Calculation method and device for regulating the time-of-use settlement price ratio of power retail users

Abstract

The present application relates to the technical field related to power dispatching, and specifically to a method and device for calculating the time-sharing settlement price regulation ratio of power retail users. The method includes: obtaining basic power data; based on the basic data, exhaustively enumerating the parameter combinations of the time-sharing settlement price regulation ratio parameters that meet the preset conditions to obtain a parameter combination set; for each parameter combination, based on the basic power data, performing iterative calculations for power market simulation clearing, and determining the wholesale market peak and valley hour determination strategy corresponding to the parameter combination in each operating scenario; for each of the parameter combinations and the corresponding wholesale market peak and valley hour determination strategy in each operating scenario, performing safety indicators and feasibility judgments, and obtaining a parameter combination that can be safely operated in all operating scenarios as the target parameter combination; performing full-scenario value calculations on each target parameter combination, and determining the target parameter combination with the highest full-scenario value as the final parameter combination.

Description

Technical Field

[0001] The present application relates to the technical field related to power dispatching, and specifically to a method and device for calculating the regulation ratio of time-sharing settlement prices for power retail users. Background Art

[0002] With the changes in the electricity supply and demand situation and the reform process of the electricity market, the electricity wholesale market has formed a time-of-use price signal. The fixed retail peak-to-valley price ratio is difficult to reflect and transmit to the time-of-use wholesale market price signal and electricity supply and demand signal. In order to match it, the electricity market policy issued also needs to be gradually relaxed to meet the needs of electricity market reform. To this end, it is necessary to gradually relax the requirements of the peak-to-valley price ratio, from a fixed ratio to a range of peak-to-valley ratios, and implement time-of-use prices for retail users to achieve connection with the wholesale market time-of-use price signals. At the same time, it is necessary to calculate the optimal regulatory ratio of the time-of-use settlement price of electricity retail users, and reduce the impact on the operation of the power system and the operation of the power market in the process of relaxing the range of peak-to-valley ratios.

[0003] There is currently a lack of ways to plan the regulatory ratio of time-of-use settlement prices for electricity retail users. Summary of the invention

[0004] In view of this, the embodiments of the present application are directed to providing a method and device for calculating the regulation ratio of time-of-use settlement prices for retail electricity users.

[0005] This application provides a method for calculating the regulatory ratio of time-of-use settlement prices for retail electricity users, including:

[0006] Obtain basic power data;

[0007] The basic power data includes: classification information of power retail users; elasticity matrix of power volume and price of power retail users; benchmark load and retail benchmark price power of each type of power retail users in each operation scenario;

[0008] Based on the basic data, exhaustively enumerate the parameter combinations of the time-sharing settlement price regulation ratio parameters that meet the preset conditions to obtain a parameter combination set;

[0009] For each parameter combination, based on the basic power data, an iterative calculation of power market simulation clearing is performed to determine the peak and valley hour determination strategy of the wholesale market corresponding to the parameter combination in each operation scenario;

[0010] For each parameter combination and the corresponding wholesale market peak and valley hour determination strategy under each operation scenario, safety indicators and feasibility judgments are made to obtain a parameter combination that can be safely operated in all operation scenarios as a target parameter combination;

[0011] The full-scene value is calculated for each target parameter combination, and the target parameter combination with the highest full-scene value is determined as the final parameter combination.

[0012] In some embodiments, obtaining basic power data includes:

[0013] Get the original data;

[0014] Based on the original data, the electricity retail users are classified, and the users with the same industrial and commercial electricity consumption characteristics and the same region are classified into one category to obtain the classification information of the electricity retail users;

[0015] For each type of user, determine its electricity quantity and price elasticity matrix based on the original data;

[0016] Based on the original data, different operation scenarios are divided, and the benchmark load and retail benchmark price electricity of each type of electricity retail user under each operation scenario are determined.

[0017] In some embodiments, for each parameter combination, based on the basic power data, an iterative calculation of power market simulation clearing is performed to determine the peak and valley hour determination strategy of the wholesale market corresponding to the parameter combination in each operation scenario, including:

[0018] Determine the peak and valley hours of the wholesale market;

[0019] Calculate user retail prices based on the basic electricity data;

[0020] Based on the basic power data, calculate the load curve of each type of user in the nth scenario for the i-th group of parameter combinations;

[0021] Perform the ith group of parameter combinations and simulate the clearing of the electricity market under the nth scenario;

[0022] If the electricity market simulation is cleared and cannot converge, the wholesale market peak and valley hour determination will be re-executed until the convergence conditions are met.

[0023] In some embodiments, for each parameter combination and the corresponding wholesale market peak and valley hour determination strategy under each operation scenario, safety indicators and feasibility judgments are performed, including:

[0024] Calculate the direct safety index for each parameter combination and the corresponding wholesale market peak and valley hour determination strategy under each operation scenario;

[0025] Determining whether the operation is safe based on the direct safety indicators;

[0026] If the operation is safe, calculate the indirect risk indicators;

[0027] A feasibility judgment is made based on the direct safety indicators and the indirect risk indicators.

[0028] In some embodiments, the direct safety indicators include: power system overload section safety indicators, power system heavy load section safety indicators, power market constraint safety indicators and power market clearing solution safety indicators.

[0029] In some embodiments, the indirect risk indicators include: wholesale and retail peak and valley time period misalignment index, wholesale and retail peak and valley price misalignment index, user electricity fee structure health index, and market entity profit change index.

[0030] In some embodiments, the calculation of the full-scenario value for each target parameter combination includes: based on the formula Calculate the value of the entire scene;

[0031] in, Represents the scenario value coefficient of the i-th group of parameter combinations in all scenarios The arithmetic mean of Represents the scenario value coefficient of the i-th group of parameter combinations in all scenarios The population standard deviation of .

[0032] The present application also provides a device for calculating the regulation ratio of time-sharing settlement price for electric power retail users, comprising:

[0033] An acquisition module is used to obtain basic power data;

[0034] The basic power data includes: classification information of power retail users; elasticity matrix of power volume and price of power retail users; benchmark load and retail benchmark price power of each type of power retail users in each operation scenario;

[0035] An exhaustive module, for exhaustively enumerating, based on the basic data, parameter combinations of the time-sharing settlement price regulation ratio parameters that meet the preset conditions to obtain a parameter combination set;

[0036] A simulation module, for performing an iterative calculation of power market simulation clearing for each parameter combination based on the basic power data, and determining a peak and valley hour determination strategy for the wholesale market corresponding to the parameter combination in each operation scenario;

[0037] A judgment module is used to make safety index and feasibility judgments for each parameter combination and the corresponding wholesale market peak and valley hour judgment strategy under each operation scenario, and obtain a parameter combination that can be safely operated in all operation scenarios as a target parameter combination;

[0038] The determination module is used to calculate the full-scene value of each target parameter combination and determine the target parameter combination with the highest full-scene value as the final parameter combination.

[0039] The present application also provides an electronic device, comprising:

[0040] A processor, and a memory for storing a program executable by the processor;

[0041] The processor is used to implement the above-mentioned method for calculating the regulation ratio of time-sharing settlement price for retail electricity users by running the program in the memory.

[0042] The present application also provides a computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, the processor executes the method for calculating the regulation ratio of the time-of-use settlement price for retail electricity users as described above.

[0043] In the solution provided in the present application, basic electricity data is obtained; wherein, the basic electricity data includes: classification information of electricity retail users; electricity quantity and electricity price elasticity matrix of electricity retail users; benchmark load and retail benchmark price electricity of each type of electricity retail users under various operating scenarios; based on the basic data, parameter combinations of time-of-use settlement price regulation ratio parameters that meet preset conditions are exhaustively enumerated to obtain a parameter combination set; for each parameter combination, based on the basic electricity data, iterative calculation of electricity market simulation clearing is performed to determine the wholesale market peak and valley hour determination strategy corresponding to the parameter combination under each operating scenario; for each parameter combination and the corresponding wholesale market peak and valley hour determination strategy under each operating scenario, safety indicators and feasibility judgments are performed to obtain a parameter combination that can be safely operated in all operating scenarios as a target parameter combination; a full-scenario value calculation is performed for each target parameter combination, and the target parameter combination with the highest full-scenario value is determined as the final parameter combination. With such a configuration, in the solution provided in the present application, the regulatory ratios of time-of-use settlement prices for different electricity retail users can be simulated based on the basic electricity data. In this way, before the actual operation, the consequences of the regulatory ratios of time-of-use settlement prices for different electricity retail users can be understood in advance, so as to adopt the appropriate regulatory ratio (i.e., parameter combination) to better dispatch electricity based on the time-of-use settlement price. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] By describing the embodiments of the present application in more detail in conjunction with the accompanying drawings, the above and other purposes, features and advantages of the present application will become more apparent. The accompanying drawings are used to provide a further understanding of the embodiments of the present application and constitute a part of the specification. Together with the embodiments of the present application, they are used to explain the present application and do not constitute a limitation of the present application. In the accompanying drawings, the same reference numerals generally represent the same components or steps.

[0045] Figure 1It is a flowchart of a method for calculating the regulation ratio of time-of-use settlement prices for electricity retail users provided in an embodiment of the present application.

[0046] Figure 2 It is a partial flow chart of a method provided by an embodiment of the present application.

[0047] Figure 3 It is a structural diagram of a device for calculating the regulation ratio of time-sharing settlement prices for retail electricity users provided in one embodiment of the present application.

[0048] Figure 4 It is a schematic diagram of the structure of an electronic device provided by an embodiment of the present application. DETAILED DESCRIPTION

[0049] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0050] Application Overview

[0051] With the changes in the electricity supply and demand situation and the reform process of the electricity market, the electricity wholesale market has formed a time-of-use price signal. The fixed retail peak-to-valley price ratio is difficult to reflect and transmit to the time-of-use wholesale market price signal and electricity supply and demand signal. In order to match it, the electricity market policy issued also needs to be gradually relaxed to meet the needs of electricity market reform. To this end, it is necessary to gradually relax the requirements of the peak-to-valley price ratio, from a fixed ratio to a range of peak-to-valley ratios, and implement time-of-use prices for retail users to achieve connection with the wholesale market time-of-use price signals. At the same time, it is necessary to calculate the optimal regulatory ratio of the time-of-use settlement price of electricity retail users, and reduce the impact on the operation of the power system and the operation of the power market in the process of relaxing the range of peak-to-valley ratios.

[0052] In the technical field of "user peak and valley prices", there have been a lot of research and applications on methods for calculating user peak and valley prices. These methods cannot solve several pain points in the business scenario of "gradually relaxing the regulation of retail peak, flat and valley price ratios":

[0053] (1) There is currently no method to assess the impact of relaxing the regulation of the retail peak-to-valley price ratio in the current environment of fixed retail peak-to-valley price ratios.

[0054] (2) There is currently no method to evaluate how to choose an appropriate ratio regulation range to relax the regulation of the fixed retail peak-to-valley price ratio under the current environment of fixed retail peak-to-valley price ratio.

[0055] (3) In the research and application of user peak-valley price calculation methods, some studies have proposed to use social benefit maximization as the objective function to solve the optimization model to obtain the optimal user peak-valley price. However, the user peak-valley price obtained by this method is limited by the accuracy of model data acquisition, model establishment and objective function description. It is directly used as the regulation of retail peak-valley price ratio, which is actually contrary to the goal of power market reform. The goal of power market reform is to leave appropriate space for market players, realize the transmission of price signals through independent decision-making by market players, and ultimately achieve supply and demand balance.

[0056] In order to solve the above problems, the present application provides a method for calculating the optimal time-of-use settlement price regulation ratio for retail electricity users, which mainly includes three steps: iterative calculation of electricity market simulation clearing, feasibility evaluation of retail time-of-use settlement price regulation ratio parameter combination, and calculation of the optimal retail time-of-use settlement price regulation ratio parameter combination.

[0057] (1) In the iterative calculation of electricity market simulation clearing, the problem is how to obtain a robust electricity market clearing result based on the retail time-of-use settlement price regulation ratio parameter combination under the current environment of fixed retail peak-valley price ratio.

[0058] A price transmission chain of “wholesale electricity market price-retail electricity market price-user load curve-wholesale electricity market clearing” is constructed, in which: 1) The transmission of “wholesale electricity market price-retail electricity market price” is based on the assumption of market equilibrium. Under market equilibrium, the retail electricity market price will reflect the time-of-use price signal of the wholesale electricity market within the scope of price ratio regulation. The retail electricity market price is calculated according to the mean of the wholesale electricity market price; 2) The transmission of “retail electricity market price-user load curve” is calculated by considering the user demand elasticity coefficients of different electricity consumption types and different regions. Users in different regions are divided into different categories, mainly considering the modeling needs in the clearing of the electricity market; 3) The transmission of “user load curve-wholesale electricity market clearing” is realized by using the electricity market simulation clearing technology, and an iterative convergence judgment is set. Only the price ratio regulation parameter combination that can converge is used to reduce the model risk in the policy implementation process.

[0059] (2) Safety and feasibility assessment of the retail time-of-use settlement price regulation ratio parameter combination. The problem is how to quantify the impact of the retail time-of-use settlement price regulation ratio on the power system and power market under the current environment of fixed retail peak-to-valley price ratio.

[0060] First, the direct safety indicators are judged. The price ratio regulation parameter combination that does not meet the direct safety indicators is not feasible, reducing the risks to the power system and power market operation during the policy implementation process. Direct safety indicators include: 1) power system section constraint indicators. It is necessary to judge whether the change in retail time-of-use price signals will lead to changes in load characteristics after the relaxation of ratio regulations, bringing risks to the safe operation of the power system; 2) power market operation constraint indicators. It is necessary to judge whether the change in load characteristics will make the power market unable to complete clearing within the market trading window period in order to meet the safe operation conditions after the relaxation of ratio regulations.

[0061] Then the indirect risk indicators are calculated. In addition to the above direct safety indicators, the retail time-of-use settlement price regulation ratio will indirectly cause risks through the operation of the power grid and the power market. The direct safety indicators and indirect risk indicators are weighted to calculate the scenario value coefficient, and the feasibility of operation is judged to ensure that the evaluated ratio regulation parameter combination is safe and feasible.

[0062] (3) The optimal retail time-sharing settlement price regulation ratio parameter combination calculation takes into account that there may be multiple price regulation ratios that are safe and feasible, and how to choose a more appropriate set of regulation ratios for application.

[0063] In principle, when selecting the optimal proportion regulation parameters, we do not use parameters with high scenario value coefficients in a certain scenario, but instead consider the performance of parameter combinations in different scenarios and select parameters with higher mean value coefficients under the same scenario value coefficient volatility as the optimal retail time-sharing settlement proportion regulation parameter combination.

[0064] After introducing the basic principles of the present application, various non-limiting embodiments of the present application will be described in detail with reference to the accompanying drawings.

[0065] Exemplary Methods

[0066] Figure 1 FIG. 1 is a flow chart of a method for calculating the regulation ratio of time-sharing settlement price for power retail users provided in one embodiment of the present application. Figure 1 As shown, the method includes the following contents.

[0067] Step S110, obtaining basic power data;

[0068] The basic power data includes: classification information of power retail users; elasticity matrix of power volume and price of power retail users; benchmark load and retail benchmark price power of each type of power retail users in each operation scenario;

[0069] Step S120, based on the basic data, exhaustively enumerate the parameter combinations of the time-sharing settlement price regulation ratio parameters that meet the preset conditions to obtain a parameter combination set;

[0070] Step S130, for each parameter combination, based on the basic power data, perform an iterative calculation of power market simulation clearing, and determine a wholesale market peak and valley hour determination strategy corresponding to the parameter combination in each operation scenario;

[0071] Step S140, for each parameter combination and the corresponding wholesale market peak and valley hour determination strategy in each operation scenario, safety index and feasibility judgment are performed to obtain a parameter combination that can be safely operated in all operation scenarios as a target parameter combination;

[0072] Step S150, calculating the full-scene value of each target parameter combination, and determining the target parameter combination with the highest full-scene value as the final parameter combination.

[0073] With such a configuration, the solution provided in this application can simulate the regulatory ratios of time-of-use settlement prices for different electricity retail users based on the basic electricity data. In this way, before actual operation, the consequences of the regulatory ratios of time-of-use settlement prices for different electricity retail users can be understood in advance, so as to adopt appropriate regulatory ratios (i.e., parameter combinations) to better dispatch electricity based on time-of-use settlement prices.

[0074] Furthermore, the acquisition of basic electricity data includes: acquiring original data; classifying electricity retail users based on the original data, grouping users with the same industrial and commercial electricity consumption characteristics and the same region into one category, and obtaining classification information of electricity retail users; for each type of user, determining its electricity quantity and price elasticity matrix based on the original data; dividing different operating scenarios based on the original data, and determining the benchmark load and retail benchmark price electricity for each type of electricity retail user in each operating scenario.

[0075] Specifically, obtaining the original data and performing preliminary calculations include the following parts:

[0076] (1) Classification of electricity retail users

[0077] Electricity retail users are classified into the same category, with the same industrial and commercial electricity consumption characteristics and the same region being grouped together. In order to make the subsequent calculation model more accurate, clustering and other means can also be used to classify electricity retail users.

[0078] (2) Electricity quantity and price elasticity matrix for electricity retail users

[0079] For each type of user, obtain its electricity quantity and electricity price elasticity matrix. The electricity quantity and electricity price elasticity matrix is ​​defined as follows:

[0080] In the formula, the diagonal elements represent self-elasticity, which refers to the ratio of the percentage change of electricity volume to the corresponding percentage change of electricity price. The remaining elements represent cross-elasticity, which refers to the ratio of the percentage change of electricity volume to the percentage change of electricity price in other time periods. The definition is expressed in the following formula:

[0081] (3) Operation scenario

[0082] Based on the historical operation data of the power system and the power market, the operation scenarios are divided. Factors considered include but are not limited to: season, weekdays and holidays, primary energy prices, etc. The method of dividing the operation scenarios includes but is not limited to clustering, etc.

[0083] Obtain historical operation data for each operation scenario, including but not limited to:

[0084] 1) Benchmark load and retail benchmark price for each type of user in the operating scenario: For each type of user in each operating scenario, obtain its historical load curve and historical retail price, and fit them into the benchmark load and retail benchmark price for this type of user.

[0085] 2) The clearing quantity and price of the wholesale electricity market under this operating scenario: For each operating scenario, obtain the unified settlement price and load level on the user side for clearing.

[0086] 3) The operation status of the power grid section under this operation scenario.

[0087] 4) Other boundary conditions for wholesale electricity market clearing under this operation scenario, such as inter-provincial interconnection line power flow, planned unit output, etc., are fitted as boundary conditions for market simulation clearing in the following steps.

[0088] 5) The historical electricity charges of each type of market entity (including power generation entities, power sales companies, and users) under this operating scenario are fitted as the profit benchmark for this scenario.

[0089] Further, based on the basic data, the parameter combinations of the time-sharing settlement price regulation ratio parameters that meet the preset conditions are exhaustively enumerated to obtain a parameter combination set. The specific process is as follows:

[0090] The retail time-sharing settlement price regulation ratio parameter combination is calculated as follows:

[0091] The retail market defines each hour of the day as a "peak period", "normal period" or "valley period", and the peak ratio and valley ratio The calculation is as follows:

[0092] = Retail price during peak hours / Retail price during normal hours

[0093] = Retail price during normal period / Retail price during off-peak period

[0094] The peak-to-valley price ratio set by the electricity sales company when signing the retail contract , The following regulatory requirements must be met:

[0095]

[0096]

[0097] This step calculates the proportional parameters required by the regulation. , , , , take the following steps to calculate:

[0098] The step size is calculated as follows:

[0099] According to the current peak ratio of the retail market and valley ratio , respectively calculate the proportional regulation parameters , , , The step size of the value:

[0100]

[0101]

[0102]

[0103]

[0104] Where r represents the number of values ​​of the proportional regulation parameter.

[0105] The proportional regulation parameter combination is calculated as follows:

[0106] The calculation ratio regulation parameter combination is:

[0107]

[0108] Where:

[0109]

[0110]

[0111]

[0112]

[0113] The proportional regulation parameter combination is calculated as follows:

[0114] The calculation ratio regulation parameter combination is:

[0115]

[0116] In some embodiments, for each parameter combination, based on the basic power data, an iterative calculation of power market simulation clearing is performed to determine the peak and valley hour determination strategy of the wholesale market corresponding to the parameter combination in each operation scenario, including:

[0117] Determine the peak and valley hours of the wholesale market;

[0118] Calculate user retail prices based on the basic electricity data;

[0119] Based on the basic power data, calculate the load curve of each type of user in the nth scenario for the i-th group of parameter combinations;

[0120] Perform the ith group of parameter combinations and simulate the clearing of the electricity market under the nth scenario;

[0121] If the electricity market simulation is cleared and cannot converge, the wholesale market peak and valley hour determination will be re-executed until the convergence conditions are met.

[0122] Specifically, the process of iterative calculation of electricity market simulation clearing is as follows:

[0123] Through iterative clearing of electricity market simulation, the simulation results of each set of retail time-of-use settlement price regulation ratio parameters in each scenario are calculated.

[0124] Determination of peak and valley hours in wholesale market:

[0125] The definition of peak and valley hours in the wholesale market is calculated as follows:

[0126] (1) The unified time-of-use settlement electricity prices on the user side of the 24-hour wholesale market are sorted from small to large.

[0127] (2) Based on the sorting results, the peak and valley hours are initially defined. The hours corresponding to the first eight electricity prices belong to the "valley period", the hours corresponding to the middle eight electricity prices belong to the "normal period", and the hours corresponding to the last eight electricity prices belong to the "peak period".

[0128] (3) The definition of peak and valley hours is adjusted. The adjustment rules are as follows:

[0129] 1) Define peak time and normal time as adjacent time periods, and normal time and valley time as adjacent time periods

[0130] 2) If hour t is one of the adjacent time periods, and hours t-2, t-1, t+1, and t+2 are another of the adjacent time periods, then adjust time period t to the other of the adjacent time periods.

[0131] Calculate user retail price.

[0132] In the nth scenario, the unified time-of-use settlement electricity price on the wholesale market user side is , then the user retail price is calculated as follows:

[0133] (1) The formula for calculating the normal-time price for retail users is:

[0134] =The weighted average price of the unified time-sharing settlement price on the user side of the wholesale market

[0135] (2) The calculation formula for the peak-time price for retail users is:

[0136]

[0137] In the formula, It is the load-weighted average price of the unified time-of-use settlement electricity price on the user side of the wholesale market in the peak period in the nth scenario.

[0138] (3) The calculation formula for the off-peak price for retail users is:

[0139]

[0140] Calculate the load curve of each type of user under the nth scenario for the regulation ratio parameter of the i-th group of retail time-of-use settlement prices.

[0141] The load of the mth user in period t is calculated as follows:

[0142]

[0143] In the formula, represents the baseline load of the mth type of user in the tth period under the nth scenario; represents the retail price of retail users in time period t, and is taken according to whether time period t belongs to the peak period, normal period, and valley period of the retail market. , , ; represents the retail benchmark price for retail users in time period t in the nth scenario; Represents the elasticity coefficient of the mth type of user.

[0144] The electricity market simulation clearing is performed for the i-th group of retail time-of-use settlement price regulation ratio parameters under the n-th scenario.

[0145] According to the historical boundary conditions of the electricity market clearing in the nth scenario, the user load curve calculated in the previous step is used to simulate the clearing of the electricity market.

[0146] Determine the iterative convergence conditions of market simulation.

[0147] Using the electricity wholesale market simulation clearing results from the previous step, recalculate the user retail price in the step "Calculate user retail price", and calculate the market simulation iteration convergence conditions as follows:

[0148]

[0149]

[0150]

[0151] In the formula, c represents the percentage parameter that controls the iterative convergence effect; , , They respectively represent the user retail peak electricity price, flat electricity price and valley electricity price obtained by recalculating the step “calculating user retail price”.

[0152] When all three inequality conditions are met, the market simulation has converged and enters the next step; if any one of them is not met, the market simulation has not converged, and the user retail peak electricity price is set to , flat electricity price Off-peak electricity price Recalculated for step "Calculate user retail price" , , , recalculate the step “calculate the load curve of each type of user under the nth scenario for the regulation ratio parameter of the retail time-of-use settlement price of the i-th group” and enter the next round of simulation clearing cycle.

[0153] If the number of cycles exceeds s and still fails to converge, it means that the i-th set of retail time-sharing settlement time-sharing ratio regulation parameters is not feasible. Take the next set of ratio regulation parameters and repeat the step "Wholesale market peak and valley hour determination".

[0154] In some embodiments, for each parameter combination and the corresponding wholesale market peak and valley hour determination strategy under each operation scenario, safety indicators and feasibility judgments are performed, including:

[0155] For each parameter combination and the corresponding wholesale market peak and valley hour determination strategy under each operation scenario, calculate the direct safety index; judge whether the operation is safe based on the direct safety index; if the operation is safe, calculate the indirect risk index; and make a feasibility judgment based on the direct safety index and the indirect risk index.

[0156] Among them, the direct safety indicators include: power system overload section safety indicators, power system heavy load section safety indicators, power market constraint safety indicators and power market clearing solution safety indicators. The indirect risk indicators include: wholesale and retail peak and valley time misalignment indicators, wholesale and retail peak and valley price misalignment indicators, user electricity fee structure health indicators, and market entity income change indicators.

[0157] The direct safety index calculation and operation safety judgment are as follows:

[0158] For the market simulation clearing results of the i-th group of retail time-sharing settlement price regulation ratio parameters in the n-th scenario, calculate the direct safety index and make an operational safety judgment.

[0159] Calculate the overload section safety index of the power system as follows:

[0160] = Number of overloaded critical sections / total number of critical sections in the power grid

[0161] Wherein, the overloaded critical section refers to the critical section where the load rate exceeds the overload rate defined for grid operation safety in the market simulation clearing model under the nth scenario.

[0162] Calculate the safety index of the heavy-load section of the power system as follows:

[0163] = Number of overloaded critical sections / total number of critical sections in the power grid

[0164] Wherein, the overloaded critical section refers to the critical section where the load rate exceeds the overload rate defined for grid operation safety in the market simulation clearing model under the nth scenario.

[0165] Calculate the security index of power market constraints as follows:

[0166] =Number of clearing constraints broken / Total number of clearing constraints

[0167] In the formula, the clearing constraints refer to the constraints under the optimization model of clearing in this simulation; the number of clearing constraints that have been broken refers to the number of constraints that cannot be met under the optimization model of clearing in this simulation.

[0168] Calculate the power market clearing solution to solve the security index, which is calculated as follows:

[0169] =Solution time / Historical average solution time for this scenario

[0170] Wherein, solution time refers to the solution time of the optimization model for clearing in this simulation; the historical average solution time in this scenario refers to the historical average solution time of the nth scenario in the actual operation of the power market.

[0171] The operational safety is judged as follows:

[0172] For the above direct safety indicators, determine whether they are within the operating safety threshold. When all indicators are less than the threshold, that is:

[0173]

[0174]

[0175]

[0176]

[0177] If the price regulation ratio parameters of the i-th group of retail time-of-use settlement are operating safely, the next step is entered; if any physical operating condition exceeds the threshold, the price regulation ratio parameters of the i-th group of retail time-of-use settlement are operating unsafely, the step of "electricity market simulation clearing iterative calculation" is entered.

[0178] The indirect risk indicator is calculated as follows:

[0179] For the market simulation clearing results of the i-th group of retail time-sharing settlement price regulation ratio parameters in the n-th scenario, calculate the indirect risk indicators.

[0180] Calculate the batch-to-retail peak-to-valley misalignment index as follows:

[0181]

[0182] In the formula, It indicates the matching degree of wholesale and retail peak and valley periods in the tth hour in the market simulation clearing results of the i-th group of retail time-sharing settlement price regulation ratio parameters under the n-th scenario. The calculation logic is:

[0183] (1) The tth hour belongs to the same peak and valley definition in both the wholesale market and the retail market, that is, it is a peak period in both the wholesale market and the retail market, it is a normal period in both the wholesale market and the retail market, or it is a valley period in both the wholesale market and the retail market.

[0184] (2) , the tth hour is the peak period in the wholesale market and the valley period in the retail market, or, the tth hour is the valley period in the wholesale market and the peak period in the retail market.

[0185] (3) , other cases.

[0186] Calculate the wholesale and retail peak-valley price misalignment index as follows:

[0187]

[0188] In the formula, , They respectively represent the user-side unified settlement point electricity price and retail time-of-use price at the t hour in the wholesale market in the market simulation clearing results of the i-th group of retail time-of-use settlement price regulation ratio parameters under the n-th scenario.

[0189] Calculate the health index of the user's electricity fee structure. The calculation formula is as follows:

[0190] = Additional electricity cost / user's total electricity cost

[0191] In the formula, the additional electricity fee refers to the additional electricity fee caused by the difference between the retail electricity price and the wholesale electricity price paid by retail users under the retail time-of-use settlement price regulation ratio parameter, which is calculated as follows:

[0192] Additional electricity cost =

[0193] In the formula, , They respectively represent the retail electricity price at the tth hour and the load level of the mth type of user in the market simulation clearing results of the ith group of retail time-of-use settlement price regulation parameters under the nth scenario.

[0194] Calculate the market entity income change index, the calculation formula is as follows:

[0195]

[0196] In the formula, It represents the rate of change of income of the mth type of market entity in the i-th group of retail time-sharing settlement price regulation ratio parameters in the n-th scenario. The calculation formula is:

[0197]

[0198] In the formula, It represents the change in the income of the mth market entity in the i-th group of retail time-sharing settlement price regulation ratio parameters in the nth scenario, Represents the profit benchmark of the mth type of market entity in the nth scenario.

[0199] The market players here include power generation players, power sales companies and power users. For market players with net cash flow income in the power market, the income is positive; for market players with net cash flow expenditure in the power market, the income is negative.

[0200] The specific process of calculating the scenario value coefficient and judging the benefit feasibility is as follows:

[0201] For the direct safety index and indirect risk index of the i-th group of retail time-sharing settlement price regulation ratio parameters in the n-th scenario, the scenario value coefficient is weighted. , and make a feasibility judgment.

[0202] After normalizing the direct safety index and the indirect risk index, calculate the scenario value coefficient of the regulation ratio parameter of the retail time-sharing settlement price in the nth scenario. , the calculation formula is as follows:

[0203]

[0204] In the formula, , Indicates the weights of the first and second direct safety indicators, , Represent the weights of the first and second indirect risk indicators respectively.

[0205] The weight calculation method includes but is not limited to:

[0206] 1) Determined based on business needs;

[0207] 2) Based on the calculation results of indirect risk indicators and direct safety indicators under all scenarios and all retail time-sharing settlement price regulation ratio parameters, it is set according to the data characteristics of the indicator sample library.

[0208] The feasibility of operating the regulation ratio parameters of the retail time-sharing settlement price of the i-th group in the n-th scenario is judged. If the scenario value coefficient Greater than or equal to threshold ,Right now:

[0209]

[0210] If the i-th group of retail time-of-use settlement price regulation ratio parameters is feasible in the n-th scenario, then the next scenario is taken for calculation (if all scenarios of the i-th group of parameters have been traversed, then the next group of parameters is taken for calculation), and the step "power market simulation clearing iterative calculation" is entered; otherwise, the group of retail time-of-use settlement price regulation ratio parameters is considered infeasible, and the next group of retail time-of-use settlement price regulation ratio parameters is taken for calculation, and the step "power market simulation clearing iterative calculation" is entered.

[0211] In some embodiments, the calculating of the full-scenario value for each target parameter combination includes:

[0212] Calculate the value of the entire scene based on the formula;

[0213] Among them, represents the overall standard deviation of the scenario value coefficients of the i-th group of parameter combinations in all scenarios, and represents the overall standard deviation of the scenario value coefficients of the i-th group of parameter combinations in all scenarios.

[0214] Specifically, the specific process for calculating the optimal retail time-sharing settlement price regulation ratio parameter is as follows:

[0215] Among the retail time-of-use settlement price regulation ratio parameters that are feasible in all scenarios, the optimal retail time-of-use settlement price regulation ratio parameter is calculated. If no retail time-of-use settlement price regulation ratio parameter is safe and feasible in all scenarios, it is determined that it is not appropriate to liberalize the time-of-use settlement price ratio of electricity retail users at present.

[0216] Calculate the full-scenario value coefficient of the i-th group of retail time-sharing settlement price regulation ratio parameters :

[0217]

[0218] In the formula Represents the scenario value coefficient of the i-th group of parameter combinations in all scenarios The arithmetic mean of Represents the scenario value coefficient of the i-th group of parameter combinations in all scenarios The population standard deviation of .

[0219] The retail time-sharing settlement price regulation ratio parameter with a high full-scenario value coefficient is the optimal retail time-sharing settlement price regulation ratio parameter.

[0220] In this way, in principle, when selecting the optimal proportion regulation parameters, we do not use parameters with high scenario value coefficients in a certain scenario, but consider the performance of parameter combinations in different scenarios, and select parameters with higher mean value coefficients under the same scenario value coefficient volatility as the optimal retail time-sharing settlement proportion regulation parameter combination.

[0221] Exemplary Devices

[0222] The device embodiments of the present application can be used to execute the method embodiments of the present application. For details not disclosed in the device embodiments of the present application, please refer to the method embodiments of the present application.

[0223] Figure 3 FIG. 1 is a block diagram of a device for calculating the regulation ratio of time-sharing settlement price for power retail users provided by one embodiment of the present application. Figure 3 As shown, the device comprises:

[0224] An acquisition module 31 is used to acquire basic power data;

[0225] The basic power data includes: classification information of power retail users; elasticity matrix of power volume and price of power retail users; benchmark load and retail benchmark price power of each type of power retail users in each operation scenario;

[0226] An exhaustive module 32 is used to exhaustively enumerate the parameter combinations of the time-sharing settlement price regulation ratio parameters that meet the preset conditions based on the basic data to obtain a parameter combination set;

[0227] A simulation module 33 is used to perform an iterative calculation of power market simulation clearing for each parameter combination based on the basic power data, and determine a wholesale market peak and valley hour determination strategy corresponding to the parameter combination in each operation scenario;

[0228] The judgment module 34 is used to make safety index and feasibility judgments for each parameter combination and the corresponding wholesale market peak and valley hour judgment strategy under each operation scenario, and obtain the parameter combination that can be safely operated in all operation scenarios as the target parameter combination;

[0229] The determination module 35 is used to calculate the full-scene value of each target parameter combination and determine the target parameter combination with the highest full-scene value as the final parameter combination.

[0230] In some embodiments, obtaining basic power data includes:

[0231] Get the original data;

[0232] Based on the original data, the electricity retail users are classified, and the users with the same industrial and commercial electricity consumption characteristics and the same region are classified into one category to obtain the classification information of the electricity retail users;

[0233] For each type of user, determine its electricity quantity and price elasticity matrix based on the original data;

[0234] Based on the original data, different operation scenarios are divided, and the benchmark load and retail benchmark price electricity of each type of electricity retail user under each operation scenario are determined.

[0235] In some embodiments, for each parameter combination, based on the basic power data, an iterative calculation of power market simulation clearing is performed to determine the peak and valley hour determination strategy of the wholesale market corresponding to the parameter combination in each operation scenario, including:

[0236] Determine the peak and valley hours of the wholesale market;

[0237] Calculate user retail prices based on the basic electricity data;

[0238] Based on the basic power data, calculate the load curve of each type of user in the nth scenario for the i-th group of parameter combinations;

[0239] Perform the ith group of parameter combinations and simulate the clearing of the electricity market under the nth scenario;

[0240] If the electricity market simulation is cleared and cannot converge, the wholesale market peak and valley hour determination will be re-executed until the convergence conditions are met.

[0241] In some embodiments, for each parameter combination and the corresponding wholesale market peak and valley hour determination strategy under each operation scenario, safety indicators and feasibility judgments are performed, including:

[0242] Calculate the direct safety index for each parameter combination and the corresponding wholesale market peak and valley hour determination strategy under each operation scenario;

[0243] Determining whether the operation is safe based on the direct safety indicators;

[0244] If the operation is safe, calculate the indirect risk indicators;

[0245] A feasibility judgment is made based on the direct safety indicators and the indirect risk indicators.

[0246] In some embodiments, the direct safety indicators include: power system overload section safety indicators, power system heavy load section safety indicators, power market constraint safety indicators and power market clearing solution safety indicators.

[0247] In some embodiments, the indirect risk indicators include: wholesale and retail peak and valley time period misalignment index, wholesale and retail peak and valley price misalignment index, user electricity fee structure health index, and market entity profit change index.

[0248] In some embodiments, the calculating of the full-scenario value for each target parameter combination includes:

[0249] Calculate the value of the entire scene based on the formula;

[0250] Among them, represents the overall standard deviation of the scenario value coefficients of the i-th group of parameter combinations in all scenarios, and represents the overall standard deviation of the scenario value coefficients of the i-th group of parameter combinations in all scenarios.

[0251] Exemplary Electronic Devices

[0252] Below, reference Figure 4 To describe an electronic device according to an embodiment of the present application. Figure 4A block diagram of an electronic device according to an embodiment of the present application is illustrated.

[0253] like Figure 4 As shown, electronic device 400 includes one or more processors 410 and memory 420 .

[0254] The processor 410 may be a central processing unit (CPU) or other forms of processing units having data processing capabilities and / or instruction execution capabilities, and may control other components in the electronic device 400 to perform desired functions.

[0255] The memory 420 may include one or more computer program products, which may include various forms of computer-readable storage media, such as volatile memory and / or non-volatile memory. The volatile memory may include, for example, random access memory (RAM) and / or cache memory (cache), etc. The non-volatile memory may include, for example, read-only memory (ROM), hard disk, flash memory, etc. One or more computer program instructions may be stored on the computer-readable storage medium, and the processor 410 may run the program instructions to implement the calculation method of the time-sharing settlement price regulation ratio of the power retail user of each embodiment of the present application described above and / or other desired functions. Various contents such as category correspondences may also be stored in the computer-readable storage medium.

[0256] In one example, the electronic device 400 may further include: an input device 430 and an output device 440 , and these components are interconnected via a bus system and / or other forms of connection mechanisms (not shown).

[0257] In addition, the input device 430 may also include, for example, a keyboard, a mouse, an interface, etc. The output device 440 may output various information to the outside, including analysis results, etc. The output device 440 may include, for example, a display, a speaker, a printer, a communication network and a remote output device connected thereto, etc.

[0258] Of course, to simplify, Figure 4 Only some of the components in the electronic device related to the present application are shown, and components such as a bus, an input / output interface, etc. are omitted. In addition, the electronic device may further include any other appropriate components according to specific application conditions.

[0259] Exemplary computer program products and computer-readable storage media

[0260] In addition to the above-mentioned methods and devices, an embodiment of the present application may also be a computer program product, which includes computer program instructions, which, when executed by a processor, enable the processor to execute the steps in the method for calculating the regulatory ratio of the time-of-use settlement price for retail electricity users according to various embodiments of the present application described in the above "Exemplary Method" section of this specification.

[0261] The computer program product may be written in any combination of one or more programming languages ​​to write program codes for performing the operations of the embodiments of the present application, including object-oriented programming languages, such as Java, C++, etc., and conventional procedural programming languages, such as "C" language or similar programming languages. The program code may be executed entirely on the user computing device, partially on the user device, as an independent software package, partially on the user computing device and partially on a remote computing device, or entirely on a remote computing device or server.

[0262] In addition, an embodiment of the present application may also be a computer-readable storage medium having computer program instructions stored thereon, which, when executed by a processor, causes the processor to execute the steps of the method for calculating the regulatory ratio of the time-of-use settlement price for retail electricity users according to various embodiments of the present application described in the above "Exemplary Method" section of this specification.

[0263] The computer readable storage medium can adopt any combination of one or more readable media. The readable medium can be a readable signal medium or a readable storage medium. The readable storage medium can include, for example, but is not limited to, a system, device or device of electricity, magnetism, light, electromagnetic, infrared, or semiconductor, or any combination of the above. More specific examples (non-exhaustive list) of readable storage media include: an electrical connection with one or more wires, a portable disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above.

[0264] The above description has been given for the purpose of illustration and description. In addition, this description is not intended to limit the embodiments of the present application to the forms disclosed herein. Although multiple example aspects and embodiments have been discussed above, those skilled in the art will recognize certain variations, modifications, changes, additions and sub-combinations thereof.

Claims

1. A method for calculating the regulation ratio of time-sharing settlement price for power retail users, characterized in that: include: Obtain basic power data; The basic power data includes: classification information of power retail users; elasticity matrix of power volume and price of power retail users; benchmark load and retail benchmark price power of each type of power retail users in each operation scenario; Based on the basic data, exhaustively enumerate the parameter combinations of the time-sharing settlement price regulation ratio parameters that meet the preset conditions to obtain a parameter combination set; For each parameter combination, based on the basic power data, an iterative calculation of power market simulation clearing is performed to determine the peak and valley hour determination strategy of the wholesale market corresponding to the parameter combination in each operation scenario; For each parameter combination and the corresponding wholesale market peak and valley hour determination strategy under each operation scenario, safety indicators and feasibility judgments are made to obtain a parameter combination that can be safely operated in all operation scenarios as a target parameter combination; Calculate the full-scene value of each target parameter combination, and determine the target parameter combination with the highest full-scene value as the final parameter combination; For each parameter combination, based on the basic power data, an iterative calculation of power market simulation clearing is performed to determine the peak and valley hour determination strategy of the wholesale market corresponding to the parameter combination in each operation scenario, including: Determine the peak and valley hours of the wholesale market; wherein the peak and valley hours of the wholesale market include: the valley hours of the wholesale market when the electricity price is lower than the preset range; the normal hours of the wholesale market when the electricity price is within the preset range; and the peak hours of the wholesale market when the electricity price is higher than the preset range; Calculate user retail prices based on the basic electricity data; Based on the basic power data, calculate the load curve of each type of user in the nth scenario for the i-th group of parameter combinations; Perform the ith group of parameter combinations and simulate the clearing of the electricity market under the nth scenario; If the power market simulation is cleared and cannot converge, the peak and valley hour determination of the wholesale market will be re-executed until the convergence conditions are met; The safety index and feasibility judgment are performed for each parameter combination and the corresponding wholesale market peak and valley hour judgment strategy under each operation scenario, including: Calculate the direct safety index for each parameter combination and the corresponding wholesale market peak and valley hour determination strategy under each operation scenario; Determining whether the operation is safe based on the direct safety indicators; If the operation is safe, calculate the indirect risk indicators; Perform feasibility judgment based on the direct safety indicators and the indirect risk indicators; The full-scenario value calculation for each target parameter combination includes: Based on the formula Calculate the value of the entire scene; in, Represents the scenario value coefficient of the i-th group of parameter combinations in all scenarios The arithmetic mean of Represents the scenario value coefficient of the i-th group of parameter combinations in all scenarios The population standard deviation of Scenario value coefficient It is the sum of the weighted sum of indirect risk indicators under different scenarios and the weighted sum of direct safety indicators under different scenarios; The direct safety indicators include: power system overload section safety indicators, power system heavy load section safety indicators, power market constraint safety indicators and power market clearing solution safety indicators; The indirect risk indicators include: wholesale and retail peak and valley time period misalignment index, wholesale and retail peak and valley price misalignment index, user electricity fee structure health index, and market entity profit change index.

2. The method for calculating the regulation ratio of time-sharing settlement price for power retail users according to claim 1 is characterized in that: The obtaining of basic power data includes: Get the original data; Based on the original data, the electricity retail users are classified, and the users with the same industrial and commercial electricity consumption characteristics and the same region are classified into one category to obtain the classification information of the electricity retail users; For each type of user, determine its electricity quantity and price elasticity matrix based on the original data; Based on the original data, different operation scenarios are divided, and the benchmark load and retail benchmark price electricity of each type of electricity retail user under each operation scenario are determined.

3. A device for calculating the regulation ratio of time-sharing settlement price for power retail users, characterized in that: include: An acquisition module is used to obtain basic power data; The basic power data includes: classification information of power retail users; elasticity matrix of power volume and price of power retail users; benchmark load and retail benchmark price power of each type of power retail users in each operation scenario; An exhaustive module, for exhaustively enumerating, based on the basic data, parameter combinations of the time-sharing settlement price regulation ratio parameters that meet the preset conditions to obtain a parameter combination set; A simulation module, for performing an iterative calculation of power market simulation clearing for each parameter combination based on the basic power data, and determining a peak and valley hour determination strategy for the wholesale market corresponding to the parameter combination in each operation scenario; A judgment module is used to make safety index and feasibility judgments for each parameter combination and the corresponding wholesale market peak and valley hour judgment strategy under each operation scenario, and obtain a parameter combination that can be safely operated in all operation scenarios as a target parameter combination; A determination module is used to calculate the full-scene value of each target parameter combination and determine the target parameter combination with the highest full-scene value as the final parameter combination; For each parameter combination, based on the basic power data, an iterative calculation of power market simulation clearing is performed to determine the peak and valley hour determination strategy of the wholesale market corresponding to the parameter combination in each operation scenario, including: Determine the peak and valley hours of the wholesale market; wherein the peak and valley hours of the wholesale market include: the valley hours of the wholesale market when the electricity price is lower than the preset range; the normal hours of the wholesale market when the electricity price is within the preset range; and the peak hours of the wholesale market when the electricity price is higher than the preset range; Calculate user retail prices based on the basic electricity data; Based on the basic power data, calculate the load curve of each type of user in the nth scenario for the i-th group of parameter combinations; Perform the ith group of parameter combinations and simulate the clearing of the electricity market under the nth scenario; If the power market simulation is cleared and cannot converge, the peak and valley hour determination of the wholesale market will be re-executed until the convergence conditions are met; The safety index and feasibility judgment are performed for each parameter combination and the corresponding wholesale market peak and valley hour judgment strategy under each operation scenario, including: Calculate the direct safety index for each parameter combination and the corresponding wholesale market peak and valley hour determination strategy under each operation scenario; Determining whether the operation is safe based on the direct safety indicators; If the operation is safe, calculate the indirect risk indicators; Perform feasibility judgment based on the direct safety indicators and the indirect risk indicators; The full-scenario value calculation for each target parameter combination includes: Based on the formula Calculate the value of the entire scene; in, Represents the scenario value coefficient of the i-th group of parameter combinations in all scenarios The arithmetic mean of Represents the scenario value coefficient of the i-th group of parameter combinations in all scenarios The population standard deviation of Scenario value coefficient It is the sum of the weighted sum of indirect risk indicators under different scenarios and the weighted sum of direct safety indicators under different scenarios; The direct safety indicators include: power system overload section safety indicators, power system heavy load section safety indicators, power market constraint safety indicators and power market clearing solution safety indicators; The indirect risk indicators include: wholesale and retail peak and valley time period misalignment index, wholesale and retail peak and valley price misalignment index, user electricity fee structure health index, and market entity profit change index.

4. An electronic device, characterized in that: include: A processor, and a memory for storing a program executable by the processor; The processor is used to implement the method for calculating the regulation ratio of time-of-use settlement price for retail electricity users according to any one of claims 1 to 2 by running the program in the memory.

5. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, which, when executed by a processor, enables the processor to execute the method for calculating the regulation ratio of the time-of-use settlement price for retail electricity users according to any one of claims 1 to 2.

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