New energy area accurate load shedding method based on real-time measurement and data uploading

Abstract

The invention relates to the field of accurate load shedding in a new energy area, in particular to an accurate load shedding method for a new energy area based on real-time measurement and data uploading. The method comprises the following steps: firstly, calculating a regional total shearable load based on interruptible load power; calculating the real-time load margin of the region based on the total shearable load of the region, the real-time output of the new energy and the fluctuation ratio of the output of the new energy; then, based on the calculated frequency deviation and the real-time load margin of each region, calculating a total load shedding demand; based on the total load shedding demand, the regional total shearable load and the real-time load margin, obtaining a distributed regional load shedding amount through a regional load optimal distribution algorithm; and finally, calculating to obtain a load shedding task of each load control terminal based on the distributed regional load shedding amount. The technical problems of non-uniform distribution of regional load shedding capacity, low efficiency, frequency deviation response lag and limitation of new energy output fluctuation on the load shedding capacity are solved.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of new energy regional precise load shedding, and in particular to a new energy regional precise load shedding method based on real-time measurement and uploaded data. BACKGROUND

[0002] With the transformation of global energy structure, the penetration rate of new energy in the power system continues to rise, and the traditional centralized power generation mode dominated by thermal power is gradually changing to a distributed power generation mode dominated by renewable energy. In particular, in regional distribution networks, the proportion of new energy grid connection is increasing year by year, greatly improving the green and low-carbon properties of the power grid. However, the volatility, intermittency and uncertainty of new energy have brought great challenges to the safe and stable operation of the power grid. In order to cope with these challenges and achieve the balance between supply and demand and the regulation capacity of the power grid under the background of high proportion of new energy grid connection, precise load shedding technology has become a key means. The new energy regional precise load shedding method based on real-time measurement and uploaded data has become a key breakthrough to ensure the frequency safety and stable operation of high-proportion renewable energy power systems, which not only improves the load shedding efficiency and reduces the impact on the user side, but also supports flexible scheduling, intelligent control and resilience response in the construction of new-type power systems, providing solid technical support for smart grids and energy transformation. SUMMARY

[0003] The present application provides a new energy regional precise load shedding method based on real-time measurement and uploaded data to solve the technical problems of uneven distribution of regional load shedding capacity, low efficiency, lagging frequency deviation response, and limitation of load shedding capacity by new energy output fluctuation.

[0004] The present application provides a new energy regional precise load shedding method based on real-time measurement and uploaded data to solve the technical problems of uneven distribution of regional load shedding capacity, low efficiency, lagging frequency deviation response, and limitation of load shedding capacity by new energy output fluctuation. A new energy regional precise load shedding method based on real-time measurement and uploaded data, comprising the following steps: S1. Based on the interruptible load power in the collected key operation data, calculate the total interruptible load of the region; based on the total interruptible load of the region, the real-time output of new energy and the fluctuation rate of new energy output, calculate the real-time load margin of the region; S2. Compare the current high-proportion new energy power grid system frequency with the nominal frequency, calculate the frequency deviation; based on the frequency deviation and the real-time load margin of each region, dynamically calculate the total load shedding demand through the total load shedding demand calculation algorithm; S3. Based on the total load shedding demand, the total interruptible load of the region and the real-time load margin, obtain the allocated regional load shedding capacity through the regional load optimization distribution algorithm; based on the allocated regional load shedding capacity, calculate the load shedding task of each load control terminal.

[0005] Preferably, S1 specifically comprises: The key operation data collected by the load control terminal includes the interruptible load power of the region, the real-time output of new energy and the fluctuation rate of new energy output; the interruptible load power of all load control terminals in the region is aggregated to calculate the total cuttable load of the region.

[0006] Preferably, S1 specifically comprises: Based on the total cuttable load of the region, the real-time output of new energy and the fluctuation rate of new energy output, real-time load margin evaluation is carried out, the real-time output of new energy is multiplied by an influence coefficient, and a fluctuation rate adjustment term is combined to obtain the real-time load margin of the region.

[0007] Preferably, S2 specifically comprises: In the total cut load demand calculation algorithm, the frequency response term and the margin correction term are added to generate the total cut load demand.

[0008] Preferably, S2 specifically comprises: The frequency deviation is normalized to generate a proportion factor, the proportion factor is multiplied by the frequency-load adjustment sensitivity coefficient, and then multiplied by the nominal load power to form the frequency response term; the margin correction coefficient is introduced, the real-time load margin of each region is multiplied by the margin correction coefficient and summed to obtain the margin correction term.

[0009] Preferably, S3 specifically comprises: In the regional load optimization distribution algorithm, based on the overcut penalty term and the margin deviation term, an optimization objective function is constructed to solve the distributed regional cut load amount that minimizes the total cost of distributing all regional cut load amounts.

[0010] Preferably, S3 specifically comprises: The distributed regional cut load amount is multiplied by the proportion of each load control terminal to obtain the cut load task of each load control terminal.

[0011] Preferably, S3 specifically comprises: The proportion of the load control terminal is the proportion of the interruptible load capacity of each load control terminal to the total cuttable load of the region.

[0012] The beneficial effects of the technical scheme of the present application are: 1. By deploying load control terminals in each region of the high-proportion new energy power grid, collecting key operation data, and calculating the total cuttable load and real-time load margin of the region, the cuttable load capacity of the region under the fluctuation of new energy output can be accurately quantified, the influence coefficient of new energy output and the fluctuation rate adjustment term are introduced, the instability of new energy output is considered comprehensively, and the deviation of the cut load amount distribution is reduced, thereby improving the stability and reliability of the power grid operation.

[0013] 2. Real-time acquisition of high-proportion new energy power grid system frequency by the master station frequency monitoring device, calculation of frequency deviation, and combination of regional real-time load margin, dynamic calculation of total load shedding demand through the frequency response term and the margin correction term, effective prevention of further deterioration of frequency, ensuring the stability of the power grid frequency, and enhancing the anti-disturbance ability of the high-proportion new energy power grid.

[0014] 3. The control center station constructs an optimization objective function based on the over-shedding penalty term and the margin deviation term through the regional load optimization distribution algorithm, comprehensively considers the importance, load shedding capacity and real-time load margin of the region, reasonably allocates the load shedding amount of each region, solves by using the interior point method, ensures that the allocation result meets the total load shedding demand, avoids excessive load shedding amount, protects key facilities, and at the same time, is close to the actual operation state of the region, improves the fairness and economy of the load shedding amount distribution of the region.

[0015] 4. According to the interruptible load capacity of each load control terminal, the regional load shedding task is decomposed to specific terminals through the proportional distribution mechanism, ensuring that the task allocation matches the actual capacity of the terminal, the fine allocation mode improves the execution efficiency of the load shedding task, and reduces the risk of power grid operation caused by improper allocation. BRIEF DESCRIPTION OF DRAWINGS

[0016] Figure 1 A flowchart of a new energy regional precise load shedding method based on real-time measurement and uploaded data. DETAILED DESCRIPTION

[0017] In order to further illustrate the technical means and effects adopted by the present application to achieve the predetermined object, the technical solutions in the embodiments of the present application will be described clearly and completely below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, not all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor are within the scope of protection of the present application.

[0018] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which the present application belongs.

[0019] The specific scheme of the new energy regional precise load shedding method based on real-time measurement and uploaded data provided by the present application will be specifically described below in conjunction with the drawings.

[0020] Referring to the drawings Figure 1 It shows a flowchart of a new energy regional precise load shedding method based on real-time measurement and uploaded data provided by an embodiment of the present application. The method comprises the following steps: S1, based on the interruptible load power in the collected key operation data, calculate the total cuttable load of the region; based on the total cuttable load of the region, the real-time output of new energy and the fluctuation rate of new energy output, calculate the real-time load margin of the region; The load control terminal is deployed in each region of the high-proportion new energy power grid, responsible for collecting key operation data, including the interruptible load power of the region, the real-time output of new energy and the fluctuation rate of new energy output. Among them, the load control terminal includes: industrial user side terminal, such as electric arc furnace of steel plant, large compressor of chemical plant, etc.; commercial user side terminal, such as central air conditioning system of large shopping mall, lighting and elevator system of office building, etc.; residential user side terminal, such as smart meter, controllable socket, distributed air conditioner controller, etc.

[0021] The load control terminal of each region uploads the collected key operation data to the control substation belonging to it; The control substation aggregates the interruptible load power of all load control terminals in the region, calculates the total cuttable load of the region, reflects the overall cuttable load potential of the region, and the calculation formula is: , Among them, represents the total cuttable load of the th region at time ; represents the summation operation on the th region from the th to the th load control terminal, which accumulates the interruptible load capacity of all load control terminals; represents the total number of load control terminals in the th region; represents the interruptible load power of the th load control terminal in the th region at time , that is, the interruptible load capacity.

[0022] In order to quantify the actual cuttable load capacity of the region under the fluctuation of new energy, based on the total cuttable load of the region, the real-time output of new energy and the fluctuation rate of new energy output, the real-time load margin is evaluated, and the real-time load margin of the region is obtained. When the real-time load margin is positive, it means that the region has surplus cuttable load capacity and can undertake more cuttable load tasks; when the real-time load margin is negative, it means that the region is under cuttable load pressure and needs to be protected first.

[0023] In the high-proportion new energy power grid, the real-time output of new energy directly determines the power supply capacity of the region. By multiplying the real-time output of new energy with an influence coefficient and combining the fluctuation rate adjustment term, the comprehensive influence of new energy output on the real-time load margin of the region is further quantified; A volatility adjustment term is introduced to reflect the impact of dynamic changes in renewable energy output on the region's load shedding capacity. In the operation of a high-proportion renewable energy power grid, the instability of renewable energy output can lead to rapid changes in power supply capacity. By normalizing the volatility of renewable energy output by dividing it by the total shedding load, a normalized volatility index is obtained, ensuring the comparability of real-time load margin calculations for regions of different sizes. The normalized volatility index is multiplied by a volatility sensitivity coefficient to form an adjustment factor. The adjustment factor is added to a benchmark value of 1 to form the volatility adjustment term, which dynamically adjusts the region's real-time load margin. The significance of the volatility adjustment term lies in quantifying the limitation of renewable energy output instability on the region's load shedding capacity. The formula for calculating the real-time load margin of a region is: , in, Indicates the first Each region in time The real-time load margin is used to quantify the region's load shedding capacity under fluctuations in new energy output; Indicates the first Each region in time Real-time output of new energy; This represents the impact coefficient of renewable energy output, used to adjust the degree of influence of renewable energy output on real-time load margin. It reflects the characteristics of different renewable energy types, such as photovoltaic power generation and wind power generation. It is preset by the power grid planning department according to the regional renewable energy types and stored in the substation database. Its value range is [range missing]. ; This represents the fluctuation sensitivity coefficient, used to adjust for the impact of renewable energy output fluctuations on real-time load margin. It reflects the region's sensitivity to renewable energy output fluctuations, is preset by the power grid planning department based on the region's renewable energy types, and is stored in the substation database. Its value range is [range missing]. ; Indicates the first Each region in time The absolute value of the volatility of new energy power output; This is a normalized volatility indicator used to reflect the strength of the volatility of new energy power output relative to the region's load shedding capacity. Indicates the adjustment factor; This represents the volatility adjustment term.

[0024] By comprehensively considering the real-time output of new energy sources, the volatility of new energy output, and the total available load of the region, the real-time load margin assessment results of the region are closer to the actual operating conditions, reducing the deviation in load shedding allocation.

[0025] S2, compare the collected current high-proportion new-energy power grid system frequency with the nominal frequency, calculate the frequency deviation; based on the frequency deviation and the real-time load margin of each region, dynamically calculate the total load shedding demand through a total load shedding demand calculation algorithm; The frequency of the current high-proportion new-energy power grid system is collected by the frequency monitoring equipment of the master station, such as the synchronous phasor measurement device PMU, and compared with the nominal frequency to calculate the frequency deviation, which reflects the operating state of the high-proportion new-energy power grid; Based on the frequency deviation and the real-time load margin of each region, the total load shedding demand required by the high-proportion new-energy power grid is dynamically calculated through a total load shedding demand calculation algorithm. The total load shedding demand calculation algorithm introduces a frequency response term to quantify the direct impact of the frequency deviation on the total load shedding demand. The frequency response term generates a proportion factor by normalizing the frequency deviation, i.e., dividing by the nominal frequency, to reflect the severity of the frequency deviation. The proportion factor is multiplied by the frequency-load regulation sensitivity coefficient to adjust the amplification or reduction effect of the frequency deviation on the total load shedding demand. The proportion factor is multiplied by the nominal load power to convert it into an actual power demand. The frequency response term reflects the load shedding demand caused by the frequency drop, and a larger value indicates that more load needs to be shed to restore frequency stability. A margin correction term is introduced to supplement the frequency response term and consider the impact of the real-time load margin of each region on the total load shedding demand. The master station obtains the real-time load margin from each regional control substation. If the real-time load margin of a region is negative, i.e., the load shedding capacity of the region is insufficient to cope with the fluctuations in new energy output, the region needs additional load shedding support. The negative values of the real-time load margins of all regions are weighted and summed, and the real-time load margin of each region is multiplied by a margin correction coefficient to control the contribution of insufficient real-time load margin to the total load shedding demand. The frequency response term and the margin correction term are added to generate the total load shedding demand. The frequency response term provides a global demand benchmark based on the frequency deviation, while the margin correction term fine-tunes according to the actual operating state of each region to ensure that the total load shedding demand can quickly respond to frequency drops and adapt to regional differences. The total load shedding demand calculation formula is as follows: , wherein, represents the total load shedding demand at time ; represents the frequency-load regulation sensitivity coefficient, which reflects the sensitivity of the frequency deviation to the total load shedding demand and adjusts the load shedding response strength. It is pre-set by the grid planning department according to the grid size and stored in the master station database. The value range is ; represents the frequency deviation, defined as , for quantifying the degree of high-proportion new energy power grid system frequency deviation from the nominal frequency, triggering load shedding demand; representing time of high-proportion new energy power grid system frequency; representing nominal frequency, determined by power grid standard, such as 50 Hz for China power grid; representing proportion factor; representing nominal load power, serving as a benchmark for total load shedding demand, for reflecting power grid scale, preset by power grid historical operation data obtained from master station database, stored in master station database; representing frequency response term; representing summation operation on all regions, for accumulating additional load shedding demand of each region with insufficient real-time load margin; representing margin correction coefficient of the region, for adjusting the influence of insufficient real-time load margin on total load shedding demand, reflecting the importance of the region, preset by power grid planning department, stored in master station database, reference value being 0.1-1.0; representing additional load shedding demand of the region with insufficient real-time load margin, quantifying the additional load shedding demand of the region when the real-time load margin of the region is negative, taking 0 when the real-time load margin of the region is positive; representing total number of regions, determined by power grid zoning plan, stored in master station database; representing margin correction term.

[0026] Based on frequency deviation, total load shedding demand is quickly quantified to prevent further frequency drop, and through the margin correction part, the influence of new energy output fluctuation of each region is comprehensively considered to ensure that the total load shedding demand fits the actual operation state.

[0027] S3, based on total load shedding demand, total available load shedding of regions and real-time load margin, the distributed regional load shedding amount is obtained through regional load optimization distribution algorithm; based on the distributed regional load shedding amount, the load shedding task of each load control terminal is calculated.

[0028] The control center station receives the total load shedding demand issued by the master station, and at the same time, obtains the total available load shedding of regions and real-time load margin from the control sub-stations of each region; The goal of regional load optimization distribution algorithm is to determine the distributed load shedding amount of each region, ensuring that the total load shedding demand is met while not exceeding the total available load shedding of each region.

[0029] An optimization objective function is constructed, including over-shedding penalty term and margin deviation term, aiming to minimize the total cost of distributing load shedding amount of all regions; The overcut penalty term considers the ratio of the allocated area cutting load to the static priority coefficient and the total cuttable load, is designed in a quadratic form to punish excessive cutting load, the higher the static priority coefficient, the greater the punishment, the smaller the allocated area cutting load, thereby protecting the key facilities; The margin deviation term is used to measure the margin deviation between the allocated cutting load of the area and the real-time load margin, the greater the margin deviation, the higher the penalty, by introducing the margin deviation weight coefficient, adjusting the contribution of the margin deviation to the total cost, encouraging the allocated cutting load to be close to the real-time load margin of the area.

[0030] The formula expression of the optimization objective function is as follows: , Wherein, represents the minimum value of the variable set ; represents the sum of all areas; represents the cost of allocating the cutting load of the first area; represents the total cost of allocating the cutting load of all areas; represents the allocated cutting load of the first area; represents the square of the allocated cutting load of the first area, representing a nonlinear penalty, used to increase the cost of allocating the cutting load of the first area quickly, to prevent overcutting; represents the static priority coefficient of the first area, used to reflect the importance of the area, which is preset by the power grid planning department according to the key load degree, infrastructure importance, power supply security level and other factors in the area, and the reference value is 0.5-2.0; represents the overcut penalty term; represents the margin deviation weight coefficient of the first area, used to adjust the contribution of the margin deviation to the optimization objective function, encouraging the allocated cutting load to be close to the real-time load margin of the area, which is preset by the power grid planning department and stored in the control center station database, and the reference value is 0.1-0.5; represents the margin deviation absolute value of the allocated cutting load of the first area and the real-time load margin of the first area at time , used to punish the deviation of the allocated cutting load from the real-time load margin of the area, to ensure reasonable allocation; represents the normalized margin deviation; represents the margin deviation term.

[0031] The constraints for optimizing the objective function include: the sum of the load shedding amounts in all regions equals the total load shedding demand, i.e. Furthermore, the load shedding amount allocated to each region must not exceed the total shedding load of the region, nor can it be a negative value. This ensures that the allocation results meet the actual needs and physical limitations of a high-proportion renewable energy power grid system.

[0032] The regional load optimization allocation algorithm uses the existing interior-point method to solve the optimization objective function. Combining the objective function and constraints, it iteratively updates the load shedding amount of the allocated regions. In each iteration, the gradient of the objective function and the constraints are calculated, and the load shedding amount of each allocated region is adjusted until the constraints of the optimization objective function are met and the optimization objective function converges to its minimum value. When the change in the optimization objective function is less than a preset threshold, such as... When the maximum number of iterations is reached, the regional load optimization allocation algorithm stops and outputs the load shedding amount of the allocated region. Based on the allocated regional load shedding capacity, load shedding tasks are distributed according to the proportion of each load control terminal. The proportion of each load control terminal represents the percentage of its interruptible load capacity to the total available load shedding capacity in the region. The allocated regional load shedding capacity is multiplied by the proportion of each load control terminal to obtain the load shedding task for each load control terminal, as expressed in the following formula: , in, Indicates the first The first region Each load control terminal at time The load shearing amount, i.e., the first The first region Each load control terminal at time The load shedding task.

[0033] By using a proportional allocation mechanism, the regional load shedding tasks are decomposed according to the interruptible load capacity of the load control terminal, ensuring that the allocation of load shedding tasks matches the actual interruptible load capacity of the load control terminal.

[0034] In summary, a method for precise load shedding in new energy areas based on real-time measurement and uploaded data has been developed.

[0035] The order of the embodiments is for illustrative purposes only and does not represent the superiority or inferiority of the embodiments. The processes depicted in the drawings do not necessarily require a specific or sequential order to achieve the desired result. In some embodiments, multitasking and parallel processing are possible or may be advantageous.

[0036] Various embodiments are described herein with reference to the drawings, in which specific embodiments are illustrated. As such, specific details of various embodiments are set forth in order to provide a thorough understanding of embodiments of the present application. However, various embodiments can be practiced without resorting to the details specifically set forth herein. As used herein, the term "exemplary" is used in the sense of serving as an example, rather than implying any quality or superiority. In other instances "exemplary embodiment" can be used to describe an embodiment in accordance with the present application. In addition, the words "a" or "an" are used herein to mean one or more things (e.g., one or more members), depending on the context of their use, and the singular word form of "a" or "an" is intended to include the plural forms as well, unless the context clearly indicates otherwise. Stated differently, to whatever extent the use of "a" or "an" may be considered to

[0037] The above embodiments are only used to illustrate the technical solutions of the present application, rather than limit the present application; although the present application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that the technical solutions recorded in the foregoing embodiments can be modified, or some technical features can be replaced by equivalent features; and these modifications or replacements do not make the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present application, and should be included in the protection scope of the present application.

Claims

1. A method for regional precise load shedding of new energy based on real-time measurement and uploading data, characterized in that, The method comprises the following steps: S1. Calculate the total interruptible load of the region based on the interruptible load power in the collected key operation data; calculate the real-time load margin of the region based on the total interruptible load of the region, the real-time output of new energy and the fluctuation rate of new energy output; S2. Compare the current high-proportion new energy power grid system frequency collected with the nominal frequency to calculate the frequency deviation; based on the frequency deviation and the real-time load margin of each region, dynamically calculate the total load shedding demand through the total load shedding demand calculation algorithm; S3. Based on the total load shedding demand, the total interruptible load of the region and the real-time load margin, obtain the allocated regional load shedding amount through the regional load optimization distribution algorithm; based on the allocated regional load shedding amount, calculate the load shedding task of each load control terminal. 2.The new energy regional precise load shedding method based on real-time measurement and uploading data according to claim 1, wherein The S1 specifically comprises: The key operation data collected by the load control terminal includes the interruptible load power of the region, the real-time output of new energy and the fluctuation rate of new energy output; the interruptible load power of all load control terminals in the region is aggregated to calculate the total interruptible load of the region. 3.The new energy regional precise load shedding method based on real-time measurement and uploading data according to claim 2, characterized in that, The S1 specifically comprises: Based on the total interruptible load of the region, the real-time output of new energy and the fluctuation rate of new energy output, the real-time load margin is evaluated, the real-time output of new energy is multiplied by an influence coefficient, and a fluctuation rate adjustment term is combined to obtain the real-time load margin of the region. 4.The new energy regional precise load shedding method based on real-time measurement and uploading data according to claim 1, characterized in that, The S2 specifically comprises: In the total load shedding demand calculation algorithm, the frequency response term and the margin correction term are added to generate the total load shedding demand.

5. The new energy regional precise load shedding method based on real-time measurement and uploading data according to claim 4, characterized in that, The S2 specifically comprises: The frequency deviation is normalized to generate a proportion factor, the proportion factor is multiplied by the frequency-load adjustment sensitivity coefficient, and then multiplied by the nominal load power to form the frequency response term; the real-time load margin of each region is multiplied by the margin correction coefficient and summed to obtain the margin correction term. 6.The new energy regional precise load shedding method based on real-time measurement and uploading data according to claim 1, characterized in that, The S3 specifically comprises: In the regional load optimization distribution algorithm, based on the over-shedding penalty term and the margin deviation term, an optimization objective function is constructed to solve the allocated regional load shedding amount that minimizes the total cost of distributing all regional load shedding amounts.

7. The new energy regional precise load shedding method based on real-time measurement and uploading data according to claim 6, characterized in that, The S3 specifically comprises: The allocated regional load shedding amount is multiplied by the proportion of each load control terminal to obtain the load shedding task of each load control terminal. 8.The new energy regional precise load shedding method based on real-time measurement and uploading data according to claim 7, characterized in that, The S3 specifically comprises: The proportion of the load control terminal is the proportion of the interruptible load capacity of each load control terminal to the total interruptible load of the region.

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