Electricity spot market index calculation method and related device

Abstract

The present invention provides a method and a related device for calculating an indicator of a spot electricity market, and relates to the technical field of electric power systems. By obtaining an indicator calculation task, and determining a case package in a preset indicator pool according to the indicator calculation task; obtaining source data corresponding to the case package to perform data aggregation to generate input data; performing calculations according to the input data to generate result data; and performing abnormal situation judgments according to the result data and generating a judgment report. The technical problem of the limitations existing in single-dimensional indicator calculation is solved.

Description

Technical Field

[0001] The present application relates to the technical field of power systems, and in particular to a method for calculating power spot market indicators and related devices. Background Art

[0002] As the operation of the electricity spot market becomes more and more complex, the rapid growth of new energy installed capacity, the tight balance of electricity and electricity, and the excessive market power of some market players have led to a high probability of abnormal clearing risks after market operation, and the previous means of manually judging abnormal information will become more and more complicated. In the face of these complex scenarios, the use of informatization and multi-dimensional indicator calculation methods to quantify market operation and judge abnormal information can greatly reduce the burden of analysis work for market operators and provide strong support for the normal operation of the electricity spot market.

[0003] In the actual operation of the electricity spot market, it is impossible to judge whether a phenomenon is an abnormal situation from a single dimension, and it is often necessary to involve multi-dimensional data analysis. For example, when judging the market power of market entities, if we only stay at the generator unit dimension to analyze the data of each unit, it is usually impossible to judge their behavior in exercising market power. However, if we analyze from the power plant dimension and the power generation group dimension, we can easily find that power plants with a high market share or units under the power generation group exercise market power by collectively bidding high prices, thereby increasing the overall market price and obtaining more profits.

[0004] Therefore, how to solve the limitations of single-dimensional indicator calculations has become a technical problem that needs to be solved urgently. Summary of the invention

[0005] In order to solve the limitations existing in the calculation of single-dimensional indicators, the present application provides a method and related devices for calculating electricity spot market indicators.

[0006] In the first aspect, the present application provides a method for calculating electricity spot market indicators using the following technical solution:

[0007] A method for calculating an electricity spot market index, comprising:

[0008] Obtaining an indicator calculation task, and determining a case package in a preset indicator pool according to the indicator calculation task;

[0009] Obtaining source data corresponding to the case package to perform data aggregation and generate input data;

[0010] Perform calculations based on the input data to generate result data;

[0011] Determine abnormal conditions based on the result data and generate a determination report;

[0012] Wherein, before the step of obtaining the indicator calculation task and determining the case package in the preset indicator pool according to the indicator calculation task, it also includes: defining all indicators related to the power spot market result analysis; generating a preset indicator pool according to all the indicators;

[0013] The step of defining all indicators related to the analysis of the power spot market results includes:

[0014] Define indicator names, define calculation formulas, configure indicator correlations, set multi-dimensional indicator thresholds, and associate data source information;

[0015] The step of obtaining the indicator calculation task and determining the case package in the preset indicator pool according to the indicator calculation task includes:

[0016] Obtain an indicator calculation task, and determine a dimension condition and a date condition in the indicator calculation task;

[0017] Generate a case package traversal condition according to the dimension condition and the date condition;

[0018] The case package is determined by traversing the preset indicator pool according to the case package traversal condition.

[0019] Optionally, the step of obtaining source data corresponding to the case package to aggregate data and generate input data includes:

[0020] Determining the source data information corresponding to the date condition in the case package;

[0021] Aggregating the source data according to the dimensional condition so that the dimensions of all data in the source data information are consistent;

[0022] The currently processed source data information is obtained and filled into the case package to generate input data according to the current case package.

[0023] Optionally, the step of performing calculation according to the input data to generate result data includes:

[0024] Obtain a dimension to be calculated corresponding to each data type in the input data and a calculation index corresponding to each dimension to be calculated;

[0025] Perform calculation on the input data according to the dimension to be calculated and the calculation index to generate result data;

[0026] The calculation dimensions include units, power plants and power generation groups, and the calculation indicators include installed capacity HHI, power generation capacity HHI, installed capacity TOP-4, power generation capacity TOP-4, surplus supply rate RSI, high / low price declaration rate, regulated capacity and entity profit analysis.

[0027] Optionally, the step of determining an abnormal situation based on the result data and generating a determination report includes:

[0028] Obtaining a determination threshold condition in a preset determination rule table, wherein the determination threshold condition includes a positive correlation threshold and a negative correlation threshold;

[0029] In the data result, judging whether there is a positive correlation abnormality according to the positive correlation threshold;

[0030] Determining whether there is a negative correlation abnormality in the data result according to the negative correlation threshold;

[0031] When it is determined that the positive correlation abnormal situation and / or the negative correlation abnormal situation exists, an abnormality determination report is generated.

[0032] In a second aspect, the present application provides a power spot market index calculation system, the power spot market index calculation system comprising:

[0033] A case package module, used to obtain an indicator calculation task and determine a case package in a preset indicator pool according to the indicator calculation task;

[0034] An input data module, used to obtain source data corresponding to the case package to perform data aggregation and generate input data;

[0035] A result data module, used for performing calculations according to the input data to generate result data;

[0036] A determination report module, used to determine abnormal conditions based on the result data and generate a determination report;

[0037] The case package module is also used to define all indicators related to the analysis of the power spot market results; and to generate a preset indicator pool based on all the indicators;

[0038] The case package module is also used to define indicator names, define calculation formulas, configure indicator correlations, set multi-dimensional indicator thresholds and associate data source information;

[0039] The case package module is further used to obtain an indicator calculation task, and determine a dimension condition and a date condition in the indicator calculation task;

[0040] Generate a case package traversal condition according to the dimension condition and the date condition;

[0041] The case package is determined by traversing the preset indicator pool according to the case package traversal condition.

[0042] In a third aspect, the present application provides a computer device, comprising: a memory and a processor, wherein the processor executes the method described above when running computer instructions stored in the memory.

[0043] In a fourth aspect, the present application provides a computer-readable storage medium, comprising instructions, which, when executed on a computer, enable the computer to execute the method described above.

[0044] In summary, the present application includes the following beneficial technical effects:

[0045] This application obtains an indicator calculation task, and determines a case package in a preset indicator pool according to the indicator calculation task; obtains source data corresponding to the case package to generate input data through data aggregation; performs calculation according to the input data to generate result data; and performs abnormal situation judgment according to the result data and generates a judgment report. This solves the technical problem of limitations existing in single-dimensional indicator calculation. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] Figure 1 It is a schematic diagram of the computer device structure of the hardware operating environment involved in the embodiment of the present application;

[0047] Figure 2 It is a flowchart of the first embodiment of the method for calculating the electricity spot market index of the present application;

[0048] Figure 3 This is a module relationship diagram of the first embodiment of the power spot market index calculation method of the present application;

[0049] Figure 4 This is a structural relationship diagram of an indicator pool table of the first embodiment of the power spot market indicator calculation method of the present application;

[0050] Figure 5 This is a flowchart of creating indicators for the first embodiment of the method for calculating indicators in the electricity spot market of the present application;

[0051] Figure 6 This is a flowchart of the indicator calculation of the first embodiment of the power spot market indicator calculation method of the present application;

[0052] Figure 7 This is a data aggregation logic diagram of the first embodiment of the power spot market index calculation method of the present application, wherein: Figure 7 (a) is a logical diagram of low-dimensional convergence to high-dimensional. Figure 7 (b) is a logical diagram of the convergence of high dimensions to low dimensions;

[0053] Figure 8 It is a structural block diagram of the first embodiment of the power spot market index calculation system of the present application. DETAILED DESCRIPTION

[0054] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below through the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0055] Reference Figure 1 , Figure 1 A schematic diagram of the computer device structure of the hardware operating environment involved in the embodiment of the present application.

[0056] like Figure 1 As shown, the computer device may include: a processor 1001, such as a central processing unit (CPU), a communication bus 1002, a user interface 1003, a network interface 1004, and a memory 1005. Among them, the communication bus 1002 is used to realize the connection and communication between these components. The user interface 1003 may include a display screen (Display), an input unit such as a keyboard (Keyboard), and the optional user interface 1003 may also include a standard wired interface and a wireless interface. The network interface 1004 may optionally include a standard wired interface and a wireless interface (such as a wireless fidelity (Wireless-Fidelity, Wi-Fi) interface). The memory 1005 may be a high-speed random access memory (Random Access Memory, RAM), or a stable non-volatile memory (Non-Volatile Memory, NVM), such as a disk storage. The memory 1005 may also be a storage device independent of the aforementioned processor 1001.

[0057] Those skilled in the art will understand that Figure 1 The structure shown in the figure does not constitute a limitation on the computer device, and may include more or less components than shown in the figure, or combine certain components, or arrange the components differently.

[0058] like Figure 1 As shown, the memory 1005 as a storage medium may include an operating system, a network communication module, a user interface module, and a power spot market index calculation program.

[0059] exist Figure 1In the computer device shown, the network interface 1004 is mainly used for data communication with the network server; the user interface 1003 is mainly used for data interaction with the user; the processor 1001 and the memory 1005 in the present application can be set in the computer device, and the computer device calls the electricity spot market index calculation program stored in the memory 1005 through the processor 1001, and executes the electricity spot market index calculation method provided in the embodiment of the present application.

[0060] The present application embodiment provides a method for calculating power spot market indicators, referring to Figure 2 , Figure 2 This is a flow chart of the first embodiment of the method for calculating electricity spot market indicators of the present application.

[0061] In this embodiment, the method for calculating the electricity spot market index includes the following steps:

[0062] Step S10: Obtain an indicator calculation task, and determine a case package in a preset indicator pool according to the indicator calculation task.

[0063] It should be noted that before obtaining the indicator calculation task and determining the case package in the preset indicator pool according to the indicator calculation task, it also includes: defining all indicators related to the power spot market result analysis; and generating a preset indicator pool according to all indicators.

[0064] It can be understood that the steps of defining all indicators related to the analysis of electricity spot market results include: defining indicator names, defining calculation formulas, configuring indicator correlations, setting multi-dimensional indicator thresholds and associating data source information.

[0065] In a specific implementation, the steps of obtaining an indicator calculation task and determining a case package in a preset indicator pool according to the indicator calculation task include: obtaining the indicator calculation task, determining dimension conditions and date conditions in the indicator calculation task; generating case package traversal conditions according to the dimension conditions and date conditions; and traversing the preset indicator pool according to the case package traversal conditions to determine the case package.

[0066] It should be noted that in order to define the calculation indicators of the power spot market results, and configure the indicators, the dimensions, thresholds, correlations, data sources and other information can be analyzed, and an indicator pool can be formed. The indicator pool includes all indicator data sets involved in the calculation in this embodiment, including key information such as indicator definition and indicator configuration, among which the indicator configuration is used as the default value and can support dynamic adjustment in subsequent case calculations.

[0067] It can be understood that in order to select a certain day as the calculation date, select the indicator set to be calculated from the indicator pool, specify one or more calculation dimensions of the selected indicator, and create a case package. The case package is the data set required for the indicator calculation on a specific day, including the indicator set, indicator dimension data, input data, calculation result data, and indicator abnormal data. This step will create a case package based on the analysis date and indicator set, and the subsequent steps will fill the corresponding data in the case package.

[0068] Step S20: Acquire source data corresponding to the case package to perform data aggregation to generate input data.

[0069] In a specific implementation, the step of obtaining source data corresponding to a case package for data aggregation to generate input data includes: determining the source data information corresponding to the date condition in the case package; aggregating the source data according to the dimension condition to keep the dimensions of all data in the source data information consistent; obtaining the currently processed source data information and filling it into the case package to generate input data according to the current case package.

[0070] It should be noted that in order to load the specific data source for a certain day required for the calculation of the indicators in the case package, the data source data is aggregated according to the selected dimension to form the input data of the case package. This step is mainly for data organization and data aggregation, and the data source is aggregated into consistent calculation dimensions. The logic of aggregation is divided into two types: high dimension to low dimension and low dimension to high dimension. Aggregation from high dimension to low dimension means splitting the data of the power generation group / power plant into power plants / units according to a certain ratio, and aggregation from low dimension to high dimension means aggregating the data of units / power plants into power plant / power generation group data.

[0071] In the specific implementation, given that there are multiple indicators in the case package, a parallel asynchronous approach will be adopted.

[0072] Step S30: Perform calculations based on the input data to generate result data.

[0073] In a specific implementation, the step of performing calculations based on input data to generate result data includes: obtaining the dimensions to be calculated corresponding to each data type in the input data and the calculation indicators corresponding to each dimension to be calculated; performing calculations in the input data according to the dimensions to be calculated and the calculation indicators to generate result data; the calculation dimensions include units, power plants and power generation groups, and the calculation indicators include installed capacity HHI, power generation capacity HHI, installed capacity TOP-4, power generation capacity TOP-4, surplus supply rate RSI, high / low price reporting rate, regulated capacity and entity benefit analysis.

[0074] Step S40: Make an abnormal situation judgment based on the result data and generate a judgment report.

[0075] In a specific implementation, the steps of judging abnormal situations based on the result data and generating a judgment report include: obtaining judgment threshold conditions in a preset judgment rule table, the judgment threshold conditions including a positive correlation threshold and a negative correlation threshold; judging whether there is a positive correlation abnormal situation in the data results based on the positive correlation threshold; judging whether there is a negative correlation abnormal situation in the data results based on the negative correlation threshold; and generating an abnormal judgment report when it is judged that there is a positive correlation abnormal situation and / or a negative correlation abnormal situation.

[0076] It should be noted that the overall calculation process design of a multi-dimensional electricity spot market index calculation method provided in this embodiment includes:

[0077] Define the calculation indicators of the power spot market results, and configure the indicator analysis dimensions, thresholds, correlations, data sources and other information to form an indicator pool;

[0078] Select a day as the calculation date, select the indicator set to be calculated from the indicator pool, specify one or more calculation dimensions of the selected indicator, and create a case package. The calculation dimension is one or more of the generator set, power plant or power generation group, which can be less than but not more than the analyzable dimensions configured in the indicator pool;

[0079] Load the specific data source for a certain day required for the indicator calculation in the case package, and aggregate the data source data according to the selected dimension to form the input data of the case package;

[0080] Based on the case package input data, calculations are performed according to the formula defined by the indicator to obtain calculation results of multiple dimensions of an indicator, forming the result data of the case package;

[0081] Based on the multi-dimensional calculation result data of the indicators in the case package, combined with the threshold and correlation configuration, the abnormal situation of the case package is further analyzed.

[0082] In the specific implementation, Figure 3 As shown, this embodiment also includes two modules: indicator pool and case management.

[0083] The indicator pool module is used to manage indicators of multi-dimensional calculations, which can be divided into the following small modules:

[0084] The indicator definition module is used to describe the expression of indicator content and calculation process. The calculation result can be used to measure the severity of a specific situation.

[0085] The analysis dimension management module is used to set indicators that can be used for calculations in the generator set dimension, power plant dimension, or power generation group dimension.

[0086] The indicator threshold management module is used to set the default value of the indicator threshold. It is an important management module for measuring whether there is abnormal information in the calculation result of the indicator.

[0087] The correlation management module is used to set the correlation attribute of indicators. Correlation is an important basis for judging whether the result is abnormal in combination with the indicator threshold. When it is positively correlated, the indicator calculation result is greater than the indicator threshold, which is an abnormal situation; when it is negatively correlated, the indicator calculation result is less than the indicator threshold, which is an abnormal situation.

[0088] The data source management module is used to manage the data source associated with each indicator. The data source is the power spot market business data set required to calculate the formula.

[0089] The case management module is used to manage case data, including input data assembly, indicator calculation and result data analysis, which can be divided into the following small modules:

[0090] The data loading module loads the data sources involved in the indicator calculation into the context according to the case date, which is used for subsequent data aggregation and indicator calculation steps.

[0091] The data aggregation module is used to convert the case input data according to the dimensions selected by the case. The conversion methods include four types: from generator set to power plant, from power plant to power generation group, from power generation group to generator set, and from power plant to generator set. The conversion logic includes accumulation and allocation according to installed capacity.

[0092] The data assembly module is used to classify and fill the aggregated data into the case package context, and finally form the case input data for use in subsequent calculation steps.

[0093] The indicator calculation module performs calculations based on the indicator formula definitions in the case package and the selected calculation dimensions. The number of calculations for the same indicator is consistent with the number of dimensions selected for the indicator. For example, if a certain indicator selects the calculation dimensions of power plants and power generation groups, it is necessary to calculate according to the formula definition using the data of the power plants and power generation groups respectively.

[0094] The calculation result storage module is used to group and store the indicator calculation results, and set the result data into the context of the case package, ultimately forming multi-dimensional result data of the case package for use in subsequent indicator calculation steps.

[0095] The abnormality judgment module combines the configuration of indicator thresholds and correlations in the case package to determine whether there are abnormalities in the results of each dimension of each indicator.

[0096] The abnormal analysis module is used to display the abnormal conditions of each dimension of the indicator, providing important data support for analyzing the overall abnormal information of the market and avoiding market operation risks.

[0097] It is understandable that in order to realize the function of the indicator pool to manage indicators, the table structure of the indicator pool module in this embodiment is designed as follows:

[0098] (Table 1) Index definition table (INDEX_DEFINTION)

[0099]

[0100] (Table 2) Index calculation dimension information table (INDEX_DIMENSION_INFO)

[0101]

[0102] (Table 3) Index threshold configuration table (INDEX_THRESHOLD_INFO)

[0103]

[0104] (Table 4) Index correlation table (INDEX_THRESHOLD_INFO)

[0105]

[0106] (Table 5) Index data source association table (INDEX_DATASOURCE_RELATION)

[0107]

[0108] The table structure relationship of the indicator pool module is as follows Figure 4 As shown: (Table 1) indicator definition table and (Table 2) indicator calculation dimension information table, (Table 3) indicator threshold configuration table, (Table 4) indicator data source association table are all one-to-many relationships, and one-to-one relationships with the indicator correlation table. All table structures are associated based on the indicator ID.

[0109] Furthermore, in the indicator pool module, the process of creating a new indicator is as follows: Figure 5 As shown, in order to describe the process more clearly, the following will take the commonly used installed capacity HHI (Herfindahl Index, a common indicator for users to measure the concentration of power generation) in the electricity spot market as an example to explain its process:

[0110] Create a new indicator, including defining the indicator ID and indicator name information, and store the data in the indicator definition table (Table 6):

[0111] (Table 6)

[0112]

[0113] Define the indicator calculation formula, describe the specific calculation process of the indicator, and update the formula data to the indicator formula field of the indicator definition table (Table 7):

[0114] (Table 7)

[0115]

[0116] Configure the analyzable dimensions of the indicator, select one or more calculation dimensions in the generator set, power plant or power generation group, and save the data in the indicator calculation dimension information table (Table 8);

[0117] (Table 8)

[0118]

[0119] Configure indicator thresholds for each dimension, describe the critical values ​​of normal and abnormal indicator results, and save the data in the indicator threshold configuration table (Table 9);

[0120] (Table 9)

[0121]

[0122] Set the indicator correlation, select positive correlation or negative correlation, and save the data to the indicator correlation table (Table 10);

[0123] (Table 10)

[0124]

[0125] Configure the data source involved in the indicator calculation, and specify its data source query conditions and calculation fields. The information is saved in the indicator data source association table (Table 11):

[0126] (Table 11)

[0127]

[0128] Based on the calculation indicators defined in the indicator pool, the indicator calculation process of this embodiment is as follows: Figure 6 In order to explain the indicator calculation process more clearly, we will also take the above-mentioned installed capacity HHI indicator as an example to specifically introduce the key calculation process of installed capacity HHI:

[0129] First, select a certain day (for example, December 1, 2023) as the calculation date, select installed capacity HHI as the calculation indicator in the indicator pool, select generator units, power plants, and power generation groups as their calculation dimensions, and create a case package.

[0130] Then, according to the data in the indicator data source association table, the data is loaded according to the date in the case package. The corresponding data source SQL for the installed HHI is: SELECT UNIIT_ID, PLANT_ID, CORP_ID, CAPATITY FROM CPMM_UNIT_INFO WHERE DATA = '20231201'. The query results are as follows (Table 12):

[0131] (Table 12)

[0132]

[0133] Secondly, according to the calculation dimension of the installed capacity HHI indicator in the case, the case input data are aggregated separately to form the installed capacity of the generator set, power plant and power generation group, and assembled into the input data of the case. The final aggregation results are shown in the following table (Table 13):

[0134] (Table 13)

[0135]

[0136] Next, according to the indicator's formula definition and case input data, multiple dimensions of the indicator are calculated respectively. According to the calculation formula:

[0137]

[0138] It can be seen that S i The total installed capacity can be calculated as 2800MW by combining the case input data. The installed capacity HHI calculations of the three calculation dimensions are as follows:

[0139] Generator assembly machine

[0140]

[0141] Power plant installed capacity

[0142]

[0143] Power Generation Group Installed Capacity

[0144]

[0145] Finally, the abnormality of the indicator calculation results is judged according to the thresholds and correlations of the multi-dimensional indicators, and then the abnormal information is comprehensively analyzed. From the definition of the installed capacity HHI indicator above, it can be seen that the indicator is positively correlated, and the thresholds of the generator set, power plant and power generation group dimensions are 1500, 2000 and 3000 respectively. Further combined with the calculation results of each dimension, it can be obtained:

[0146] The HHI calculation result of the generator assembly unit is 1173, which is less than the threshold of 1500. There is no abnormality, indicating that the competition is relatively sufficient;

[0147] The calculated HHI of power plant installed capacity is 2168, which is greater than its threshold of 2000. There is an abnormal situation, but the margin of exceeding the threshold is small, indicating that there are large-scale power plants, but the overall degree of competition is high;

[0148] The HHI calculation result of the power generation group is 3469, which is greater than its threshold of 3000. There is an abnormal situation, and the margin of excess over the threshold is large, indicating that the market is highly concentrated and overall competition is weak.

[0149] Analyzing the above-mentioned multi-dimensional abnormal situations, we can learn that during the operation of the electricity spot market, there is a risk that power plants and power generation groups will exercise market power and thus manipulate the overall market price.

[0150] Furthermore, the data source aggregation logic involved in the above calculation process is as follows Figure 7 As shown, there are two types of aggregation logic involved in this embodiment, namely, low-dimensional aggregation to high-dimensional aggregation and high-dimensional aggregation to low-dimensional aggregation, which are specifically described as follows:

[0151] The convergence of low dimensions to high dimensions is like Figure 7 As shown in (a), there are two types of convergence: from generator sets to power plants and from power plants to power generation group dimensions. The convergence method of these two types is accumulation, that is, the values ​​of all low dimensions under the high dimension are added together to finally obtain the high-dimensional value. Taking installed capacity as an example, power plant 1 includes three units, generator set 1, generator set 2 and generator set 3, with installed capacities of P1, P2 and P3 respectively. Then the installed capacity of power plant 1 is P1+P2+P3. The logic of convergence of power plants to power generation group dimensions is the same.

[0152] Higher dimensions converge to lower dimensions Figure 7 As shown in (b), there are also two types of aggregation: the power generation group converges to the power generation unit and the power plant converges to the power generation group. The two types of aggregation are allocated according to the installed capacity, that is, the high-dimensional value is allocated according to the proportion of the installed capacity in the low dimension. Taking the regulated capacity of the power generation group as an example, the regulated capacity of the power generation group 1 is P, and the installed capacities of its three power generation units are C1, C2 and C3 respectively. Then the regulated capacities of these three power generation units are , and The same logic applies to power plants converging to generating units.

[0153] In order to implement this embodiment, the facade design pattern is adopted in the code design. According to the division of business, three facade service classes are designed, namely the index configuration facade service class (IndexFacadeService), the case data facade service class (CaseDataFacadeService) and the calculator facade service class (CalculateFacadeService). The method definitions are as follows:

[0154] Indicator configuration facade service class:

[0155] void createIndex(IndexDTO index);

[0156] Create a new indicator method.

[0157] IndexDTO getIndexInfoByCode(String indexCode);

[0158] Methods for obtaining information such as metric thresholds and correlations.

[0159] Case data facade service class:

[0160] List <data>loadDataSource(Date date,List <string>indexCodeList);

[0161] Load data by date and indicator code.

[0162] List <data>handleDataSource(List <data>list, Integer dimension);

[0163] Aggregate data sources based on target dimensions.

[0164] Boolean judgeException(BigDecimal value,IndexDTO index);

[0165] Determine whether the indicator calculation results are abnormal.

[0166] void saveIndexResult(IndexResultDTO result);

[0167] The indicator results are saved in the database.

[0168] Calculator facade service category:

[0169] List <indexresultdto>calculate(List <data>list, IndexDTO index);

[0170] Executes indicator calculation and returns the calculation result.

[0171] This embodiment obtains the indicator calculation task, and determines the case package in the preset indicator pool according to the indicator calculation task; obtains the source data corresponding to the case package to generate input data through data aggregation; performs calculation according to the input data to generate result data; and judges the abnormal situation according to the result data and generates a judgment report. This solves the technical problem of limitations existing in single-dimensional indicator calculation.

[0172] In addition, an embodiment of the present application also proposes a computer-readable storage medium, on which a program for calculating electricity spot market indicators is stored. When the program for calculating electricity spot market indicators is executed by a processor, the steps of the method for calculating electricity spot market indicators as described above are implemented.

[0173] Reference Figure 8 , Figure 8 This is a structural block diagram of the first embodiment of the power spot market index calculation system of the present application.

[0174] like Figure 8 As shown, the power spot market index calculation system proposed in the embodiment of the present application includes:

[0175] The case package module 10 is used to obtain the indicator calculation task and determine the case package in the preset indicator pool according to the indicator calculation task;

[0176] An input data module 20 is used to obtain source data corresponding to the case package to perform data aggregation and generate input data;

[0177] A result data module 30, used for performing calculations based on input data to generate result data;

[0178] The determination and reporting module 40 is used to determine abnormal situations based on the result data and generate a determination report.

[0179] It should be understood that the above is only an example and does not constitute any limitation on the technical solution of the present application. In specific applications, technicians in this field can make settings as needed, and the present application does not impose any limitation on this.

[0180] This embodiment obtains the indicator calculation task, and determines the case package in the preset indicator pool according to the indicator calculation task; obtains the source data corresponding to the case package to generate input data through data aggregation; performs calculation according to the input data to generate result data; and judges the abnormal situation according to the result data and generates a judgment report. This solves the technical problem of limitations existing in single-dimensional indicator calculation.

[0181] It should be noted that the workflow described above is merely illustrative and does not limit the scope of protection of the present application. In practical applications, technicians in this field can select part or all of it according to actual needs to achieve the purpose of the present embodiment, and no limitation is made here.

[0182] In addition, for technical details not described in detail in this embodiment, please refer to the method for calculating electricity spot market indicators provided in any embodiment of the present application, which will not be repeated here.

[0183] In addition, it should be noted that, in this article, the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, article or system including a series of elements includes not only those elements, but also includes other elements not explicitly listed, or also includes elements inherent to such process, method, article or system. In the absence of further restrictions, an element defined by the sentence "includes a ..." does not exclude the existence of other identical elements in the process, method, article or system including the element.

[0184] The serial numbers of the above-mentioned embodiments of the present application are for description only and do not represent the advantages or disadvantages of the embodiments.

[0185] Through the description of the above implementation methods, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus a necessary general hardware platform, and of course by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present application, or the part that contributes to the prior art, can be embodied in the form of a software product, which is stored in a storage medium (such as a read-only memory (ROM) / RAM, a magnetic disk, or an optical disk), and includes a number of instructions for a terminal device (which can be a mobile phone, a computer, a server, or a network device, etc.) to execute the methods of each embodiment of the present application.

[0186] The above are only preferred embodiments of the present application, and the scope of the present application is not limited thereto. Any equivalent structure or equivalent process transformation made using the contents of the present application specification and drawings, or directly or indirectly applied in other related technical fields, are also included in the protection scope of the present application.< / data> < / indexresultdto> < / data> < / data> < / string> < / data>

Claims

1. A method for calculating electricity spot market indicators, characterized in that: include: Define all indicators related to the analysis of electricity spot market results, including: Define indicator names, define indicator calculation formulas, configure indicator correlations, set multi-dimensional indicator thresholds and indicator calculation-related data source information; By configuring indicators, you can analyze dimensions, indicator thresholds, indicator correlations, and indicator calculation-related data source information to form a preset indicator pool; Obtain an indicator calculation task, select a certain day as the calculation date, select an indicator set to be calculated from the preset indicator pool, and specify multiple calculation dimensions of the selected indicators to create a case package; The case package is a data set required for the calculation of indicators on a specific day, including a set of indicator sets, indicator dimension data, input data, calculation result data, and indicator abnormal data; Loading the indicator calculation associated data source corresponding to a certain day required for the indicator calculation in the case package, and filling the indicator calculation associated data source into the case package according to the selected indicator dimension data to form the input data of the case package; Based on the input data of the case package, calculation is performed according to the indicator calculation formula to obtain calculation results of multiple dimensions of each indicator in the indicator set to be calculated, forming calculation result data of the case package; Based on the multi-dimensional calculation result data of the indicators in the case package, the abnormal situation of the case package is analyzed in combination with the indicator threshold and the indicator correlation.

2. The method for calculating electricity spot market indicators according to claim 1, characterized in that: The method further comprises: Determine the data source corresponding to the date condition in the case package; The data sources are aggregated according to dimensional conditions to keep the dimensions of all data in the data sources consistent.

3. The method for calculating electricity spot market indicators according to claim 1, characterized in that: The method comprises: The calculation dimensions include units, power plants and power generation groups, and the calculation indicators include installed capacity HHI, power generation capacity HHI, installed capacity TOP-4, power generation capacity TOP-4, surplus supply rate RSI, high / low price declaration rate, regulated capacity and entity profit analysis.

4. The method for calculating electricity spot market indicators according to claim 1, characterized in that: The step of analyzing the abnormal situation of the case package based on the multi-dimensional calculation result data of the indicators in the case package in combination with the indicator threshold and the indicator correlation includes: Obtaining a determination threshold condition in a preset determination rule table, wherein the determination threshold condition includes a positive correlation threshold and a negative correlation threshold; Determining whether there is a positive correlation abnormality in the result data according to the positive correlation threshold; Determining whether there is a negative correlation abnormality in the result data according to the negative correlation threshold; When it is determined that the positive correlation abnormal situation and / or the negative correlation abnormal situation exists, an abnormality determination report is generated.

5. A power spot market index calculation system, characterized in that: Execute the method as claimed in claim 1.

6. A computer device, characterized in that: The device comprises: a memory and a processor, wherein the processor executes the method according to any one of claims 1 to 4 when running computer instructions stored in the memory.

7. A computer-readable storage medium, characterized in that: The method comprises instructions, which, when executed on a computer, cause the computer to execute the method according to any one of claims 1 to 4.

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