Method and device for determining target electric quantity data set, medium and equipment

Abstract

The invention relates to a target electric quantity data set determination method and device, a medium and equipment, and relates to the technical field of the electric power industry, and the method comprises the steps: obtaining an electric power data set from an electric power database, obtaining the spot price of a whole network reference point and a preset spot transaction settlement rule from an electric power transaction system, the electric power data set is a set of numerical values of electric power produced by each transaction unit in each first preset time period in a preset reference year; using a power dispatching server to obtain a target electric quantity data set and / or a corresponding target electricity price according to the power data set, the spot electricity price and the preset spot transaction settlement rule, the target electric quantity data set being within a target year, and the target electricity price being within a target year; according to the set of the values of the target electric quantity generated by each transaction unit in each second preset time period, the efficiency and accuracy of determining the target electric quantity data set and the target electricity price corresponding to the maximum income in the new energy power transaction are improved.

Description

Technical Field

[0001] The present disclosure relates to the technical field of the electric power industry, and in particular, to a method, device, medium and equipment for determining a target electricity data set. Background Art

[0002] With the advancement of power system reform, the marketing methods of new energy power generation companies are changing. Under the guidance of preset spot trading settlement rules, the share of power market transactions continues to expand, and the economic benefits of new energy companies in the spot market and ancillary service market are gradually improving.

[0003] However, related technologies often rely on manual formulation of trading volume and electricity prices, which is not only inefficient and inaccurate, but also increasingly difficult and less reusable with the frequent adjustments to medium- and long-term electricity trading rules and spot trading rules. Summary of the invention

[0004] In order to overcome the problems existing in the related art, the present disclosure provides a method, device, medium and equipment for determining a target power data set.

[0005] According to a first aspect of an embodiment of the present disclosure, a method for determining a target power data set is provided, including: Obtaining a power data set from a power database, and obtaining a spot electricity price of a reference point of the entire network and a preset spot transaction settlement rule from a power trading system, wherein the power data set is a set of values ​​of power produced by each trading unit in each first preset time period in a preset reference year; Utilizing the power dispatching server, a target electricity quantity data set and / or its corresponding target electricity price is obtained according to the power data set, the spot electricity price and the preset spot transaction settlement rules. The target electricity quantity data set is a collection of numerical values ​​of the target electricity quantity produced by each trading unit in each second preset time period within the target year.

[0006] Optionally, the using of the power dispatching server to obtain the target power data set and / or its corresponding target power price according to the power data set, the spot power price and the preset spot transaction settlement rule includes: Performing statistics on each data of the power data set to obtain an electric quantity data set, wherein the electric quantity data set is a set of numerical values ​​of the electric quantity produced by each trading unit in each second preset time period in the target year; Increasing or decreasing each data of the electric quantity data set to obtain an adjusted electric quantity data set; Obtaining an adjusted electricity price according to the spot electricity price, the preset spot transaction settlement rule and the adjusted electricity quantity data set; Return to execute the step of increasing or decreasing each data of the electric quantity data set to obtain an adjusted electric quantity data set, until the adjusted electricity price is maximum and less than a preset electricity price threshold, and use the adjusted electric quantity data set in the last cycle as the target electric quantity data set, and the adjusted electricity price as the target electricity price.

[0007] Optionally, the performing statistics on each data of the power data set to obtain the power data set includes: For each of the trading units, the power data of the trading unit is counted according to the energy type used to produce electricity by the trading unit to obtain the power data set, and the length of the second preset time period is K times the length of the first preset time period, where K is a natural number greater than 1.

[0008] Optionally, for each of the trading units, according to the energy type of the trading unit for generating electricity, collecting statistics on the electricity data of the trading unit to obtain the electricity data set includes: For each of the transaction units, the following steps are performed to obtain the electricity quantity data set: When the power generated by the trading unit is wind power and the discrete degree of the power data of the trading unit is greater than or equal to the preset discrete value, the average value of K consecutive power data of the trading unit is used as the power data of the trading unit in a second preset time period; When the power generated by the transaction unit is wind power and the discrete degree of the power data of the transaction unit is less than the preset discrete value, the median value of K consecutive power data of the transaction unit is used as the power data of the transaction unit in a second preset time period; In the case where the electricity produced by the transaction unit is photovoltaic, the median value or the maximum probability value of K consecutive power data of the transaction unit is used as the electricity data of the transaction unit in the second preset time period.

[0009] Optionally, increasing or decreasing each data of the electric quantity data set to obtain an adjusted electric quantity data set includes: The peak electricity data, flat electricity data and valley electricity data of the electricity data set are increased or decreased according to a first ratio, a second ratio and a third ratio, respectively, to obtain the adjusted electricity data set, wherein the peak electricity data is the electricity data during the peak electricity consumption period in the electricity data set, the flat electricity data is the electricity data during the stable electricity consumption period in the electricity data set, and the valley electricity data is the electricity data during the valley electricity consumption period in the electricity data set.

[0010] Optionally, the peak-segment electricity data, the flat-segment electricity data, and the valley-segment electricity data of the electricity data set are increased or decreased according to a first ratio, a second ratio, and a third ratio, respectively, to obtain the adjusted electricity data set, including: The first ratio, the second ratio and the third ratio are respectively configured within a preset range, and are increased or decreased with a preset step length to obtain an adjusted first ratio, an adjusted second ratio and an adjusted third ratio; The peak power data, the flat power data and the valley power data are increased or decreased in turn according to the adjusted first ratio, the adjusted second ratio and the adjusted third ratio to obtain the adjusted power data set.

[0011] Optionally, it also includes: According to the spot electricity price, the preset spot transaction settlement rules, the target electricity quantity data set and the target electricity price, the calculated parameter values ​​of each of the transaction units are obtained respectively.

[0012] According to a second aspect of an embodiment of the present disclosure, a device for determining a target power data set is provided, including: A data acquisition module is used to acquire a power data set from a power database, and to acquire the spot electricity price of the reference point of the entire network and preset spot transaction settlement rules from a power trading system, wherein the power data set is a collection of power data produced by each trading unit in each first preset time period in a preset reference year; The target electricity data set determination module is used to obtain a target electricity data set and / or its corresponding target electricity price based on the electricity data set, the spot electricity price and the preset spot transaction settlement rules. The target electricity data set is a set of numerical values ​​of the target electricity produced by each trading unit in each second preset time period within the target year.

[0013] According to a third aspect of an embodiment of the present disclosure, a non-temporary computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the steps of any one of the methods provided in the first aspect of the present disclosure are implemented.

[0014] According to a fourth aspect of an embodiment of the present disclosure, there is provided an electronic device, including: a memory having a computer program stored thereon; A processor is used to execute the computer program in the memory to implement the steps of any one of the methods provided in the first aspect of the present disclosure.

[0015] Through the above technical solution, an electricity data set including the numerical value of electricity produced by each trading unit in each first preset time period within a preset reference year, the spot electricity price of the reference point of the entire network and the preset spot transaction settlement rules are obtained, and then the target electricity data set and / or its corresponding target electricity price are obtained based on the electricity data set, the spot electricity price and the preset spot transaction settlement rules, which can improve the efficiency and accuracy of determining the target electricity data set and target electricity price corresponding to achieving maximum benefits in new energy power transactions.

[0016] Other features and advantages of the present disclosure will be described in detail in the following detailed description. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] The accompanying drawings are used to provide a further understanding of the present disclosure and constitute a part of the specification. Together with the following specific embodiments, they are used to explain the present disclosure but do not constitute a limitation of the present disclosure. In the accompanying drawings: Figure 1 is a flow chart showing a method for determining a target power data set according to an exemplary embodiment; Figure 2 is a power data set for 2023 according to an exemplary embodiment; Figure 3 is the spot electricity price of the reference point of the entire network according to an exemplary embodiment; Figure 4 It is the electricity price corresponding to the peak-segment electricity data and the flat-segment electricity data after being adjusted according to the first ratio, the second ratio and the third ratio according to an exemplary embodiment; Figure 5 is a calculated parameter value of a portion of a transaction unit according to an exemplary embodiment; Figure 6 is a block diagram of a device for determining a target power data set according to an exemplary embodiment; Figure 7 It is a block diagram of an electronic device according to an exemplary embodiment. DETAILED DESCRIPTION

[0018] The specific implementation of the present disclosure is described in detail below in conjunction with the accompanying drawings. It should be understood that the specific implementation described herein is only used to illustrate and explain the present disclosure, and is not used to limit the present disclosure.

[0019] It should be noted that all actions of acquiring signals, information or data in the present disclosure are carried out in compliance with the relevant data protection laws and policies of the country where the device is located and with the authorization given by the owner of the corresponding device.

[0020] In order to make the purpose, technical solutions and advantages of the present disclosure more clearly understood, the present disclosure is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present disclosure and are not intended to limit the present disclosure. In addition, the technical features involved in each embodiment of the present disclosure described below can be combined with each other as long as they do not conflict with each other.

[0021] Figure 1 FIG. 1 is a flow chart showing a method for determining a target power data set according to an exemplary embodiment. Figure 1 As shown, the method for determining the target power data set provided by the embodiment of the present disclosure can be applied to scenarios where future power supply needs to be predicted and planned, and is applicable to the formulation of medium- and long-term power trading strategies in terms of time dimension, and is particularly applicable to the formulation of power trading strategies for new energy in terms of energy type. The method includes the following steps.

[0022] In step 110, an electric power data set is obtained from an electric power database, and the spot electricity price of the reference point of the entire network and the preset spot trading settlement rules are obtained from the electric power trading system. The electric power data set is a collection of numerical values ​​of the electric power produced by each trading unit in each first preset time period within a preset reference year.

[0023] In step 120, a target electricity quantity dataset and / or its corresponding target electricity price is obtained by utilizing a power dispatching server according to the power dataset, the spot electricity price, and the preset spot transaction settlement rules. The target electricity quantity dataset is a set of numerical values ​​of the target electricity quantity produced by each trading unit in each second preset time period within the target year.

[0024] Here, the target year refers to the year in which electricity trading is required. The preset reference year can be a year adjacent to the target year. For example, it is necessary to make an electricity trading decision for 2024, that is, 2024 is the target year, and the electricity data sets of the three reference years of 2021, 2022 and 2023 can be used. The first preset time period can be the standard time scale for the trading unit to record the electricity value, such as 1 minute, 5 minutes. The second preset time period refers to the time interval corresponding to the electricity data of each trading unit in the target electricity data set. The target electricity refers to the electricity that each trading unit should sign within each second preset time period to obtain the optimal electricity trading income. The target electricity price refers to the unit electricity price that each trading unit should sign to obtain the optimal electricity trading income.

[0025] Figure 2 is a power data set for 2023 according to an exemplary embodiment. Figure 2As shown, the trading units include Jingzi 1, Jingzi 2, Yuxin, Yuxin (dam), Qiaosan, Ansi 2, Xiangyang 1, Xiangyang 2, Gongpoquan, Pingshan Lake 1, Pingshan Lake 2, Nantan Photovoltaic 1, Nantan Photovoltaic 2, Shunhua Photovoltaic, Gongpoquan Photovoltaic Phase II, Shengguang 1 and Shengguang 2. Among them, Jingzi 1, Jingzi 2, Yuxin, Yuxin (dam), Qiaosan, Ansi 2, Xiangyang 1, Xiangyang 2, Gongpoquan, Pingshan Lake 1 and Pingshan Lake 2 are wind power trading units, and Nantan Photovoltaic 1, Nantan Photovoltaic 2, Shunhua Photovoltaic, Gongpoquan Photovoltaic Phase II, Shengguang 1 and Shengguang 2 are photovoltaic trading units. Figure 2 Each value in is the value of electricity produced by the corresponding trading unit within every 5 minutes (the first preset time period).

[0026] Figure 3 It is the spot electricity price of the whole network reference point shown according to an exemplary embodiment, including the spot electricity price of the whole network reference point of each trading unit in each month. The spot electricity price of the whole network reference point refers to the spot electricity price used as the reference price of the entire power system or power grid corresponding to the trading unit in the power spot market. The electricity prices of different trading units in different periods may be different. The spot electricity price refers to the electricity price of instant transactions in the power spot market.

[0027] The preset spot transaction settlement rules may include a settlement cycle, a settlement price, and a settlement rule. The settlement cycle may be different time periods such as hourly, daily, or monthly. For example, the electricity price and electricity volume are settled once every hour. The settlement price can be determined according to different market mechanisms, such as a unified clearing price, a marginal clearing price, etc. For example, a unified clearing price is adopted, that is, all buyers and sellers settle at the same price. The settlement rules may include electricity volume restrictions, price upper and lower limits, etc. For example, the electricity volume is limited to no more than 100 megawatt-hours per hour, and the price cap is 500 yuan / megawatt-hour. The specific preset spot transaction settlement rules are determined according to the actual situation of different electricity markets, and are not specifically limited in this disclosure.

[0028] The target electricity data set refers to the amount of electricity that each trading unit should sign in order to obtain the optimal electricity trading income in the year when electricity trading is required. The target electricity price refers to the price per unit of electricity that each trading unit should sign in order to obtain the optimal electricity trading income in the year when electricity trading is required. The target electricity data set and target electricity price can provide a basis for electricity trading for electricity trading participants.

[0029] The power dispatch server refers to a high-performance computing device used in the power system for new energy power trading calculations, which can obtain power data sets from the power database. In addition, the power dispatch server can also be replaced by power computing nodes, power edge computing devices, power distributed computing clusters, power data centers, power cloud computing platforms, power high-performance computing systems, etc.

[0030] For example, assuming that this method is applicable to determining the target electricity data set for a certain target year (such as 2024). Then, the actual power generation data of each trading unit in each preset period in the last 3-5 years (such as 2019-2023) can be obtained from the power database as a reference power data set. This can not only reflect the historical situation of the power system, but also provide sufficient data support for the subsequent calculation of the target electricity for the target year.

[0031] Obtain the spot electricity price of the reference point of the entire network and the preset spot transaction settlement rules from the power trading system. For example, assume that the power transaction adopts centralized power trading and uses an independent power trading system as a trading platform for power trading. The spot electricity price of the reference point of the entire network of the power trading system can be obtained regularly (such as every hour). The power trading system usually has clear power trading settlement rules and stipulates various settlement methods and mechanisms for power trading. The transaction settlement rules can be obtained through the public information of the power trading system.

[0032] Through the above technical solution, an electricity data set including the numerical value of electricity produced by each trading unit in each first preset time period within a preset reference year, the spot electricity price of the reference point of the entire network and the preset spot trading settlement rules are obtained, and then the target electricity data set and / or its corresponding target electricity price are obtained based on the electricity data set, the spot electricity price and the preset spot trading settlement rules, which can improve the efficiency and accuracy of determining the target electricity data set and target electricity price corresponding to achieving maximum profit in new energy power trading.

[0033] In a possible embodiment, step 120 includes: performing statistics on each data of the power data set to obtain an electricity data set, wherein the electricity data set is a set of numerical values ​​of the electricity produced by each trading unit in each second preset time period within the target year; increasing or decreasing each data of the electricity data set to obtain an adjusted electricity data set; obtaining an adjusted electricity price according to the spot electricity price, the preset spot transaction settlement rules and the adjusted electricity data set; returning to execute the increase or decrease of each data of the electricity data set to obtain an adjusted electricity data set until the adjusted electricity price is the largest and less than the preset electricity price threshold, and using the adjusted electricity data set in the last cycle as the target electricity data set, and the adjusted electricity price as the target electricity price.

[0034] Here, the power data set is the intermediate value in the process of multiple statistics and adjustments of the power data set, and the target power data set is the final value obtained based on the last statistical and adjusted power data set. One or more statistical methods such as summation statistics, average statistics, median statistics, standard deviation statistics, and probability statistics can be used to perform statistics on each data of the power data set to obtain the power data set.

[0035] One or more of the fixed increase and decrease range method, random increase and decrease range method, increase and decrease method based on statistical distribution, increase and decrease method based on correlation, etc. can be used to increase or decrease each data of the power data set to obtain an adjusted power data set.

[0036] It should be understood that when increasing or decreasing each data in the electric quantity data set, the increase cannot exceed twice the maximum carrying capacity of the power generation system of the trading unit corresponding to the electric quantity data, and the decrease is generally not less than 0.1 times the maximum carrying capacity. Because the adjustment range is limited, all possible combinations of electric quantity data sets can be traversed within this adjustment range through exhaustive method, and the corresponding electricity price is calculated. The combination with the largest electricity price is found as the target electric quantity data set, and the corresponding electricity price is used as the target electricity price.

[0037] In a possible embodiment, statistics are performed on each data of the power data set to obtain the power data set, including: for each of the trading units, according to the energy type for producing electricity by the trading unit, statistics are performed on the power data of the trading unit to obtain the power data set, the duration of the second preset time period is K times the duration of the first preset time period, and K is a natural number greater than 1.

[0038] It should be understood that in order to aggregate the power data into a longer time interval to reduce the amount of data, improve computing efficiency, and match other operating time scales of the power system (such as 15 minutes), the length of the second preset period is set to K times the length of the first preset period, and K can be a natural number greater than 1, such as 2 or 3. For example, the first preset period can be 5 minutes, K can be 3, and the second preset period is 15 minutes.

[0039] To count the power data of a trading unit based on the energy type used to produce electricity, we first need to determine the energy type produced by the trading unit, and then determine the appropriate statistical method based on the distribution characteristics of its energy data. For example, new energy types include wind energy, solar energy, etc., and fossil fuels include coal, natural gas, oil, etc., as well as nuclear energy. By counting power data based on energy types, we can improve calculation efficiency while ensuring statistical accuracy.

[0040] In a possible embodiment, for each of the trading units, according to the energy type of electricity generated by the trading unit, the electricity data of the trading unit are counted to obtain the electricity data set, including: for each of the trading units, the following steps are performed to obtain the electricity data set: when the electricity generated by the trading unit is wind power and the discreteness of the electricity data of the trading unit is greater than or equal to a preset discrete value, the average value of K consecutive electricity data of the trading unit is used as the electricity data of the trading unit in a second preset time period; when the electricity generated by the trading unit is wind power and the discreteness of the electricity data of the trading unit is less than the preset discrete value, the median value of K consecutive electricity data of the trading unit is used as the electricity data of the trading unit in a second preset time period; when the electricity generated by the trading unit is photovoltaic, the median value or maximum probability value of K consecutive electricity data of the trading unit is used as the electricity data of the trading unit in a second preset time period.

[0041] It should be understood that wind power generation is greatly affected by factors such as weather, and its power output often has large fluctuations and discreteness. Therefore, different statistical methods need to be used according to the different degrees of discreteness to better reflect the actual power generation characteristics of wind power and improve the accuracy of statistics. When the degree of discreteness is large, such as greater than or equal to the preset discrete value, the average value can be used to suppress the influence of discrete points and obtain more stable data; when the degree of discreteness is small, such as less than the preset discrete value, the median value can be used to more accurately reflect the central trend of the data.

[0042] In contrast, photovoltaic power generation is less affected by weather factors, and its power output fluctuations are relatively small. Therefore, the maximum probability value after the median value can be directly used without distinguishing according to the degree of dispersion.

[0043] In addition, the aforementioned method mentions that the electricity data set includes electricity data of each trading unit in each second preset time period, wherein the length of the second preset time period is K times the length of the first preset time period, and the statistical values ​​of K consecutive electricity data are used as the electricity data of the trading unit in a second preset time period to achieve time granularity matching.

[0044] According to the actual power generation characteristics of different types of new energy power, the above-mentioned differentiated statistical method is used for calculation to avoid unified invalid calculation of power data, which can improve the efficiency and accuracy of obtaining the power data of various types of new energy power, thereby improving the efficiency and accuracy of determining the target power data set and target electricity price corresponding to the maximum profit in the new energy power transaction. In a possible embodiment, the increase or decrease of each data of the power data set to obtain the adjusted power data set includes: the peak power data, the flat power data and the valley power data of the power data set are increased or decreased in accordance with the first ratio, the second ratio and the third ratio respectively to obtain the adjusted power data set, the peak power data is the power data of the peak power consumption period in the power data set, the flat power data is the power data of the stable power consumption period in the power data set, and the valley power data is the power data of the low power consumption period in the power data set.

[0045] Generally speaking, peak electricity consumption usually occurs during the morning and evening peak hours on weekdays, as well as during the noon and afternoon hours in summer. Stable electricity consumption usually occurs during the morning and afternoon hours on weekdays, as well as in spring and autumn. Low electricity consumption usually occurs late at night and during some periods during holidays.

[0046] By using different adjustment ratios for electricity data in different time periods, the overall electricity and electricity price plan can be better optimized. Peak electricity generally has higher returns, and the proportion of peak electricity data can be appropriately increased to improve overall returns. Flat electricity is relatively stable, and a relatively small adjustment ratio can be used to adjust flat electricity data. Valley electricity usually has lower returns, and the proportion of valley electricity data can be appropriately reduced to reduce overall costs.

[0047] Through the above-mentioned segmented adjustment method, the target electricity data set and target electricity price plan can be optimized more flexibly, thereby improving the overall benefits of new energy power trading.

[0048] In a possible embodiment, the peak power data, the flat power data, and the valley power data of the power data set are increased or decreased according to a first ratio, a second ratio, and a third ratio, respectively, to obtain the adjusted power data set, including: respectively configuring the first ratio, the second ratio, and the third ratio within a preset range, and increasing or decreasing them with a preset step size to obtain the adjusted first ratio, the adjusted second ratio, and the adjusted third ratio; increasing or decreasing the peak power data, the flat power data, and the valley power data according to the adjusted first ratio, the adjusted second ratio, and the adjusted third ratio, respectively, to obtain the adjusted power data set.

[0049] It should be understood that when increasing or decreasing each data in the electricity data set, the increase cannot exceed twice the maximum carrying capacity of the power generation system of the trading unit corresponding to the electricity data, and the decrease is generally not less than 0.1 times the maximum carrying capacity. Therefore, the preset range can be [0.1, 2], [0.5, 2], [0.1, 1.5], [0.5, 1.5], preferably [0.5, 1.5]. The preset step size can be 0.1, 0.2, 0.4, 0.5, preferably 0.5. If the preset range is set to [0.5, 1.5] and the preset step size is set to 0.5, the first ratio, the second ratio and the third ratio can take values ​​of 0.5, 1 or 1.5, and there are 27 combinations in total, that is, a maximum of 27 cycles can be performed to find the combination with the highest electricity price. Figure 4 is an exemplary embodiment showing the corresponding electricity prices of the peak-segment electricity data and the flat-segment electricity data after being adjusted according to the first ratio, the second ratio, and the third ratio, such as Figure 4 As shown, it can be seen that when the peak quantity data (peak), the flat electricity data (flat) and the valley electricity data (valley) are respectively 1, 1 and 0.5, the highest (actual total) electricity price is 180.

[0050] By setting the preset range and preset step size, it is possible to formulate trading volume and electricity prices that are in line with actual production conditions and improve the efficiency of determining trading volume and electricity prices.

[0051] In a possible embodiment, the method further includes: obtaining a calculated parameter value of each of the transaction units according to the spot electricity price, the preset spot transaction settlement rule, the target electricity data set and the target electricity price.

[0052] Here, the calculated parameter values ​​include medium- and long-term total electricity, base electricity, transaction electricity, real-time online SCADA electricity, medium- and long-term electricity as a percentage of actual power generation (%), positive spot electricity price the day before, negative spot electricity price the day before, real-time positive spot electricity price, real-time negative spot electricity price, positive spot electricity price, negative spot electricity price, net spot electricity price, medium- and long-term total electricity price, base electricity price, transaction electricity price, average settlement electricity price, the difference between the positive spot price of this station and the medium- and long-term average price of the province, the difference between the negative spot price of this station and the medium- and long-term average price of the province, positive spot electricity charge the day before, negative spot electricity charge the day before, real-time positive spot electricity charge, real-time negative spot electricity charge, positive spot electricity charge, negative spot electricity charge, net spot electricity charge, medium- and long-term transaction electricity charge, medium- and long-term transaction congestion electricity charge, medium- and long-term transaction hedging electricity charge, average settlement electricity charge, medium- and long-term deviation recovery and compensation, estimated shared electricity charge, medium- and long-term average price of the province, average price per kilowatt-hour of spot-related expenses, average price per kilowatt-hour of detailed rules, and average price of ancillary services.

[0053] Figure 5 is a calculated parameter value of a part of a transaction unit according to an exemplary embodiment, such as Figure 4 and 5 As shown, you can see the calculated parameter values ​​of each transaction unit, as well as the total calculated parameter values ​​of each transaction unit.

[0054] By statistically analyzing and adjusting the power data set, we can obtain the target electricity data set and target electricity price, which can better optimize the trading plan; taking differentiated statistical methods according to the characteristics of different types of new energy can improve the accuracy of data processing; adjusting the electricity data in segments can balance the value of electricity in different periods, which is conducive to improving overall benefits, thereby improving the economy and efficiency of new energy transactions.

[0055] By adjusting the electricity data set within the preset range, the optimal combination of electricity data and electricity price can be explored; by flexibly adjusting the proportional coefficient, it can adapt to different actual situations; and by controlling the adjustment range, adverse effects caused by excessive adjustments can be avoided, thereby improving the efficiency of determining the target electricity data set and target electricity price.

[0056] According to the spot electricity price, trading rules and target electricity data, the detailed measurement parameters of each trading unit are obtained. These measurement parameters can provide a basis for the refined management of new energy power transactions, improve the overall operational efficiency, and thus realize the refined management of new energy power transactions.

[0057] Figure 6 is a block diagram of a device for determining a target power data set according to an exemplary embodiment. Figure 6 The device includes: a data acquisition module 610 and a target power data set determination module 620.

[0058] The data acquisition module 610 is used to obtain a power data set from the power database, and obtain the spot electricity price of the reference point of the entire network and the preset spot transaction settlement rules from the power trading system. The power data set is a collection of power data produced by each trading unit in each first preset time period within a preset reference year.

[0059] The target electricity data set determination module 620 is used to obtain a target electricity data set and / or its corresponding target electricity price based on the electricity data set, the spot electricity price and the preset spot transaction settlement rules. The target electricity data set is a set of numerical values ​​of the target electricity produced by each trading unit in each second preset time period within the target year.

[0060] Optionally, the target power data set determination module 620 includes: A first determination module is used to perform statistics on each data of the power data set to obtain an electric quantity data set, wherein the electric quantity data set is a set of numerical values ​​of the electric quantity produced by each trading unit in each second preset time period in the target year; A second determination module is used to increase or decrease each data of the power data set to obtain an adjusted power data set; A third determination module, configured to obtain an adjusted electricity price according to the spot electricity price, the preset spot transaction settlement rule and the adjusted electricity quantity data set; A loop execution module is used to return to execute the increase or decrease of each data of the electricity data set to obtain an adjusted electricity data set, until the adjusted electricity price is the largest and less than a preset electricity price threshold, and use the adjusted electricity data set in the last loop as the target electricity data set, and the adjusted electricity price as the target electricity price.

[0061] Optionally, the first determining module includes a fourth determining module, configured to: For each of the trading units, the power data of the trading unit is counted according to the energy type used to produce electricity by the trading unit to obtain the power data set, and the length of the second preset time period is K times the length of the first preset time period, where K is a natural number greater than 1.

[0062] Optionally, the fourth determining module is used to: For each of the transaction units, the following steps are performed to obtain the electricity quantity data set: When the power generated by the trading unit is wind power and the discrete degree of the power data of the trading unit is greater than or equal to the preset discrete value, the average value of K consecutive power data of the trading unit is used as the power data of the trading unit in a second preset time period; When the power generated by the transaction unit is wind power and the discrete degree of the power data of the transaction unit is less than the preset discrete value, the median value of K consecutive power data of the transaction unit is used as the power data of the transaction unit in a second preset time period; In the case where the electricity produced by the transaction unit is photovoltaic, the median value or the maximum probability value of K consecutive power data of the transaction unit is used as the electricity data of the transaction unit in the second preset time period.

[0063] Optionally, the second determining module includes a fifth determining module, configured to: The peak electricity data, flat electricity data and valley electricity data of the electricity data set are increased or decreased according to a first ratio, a second ratio and a third ratio, respectively, to obtain the adjusted electricity data set, wherein the peak electricity data is the electricity data during the peak electricity consumption period in the electricity data set, the flat electricity data is the electricity data during the stable electricity consumption period in the electricity data set, and the valley electricity data is the electricity data during the valley electricity consumption period in the electricity data set.

[0064] Optionally, the fifth determining module is used to: The first ratio, the second ratio and the third ratio are respectively configured within a preset range, and are increased or decreased with a preset step length to obtain an adjusted first ratio, an adjusted second ratio and an adjusted third ratio; The peak power data, the flat power data and the valley power data are increased or decreased in turn according to the adjusted first ratio, the adjusted second ratio and the adjusted third ratio to obtain the adjusted power data set.

[0065] Optionally, the device for determining the target power data set further includes a sixth determination module, configured to: According to the spot electricity price, the preset spot transaction settlement rules, the target electricity data set and the target electricity price, the calculated parameter values ​​of each transaction unit are obtained respectively.

[0066] Regarding the device in the above embodiment, the specific manner in which each module performs operations has been described in detail in the embodiment of the method, and will not be elaborated here.

[0067] Figure 7 FIG. 7 is a block diagram of an electronic device 700 according to an exemplary embodiment. Figure 7 As shown, the electronic device 700 may include: a processor 701 , a memory 702 . The electronic device 700 may also include one or more of a multimedia component 703 , an input / output (I / O) interface 704 , and a communication component 705 .

[0068] The processor 701 is used to control the overall operation of the electronic device 700 to complete all or part of the steps in the above-mentioned method for determining the target power data set. The memory 702 is used to store various types of data to support the operation of the electronic device 700, and these data may include instructions for any application or method used to operate on the electronic device 700, and application-related data, such as contact data, sent and received messages, pictures, audio, video, etc. The memory 702 can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (Static Random Access Memory, referred to as SRAM), electrically erasable programmable read-only memory (Electrically Erasable Programmable Read-Only Memory, referred to as EEPROM), erasable programmable read-only memory (Erasable Programmable Read-Only Memory, referred to as EPROM), programmable read-only memory (Programmable Read-Only Memory, referred to as PROM), read-only memory (Read-Only Memory, referred to as ROM), magnetic memory, flash memory, magnetic disk or optical disk. The multimedia component 703 may include a screen and an audio component. The screen may be, for example, a touch screen, and the audio component is used to output and / or input audio signals. For example, the audio component may include a microphone for receiving external audio signals. The received audio signal may be further stored in the memory 702 or sent through the communication component 705. The audio component also includes at least one speaker for outputting audio signals. The I / O interface 704 provides an interface between the processor 701 and other interface modules, and the above-mentioned other interface modules may be keyboards, mice, buttons, etc. These buttons may be virtual buttons or physical buttons. The communication component 705 is used for wired or wireless communication between the electronic device 700 and other devices. Wireless communication, such as Wi-Fi, Bluetooth, Near Field Communication (NFC), 2G, 3G, 4G, NB-IOT, eMTC or other 5G, etc., or a combination of one or more of them, is not limited here. Therefore, the corresponding communication component 705 may include: Wi-Fi module, Bluetooth module, NFC module, etc.

[0069] In an exemplary embodiment, the electronic device 700 can be implemented by one or more application specific integrated circuits (ASIC), digital signal processors (DSP), digital signal processing devices (DSPD), programmable logic devices (PLD), field programmable gate arrays (FPGA), controllers, microcontrollers, microprocessors or other electronic components to execute the above-mentioned method for determining the target power data set.

[0070] In another exemplary embodiment, a computer-readable storage medium including program instructions is also provided, and when the program instructions are executed by a processor, the steps of the method for determining the target power data set described above are implemented. For example, the computer-readable storage medium may be the memory 702 including the program instructions, and the program instructions may be executed by the processor 701 of the electronic device 700 to complete the method for determining the target power data set described above.

[0071] The preferred embodiments of the present disclosure are described in detail above in conjunction with the accompanying drawings; however, the present disclosure is not limited to the specific details in the above embodiments. Within the technical concept of the present disclosure, a variety of simple modifications can be made to the technical solution of the present disclosure, and these simple modifications all fall within the protection scope of the present disclosure.

[0072] It should also be noted that the various specific technical features described in the above specific embodiments can be combined in any suitable manner without contradiction. In order to avoid unnecessary repetition, the present disclosure will not further describe various possible combinations.

[0073] In addition, various embodiments of the present disclosure may be arbitrarily combined, and as long as they do not violate the concept of the present disclosure, they should also be regarded as the contents disclosed by the present disclosure.

Claims

1. A method for determining a target power data set, characterized in that: include: Obtaining a power data set from a power database, and obtaining a spot electricity price of a reference point of the entire network and a preset spot transaction settlement rule from a power trading system, wherein the power data set is a set of values ​​of power produced by each trading unit in each first preset time period in a preset reference year; Utilizing the power dispatching server, a target electricity quantity data set and / or its corresponding target electricity price is obtained according to the power data set, the spot electricity price and the preset spot transaction settlement rules. The target electricity quantity data set is a collection of numerical values ​​of the target electricity quantity produced by each trading unit in each second preset time period within the target year.

2. The method according to claim 1, characterized in that The method of using the power dispatching server to obtain the target power data set and / or its corresponding target power price according to the power data set, the spot power price and the preset spot transaction settlement rule includes: Performing statistics on each data of the power data set to obtain an electric quantity data set, wherein the electric quantity data set is a set of numerical values ​​of the electric quantity produced by each trading unit in each second preset time period in the target year; Increasing or decreasing each data of the electric quantity data set to obtain an adjusted electric quantity data set; Obtaining an adjusted electricity price according to the spot electricity price, the preset spot transaction settlement rule and the adjusted electricity quantity data set; Return to execute the step of increasing or decreasing each data of the electric quantity data set to obtain an adjusted electric quantity data set, until the adjusted electricity price is maximum and less than a preset electricity price threshold, and use the adjusted electric quantity data set in the last cycle as the target electric quantity data set, and the adjusted electricity price as the target electricity price.

3. The method according to claim 2, characterized in that The step of performing statistics on each data of the power data set to obtain the power data set includes: For each of the trading units, the power data of the trading unit is counted according to the energy type used to produce electricity by the trading unit to obtain the power data set, and the length of the second preset time period is K times the length of the first preset time period, where K is a natural number greater than 1.

4. The method according to claim 3, characterized in that For each of the trading units, according to the energy type of the trading unit for generating electricity, collecting the electricity data of the trading unit to obtain the electricity data set includes: For each of the transaction units, the following steps are performed to obtain the electricity quantity data set: When the power generated by the trading unit is wind power and the discreteness of the power data of the trading unit is greater than or equal to the preset discrete value, the average value of K consecutive power data of the trading unit is used as the power data of the trading unit in a second preset time period; When the power generated by the transaction unit is wind power and the discreteness of the power data of the transaction unit is less than the preset discrete value, the median value of K consecutive power data of the transaction unit is used as the power data of the transaction unit in a second preset time period; In the case where the electricity produced by the transaction unit is photovoltaic, the median value or the maximum probability value of K consecutive power data of the transaction unit is used as the electricity data of the transaction unit in the second preset time period.

5. The method according to any one of claims 2 to 4, characterized in that: The step of increasing or decreasing each data of the electric quantity data set to obtain an adjusted electric quantity data set includes: The peak electricity data, flat electricity data and valley electricity data of the electricity data set are increased or decreased according to a first ratio, a second ratio and a third ratio, respectively, to obtain the adjusted electricity data set, wherein the peak electricity data is the electricity data during the peak electricity consumption period in the electricity data set, the flat electricity data is the electricity data during the stable electricity consumption period in the electricity data set, and the valley electricity data is the electricity data during the valley electricity consumption period in the electricity data set.

6. The method according to claim 5, characterized in that The peak-segment electricity data, the flat-segment electricity data, and the valley-segment electricity data of the electricity data set are increased or decreased according to a first ratio, a second ratio, and a third ratio, respectively, to obtain the adjusted electricity data set, including: The first ratio, the second ratio and the third ratio are respectively configured within a preset range, and are increased or decreased with a preset step length to obtain an adjusted first ratio, an adjusted second ratio and an adjusted third ratio; The peak power data, the flat power data and the valley power data are increased or decreased in turn according to the adjusted first ratio, the adjusted second ratio and the adjusted third ratio to obtain the adjusted power data set.

7. The method according to any one of claim 6, characterized in that: Also includes: According to the spot electricity price, the preset spot transaction settlement rules, the target electricity data set and the target electricity price, the calculated parameter values ​​of each transaction unit are obtained respectively.

8. A device for determining a target power data set, characterized in that: include: A data acquisition module is used to acquire a power data set from a power database, and to acquire the spot electricity price of the reference point of the entire network and preset spot transaction settlement rules from a power trading system, wherein the power data set is a collection of power data produced by each trading unit in each first preset time period in a preset reference year; The target electricity data set determination module is used to obtain a target electricity data set and / or its corresponding target electricity price based on the electricity data set, the spot electricity price and the preset spot transaction settlement rules. The target electricity data set is a set of numerical values ​​of the target electricity produced by each trading unit in each second preset time period within the target year.

9. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 7 are implemented.

10. An electronic device, characterized in that: include: a memory having a computer program stored thereon; A processor, configured to execute the computer program in the memory to implement the steps of the method according to any one of claims 1 to 7.

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