Virtual power plant cooperative scheduling optimization method based on load control technology

Abstract

The invention relates to the technical field of virtual power plant resource scheduling, in particular to a load control technology-based virtual power plant collaborative scheduling optimization method, which comprises the following steps of: determining a power load distribution diagram based on a virtual power grid, a geographic distribution diagram and power load data; according to each piece of real-time power load data, determining whether to carry out single-color system gradient color assignment on the corresponding controllable load resource in the power load distribution diagram or not; determining an overall color assignment equivalent according to a color assignment result of the power load distribution diagram so as to determine a real-time load characterization trend of the virtual power plant; determining a plurality of overload areas according to the judgment result of the overload trend and triggering a scheduling mechanism of each overload area; and determining a scheduling method according to the load power and the power grid frequency of each overload area. According to the invention, targeted scheduling is carried out on the overload area of the virtual power plant based on the condition of non-uniform load distribution in the virtual power plant, and the scheduling efficiency is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of virtual power plant resource scheduling, and particularly to a collaborative scheduling optimization method for virtual power plants based on load control technology. Background Art

[0002] The scheduling optimization of virtual power plants (VPPs) is a key technology in the field of energy management, aiming to integrate distributed energy resources (DERs), such as photovoltaic, wind power, energy storage systems, and controllable loads, and achieve a balance between economy and stability through optimized scheduling. The core lies in using advanced information and communication technologies (ICTs) and optimization algorithms, such as mixed-integer linear programming (MILP), heuristic algorithms, and artificial intelligence (AI) methods, to collaboratively manage multi-source heterogeneous energy. Virtual power plants aggregate dispersed DERs, participate in electricity market transactions, provide ancillary services such as frequency regulation and reserve, while reducing grid volatility and enhancing the consumption capacity of renewable energy. Scheduling optimization needs to consider various constraints, such as equipment operation characteristics, grid security, market rules, and user requirements, to achieve goals such as minimizing costs, maximizing revenues, or minimizing carbon emissions.

[0003] Chinese Patent Application No. 202311523811.5 discloses a virtual power plant resource optimization scheduling method and system based on load control cost, including: deploying schedulable resources inside the virtual power plant, obtaining the basic information and real-time data of the schedulable resources; establishing an operation constraint model for the schedulable resources inside the virtual power plant; establishing a control cost model for the user-side load inside the virtual power plant; establishing a hierarchical optimization scheduling model for the virtual power plant's day-ahead plan - intra-day optimization, and solving the virtual power plant resource scheduling target. According to the solution of the present invention, the present invention helps to synergistically optimize the interaction of source-load-storage resources; reduces the operating cost of the virtual power plant; the present invention proposes a method for formulating a day-ahead scheduling plan and real-time intra-day optimization, which can eliminate the influence of part of the electricity price or electricity quantity prediction error; the present invention can provide technical support for the virtual power plant to participate in electricity market transactions, and can provide solutions for improving the consumption of new energy, meeting energy demand, and promoting energy supply quality.

[0004] Therefore, the prior art has the following problems:

[0005] The prior art does not consider the uneven load distribution in the virtual power plant and performs overall scheduling on the virtual power plant rather than specifically scheduling the overloaded area, resulting in low efficiency. Summary of the Invention

[0006] To this end, the present invention provides a collaborative scheduling optimization method for virtual power plants based on load control technology to overcome the problems in the prior art that do not consider the uneven load distribution in the virtual power plant and perform overall scheduling on the virtual power plant rather than specifically scheduling the overloaded area, resulting in low efficiency.

[0007] To achieve the above object, the present invention provides a collaborative scheduling optimization method for a virtual power plant based on load control technology, including:

[0008] Obtain the virtual power grid of the virtual power plant, the geographical distribution map of each controllable load resource, and the historical data of various controllable load resources;

[0009] Obtain the real-time power load data between each of the controllable load resources and the virtual power grid;

[0010] Based on the virtual power grid, the geographical distribution map, and the power load data, determine a power load distribution map;

[0011] According to each of the real-time power load data, determine whether to perform single-color gradient coloring on the corresponding controllable load resources in the power load distribution map;

[0012] According to the coloring result of the power load distribution map, determine the overall coloring equivalent to determine the real-time load characterization trend of the virtual power plant;

[0013] According to the determination result of the load overload trend, determine several load overload regions and trigger the scheduling mechanism of each load overload region;

[0014] According to the load power and grid frequency of each of the load overload regions, determine a scheduling method.

[0015] Further, the controllable load resources include distributed generation resources, demand response resources, and energy storage resources;

[0016] Among them, the historical data of the various controllable load resources includes the historical power generation data of each of the distributed generation resources, the historical power consumption data of each of the demand response resources, and the actual energy storage value and the ideal energy storage value of each of the energy storage resources.

[0017] Further, the process of determining whether to perform single-color gradient coloring on the corresponding controllable load resources in the power load distribution map according to each of the real-time power load data includes,

[0018] According to the real-time power load, determine whether to perform single-color gradient load, where,

[0019] If the real-time power load is greater than the preset power load, it is determined to perform single-color gradient coloring on the corresponding controllable load resources in the power load distribution map;

[0020] According to the result of performing single-color gradient coloring, combine the ratio of the real-time power load to the preset power load to determine the coloring value.

[0021] Further, the process of determining the coloring value in combination with the ratio of the real-time power load to the preset power load includes

[0022] Determine the ratio of the real-time power load to the preset power load and determine it as the power load ratio;

[0023] Determine the coloring value according to the power load ratio, where

[0024] If the power load ratio is greater than or equal to the first preset ratio, it is determined that the coloring value is the maximum color value in the coloring range corresponding to the single-color gradient;

[0025] If the power load ratio is less than or equal to the second preset ratio, it is determined to determine the coloring value according to the power load ratio and the first coloring range;

[0026] If the power load ratio is greater than the second preset ratio and the power load ratio is less than the first preset ratio, it is determined to determine the coloring value according to the power load ratio and the second coloring range.

[0027] Further, the coloring range corresponding to the single-color gradient consists of the first coloring range and the second coloring range.

[0028] Further, the process of determining the overall coloring equivalent according to the coloring result of the power load distribution map to determine the real-time load characterization trend of the virtual power plant includes

[0029] Determine the coloring proportion of each coloring value;

[0030] Weight each coloring value based on the coloring proportion;

[0031] Determine the overall coloring equivalent according to the sum of the weighted coloring values;

[0032] Determine the real-time load characterization trend according to the comparison result between the overall coloring equivalent and the preset coloring equivalent;

[0033] Among them, the load characterization trend includes a load overload trend and a load stability trend.

[0034] Further, determining the real-time load characterization trend according to the comparison result between the overall coloring equivalent and the preset coloring equivalent includes

[0035] If the overall coloring equivalent is greater than or equal to the preset coloring equivalent, it is determined that the real-time load characterization trend is a load overload trend;

[0036] If the overall coloring equivalent is less than the preset coloring equivalent, it is determined that the real-time load characterization trend is a load stability trend.

[0037] Further, the process of determining several load overload regions according to the determination result of the load overload trend includes

[0038] Determine all the coloring positions and the corresponding load areas on the power load distribution map according to the determination result of the load overload trend;

[0039] Set the coloring positions with coloring values in the second coloring range as key load positions and the corresponding key load areas;

[0040] Determine the number of adjacent coloring positions in each key load area and the average distance between each adjacent coloring position and the key coloring position;

[0041] Determine whether the key load area is a load overload area according to the number of adjacent coloring positions and the average distance, where,

[0042] If the number of adjacent coloring positions is greater than or equal to the preset number and the average distance is less than or equal to the preset distance, then determine that the load area is a load overload area;

[0043] If the number of adjacent coloring positions is less than the preset number and the average distance is greater than the preset distance, then determine that the load area is a load stable area;

[0044] If the number of adjacent coloring positions is less than the preset number or the average distance is greater than the preset distance, then determine that the load area is a load monitoring area.

[0045] Further, the process of determining the dispatching method according to the load power and grid frequency of each load overload area includes,

[0046] Obtain the load power and grid frequency of each load overload area;

[0047] Determine whether the grid frequency deviates from the rated range;

[0048] Determine the dispatching method according to the determination result of whether the grid frequency deviates from the rated range.

[0049] Further, determining the dispatching method according to the determination result of whether the grid frequency deviates from the rated range includes,

[0050] If the grid frequency deviates from the rated range, then determine the dispatching method according to the grid frequency, where,

[0051] If the grid frequency is lower than the first frequency threshold, then determine to increase the input power of the external large power grid;

[0052] If the grid frequency is higher than the second frequency threshold, then determine to charge the energy storage resource and output it to the external large power grid after charging is completed;

[0053] If the grid frequency does not deviate from the rated range, then dispatch the energy storage resource according to the load power.

[0054] Compared with the prior art, the beneficial effects of the present invention are as follows. By obtaining the geographical distribution maps of the virtual power grid and various controllable load resources, as well as the historical data of various types of controllable load resources, the present invention realizes the comprehensive integration and intuitive presentation of the virtual power plant resources: the geographical distribution maps incorporate geographical information, which is convenient for combining with GIS technology to deeply analyze the resource distribution and the convenience of grid access, providing a basis for reasonably planning the resource layout; at the same time, the power load distribution maps determined based on these data not only display the positional relationships, geographical locations, and topographical and geomorphic information of the controllable load resources, but also can show their power load data, presenting the complex power system information in a visual way, facilitating quickly grasping the overall situation and making scientific decisions;

[0055] Furthermore, at the level of real-time data monitoring and analysis, real-time power load data between each controllable load resource and the virtual power grid are obtained, covering multi-dimensional data such as distributed generation, demand-side response, and energy storage resources, such as power generation power, power consumption power, state of charge, etc.; these real-time data provide strong support for accurately analyzing the operating state of the power system, and can timely detect potential problems in the power system, such as abnormal voltage and current of power generation equipment, low power factor on the demand side, etc., providing an accurate basis for subsequent dispatching decisions;

[0056] Furthermore, in terms of optimizing the dispatching strategy, the power load distribution map is updated and colored in real time according to the real-time power load data, and the overall coloring equivalent is determined to judge the real-time load characterization trend of the virtual power plant; once the load overload trend is determined, the load overload area is quickly determined and the dispatching mechanism is triggered, and the dispatching method is determined according to the load power and the grid frequency, realizing the dynamic and accurate dispatching of the power system; this data-driven dispatching method can timely respond to the power load changes, effectively balance the power supply and demand, maintain the stability of the grid frequency and voltage, enhance the stability and reliability of the power system, avoid power failures caused by load overload, and ensure the safe operation of the power system. BRIEF DESCRIPTION OF THE DRAWINGS

[0057] Figure 1 It is a step diagram of the virtual power plant collaborative dispatching optimization method based on the load control technology in the embodiment of the present invention;

[0058] Figure 2 It is a process diagram of performing single-color gradient coloring in the embodiment of the present invention;

[0059] Figure 3 It is a process diagram of determining the real-time load characterization trend of the virtual power plant in the embodiment of the present invention;

[0060] Figure 4 It is a process diagram of determining the load overload area in the embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0061] In order to make the objectives and advantages of the present invention more clearly understood, the present invention will be further described below in conjunction with embodiments; it should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0062] The preferred embodiments of the present invention will be described below with reference to the accompanying drawings. Those skilled in the art should understand that these embodiments are only used to explain the technical principles of the present invention and do not limit the protection scope of the present invention.

[0063] It should be noted that in the description of the present invention, the terms indicating the direction or positional relationship such as "upper", "lower", "left", "right", "inner", "outer", etc. are based on the direction or positional relationship shown in the drawings. This is only for convenience of description and does not indicate or imply that the device or element must have a specific orientation, be constructed and operated in a specific orientation, and therefore should not be construed as a limitation to the present invention.

[0064] In addition, it should also be noted that in the description of the present invention, unless otherwise clearly specified and limited, the terms "installed", "connected", and "connected" should be understood in a broad sense. For example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be directly connected or indirectly connected through an intermediate medium, and it can be the communication inside two elements. For those skilled in the art, the specific meanings of the above terms in the present invention can be understood according to specific situations.

[0065] Please refer to Figure 1 as shown, which is a step diagram of the virtual power plant collaborative scheduling optimization method based on load control technology in an embodiment of the present invention. An embodiment of the present invention provides a virtual power plant collaborative scheduling optimization method based on load control technology, including:

[0066] Step S1, obtaining the virtual power grid of the virtual power plant, the geographical distribution map of each controllable load resource, and the historical data of various controllable load resources;

[0067] It can be understood that the virtual power grid is an important part of the virtual power plant, which connects distributed power resources (power generation), energy storage resources, demand response resources (power consumption), etc. located in different geographical locations to form a virtual and schedulable power grid system; the virtual power grid is not a power grid with a physical entity in the traditional sense, without the physical connection of actual transmission and distribution lines and substations and other hardware facilities, but through an information network and software system to achieve the "virtual connection" between each part, and logically form a unified power grid architecture;

[0068] It can be understood that the geographical distribution map highlights the elements of geographical information, indicating that the map not only simply shows the resource distribution, but may also contain detailed geographical information such as geographical coordinates, topography, etc., which can present the relationship between resources and geographical locations more accurately, facilitate integration with technologies such as Geographic Information System (GIS) for more in-depth analysis and applications, such as evaluating the convenience of resource distribution and grid access in different regions;

[0069] Step S2, obtain the real-time power load data between each of the controllable load resources and the virtual power grid; in implementation, it includes: (1) Real-time power load data of distributed generation resources: ① Generation power: refers to the actual electrical power output by distributed generation equipment at the current moment, usually measured in kilowatts (kW) or megawatts (MW), reflecting the ability of distributed generation resources to inject electrical energy into the virtual power grid; ② Generated energy: is the cumulative electrical energy generated by distributed generation resources from a certain moment to the current moment, generally measured in kilowatt-hours (kWh), used to count the total amount of electrical energy generated by distributed generation resources within a certain period; ③ Generation voltage and current: the voltage and current values output by the generation equipment, measured in volts (V) and amperes (A) respectively, which may affect the generation efficiency and even cause equipment failures; (2) Real-time power load data of demand response resources; ① Power consumption: represents the electrical power consumed by various electrical equipment on the demand side at the current moment, also measured in kW or MW, reflecting the consumption of electrical energy on the demand side by the virtual power grid; ② Electricity consumption: the cumulative electrical energy consumed by demand response resources from a certain starting time to the current moment, measured in kWh; ③ Power factor: is an indicator to measure the energy utilization efficiency of electrical equipment, dimensionless, with a value between 0 and 1. A too low power factor will lead to a decrease in the transmission efficiency of the power grid and an increase in line losses; (3) Real-time power load data of energy storage resources: ① Charge and discharge power: represents the power at which the energy storage device absorbs electrical energy from the virtual power grid during charging and releases electrical energy to the virtual power grid during discharging, measured in kW or MW; ② State of Charge (SOC): reflects the percentage of the remaining electrical energy of the energy storage device at the current moment; ③ Charge and discharge times: counts the number of charge and discharge cycles of the energy storage device from the time of commissioning to the current moment;

[0070] Step S3, determine the power load distribution map based on the virtual power grid, the geographical distribution map, and the power load data; it can be understood that the power load distribution map contains both the positional relationship of all controllable load resources in the virtual power grid and information on their geographical locations and topography, and can also display the power load data of any controllable load resource;

[0071] Step S4: Determine whether to perform single - color gradient coloring on the corresponding controllable load resources in the power load distribution map according to each piece of the real - time power load data. Meanwhile, during implementation, the power load distribution map is also updated in real - time based on the real - time power load data. It can be understood that the power load distribution map can be updated in real - time according to the real - time power load data. In addition, the visualization of the power load distribution map is increased by using the coloring method.

[0072] Step S5: Determine the overall coloring equivalent according to the coloring result of the power load distribution map to determine the real - time load characterization trend of the virtual power plant.

[0073] Step S6: Determine several load overload areas according to the determination result of the load overload trend and trigger the scheduling mechanism for each load overload area. It can be understood that if the load characterization trend is not the load overload trend (i.e., the load stable trend), it is determined that the current load is within the tolerance range of the corresponding virtual power plant, so no scheduling is required.

[0074] Step S7: Determine the scheduling method according to the load power and grid frequency of each load overload area.

[0075] Specifically, in step S1, the controllable load resources include distributed generation resources, demand - side response resources, and energy storage resources.

[0076] Among them, the historical data of each type of controllable load resource includes the historical power generation data of each distributed generation resource (mainly including historical power generation power and historical power generation amount), the historical power consumption data of each demand - side response resource (mainly including historical power consumption power and historical power consumption amount), and the actual energy storage value and ideal energy storage value of each energy storage resource.

[0077] It can be understood that the grid frequency refers to the number of times the alternating current completes periodic changes per unit time, with the unit of Hertz (Hz). It reflects the rotational speed of the rotor of the alternator. In the power system standard frequency in China, it is stipulated as 50 Hz, that is, the rotor of the generator rotates 50 times per second, thus generating alternating current that changes according to the sine law. The load power refers to the electric power consumed by various electrical equipment (such as industrial motors, household appliances, etc.) in the power system during operation, usually with the unit of watt (W) / kilowatt (kW) / megawatt (MW), etc. It reflects the rate at which the electrical equipment draws electrical energy from the power grid and is an important indicator to measure the load size of the power system.

[0078] Please refer to Figure 2 As shown, it is the process diagram of single - color gradient coloring in the embodiment of the present invention. Specifically, in step S4, the process of determining whether to perform single - color gradient coloring on the corresponding controllable load resources in the power load distribution map according to each piece of the real - time power load data includes,

[0079] Step S41: Determine whether to perform single - color gradient load on the controllable load resource according to the real - time power load of each controllable load resource. Among them,

[0080] if the real - time power load is greater than the preset power load, it is determined to perform single - color gradient coloring on the corresponding controllable load resource in the power load distribution map;

[0081] if the real - time power load is less than or equal to the preset power load, it is determined not to perform single - color gradient coloring on the corresponding controllable load resource in the power load distribution map;

[0082] In implementation, both the real - time power load and the preset power load refer to the corresponding electric power, that is, real - time electric power and preset electric power;

[0083] It can be understood that the preset electric power (preset power load) is determined by the average value of the electric power in the historical data of various controllable load resources: (1) For distributed generation resources, its preset power load is 1.1 - 1.2 times the average value of historical generation power; (2) For demand - side response resources: its preset power load is 1.1 - 1.2 times the average value of historical power consumption;

[0084] Step S42: Determine the coloring value according to the result of single - color gradient coloring and in combination with the ratio of the real - time power load to the preset power load.

[0085] It can be understood that by comparing the real - time power load with the preset power load, it is decided whether to perform single - color gradient coloring on the corresponding controllable load resource; this method shows the power load status with an intuitive visual effect, enabling staff to quickly identify from the power load distribution map which controllable load resources have power loads exceeding the normal range, clearly grasping the operating conditions of each part of the virtual power plant at a glance, improving the information acquisition efficiency, avoiding manual checking of data one by one, saving time and effort; secondly, based on the result of single - color gradient coloring and in combination with the ratio of the real - time power load to the preset power load, the coloring value is determined to achieve a precise quantitative presentation of the load level; different coloring values correspond to different degrees of load deviation, and the darker the color, the higher the real - time power load relative to the preset power load, which can more intuitively reflect the load tension degree of the controllable load resource, providing a more accurate visual basis for subsequent dispatching decisions; the preset power load is determined based on the average value of the electric power in the historical data of various controllable load resources, and is set to 1.1 - 1.2 times the average value of historical power for distributed generation resources and demand - side response resources respectively. This setting not only considers the historical operation rules of the resources but also reserves a certain margin for the normal operation range, meeting the actual operation requirements, being able to more reasonably judge whether the real - time power load is abnormal, avoiding misjudgment or failure to detect potential problems in a timely manner due to unreasonable preset values, thus ensuring the stable operation of the power system.

[0086] Specifically, in step S42, the process of determining the coloring value in combination with the ratio of the real-time power load to the preset power load includes,

[0087] Step S421, determine the ratio of the real-time power load to the preset power load and determine it as the power load ratio; that is, power load ratio = real-time power load ÷ preset power load; it can be understood that when single-color gradient coloring is satisfied, the real-time power load must be greater than the preset power load, so the power load ratio must be greater than 1;

[0088] Step S422, determine the coloring value according to the power load ratio, where,

[0089] If the power load ratio is greater than or equal to the first preset ratio, it is determined that the coloring value is the maximum color value in the coloring range corresponding to the single-color gradient color; it can be understood that the first preset ratio is set as a relatively large number. When it is greater than or equal to the first preset ratio, it means that the real-time power load of this controllable load resource is very large, so it is directly set as the maximum color value in the coloring range;

[0090] If the power load ratio is less than or equal to the second preset ratio, it is determined that the coloring value is determined according to the power load ratio and the first coloring range; it can be understood that the second preset ratio is set as a relatively small number. When it is less than or equal to the second preset ratio, it means that the real-time power load of this controllable load resource is relatively small, so the coloring value is determined according to the power load ratio: coloring value = power load ratio × the minimum value of the first coloring range;

[0091] If the power load ratio is greater than the second preset ratio and the power load ratio is less than the first preset ratio, it is determined that the coloring value is determined according to the power load ratio and the second coloring range; it can be understood that when it is greater than the second preset ratio and less than the first preset ratio, it means that the real-time power load of this controllable load resource is relatively large. Therefore, when determining the coloring value according to the power load ratio, the size of the final coloring value should be increased accordingly: coloring value = 1.5 × power load ratio × the minimum value of the second coloring range;

[0092] In implementation, when the obtained value of the coloring value is a decimal, the principle of "rounding" is usually adopted. In addition, if the calculated coloring value is greater than the maximum color value of the coloring range, the maximum color value is used as the coloring value;

[0093] In implementation, the first preset ratio is greater than the second preset ratio, and both are greater than 1; generally, the first preset ratio is set to 1.7 - 2, and the second preset ratio is set to 1.2 - 1.4.

[0094] It can be understood that the single-color gradient color can be set as the gradient color of any color system, including: red color system, green color system, blue color system, yellow color system, etc. The color assignment range of the single-color gradient color is determined by RGB. For example, the values of the G and B channels in the red color system are both 0, and the value of the R channel ranges from 100 to 225. Then, when assigning colors, the specific color can be adjusted by adjusting the value of the R channel, and its corresponding color assignment range is [150, 225]. When specifically assigning colors, set G = B = 0, and R is the calculated color assignment value;

[0095] It can be understood that for any single-color system, the colors of two channels in the R, G, and B channels are fixed values, and the value of the third channel can be changed within the range of 0 to 225.

[0096] It can be understood that taking the power load ratio as a key indicator, the real-time power load situation of controllable load resources is quantitatively evaluated; according to different power load ratio ranges, a differential color assignment value determination method is adopted, which can accurately reflect the size of the load.

[0097] Specifically, in step S4, the color assignment range corresponding to the single-color gradient color consists of a first color assignment range and a second color assignment range.

[0098] In implementation, the maximum value of the first color assignment range is equal to the minimum value of the second color assignment range, the maximum color value in the color assignment range is equal to the maximum value of the second color assignment range, and the minimum color value in the color assignment range is equal to the minimum value of the first color assignment range;

[0099] In implementation, the first color assignment range is usually determined according to a first preset ratio, and the maximum value of the first color assignment range = the first preset ratio × the minimum color value in the color assignment range.

[0100] Please refer to Figure 3 As shown, it is a process diagram for determining the real-time load characterization trend of the virtual power plant in an embodiment of the present invention. Specifically, in step S5, the process of determining the overall color assignment equivalent according to the color assignment result of the power load distribution map to determine the real-time load characterization trend of the virtual power plant includes,

[0101] Step S51, determining the color assignment proportion of each color assignment value; it can be understood that according to the specific color assignment value of the controllable load resource with color assignment, the proportion of each color assignment value (denoted as the color assignment proportion) can be determined. According to the proportion of the color assignment value, the overall load situation of the current virtual power plant can be generally understood;

[0102] Step S52, weighting each color assignment value based on the color assignment proportion; in implementation, the color assignment values include A, B, C, and D respectively, and the corresponding color assignment proportions are a, b, c, and d respectively. The weighted color assignment values are aA, bB, cC, and dD respectively;

[0103] Step S53, determine the overall coloring equivalent according to the sum of the weighted coloring values; the overall coloring equivalent = aA + bB + cC + dD;

[0104] Step S54, determine the real-time load characterization trend according to the comparison result between the overall coloring equivalent and the preset coloring equivalent; in implementation, the preset coloring equivalent is set as the product of the preset coloring value and the preset coloring ratio; among them, the value range of the preset coloring value is usually x1 to x2, x1 = 0.3×(maximum color value - minimum color value)+minimum color value, x2 = 0.5×(maximum color value - minimum color value)+minimum color value; the preset coloring ratio is usually 40% - 60%; the specific value also needs to be determined according to the load-bearing capacity of the virtual power plant (the quantity and energy storage capacity of the energy storage resources); in implementation, the preset coloring equivalent is preferably set as x1×50%;

[0105] It can be understood that the preset coloring equivalent represents the load-bearing capacity of the current virtual power plant;

[0106] Among them, the load characterization trend includes a load overload trend and a load stability trend.

[0107] It can be understood that by determining the coloring ratio of each coloring value, the distribution ratio of controllable load resources with different load levels in the virtual power plant can be understood from an overall perspective, and then a preliminary rough judgment of the overall load situation of the current virtual power plant can be obtained; weighting each coloring value based on the coloring ratio, and then calculating the sum of the weighted coloring values to determine the overall coloring equivalent. This method comprehensively considers all colored controllable load resources and their corresponding load levels, realizes a comprehensive and accurate quantitative assessment of the real-time load status of the virtual power plant, and avoids making one-sided judgments based on only single data or local conditions;

[0108] It can be understood that comparing the overall coloring equivalent with the preset coloring equivalent can clearly judge the real-time load characterization trend of the virtual power plant; the preset coloring equivalent represents the load-bearing capacity of the current virtual power plant, which has strong pertinence and practicability; through comparison, if the overall coloring equivalent is greater than the preset coloring equivalent, it can be determined as a load overload trend; otherwise, it is a load stability trend; this judgment result provides a key basis for whether load dispatching is needed in the follow-up, helps to timely discover potential power supply risks, and takes measures in advance to ensure the stable operation of the power system;

[0109] It can be understood that the value ranges of the preset coloring value and the preset coloring ratio have a certain degree of flexibility and can be adjusted according to the actual load - bearing capacity of the virtual power plant. In implementation, when the energy storage resources of the virtual power plant are rich and the energy storage capacity is strong, the value of the preset coloring equivalent can be appropriately increased to adapt to its higher load - bearing capacity. Conversely, if the load - bearing capacity is weak, the preset value is adjusted accordingly. This flexibility enables the method to be applicable to virtual power plants of different scales and configurations, improving the generality and adaptability of the method and providing effective technical support for the load management of various virtual power plants.

[0110] Specifically, in step S54, determining the real - time load characterization trend according to the comparison result between the overall coloring equivalent and the preset coloring equivalent includes,

[0111] If the overall coloring equivalent is greater than or equal to the preset coloring equivalent, it is determined that the real - time load characterization trend is a load overload trend. It can be understood that at this time, it represents that the real - time load of the current virtual power plant has exceeded the load - bearing capacity of the virtual power plant and is in an overloaded state.

[0112] If the overall coloring equivalent is less than the preset coloring equivalent, it is determined that the real - time load characterization trend is a load - stable trend. It can be understood that this represents that the real - time load of the current virtual power plant has not exceeded the load - bearing capacity of the virtual power plant and is in a stable state.

[0113] It can be understood that by comparing the overall coloring equivalent with the preset coloring equivalent, the real - time load characterization trend of the virtual power plant can be quickly and accurately judged. When the overall coloring equivalent is greater than or equal to the preset coloring equivalent, it is clear that the real - time load of the current virtual power plant has exceeded the load - bearing capacity and is in an overloaded state, providing a key signal for timely starting load dispatching and taking countermeasures. When the overall coloring equivalent is less than the preset coloring equivalent, it can be determined that the real - time load has not exceeded the load - bearing capacity and is in a stable state, helping the staff to timely grasp the operation state of the virtual power plant, ensuring the stable operation of the power system, and avoiding power supply problems caused by the failure to timely identify load abnormalities.

[0114] Please refer to Figure 4 As shown, it is a process diagram for determining the load overload area in an embodiment of the present invention. Specifically, in step S6, the process of determining several load overload areas according to the determination result of the load overload trend includes,

[0115] Step S61, determining all the colored positions on the power load distribution map according to the determination result of the load overload trend;

[0116] Step S62: Set the coloring positions with coloring values within the second coloring range as the key load positions and the corresponding key load areas. It can be understood that the key load area is a circle centered on the key load position with a preset length as the radius. In implementation, the preset length is usually set to 10m to 30m.

[0117] Step S63: Determine the number of adjacent coloring positions in each key load area and the average distance between each adjacent coloring position and the key coloring position. It can be understood that all coloring positions in the key load area except the key load position are adjacent coloring positions.

[0118] Step S64: Determine whether the key load area is an overloaded load area based on the number of adjacent coloring positions and the average distance, where

[0119] if the number of adjacent coloring positions is greater than or equal to the preset number and the average distance is less than or equal to the preset distance, then determine that the load area is an overloaded load area; at this time, coordination and scheduling of this area are required.

[0120] if the number of adjacent coloring positions is less than the preset number and the average distance is greater than the preset distance, then determine that the load area is a stable load area; at this time, coordination and scheduling of this area are not required.

[0121] if the number of adjacent coloring positions is less than the preset number or the average distance is greater than the preset distance, then determine that the load area is a load monitoring area; at this time, collaborative scheduling of this area is not required but key monitoring of this area is required.

[0122] In implementation, the preset distance is usually set to half of the preset length, and the preset number is usually between 10 and 20.

[0123] It can be understood that by determining all coloring positions, setting the coloring positions with coloring values within the second coloring range as the key load positions, thereby determining the key load areas, and then analyzing the number of adjacent coloring positions and the average distance within the areas, to judge whether the area is an overloaded load area; this process can effectively identify the areas that truly require coordination and scheduling, avoid blind scheduling, and save manpower, material resources, and time costs; at the same time, clarify the load monitoring areas, conduct key monitoring on them, prevent the risk of load overload in advance, ensure that the virtual power plant can be reasonably managed and effectively monitored under different load states, and guarantee the stable operation of the power system.

[0124] Specifically, in step S7, the process of determining the scheduling method according to the load power and grid frequency of each overloaded load area includes

[0125] Step S71: Obtain the load power and grid frequency of each overloaded load area.

[0126] Step S72: Determine whether the grid frequency deviates from the rated range;

[0127] Step S73: Determine the dispatching method according to the determination result of whether the grid frequency deviates from the rated range.

[0128] It can be understood that by obtaining the load power and grid frequency in the load overload area and determining the dispatching method based on whether the grid frequency deviates from the rated range, this process provides a scientific basis for the dispatching decision of the virtual power plant during load overload: on the one hand, accurately obtaining the key data in the load overload area can comprehensively grasp the abnormal conditions of the power system; on the other hand, using the grid frequency as an important judgment index makes the determination of the dispatching method more targeted and effective; when the grid frequency deviates from the rated range, corresponding emergency measures can be taken to stabilize the frequency; if it does not deviate, conventional load regulation strategies can be implemented to ensure that the power system can be reasonably and efficiently dispatched under different operating states, maintain the stability and reliability of the system, and ensure the safety and stability of power supply.

[0129] Specifically, in step S73, determining the dispatching method according to the determination result of whether the grid frequency deviates from the rated range includes:

[0130] If the grid frequency deviates from the rated range (i.e., not within the rated range), then determine the dispatching method according to the grid frequency, where:

[0131] If the grid frequency is lower than the first frequency threshold, it is determined to increase the input power of the external large grid;

[0132] If the grid frequency is higher than the second frequency threshold, it is determined to charge the energy storage resource and output it to the external large grid after charging is completed; in implementation, the first frequency threshold is the minimum value of the rated range, and the second frequency threshold is the maximum value of the rated range;

[0133] It can be understood that the stability of the grid frequency reflects the stability of the virtual power plant's power system. Large frequency fluctuations may cause instability of the power system and even lead to serious accidents such as system disconnection and power outage; therefore, when the grid frequency deviates from the rated range, it is necessary to stabilize the operation of the virtual power plant through the external large grid;

[0134] If the grid frequency does not deviate from the rated range, then dispatch the energy storage resource according to the load power; it can be understood that small frequency fluctuations usually mean that the power system operates stably, and each power generation device and power consumption device can operate at the normal frequency, and the performance and life of the devices can be guaranteed; therefore, when the power system operates stably, the operation of the virtual power plant can be stabilized by dispatching the energy storage resources inside the virtual power plant;

[0135] In implementation, the number of scheduled energy storage resources is determined according to the current total load power of the load overload area, and the energy storage resources near the load overload area are selected according to the "proximity principle" during scheduling.

[0136] In implementation, the number of scheduled energy storage resources = (total load power - average load power when the critical load area is in a load stable trend) ÷ discharge power of a single energy storage resource;

[0137] In implementation, the rated frequency of the power system is 50Hz. Generally, the allowable deviation range of the grid frequency during normal operation is ±0.2Hz to ±0.5Hz. In the ideal case where the power system operates relatively stably and the load changes little, the frequency deviation is usually controlled within ±0.2Hz; thus, the rated range is 49.8Hz to 50.2Hz.

[0138] It can be understood that when the grid frequency deviates from the rated range, such as when it is lower than the first frequency threshold of 49.8Hz, the input power of the external large power grid is increased. When it is higher than the second frequency threshold of 50.2Hz, the energy storage resources are first charged and then output to the external large power grid. This can effectively utilize the power of the external large power grid to stabilize the operation of the virtual power plant and avoid serious accidents such as power system instability, system disconnection, and power outage caused by large frequency fluctuations. When the grid frequency does not deviate from the rated range, the energy storage resources are scheduled according to the load power. The number of scheduled resources is scientifically determined according to the current total load power of the load overload area, and the energy storage resources nearby are selected following the "proximity principle", making full use of the internal resources of the virtual power plant to maintain stable operation, ensuring the equipment performance and lifespan when the power system is stable, achieving reasonable and efficient scheduling of the virtual power plant under different operating states, and enhancing the stability and reliability of the power system.

[0139] So far, the technical solution of the present invention has been described in conjunction with the preferred embodiments shown in the accompanying drawings. However, it is easy for those skilled in the art to understand that the protection scope of the present invention is obviously not limited to these specific embodiments. Without departing from the principle of the present invention, those skilled in the art can make equivalent changes or substitutions to the relevant technical features, and the technical solutions after these changes or substitutions will all fall within the protection scope of the present invention.

[0140] The above are only the preferred embodiments of the present invention and are not used to limit the present invention; for those skilled in the art, the present invention can have various changes and modifications. Any modification, equivalent substitution, improvement, etc. made within the spirit and principle of the present invention shall be included within the protection scope of the present invention.

Claims

1. A collaborative scheduling optimization method for a virtual power plant based on load control technology, characterized in that Including: Obtain the virtual power grid of the virtual power plant, the geographical distribution map of each controllable load resource, and the historical data of various controllable load resources; Obtain the real-time power load data between each of the controllable load resources and the virtual power grid; Determine the power load distribution map based on the virtual power grid, the geographical distribution map, and the power load data; Determine whether to perform single-color gradient coloring on the corresponding controllable load resources in the power load distribution map according to each of the real-time power load data; Determine the overall coloring equivalent according to the coloring result of the power load distribution map to determine the real-time load characterization trend of the virtual power plant; Determine several load overload areas according to the determination result of the load overload trend and trigger the dispatching mechanism of each load overload area; Determine the dispatching method according to the load power and grid frequency of each of the load overload areas.

2. The collaborative scheduling optimization method of the virtual power plant based on the load control technology according to claim 1, wherein The controllable load resources include distributed generation resources, demand response resources, and energy storage resources; Among them, the historical data of various controllable load resources includes the historical power generation data of each distributed generation resource, the historical power consumption data of each demand response resource, and the actual energy storage value and ideal energy storage value of each energy storage resource.

3. The collaborative scheduling optimization method for virtual power plants based on load control technology according to claim 2, characterized in that The process of determining whether to perform single-color gradient coloring on the corresponding controllable load resources in the power load distribution map according to each of the real-time power load data includes, Determine whether to perform single-color gradient load on the controllable load resource according to the real-time power load of each controllable load resource, where, If the real-time power load is greater than the preset power load, it is determined that single-color gradient coloring is performed on the corresponding controllable load resource in the power load distribution map; According to the result of single-color gradient coloring, determine the coloring value in combination with the ratio of the real-time power load to the preset power load.

4. The collaborative scheduling optimization method of the virtual power plant based on the load control technology according to claim 3, wherein, The process of determining the coloring value in combination with the ratio of the real-time power load to the preset power load includes, Determine the ratio of the real-time power load to the preset power load and determine it as the power load ratio; Determine the coloring value according to the power load ratio, where, If the power load ratio is greater than or equal to the first preset ratio, it is determined that the coloring value is the maximum color value in the coloring range corresponding to the single-color gradient color; If the power load ratio is less than or equal to the second preset ratio, it is determined that the coloring value is determined according to the power load ratio and the first coloring range; If the power load ratio is greater than the second preset ratio and the power load ratio is less than the first preset ratio, it is determined that the coloring value is determined according to the power load ratio and the second coloring range.

5. The collaborative scheduling optimization method of the virtual power plant based on the load control technology according to claim 4, wherein The coloring range corresponding to the single-color gradient color consists of a first coloring range and a second coloring range.

6. The collaborative scheduling optimization method of the virtual power plant based on the load control technology according to claim 1, characterized in that, The process of determining the overall coloring equivalent according to the coloring result of the power load distribution map to determine the real-time load characterization trend of the virtual power plant includes, Determine the coloring proportion of each coloring value; Weight each coloring value based on the coloring proportion; Determine the overall coloring equivalent according to the sum of the weighted coloring values; Determine the real-time load characterization trend according to the comparison result between the overall coloring equivalent and the preset coloring equivalent; Among them, the load characterization trend includes a load overload trend and a load stability trend.

7. The collaborative scheduling optimization method for virtual power plants based on load control technology according to claim 5, characterized in that, Determine the real-time load characterization trend according to the comparison result between the overall coloring equivalent and the preset coloring equivalent, including, If the overall coloring equivalent is greater than or equal to the preset coloring equivalent, it is determined that the real-time load characterization trend is a load overload trend; If the overall coloring equivalent is less than the preset coloring equivalent, it is determined that the real-time load characterization trend is a load stable trend.

8. The collaborative scheduling optimization method of the virtual power plant based on the load control technology according to claim 1, wherein The process of determining a number of load overload regions according to the determination result of the load overload trend includes, Determining all the coloring positions and the corresponding load regions on the power load distribution map according to the determination result of the load overload trend; Setting the coloring positions with coloring values in the second coloring range as key load positions and the corresponding key load regions; Determining the number of adjacent coloring positions in each key load region and the average distance between each adjacent coloring position and the key coloring position; Determining whether the key load region is a load overload region according to the number of adjacent coloring positions and the average distance, where, If the number of adjacent coloring positions is greater than or equal to the preset number and the average distance is less than or equal to the preset distance, it is determined that the load region is a load overload region; If the number of adjacent coloring positions is less than the preset number and the average distance is greater than the preset distance, it is determined that the load region is a load stable region; If the number of adjacent coloring positions is less than the preset number or the average distance is greater than the preset distance, it is determined that the load region is a load monitoring region.

9. The collaborative scheduling optimization method of the virtual power plant based on the load control technology according to claim 1, wherein The process of determining the dispatching method according to the load power and grid frequency of each load overload region includes, Obtaining the load power and grid frequency of each load overload region; Determining whether the grid frequency deviates from the rated range; Determining the dispatching method according to the determination result of whether the grid frequency deviates from the rated range.

10. The collaborative scheduling optimization method for a virtual power plant based on load control technology according to claim 9, characterized in that, Determining the dispatching method according to the determination result of whether the grid frequency deviates from the rated range includes, If the grid frequency deviates from the rated range, determining the dispatching method according to the grid frequency, where, If the grid frequency is lower than the first frequency threshold, it is determined to increase the input power of the external large power grid; If the grid frequency is higher than the second frequency threshold, it is determined to charge the energy storage resource and output it to the external large power grid after charging is completed; If the grid frequency does not deviate from the rated range, dispatching the energy storage resource according to the load power.

Images