necessary to ensure the consumption of new - energy power generation while considering energy security, and fully consider the impact of the volatility, randomness, and intermittency of new energy on the safe and stable operation of the power grid. Through the coordinated planning of new energy, the power grid, and the load, on the one hand, it ensures the consumption of new - energy output, and on the other hand, it maximally ensures the safe and reliable operation of the power grid. At the same time, fully considering the impact of the volatility, randomness, and intermittency of new energy on the safe and stable operation of the power grid, through the limitations of the grid - bearing capacity and the predicted load, quantitatively determine the suitable planned installed capacity scale of new energy, that is, the installed capacity limit, and finally give suggestions on the development scale and development time sequence of the installation project, which is more practical.

[0024] In this embodiment, the new energy includes wind - power new energy and photovoltaic new energy.

[0025] Considering that the development planning of existing wind and light resources needs to simultaneously consider the grid - bearing capacity, the developable situation of wind and light resources, that is, the developable situation of new energy, the situation of traditional thermal power generation, that is, non - new - energy power generation, the current load, and the load prediction situation, involving different entities in various industries. Each entity often starts from its own considerations and lacks overall coordinated interaction. Generally, it is decided by human judgment based on research information and considerations such as economic development, without a specific quantification method, resulting in an increase in configuration costs and affecting the stability of the operation of the power - grid system. Therefore, based on the comprehensive analysis of multiple factors such as the grid - bearing capacity in the current state and the planned state, the development situation of wind and light resources (new energy), the situation of traditional thermal power generation, the energy - storage configuration situation, the current load, and the load prediction situation, this invention conducts quantitative calculation and evaluation of the installed capacity of wind and light resource development, and finally gives suggestions on the development time sequence and development scale.

[0026] In this embodiment, before executing S1, Figure 2 As shown, to determine the current power supply configuration of the area to be configured, the current wind power AMW, the current photovoltaic BMW, and the current thermal power generation CMW, where MW is the unit. Compared with the local load Pl, if (A+B+C) / Pl<1.2, the source and load are basically matched, otherwise the source and load are not matched, and the generated electricity is mainly for power transmission and consumption. The amount of electricity sent depends on the carrying capacity of the power transmission channel and the consumption capacity of the transmission destination. When the source and load are basically matched and local consumption is the main method, it is necessary to perform subsequent power optimization configuration for the area to be configured. Therefore, the total installed capacity increment of new energy suitable for the area to be configured with basic source and load matching is obtained.

[0027] In this embodiment, before obtaining the new energy suitable total installed capacity increment in the above S1, it is necessary to obtain the new energy development boundary in advance. The process of obtaining the new energy development boundary may include: Based on the geographic information of the area to be configured, determine the installed capacity per unit area of ​​new energy and the area available for new energy in the area to be configured; Calculate the product of the installed capacity per unit area of ​​new energy and the available area of ​​new energy in the area to be configured to obtain the maximum potential for new energy development; The maximum new energy development potential is taken as the upper limit of the new energy development boundary, and the existing new energy installation capacity in the area to be configured is taken as the lower limit of the new energy development boundary to obtain the new energy development boundary.

[0028] Specifically, when evaluating the maximum new energy development potential and wind and solar development potential, wind power new energy and photovoltaic new energy are calculated separately; the maximum wind development potential A' and the maximum light development potential B' of wind and solar resources are evaluated according to the wind and solar development potential model, in MW. In this way, the installed capacity range of wind and solar development is determined, with the maximum value being A' and B', and the minimum value being the current wind and solar installed capacity, that is, the existing new energy installed capacity.

[0029] The specific determination method of A' and B' is as follows: first, obtain the land use type, elevation, slope, slope direction and other land use information of the area to be configured, calculate it with a 100-meter resolution grid, eliminate the unusable areas such as ecological red lines and military areas, eliminate the areas with poor wind and solar resources and the areas with a kilowatt-hour cost higher than the local electricity price, and screen and determine the land area that can be installed with wind and solar new energy; then, calculate the maximum wind and solar development potential of the assessment area, i.e. the area to be configured, based on the installed capacity per unit area of ​​wind and solar and the kilowatt-hour cost; among which, the kilowatt-hour cost of the area corresponding to the wind and solar available area is not lower than the local electricity price. If the same area of ​​new energy available area can be installed with both wind power and photovoltaic power, it is necessary to divide this area of ​​new energy available area into the new energy type with a lower kilowatt-hour cost by comparing the kilowatt-hour costs of wind and solar power; Finally, calculate the maximum new energy development potential according to the following formula. The maximum new energy development potential includes the maximum wind development potential A' and the maximum solar development potential B': The maximum wind development potential A' = the installed capacity per unit area of wind * the available area of wind; The maximum solar development potential B' = the installed capacity per unit area of solar * the available area of solar.

[0030] In the above S1, by obtaining the total appropriate installed capacity increment of new energy, the overall development scale suggestion for the area to be configured during the period to be configured can be given, providing a general direction for subsequent specific configuration; In this embodiment, when obtaining the total appropriate installed capacity increment of new energy for the area to be configured during the period to be configured in the above S1, it may include: Based on the historical operation data of the source, grid, and load in the area to be configured, predict the load prediction quantity of the last sub-period in the area to be configured during the period to be configured through the load prediction model; Take the previously obtained new energy development boundary as a constraint condition, and construct an objective function with the goal of minimizing the total output difference between the power output of the area to be configured and the load prediction quantity of the last sub-period; the power output is the sum of the new energy output and the non-new energy output; Assume that the non-new energy output does not increase, solve the objective function, and obtain the optimal new energy output and the corresponding total appropriate installed capacity increment of new energy.

[0031] For example, one sub-period is one year. After determining the value range of the installed capacity of wind and solar, calculate the hourly power output and load curve of various power sources within one year, and calculate the sum of the differences between the hourly power output and the load for 8760 hours in one year , that is, calculate the total output difference between the power output of the area to be configured and the load prediction quantity of the last sub-period; With the goal of minimizing Construct an objective function, which is expressed as: =min

[0032] Among them, is the load prediction quantity of the last sub-period, and the relationship between the installed capacity of wind and solar and the output: =(the existing installed capacity of wind power + the total installed capacity increment of wind power) * the output coefficient of wind power; the total installed capacity increment of wind power is the wind power to be installed during the entire period to be configured; =(the existing installed capacity of photovoltaic + the total installed capacity increment of photovoltaic) * the output coefficient of photovoltaic; the total installed capacity increment of photovoltaic is the wind power to be installed during the entire period to be configured; Assume that the non-new energy output does not increase, is the current installed capacity of thermal power; Since the wind and solar resource varies in different regions, the values of the wind and solar output coefficients are different. Generally, the photovoltaic output coefficient ranges from 0.4 to 0.8, and the wind power output coefficient ranges from 0.3 to 0.8. The specific data can be calculated according to the local installed capacity of wind and solar and the power generation output. The calculation formula of the output coefficient cp of wind and solar is the same, which is expressed as: Output coefficient cp = (actual output power) / (theoretical maximum output power).

[0033] In this embodiment, when specifically solving the objective function, there is a reasonable planning range of installed capacity of wind and solar resources, that is, the new energy development boundary, which is expressed here as: wind power installed capacity boundary A - A', photovoltaic installed capacity boundary B - B'; Assuming that the thermal power maintains the existing scale without increase, use the Monatello method or other existing algorithms for solving the objective function to calculate min within the installed capacity range of wind and solar, and obtain the total appropriate installed capacity increment of new energy corresponding to the optimal new energy output, which is correspondingly expressed as the total installed capacity increment of wind power and the total installed capacity increment of photovoltaic .

[0034] The specific steps for solving the objective function can be: (1) Define the problem: First, it is necessary to clarify the mathematical model and objective function of the problem, as well as the variables or parameters to be solved. The installed capacity of wind and solar takes values within the range of A - A' and B - B', and the minimum is obtained.

[0035] (2) Random sampling: Generate random samples, which can be random numbers with uniform distribution or normal distribution. According to the sampling rules, map the random numbers to the domain of the problem to obtain a set of sampling points.

[0036] (3) Simulation calculation: Substitute the sampling points into the objective function to obtain the function values of the objective function. According to the magnitude relationship of the function values, count the number of samples that meet the conditions to obtain the estimated value of the objective function in the sampling area.

[0037] (4) Statistical analysis: According to the law of large numbers and the central limit theorem, use the data obtained from sampling to calculate statistical quantities such as the expected value, variance, and confidence interval of the problem, and conduct further analysis and inference based on the results.

[0038] In this embodiment, after obtaining the total appropriate installed capacity increment of new energy in the area to be configured during the period to be configured, it further includes: Based on the total appropriate installed capacity increment of new energy, use the clustering algorithm to obtain the total installed capacity increment of non - new energy required for peak shaving of the power grid system.

[0039] In this embodiment, based on the total incremental installed capacity of new energy, a clustering algorithm is used to obtain the total incremental installed capacity of non-new energy required for peak shaving of the power grid system, including: Calculate the sum of the total incremental installed capacity of new energy and the existing installed capacity of new energy to obtain the final installed capacity of the area to be configured; Based on the final installed capacity, use the clustering algorithm to determine the moment when the difference between the hourly output of the final installed capacity and the load prediction of the last sub-period within the period to be configured is the largest, and obtain the output difference at the moment with the largest difference; Perform non-new energy output efficiency conversion on the output difference to obtain the total incremental installed capacity of non-new energy.

[0040] Specifically, when the suitable installed capacity of wind and light, that is, the total incremental installed capacity of new energy, is 、 Use the clustering algorithm to calculate the output difference P at the moment when the hourly output and the load differ greatly. Due to the intermittent characteristics of wind and light output, this part needs to be compensated by traditional thermal power or energy storage. The output of thermal power and energy storage is relatively stable and has strong controllability. The output difference P obtained through the clustering algorithm can guide the installed capacity ratio of thermal power or energy storage , that is, the installed capacity ratio of non-new energy. For thermal power, the installed capacity of thermal power = output difference P / 0.95, and for energy storage, the installed capacity of energy storage = output difference P / 0.8. 0.95 and 0.8 mainly consider the output efficiency of thermal power and energy storage, and can be adjusted as appropriate according to the actual situation.

[0041] While carrying out the coordinated planning of the power source, grid and load, comprehensively considering the peak shaving effects of traditional power sources and energy storage, that is, non-new energy, can gradually realize the active support ability of new energy, enhance the system's toughness, elasticity and self-healing ability, and ensure energy security and energy quality.

[0042] The above calculated suitable installed capacity of wind and light 、 is the final installed capacity. Only considering from the perspectives of resource development and load matching, the bearing capacity and planning of the power grid itself, as well as the growth and change of the load with economic development are not considered, and actual power source configuration cannot be carried out. Therefore, in the above S2, under the constraints of the power grid bearing capacity and load prediction, the total incremental installed capacity of new energy is divided on the regional grid and in time to obtain the installed capacity limit of each sub-region in each sub-period and the total installed capacity limit of the area to be configured in each sub-period; For example, gridify the power grid bearing capacity Cgridi and load prediction Pli in the i-th year, and match them with the installed capacity of wind and light in the same grid, then the installed capacity of wind and light that is more in line with the objective conditions within the grid in the i-th year can be obtained 、 That is, the installed capacity limit of each sub-region in each sub-period. The grid can be divided by administrative districts, counties, and townships, or by power grid management units (power supply areas, power supply grids), etc.

[0043] In order to give suggestions on the development timing of each installed capacity project to facilitate the specific implementation of each installed capacity project, in the above S3, the development timing of each installed capacity project is determined by calculating the development suitability of each installed capacity project, so that this method can be practically applied.

[0044] In this embodiment, when calculating the development suitability in the above S3, it may include: Based on each installed capacity project, in each sub-period, calculate the difference between the installed capacity limit of the sub-region where the installed capacity project is located in the sub-period and the installed capacity of the installed capacity project to obtain the installed capacity configuration deviation; When the installed capacity configuration deviation is negative, set the installed capacity goodness of the installed capacity project in the sub-period to zero; When the installed capacity configuration deviation is non-negative, set the installed capacity goodness of the installed capacity project in the sub-period to be inversely proportional to the installed capacity configuration deviation to obtain the installed capacity goodness of the installed capacity project in the sub-period; Perform a weighted sum of the installed capacity goodness of the installed capacity project in the sub-period, the power grid carrying capacity coefficient of the sub-region where the installed capacity project is located in the sub-period, and the growth coefficient of the load forecast amount to calculate the development suitability of the installed capacity project in the sub-period.

[0045] It should be noted that when the installed capacity configuration deviation is negative, that is, when the installed capacity of this installed capacity project is greater than the corresponding installed capacity limit, this installed capacity project is definitely not suitable for configuration in the sub-region and sub-period corresponding to this installed capacity limit. Therefore, set the installed capacity goodness at this time to zero.

[0046] In this embodiment, the process of obtaining the growth coefficient of the load forecast amount of the sub-region where the installed capacity project is located in the sub-period includes: Obtain the load forecast amount of the sub-region where the installed capacity project is located in the sub-period and the actual load amount of the sub-region where the installed capacity project is located; Calculate the difference between the load forecast amount of the sub-region where the installed capacity project is located in the sub-period and the actual load amount of the sub-region where the installed capacity project is located to obtain the load forecast growth amount; After coefficientizing the load forecast growth amount, obtain the growth coefficient of the load forecast amount of the sub-region where the installed capacity project is located in the sub-period.

[0047] Specifically, the process of coefficientizing is: divide the load growth situation, that is, the load forecast growth amount, into three situations: slow, average, and good according to specific values, and assign load growth coefficients of 0.1, 0.4, and 0.5 to these three situations respectively; In this embodiment, the grid carrying capacity is divided into three cases: restricted, normal, and good according to specific values, and carrying capacity evaluation coefficients, namely grid carrying capacity coefficients of 0.1, 0.3, and 0.6, are assigned to these three cases respectively; see Table 1 for details. Table 1 Coefficient Table of Grid Carrying Capacity and Load Growth

[0048] Take the development suitability of each recorded wind / solar project as the objective function, and calculate the development suitability Fn. Sort them in descending order of the Fn value, and give priority to the development of those with higher values, and develop the others later. It should be noted that the recorded wind / solar projects are the installed projects obtained in S1, and these installed projects are reported by the actual installed companies according to factors such as regional demands during actual implementation; in another possible implementation method, these installed projects can also be divided by the headquarters according to the limitations of the total suitable installed capacity increment of new energy, grid carrying capacity, and load prediction volume.

[0049] The calculation formula of the development suitability Fn is expressed as: Fn = a * Nn + b * In + c * Jn Among them, Nn is the installed capacity of the nth installed project, that is, the wind / solar installed capacity increment, In is the carrying capacity evaluation coefficient of the sub-region where the nth installed project is located in a certain sub-period, and Jn is the load growth coefficient of the sub-region where the nth installed project is located in the same sub-period; n = 1, 2, 3…, and a, b, and c are the weights of Nn, In, and Jn respectively. Consider the nth installed project, consider the grid carrying capacity situation and load growth coefficient of the sub-region where the nth installed project is located in a certain sub-period, and use the analytic hierarchy process to determine the weights of a, b, and c.

[0050] The specific steps of the analytic hierarchy process are as follows: ①Construct a hierarchical structure: Take the development suitability as the top layer, the three influencing factors of installed capacity, carrying capacity, and load growth coefficient as the middle layer, and each project as the bottom layer.

[0051] ②Construct a judgment matrix: For the three factors in the middle layer, compare their relative importance through methods such as expert scoring, and construct a judgment matrix. Commonly used scales are from 1 - 5 points or 1 - 9 points.

[0052] ③Calculate the weights: Use methods such as the eigenvector method or sum-product method of the judgment matrix to calculate the weights of the three factors.

[0053] ④Consistency test: To ensure the rationality of the judgment matrix, a consistency test is required. If the test is passed, the weights are valid; otherwise, the judgment matrix needs to be adjusted.

[0054] Considering the implementation of the carbon peak and carbon neutrality goals and the trend of vigorously developing wind and solar new energy, the upper limit of the installed capacity of wind and solar in the i-th year is , ; Considering that the current levelized cost of electricity (LCOE) of wind and solar power plants is relatively high compared to traditional thermal power generation, in actual planning, it is necessary to combine the actual situation, and generally take 0.3 0.7 , as the final planned installed capacity to achieve the economic correction of wind and solar.

[0055] Through the above steps, considering factors such as the development potential of wind and solar resources, the grid carrying capacity, the current load and the change of predicted load, the installed capacity of wind and solar resources in the i-th year is obtained. It can be used as a reference for the new energy development plan, an auxiliary support for the power company's power plan, and a reference for the timing of new energy development of power generation enterprises.

[0056] The present invention is an evaluation method that comprehensively considers the grid carrying capacity in the current state and the planned state, the new energy development of wind and solar resources, the situation of traditional thermal power generation, the current load and the load prediction situation, specifically including the determination of the development potential of wind and solar, the source-load matching, the thermal power / storage peak shaving, the source-grid matching, etc. Based on the evaluation of the development potential of wind and solar, the difference and matching of the 8760-hour load curve and the hourly output curve of wind and solar power plants, the suitable planned installed scale of wind and solar is quantitatively determined.

[0057] Using the present invention can support the implementation of the carbon peak and carbon neutrality goals and the planning of the new power system; support each region to carry out reasonable new energy development plans and dual-carbon plans; support grid planning and help project entities optimize the project development timing.

[0058] Embodiment 2: Based on the same inventive concept, the present invention also provides a power optimization configuration system based on the coordinated interaction of source, grid and load, as Figure 3 shown, including: A data acquisition module for acquiring the total suitable installed capacity increment of new energy and all installed projects in the area to be configured during the period to be configured; A grid-based allocation module for dividing the area to be configured into several sub-areas, dividing the period to be configured into several sub-periods, and allocating the total installed capacity increment of new energy based on the grid carrying capacity of each sub-area in each sub-period and the limit of the predicted load volume in each sub-period, to obtain the installed capacity limit of each sub-area in each sub-period and the total installed capacity limit of the area to be configured in each sub-period; A development suitability calculation module for, based on each installed project, in each sub-period, calculating the weighted sum of the installation quantity goodness of the installed project in the sub-period, the grid carrying capacity coefficient of the sub-area where the installed project is located in the sub-period, and the growth coefficient of the predicted load volume, to calculate the development suitability of the installed project in the sub-period; A power optimization configuration module, which is used to perform power optimization configuration by selecting at least one installed capacity project in a sub-period according to the development suitability of each installed capacity project in the sub-period, with the total installed capacity limit of the sub-period and the installed capacity limits of the sub-regions where each installed capacity project is located as constraints.

[0059] In this embodiment, the development suitability calculation module is specifically used for: Based on each installed capacity project, in each sub-period, calculate the difference between the installed capacity limit of the sub-region where the installed capacity project is located in the sub-period and the installed capacity of the installed capacity project to obtain the installed capacity configuration deviation. When the installed capacity configuration deviation is negative, set the installed capacity goodness of the installed capacity project in the sub-period to zero. When the installed capacity configuration deviation is non-negative, set the installed capacity goodness of the installed capacity project in the sub-period to be inversely proportional to the installed capacity configuration deviation. Perform a weighted sum of the installed capacity goodness of the installed capacity project in the sub-period, the grid carrying capacity coefficient of the sub-region where the installed capacity project is located in the sub-period, and the growth coefficient of the load forecast quantity, and calculate the development suitability of the installed capacity project in the sub-period.

[0060] In this embodiment, the development suitability calculation module is specifically used for: Obtain the load forecast quantity of the sub-region where the installed capacity project is located in the sub-period and the actual load quantity of the sub-region where the installed capacity project is located. Calculate the difference between the load forecast quantity of the sub-region where the installed capacity project is located in the sub-period and the actual load quantity of the sub-region where the installed capacity project is located to obtain the load forecast growth quantity. After coefficientizing the load forecast growth quantity, obtain the growth coefficient of the load forecast quantity of the sub-region where the installed capacity project is located in the sub-period.

[0061] In this embodiment, the data acquisition module is specifically used for: Based on the historical operation data of the power source, grid, and load in the area to be configured, predict the load forecast quantity of the last sub-period in the period to be configured in the area to be configured through a load forecasting model. Take the pre-obtained new energy development boundary as a constraint condition, and construct an objective function with the goal of minimizing the total output difference between the power output of the area to be configured and the load forecast quantity of the last sub-period; the power output is the sum of the new energy output and the non-new energy output. Assuming that the non-new energy output does not increase, solve the objective function to obtain the optimal new energy output and the corresponding total installed capacity increment of the suitable new energy.

[0062] In this embodiment, the data acquisition module is specifically used for: Based on the geographical information of the area to be configured, determine the installed capacity per unit area of new energy and the available area of new energy in the area to be configured. Calculate the product of the installed capacity per unit area of new energy and the available area of new energy in the area to be configured to obtain the maximum new energy development potential; Use the maximum new energy development potential as the upper limit value of the new energy development boundary, and use the existing new energy installed capacity in the area to be configured as the lower limit value of the new energy development boundary to obtain the new energy development boundary.

[0063] In this embodiment, after obtaining the total suitable installed capacity increment of new energy in the area to be configured during the period to be configured, it further includes: A non-new energy increment acquisition module, configured to use a clustering algorithm to obtain the total non-new energy installed capacity increment required for power grid system peak regulation based on the total suitable installed capacity increment of new energy.

[0064] In this embodiment, the non-new energy increment acquisition module is specifically configured to: Calculate the sum of the total suitable installed capacity increment of new energy and the existing new energy installed capacity to obtain the final installed capacity in the area to be configured; Based on the final installed capacity, use a clustering algorithm to determine the moment when the difference between the hourly output of the final installed capacity and the load prediction value in the last sub-period during the period to be configured is the largest, and obtain the output difference at the moment when the difference is the largest; Perform non-new energy output efficiency conversion on the output difference to obtain the total non-new energy installed capacity increment.

[0065] Embodiment 3 As Figure 4 shown, the present invention further provides an electronic device, which may be a computer device, a single-chip microcomputer device, an intelligent mobile device, etc. The electronic device in this embodiment may include a processor, a memory, a transceiver component, etc. The memory, the processor, and the transceiver component are connected through a bus; the memory can be used to store an execution program, and an exemplary execution program may include instructions; the processor is used to execute the instructions stored in the memory. The memory can also be used to store data, and the data can be called and / or modified when the instructions are executed.

[0066] The processor may be a Central Processing Unit (CPU), or may also be other general-purpose processors, Digital Signal Processors (DSPs), Application Specific Integrated Circuits (ASICs), Field-Programmable Gate Arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. It is the computing core and control core of the terminal, and is suitable for implementing one or more instructions. Specifically, it is suitable for loading and executing one or more instructions in the storage medium to implement the corresponding method flow or corresponding function, so as to implement the steps of a power optimization configuration method based on source-network-load coordinated interaction in the above embodiments.

[0067] Embodiment 4 Based on the same inventive concept, the present invention also provides a readable storage medium, specifically an electronic device-readable storage medium (Memory). The electronic device-readable storage medium is a memory device in the electronic device, used to store programs and data. It can be understood that the storage medium here can include both the built-in storage medium in the electronic device, and of course, can also include the extended storage medium supported by the electronic device. The storage medium provides a storage space, and this storage space stores the operating system of the terminal. And, in this storage space, there are also stored one or more instructions suitable for being loaded and executed by the processor. These instructions can be one or more execution programs (including program codes). It should be noted that the storage medium here can be a high-speed RAM memory, or a non-volatile memory, such as at least one disk memory. By the processor loading and executing one or more instructions stored in the storage medium, the steps of a power optimization configuration method based on source-network-load coordinated interaction in the above embodiments can be implemented.

[0068] Those skilled in the art should understand that the embodiments of the present invention can be provided as a method, a system, or a computer program product. Therefore, the present invention can take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present invention can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk memories, CD-ROMs, optical memories, etc.) containing computer-usable program codes.

[0069] The present invention is described with reference to the flowcharts and / or block diagrams of methods, apparatuses (systems), and computer program products according to embodiments of the present invention. It should be understood that each flow and / or block in the flowchart and / or block diagram, and the combination of flows and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing devices to generate a machine, such that the instructions executed by the processor of the computer or other programmable data processing devices generate means for implementing the functions specified in one flow Figure 1 one flow or multiple flows and / or blocks Figure 1 or in multiple blocks.

[0070] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to work in a specific manner, such that the instructions stored in the computer-readable memory generate a manufactured article including instruction means that implement the functions specified in one flow Figure 1 one flow or multiple flows and / or blocks Figure 1 or in multiple blocks.

[0071] These computer program instructions can also be loaded onto a computer or other programmable data processing device, such that a series of operation steps are executed on the computer or other programmable device to generate a computer-implemented process, so that the instructions executed on the computer or other programmable device provide steps for implementing the functions specified in one flow Figure 1 one flow or multiple flows and / or blocks Figure 1 or in multiple blocks.

[0072] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit the scope of its protection. Although the present invention has been described in detail with reference to the above embodiments, those of ordinary skill in the art should understand that after reading the present invention, various changes, modifications, or equivalent replacements can still be made to the specific implementation manners of the application. However, these changes, modifications, or equivalent replacements are all within the scope of the protection of the claims of the present invention.

Claims

1. A power optimization configuration method based on source-grid-load coordinated interaction, characterized in that: include: Obtain the total installed capacity increment and all installed capacity projects of new energy suitable for the area to be configured during the period to be configured; Gridding the area to be configured into a plurality of sub-areas, dividing the period to be configured into a plurality of sub-periods, allocating the total installed capacity increment of new energy sources based on the grid carrying capacity of each sub-area in each sub-period and the load forecast amount in each sub-period, and obtaining the installed capacity limit of each sub-area in each sub-period and the total installed capacity limit of the area to be configured in each sub-period; Based on each installed capacity project, in each sub-period, the installed capacity excellence of the installed capacity project in the sub-period, the grid carrying capacity coefficient of the sub-region where the installed capacity project is located in the sub-period, and the growth coefficient of the load forecast are weighted and summed to calculate the development suitability of the installed capacity project in the sub-period; Taking the total installed capacity limit of the sub-period and the installed capacity limit of the sub-region where each installed capacity project is located as constraints, and according to the development suitability of each installed capacity project in the sub-period, at least one installed capacity project is selected in the sub-period for power optimization configuration.

2. The method according to claim 1, characterized in that Based on each installed capacity project, in each sub-period, the weighted sum of the installed capacity excellence of the installed capacity project in the sub-period, the grid carrying capacity coefficient of the sub-region where the installed capacity project is located in the sub-period, and the growth coefficient of the load forecast quantity is calculated to obtain the development suitability of the installed capacity project in the sub-period, including: Based on each installed capacity project, in each sub-period, calculate the difference between the installed capacity limit of the sub-region where the installed capacity project is located in the sub-period and the installed capacity of the installed capacity project to obtain the installed capacity configuration deviation; When the installed capacity configuration deviation is a negative value, the installed capacity quality of the installed capacity project in the sub-period is set to zero; When the installed capacity configuration deviation is a non-negative value, the installed capacity quality of the installed capacity project in the sub-period is inversely proportional to the installed capacity configuration deviation; The development suitability of the installed capacity project in the sub-period is calculated by taking a weighted sum of the installed capacity excellence of the installed capacity project in the sub-period, the grid carrying capacity coefficient of the sub-region where the installed project is located in the sub-period, and the growth coefficient of the load forecast.

3. The method according to claim 1 or 2, characterized in that The process of obtaining the growth coefficient of the load forecast amount in the sub-region where the installed capacity project is located in the sub-period includes: Obtaining the load forecast of the sub-region where the installed project is located in the sub-period and the actual load of the sub-region where the installed project is located; Calculate the difference between the load forecast amount of the sub-region where the installed project is located in the sub-period and the actual load amount of the sub-region where the installed project is located to obtain the load forecast growth amount; The load forecast growth amount is coefficientized to obtain the growth coefficient of the load forecast amount in the sub-region where the installed capacity project is located in the sub-period.

4. The method according to claim 1 or 2, characterized in that: The obtaining of the suitable total installed capacity increment of new energy in the area to be configured during the period to be configured includes: Based on the historical operation data of the source grid load in the area to be configured, the load forecasting model is used to predict the load forecast of the area to be configured in the last sub-period within the period to be configured; Taking the pre-acquired new energy development boundary as a constraint condition, constructing an objective function with the goal of minimizing the total output difference between the power output of the area to be configured and the load forecast amount of the last sub-period; the power output is the sum of the new energy output and the non-new energy output; Assuming that the non-renewable energy output does not increase, the objective function is solved to obtain the optimal new energy output and the appropriate total installed capacity increase of new energy corresponding to the optimal new energy output.

5. The method according to claim 4, characterized in that The process of obtaining the new energy development boundary includes: Determine the installed capacity per unit area of ​​new energy and the available area of ​​new energy in the area to be configured based on the geographic information of the area to be configured; Calculate the product of the installed capacity per unit area of ​​the new energy and the available area of ​​the new energy in the area to be configured to obtain the maximum new energy development potential; The maximum new energy development potential is used as the upper limit of the new energy development boundary, and the existing new energy installation capacity of the area to be configured is used as the lower limit of the new energy development boundary to obtain the new energy development boundary.

6. The method according to claim 1 or 2, characterized in that: After obtaining the increment of the total installed capacity of new energy suitable for the area to be configured during the period to be configured, the method further includes: Based on the suitable total installed capacity increment of renewable energy, a clustering algorithm is used to obtain the total installed capacity increment of non-renewable energy required for peak load regulation of the power grid system.

7. The method according to claim 6, characterized in that The method of using a clustering algorithm to obtain the total installed capacity increment of non-new energy sources required for peak load regulation of the power grid system based on the total installed capacity increment of new energy sources includes: Calculate the sum of the total suitable installed capacity increment of the new energy and the existing installed capacity of new energy to obtain the final installed capacity of the area to be configured; Based on the final installed capacity, a clustering algorithm is used to determine the moment when the difference between the hourly output of the final installed capacity and the load forecast of the last sub-period in the period to be configured is the largest, and the output difference at the moment when the difference is the largest is obtained; The output difference is converted into non-renewable energy output efficiency to obtain the total installed capacity increment of non-renewable energy.

8. A power optimization configuration system based on source-grid-load coordinated interaction, characterized in that: include: A data acquisition module is used to obtain the total installed capacity increment and all installed capacity projects of new energy suitable for the area to be configured during the period to be configured; A grid allocation module, used for gridding the area to be configured into a plurality of sub-areas, dividing the period to be configured into a plurality of sub-periods, allocating the total installed capacity increment of the new energy source based on the grid carrying capacity of each sub-area in each sub-period and the load forecast amount in each sub-period, and obtaining the installed capacity limit of each sub-area in each sub-period and the total installed capacity limit of the area to be configured in each sub-period; A development suitability calculation module is used to calculate the development suitability of the installed capacity of each installed capacity project in each sub-period by weighted summing the installed capacity merit of the installed capacity project in the sub-period, the grid carrying capacity coefficient of the sub-region where the installed capacity project is located in the sub-period, and the growth coefficient of the load forecast, so as to obtain the development suitability of the installed capacity project in the sub-period; The power optimization configuration module is used to select at least one installed capacity project in the sub-period for power optimization configuration based on the total installed capacity limit in the sub-period and the installed capacity limit in the sub-region where each installed capacity project is located as constraints, according to the development suitability of each installed capacity project in the sub-period.

9. An electronic device, characterized in that: include: at least one processor and memory; The memory and the processor are connected via a bus; The memory is used to store one or more programs; When the one or more programs are executed by the at least one processor, a power optimization configuration method based on source-grid-load coordinated interaction as described in any one of claims 1 to 7 is implemented.

10. A readable storage medium, characterized in that: An execution program is stored thereon, and when the execution program is executed, a power supply optimization configuration method based on source-grid-load coordinated interaction as described in any one of claims 1 to 7 is implemented.

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