Electric power spot market operation risk monitoring and early warning method

Abstract

The invention discloses an electric power spot market operation risk monitoring and early warning method, and the method comprises the steps: carrying out the data collection of an electric power spot market, and obtaining the electric power spot data; performing data preprocessing on the electric power spot data to obtain preprocessed data; performing data verification on the preprocessed data to obtain target data; and carrying out electric power spot market operation risk monitoring and early warning according to the target data. Risk assessment and early warning are carried out on the electric power spot transaction, the accuracy and rapidity of system security check are improved, and the security and accuracy of the electric power spot transaction are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of monitoring and early warning, and in particular to a method for monitoring and early warning of operational risks in a power spot market. Background Art

[0002] Electricity spot trading refers to a form of transaction in which electricity producers, consumers and internal institutions can conduct real-time transactions in the electricity market. This trading method allows participants to conduct real-time transactions between actual electricity demand and supply. Therefore, energy and electricity spot trading is usually conducted through the electricity market platform, where the responder and seller can submit transaction orders and trade according to market prices and rules. In the existing technology, there is a lack of risk assessment and early warning of electricity spot trading during the operation of the electricity spot market, which makes it difficult to verify the safety of the system, and it is also impossible to conduct transactions safely and accurately. Summary of the invention

[0003] The present invention aims to solve at least one of the technical problems in the above-mentioned technology to a certain extent. To this end, the purpose of the present invention is to propose a method for monitoring and early warning of operational risks in the power spot market, to conduct risk assessment and early warning for power spot transactions, to improve the accuracy and rapidity of system safety verification, and to improve the safety and accuracy of power spot transactions.

[0004] To achieve the above objectives, an embodiment of the present invention proposes a method for monitoring and early warning of power spot market operation risks, including: Collect data from the electricity spot market to obtain electricity spot data; Preprocessing the electricity spot data to obtain preprocessed data; Perform data verification on the preprocessed data to obtain the target data; Conduct electricity spot market operational risk monitoring and early warning based on target data.

[0005] According to some embodiments of the present invention, data collection is performed on the electricity spot market to obtain electricity spot data, including: The operation data of the electricity spot market is captured based on the data acquisition interface during a preset monitoring period, the captured data is identified based on the operation characteristics, different types of operation orders are distinguished, and a classified set is obtained as the electricity spot data; wherein the operation characteristics include operation time, operation power, operation unit price, operation system load data, unit operation quotation data and section limit data.

[0006] According to some embodiments of the present invention, data preprocessing is performed on power spot data to obtain preprocessed data, including: Clean the electricity spot data to obtain cleaned data; The cleaned data is formatted according to data standards to obtain preprocessed data.

[0007] According to some embodiments of the present invention, performing data verification on preprocessed data to obtain target data includes: Establish a calibration database for the electricity spot market; Define data verification tasks based on preprocessed data and verification database; each data verification task has a corresponding verification data set, verification rules, and a processing method for verification results; Generate a data verification task list based on several data verification tasks; Perform data verification according to the data verification task list to obtain the target data.

[0008] According to some embodiments of the present invention, establishing a verification database for a power spot market includes: Collect relevant requirements for data verification from relevant laws, policies, standards and market operation rules of the power spot market, organize the relevant requirements, and obtain a verification rule set, including data format verification rules, data range verification rules and data logical relationship verification rules; Classifying the verification rule set to obtain classified data; the classified data includes basic data verification, business logic verification and compliance verification; Encode each rule in the classification data to obtain encoded data; Store the coded data into the database and build a verification database.

[0009] According to some embodiments of the present invention, performing data verification according to the data verification task list to obtain target data includes: Based on the hardware resources of the monitoring and early warning system and the scale of the data verification tasks in the data verification task list, a data verification task thread pool is constructed; Allocate the data verification tasks in the data verification task list to threads in the data verification task thread pool based on the load balancing strategy; Each thread calls the data verification engine to verify the pre-processed data corresponding to the specified data verification task according to the verification rules; The threads in the data verification task thread pool execute data verification tasks in parallel and return the verification results to the main thread. The main thread summarizes and analyzes the verification results, generates a verification report, and obtains the target data based on the verification report.

[0010] According to some embodiments of the present invention, each thread calls a data verification engine to verify the pre-processed data corresponding to the specified data verification task according to the verification rule, including: When verifying the operating system load data in the preprocessed data, check the integrity of the operating system load data, whether the change amplitude of the load adjacent points exceeds the set threshold, whether the operating system load forecast is greater than the total bus load after deducting the power supply plan, and whether the deviation percentage between the system load and the total bus load is within the set range; When verifying the unit operation quotation data in the pre-processed data, check whether the unit operation quotation range is within the maximum and minimum technical output range of the unit, whether the unit segment quotation is within the set upper and lower limits, whether the unit quotation segment number is within the set maximum quotation segment number, whether the unit start-up and shutdown costs are complete, and whether the start-up and shutdown costs are within the set upper and lower limits; When verifying the section limit data in the preprocessing data, the section positive limit is non-negative, the section reverse limit is non-positive, and the absolute values ​​of the section positive and reverse limits are verified to be within the set threshold range.

[0011] According to some embodiments of the present invention, the power spot market operation risk monitoring and early warning are performed according to the target data, including: Set risk indicators and build a risk assessment system based on risk indicators; Evaluate the target data according to the risk assessment system to obtain the risk assessment results; Conduct electricity spot market operation risk monitoring and early warning based on risk assessment results.

[0012] According to some embodiments of the present invention, the further comprising: According to the risk assessment results, query the preset risk assessment results-treatment measures data table to determine the target treatment measures; The corresponding control command signal is generated according to the target processing measures and transmitted to the control module of the power spot market.

[0013] According to some embodiments of the present invention, the further comprising: Before transmitting the control command signal to the control module of the power spot market, calculating the transmission reliability value of the control command signal, and transmitting the signal when it is determined that the transmission reliability value is greater than a preset threshold; Calculate the transmission reliability value of the control command signal, including: Calculate the amplitude characteristic value of the control command signal : in, To control the power of the effective signal in the command signal; To control the power of noise in the command signal; is the number of signal nodes in the control command signal; For the The energy at each signal node; is the average energy of the signal node; According to the amplitude characteristic value of the control command signal , calculate the transmission reliability value of the control command signal : in, is the variance of the noise in each signal node; is the estimated transmission time of the control command signal; To control the vibration frequency of the effective signal in the command signal; It is the vibration frequency of the noise in the control command signal.

[0014] The present invention proposes a method for monitoring and early warning of the operation risk of the power spot market. Through the four steps of data collection, preprocessing, verification and monitoring and early warning, the comprehensive monitoring and early warning of the operation risk of the power spot market is realized, and the accuracy and reliability of the data, as well as the effectiveness of risk monitoring and early warning are ensured. Risk assessment and early warning are carried out for power spot transactions, the accuracy and rapidity of system security verification are improved, and the security and accuracy of power spot transactions are improved.

[0015] Other features and advantages of the present invention will be described in the following description, and partly become apparent from the description, or understood by practicing the present invention. The purpose and other advantages of the present invention can be realized and obtained by the structures particularly pointed out in the written description and the accompanying drawings.

[0016] The technical solution of the present invention is further described in detail below through the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings: Figure 1 is a block diagram of a method for monitoring and early warning of power spot market operation risks according to an embodiment of the present invention; Figure 2 is a flow chart of obtaining preprocessed data according to one embodiment of the present invention; Figure 3 is a flowchart of obtaining target data according to an embodiment of the present invention. DETAILED DESCRIPTION

[0018] The preferred embodiments of the present invention are described below in conjunction with the accompanying drawings. It should be understood that the preferred embodiments described herein are only used to illustrate and explain the present invention, and are not used to limit the present invention.

[0019] like Figure 1 As shown, the embodiment of the present invention proposes a method for monitoring and early warning of power spot market operation risks, including steps S1-S4: S1. Collect data from the electricity spot market to obtain electricity spot data; S2. Preprocess the electricity spot data to obtain preprocessed data; S3, perform data verification on the preprocessed data to obtain target data; S4. Monitor and warn of electricity spot market operation risks based on target data.

[0020] The working principle of the above technical solution is as follows: set up a data acquisition interface, connect with the relevant systems of the power spot market, determine the time interval and scope of data acquisition, and ensure the comprehensiveness and timeliness of the data. Obtain data from the power trading system, the monitoring system of the power production enterprise, the power grid dispatching center, etc. Perform data preprocessing on the power spot data to obtain preprocessed data, including data cleaning and data standardization. Use data cleaning tools or write scripts to preprocess the data to improve the data quality. Perform data verification on the preprocessed data to obtain the target data, write data verification rules, and verify the data one by one. For data that fails the verification, mark or correct it to ensure the accuracy and reliability of the data. Data verification includes data integrity verification, data consistency verification, etc. Continuously monitor the operation data of the power spot market and detect abnormal situations in time. When abnormal situations are found, issue early warning signals in time so that relevant personnel can take countermeasures.

[0021] The beneficial effects of the above technical solution are as follows: through the four steps of data collection, preprocessing, verification and monitoring and early warning, comprehensive monitoring and early warning of the operational risks of the power spot market are achieved, ensuring the accuracy and reliability of the data, as well as the effectiveness of risk monitoring and early warning. Risk assessment and early warning of power spot transactions are carried out to improve the accuracy and speed of system safety verification, and improve the safety and accuracy of power spot transactions.

[0022] According to some embodiments of the present invention, data collection is performed on the electricity spot market to obtain electricity spot data, including: The operation data of the electricity spot market is captured based on the data acquisition interface during a preset monitoring period, the captured data is identified based on the operation characteristics, different types of operation orders are distinguished, and a classified set is obtained as the electricity spot data; wherein the operation characteristics include operation time, operation power, operation unit price, operation system load data, unit operation quotation data and section limit data.

[0023] The working principle of the above technical solution: The preset monitoring period is to determine the time range for data collection, such as a specific time period every day, week or month. This period matches the operating cycle of the electricity spot market in order to capture the complete operation of the market. In the captured data, different types of data are distinguished according to specific operating characteristics. These operating characteristics include operating time (such as the specific time when the transaction occurs), operating power (such as the amount of power traded), operating unit price (such as the transaction price of electricity), operating system load data (such as the real-time load situation of the power grid), unit operation quota data (such as quotation information of power plants) and section limit data (such as the transmission capacity limit of the power grid). According to the operating characteristics, the captured data is further classified into different types of operating orders. These orders include power trading orders, power production plan orders, power grid dispatching instructions, etc.

[0024] The beneficial effects of the above technical solution are: by capturing the operational data of the electricity spot market based on the data acquisition interface within a preset monitoring period, the accuracy and comprehensiveness of data acquisition are improved, the required operational data is effectively collected from the electricity spot market, and data classification is performed at the same time to obtain a classification set as electricity spot data.

[0025] like Figure 2 As shown, according to some embodiments of the present invention, data preprocessing is performed on the power spot data to obtain preprocessed data, including steps S21-S22: S21, cleaning the electricity spot data to obtain cleaned data; S22, formatting the cleaned data according to data standards to obtain pre-processed data.

[0026] Working principle of the above technical solution: Identify and handle missing values: Check whether there are missing values ​​(such as empty values, NULL values, etc.) in the data. According to the actual situation, fill (such as using mean, median, mode, etc.), interpolation (such as linear interpolation, polynomial interpolation, etc.) or deletion methods are used to handle missing values. Identify and handle outliers: Identify outliers in the data through statistical methods (such as box plots, Z scores, etc.) or business rules. Correct outliers (such as replacing them with reasonable values), delete or retain (if outliers have business significance). Remove duplicate data: Check whether there are duplicate records in the data. Remove duplicate records to ensure the uniqueness of the data. Handle data inconsistency: Check whether the field values ​​in the data are consistent (such as date format, unit, etc.). Convert or correct inconsistent data to ensure data consistency. Data cleaning is carried out to remove noise, outliers and missing values ​​in power spot data to ensure the accuracy and completeness of the data.

[0027] Unify data types: Ensure that the data type of each field is consistent with the expected data type (such as integer, floating point number, string, etc.). Convert fields with inconsistent data types. Unify data formats: Format date, time, number and other fields. For example, format the date field as "YYYY-MM-DD", format the time field as "HH:MM:SS", and format the number field to the specified number of decimal places. Standardize field naming: Name the fields using unified naming rules. Avoid using special characters, spaces, or abbreviations and other non-standard naming methods. Standardize data units: Ensure that the units in the data are unified and meet business requirements. Convert data with inconsistent units. Create a data dictionary: Create a data dictionary for each field in the data set to explain the meaning, data type, format, value range and other information of the field. The purpose of data standard formatting is to convert the cleaned data into a unified and standardized format to facilitate subsequent data analysis and processing.

[0028] The beneficial effects of the above technical solution are: effective preprocessing of electricity spot data to obtain high-quality, standardized preprocessed data.

[0029] like Figure 3 As shown, according to some embodiments of the present invention, data verification is performed on the preprocessed data to obtain target data, including steps S31-34: S31. Establishing a verification database for the electricity spot market; S32. Define data verification tasks based on the preprocessed data and the verification database; each data verification task has a corresponding verification data set, verification rules, and a processing method for the verification results; S33, generating a data verification task list according to a number of data verification tasks; S34. Perform data verification according to the data verification task list to obtain target data.

[0030] The working principle of the above technical solution is as follows: Establish a verification database containing data standards, rules, historical data and business logic related to the power spot market. Determine the verification data set: Select the data set to be verified from the preprocessed data. Formulate verification rules: Formulate specific verification rules according to the data standards and rules in the verification database. These rules include value range verification, data type verification, data format verification, business logic verification, etc. Define the processing method of the verification result: For each verification task, define the processing method of the verification result. For example, if the data does not meet the verification rules, you can choose to mark it as an error, correct the data, or delete the data. According to several data verification tasks, generate a data verification task list, including: Create a task list: Create a data verification task list in the system. Add tasks: Add each defined data verification task to the task list. Set priority and order: Set the priority and verification order for the tasks in the task list as needed. Based on the task list, batch verification is performed. According to the task order in the data verification task list, batch verification is performed on the preprocessed data, and target data that meets the business rules and target requirements is obtained.

[0031] Perform data verification according to the data verification task list to obtain target data, including: Execute verification tasks: Execute data verification tasks one by one in the order in the task list.

[0032] Process verification results: Process data that does not meet the verification rules according to the verification result processing method of each task.

[0033] Generate target data: Integrate all verified and processed data into target data.

[0034] Verify target data: Verify the target data again to ensure the quality and accuracy of the data.

[0035] The beneficial effects of the above technical solution are: comprehensive data verification is performed on the pre-processed data to ensure the correctness, completeness and consistency of the data, and ultimately obtain the target data that meets business requirements.

[0036] According to some embodiments of the present invention, establishing a verification database for a power spot market includes: Collect relevant requirements for data verification from relevant laws, policies, standards and market operation rules of the power spot market, organize the relevant requirements, and obtain a verification rule set, including data format verification rules, data range verification rules and data logical relationship verification rules; Classifying the verification rule set to obtain classified data; the classified data includes basic data verification, business logic verification and compliance verification; Encode each rule in the classification data to obtain encoded data; Store the coded data into the database and build a verification database.

[0037] The working principle of the above technical solution: systematically collect requirements related to data verification from relevant laws, policies, standards and market operation rules of the electricity spot market. Carefully analyze and organize the collected requirements and summarize them into a set of verification rules. These rule sets include: Data format verification rules: check whether the format of the data is correct, such as date format, number format, string format, etc. Data range verification rules: check whether the data is within the specified reasonable range, such as the upper and lower limits of data such as electricity volume, electricity price, and load. Data logical relationship verification rules: check whether the data satisfies specific logical relationships, such as the relationship between electricity volume and electricity price, and the balance relationship between load and power generation.

[0038] The sorted verification rule sets are classified to obtain three types of data: basic data verification, business logic verification, and compliance verification. Basic data verification: focuses on the basic attributes of data, such as format, type, integrity, etc. Business logic verification: checks whether the internal relationships between data are consistent according to the business logic of the power spot market. Compliance verification: ensures that the data complies with the requirements of relevant laws, policies, and market rules.

[0039] Uniquely encode each rule in the classified data so that it can be identified and managed in the database. The code includes information such as rule type, rule number, and rule description. Establish a rule library to store the encoded rules and continuously update and improve them.

[0040] According to the requirements of the verification rule set and classified data, the database table structure is designed, including the rule table, rule classification table, rule coding table, etc. The encoded verification rules are stored in the database to build the verification database. The database is optimized, such as index design and query optimization, to improve the efficiency and accuracy of data verification.

[0041] The beneficial effects of the above technical solution are: it is easy to establish a comprehensive, accurate and efficient electricity spot market verification database, and provide strong support for data verification work in the electricity spot market.

[0042] According to some embodiments of the present invention, performing data verification according to the data verification task list to obtain target data includes: Based on the hardware resources of the monitoring and early warning system and the scale of the data verification tasks in the data verification task list, a data verification task thread pool is constructed; Allocate the data verification tasks in the data verification task list to threads in the data verification task thread pool based on the load balancing strategy; Each thread calls the data verification engine to verify the pre-processed data corresponding to the specified data verification task according to the verification rules; The threads in the data verification task thread pool execute data verification tasks in parallel and return the verification results to the main thread. The main thread summarizes and analyzes the verification results, generates a verification report, and obtains the target data based on the verification report.

[0043] The working principle of the above technical solution is: Evaluate the hardware resources of the monitoring and early warning system, including CPU, memory, disk I / O, etc., to determine the parallelism of data verification tasks that can be supported. Analyze the task scale in the data verification task list, including the data volume and complexity of each task. Based on the hardware resources and task scale, build a data verification task thread pool of appropriate size. The size of the thread pool should be able to fully utilize the hardware resources while avoiding excessive competition that leads to performance degradation. Use load balancing strategies such as polling, weighted polling, random allocation, etc. to assign tasks in the data verification task list to threads in the thread pool. The load balancing strategy ensures that tasks are evenly distributed among threads to avoid overloading some threads while other threads are idle. Pass the assigned task information (such as task ID, data location, verification rules, etc.) to the corresponding thread. After each thread obtains the task from the task queue, it calls the data verification engine for verification. The data verification engine is a software component that encapsulates verification rules and data processing logic. According to the verification rules, the pre-processed data corresponding to the data verification task is verified. The verification process includes data format checking, data range verification, data logical relationship verification, etc. The verification results (such as pass, fail, error information, etc.) are recorded for subsequent analysis and processing. The threads in the data verification task thread pool execute the data verification tasks in parallel to improve the verification efficiency. After each thread completes the verification task, it returns the verification result to the main thread. The main thread summarizes and analyzes the received verification results and generates a verification report. The verification report should include information such as task completion status, error statistics, and error details. According to the verification report, the pre-processed data is corrected or screened to obtain the target data that meets the business requirements.

[0044] The beneficial effects of the above technical solution are as follows: According to the problems and performance bottlenecks found during the verification process, the monitoring and early warning system, data verification engine and thread pool are optimized. At the same time, the verification results and feedback are provided to the data provider or business party to facilitate the improvement of data quality. The data verification task can be performed efficiently, the target data that meets the business requirements can be obtained, and the performance and reliability of the entire monitoring and early warning system can be improved.

[0045] According to some embodiments of the present invention, each thread calls a data verification engine to verify the pre-processed data corresponding to the specified data verification task according to the verification rule, including: When verifying the operating system load data in the preprocessed data, check the integrity of the operating system load data, whether the change amplitude of the load adjacent points exceeds the set threshold, whether the operating system load forecast is greater than the total bus load after deducting the power supply plan, and whether the deviation percentage between the system load and the total bus load is within the set range; When verifying the unit operation quotation data in the pre-processed data, check whether the unit operation quotation range is within the maximum and minimum technical output range of the unit, whether the unit segment quotation is within the set upper and lower limits, whether the unit quotation segment number is within the set maximum quotation segment number, whether the unit start-up and shutdown costs are complete, and whether the start-up and shutdown costs are within the set upper and lower limits; When verifying the section limit data in the preprocessing data, the section positive limit is non-negative, the section reverse limit is non-positive, and the absolute values ​​of the section positive and reverse limits are verified to be within the set threshold range.

[0046] The working principle of the above technical solution: Operation system load data verification: Data integrity check: Verify whether the operation system load data is complete, that is, check whether there are missing or abnormal data points. Load adjacent point change amplitude verification: Calculate the change amplitude of adjacent data points in the load data. Check whether these change amplitudes exceed the preset threshold to determine the rationality of the load data. Load forecast and bus load total verification: Obtain the operation system load forecast value from the preprocessed data. After deducting the power supply plan, calculate the remaining load. Compare the remaining load with the bus load total to check whether it is greater than the bus load total to ensure the accuracy of the load data. System load and bus load total deviation verification: Calculate the deviation percentage between the system load and the bus load total. Check whether this deviation percentage is within the set range to evaluate the overall accuracy of the load data.

[0047] Unit operation quotation data verification: Quotation range verification: Get the unit operation quotation from the preprocessed data. Check whether the quotation is within the maximum and minimum technical output range of the unit to ensure the rationality of the quotation. Segment quotation verification: Check whether the unit segment quotation is within the set upper and lower limits. Ensure that the number of quotation segments does not exceed the set maximum number of quotation segments to avoid overly complex or unreasonable quotations. Start-stop cost verification: Check whether the unit start-stop costs are complete. Verify whether the start-stop costs are within the set upper and lower limits to ensure the rationality of the costs.

[0048] Section limit data verification: Section limit non-negative / non-positive check: Perform a non-negative check on the section positive limit to ensure that there are no negative values. Perform a non-positive check on the section reverse limit to ensure that there are no positive values. Section positive and reverse limit absolute value check: Calculate the absolute value of the section positive and reverse limits. Check whether these absolute values ​​are within the set threshold range to evaluate the rationality of the section limit data.

[0049] The beneficial effects of the above technical solution are as follows: through the implementation of the verification rules, it can be ensured that the key data in the electricity spot market is fully verified and validated in the preprocessing stage, thereby improving the accuracy and reliability of the data.

[0050] According to some embodiments of the present invention, the power spot market operation risk monitoring and early warning are performed according to the target data, including: Set risk indicators and build a risk assessment system based on risk indicators; Evaluate the target data according to the risk assessment system to obtain the risk assessment results; Conduct electricity spot market operation risk monitoring and early warning based on risk assessment results.

[0051] Working principle of the above technical solution: Types of operational risks existing in the electricity spot market, such as price fluctuation risk, supply and demand imbalance risk, system stability risk, etc. For each risk type, select specific indicators that can reflect its risk level and changing trend. For example, for price fluctuation risk, you can choose indicators such as electricity price volatility and electricity price standard deviation; for supply and demand imbalance risk, you can choose indicators such as supply-demand ratio and load forecast deviation. According to historical data and industry standards, set a reasonable threshold or range for each risk indicator so that it can be compared and judged in subsequent risk assessments.

[0052] Based on the selected risk indicators, a risk assessment model is designed, namely a risk assessment system, which is a threshold judgment model. The risk assessment cycle is set, such as daily, weekly, monthly, etc., to ensure timely monitoring of the operational risks of the power spot market.

[0053] Use visualization tools or dashboards to display risk assessment results in real time so that market operators can understand the operational risk status of the electricity spot market at any time. When one or some risk indicators exceed the set threshold, the early warning mechanism is triggered and a warning message is sent to the market operator to remind it to take appropriate countermeasures. Based on the early warning information, the market operator formulates specific countermeasures, such as adjusting the power generation plan, optimizing the quotation strategy, and strengthening supply and demand management, to reduce operational risks. After implementing the countermeasures, continue to monitor and evaluate the operational risks of the electricity spot market, and adjust the countermeasures based on the evaluation results to achieve effective risk control.

[0054] The beneficial effects of the above technical solution are: to achieve comprehensive monitoring and early warning of operational risks in the electricity spot market, to provide decision-making support for market operators, and to ensure the stable operation of the electricity market.

[0055] According to some embodiments of the present invention, the further comprising: According to the risk assessment results, query the preset risk assessment results-treatment measures data table to determine the target treatment measures; The corresponding control command signal is generated according to the target processing measures and transmitted to the control module of the power spot market.

[0056] The working principle of the above technical solution is: obtain the latest risk assessment results from the risk assessment system, including key information such as risk type, risk level, and risk probability. According to the risk assessment results, query the preset risk assessment result-treatment measure data table. This data table should preset corresponding treatment measures for different risk types and levels in advance according to the characteristics and operating experience of the power spot market. In the data table, find the treatment measure that best matches the current risk assessment result as the target treatment measure. According to the control module requirements of the power spot market, design the format and content of the control instruction. This includes key information such as instruction type, target equipment, and operating parameters. Based on the target treatment measure, combined with the control instruction format, generate the corresponding control instruction signal. For example, if the target treatment measure is to adjust the power generation plan, the control instruction includes specific information such as the unit number and power generation power to be adjusted. According to the communication architecture of the power spot market, select a transmission channel, such as network transmission, dedicated line transmission, etc., to transmit the control instruction signal to the control module. During the transmission process, monitor the transmission status to ensure that the instruction signal can successfully reach the control module. If the transmission fails, the instruction should be resent or other remedial measures should be taken. After executing the instructions, the control module will return the execution results or status information. Receive this feedback to monitor and evaluate the effectiveness of the treatment measures.

[0057] The beneficial effects of the above technical solution are as follows: based on the risk assessment results, the target processing measures are quickly determined and the corresponding control command signals are generated, thereby achieving effective control of the operational risks of the electricity spot market, helping to ensure the stable operation of the market, and improving operational efficiency and risk management levels.

[0058] According to some embodiments of the present invention, the further comprising: Before transmitting the control command signal to the control module of the power spot market, calculating the transmission reliability value of the control command signal, and transmitting the signal when it is determined that the transmission reliability value is greater than a preset threshold; Calculate the transmission reliability value of the control command signal, including: Calculate the amplitude characteristic value of the control command signal : in, To control the power of the effective signal in the command signal; To control the power of noise in the command signal; is the number of signal nodes in the control command signal; For the The energy at each signal node; is the average energy of the signal node; According to the amplitude characteristic value of the control command signal , calculate the transmission reliability value of the control command signal : in, is the variance of the noise in each signal node; is the estimated transmission time of the control command signal; To control the vibration frequency of the effective signal in the command signal; It is the vibration frequency of the noise in the control command signal.

[0059] The working principle and beneficial effects of the above technical solution: After calculating the transmission reliability value of the control command signal and confirming that it is greater than the preset threshold, the signal is transmitted, which can greatly improve the reliability and security of the transmission. First, the amplitude characteristic value A of the control command signal is calculated. This value reflects the relative strength of the effective signal and the noise in the signal, as well as the energy distribution of the signal node. The amplitude characteristic value A is used to calculate the transmission reliability value T of the control command signal. This value comprehensively considers the amplitude, noise variance, transmission time and vibration frequency of the signal. If T is greater than the preset threshold, it means that the transmission reliability of the control command signal is high and the signal can be transmitted; if T is less than or equal to the preset threshold, it is necessary to re-evaluate the signal quality or take other measures to improve the transmission reliability. Ensure the reliability and security of the control command signal during the transmission process, thereby achieving effective control of the operational risks of the power spot market.

[0060] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. A method for monitoring and early warning of power spot market operation risks, characterized in that: include: Collect data from the electricity spot market to obtain electricity spot data; Preprocessing the electricity spot data to obtain preprocessed data; Perform data verification on the preprocessed data to obtain the target data; Conduct risk monitoring and early warning of power spot market operations based on target data; Perform data verification on the preprocessed data to obtain the target data, including: Establish a calibration database for the electricity spot market; Define data verification tasks based on preprocessed data and verification database; each data verification task has a corresponding verification data set, verification rules, and processing method for verification results; Generate a data verification task list based on several data verification tasks; Perform data verification according to the data verification task list to obtain the target data.

2. The method for monitoring and early warning of power spot market operation risks according to claim 1, characterized in that: Collect data from the electricity spot market to obtain electricity spot data, including: The operation data of the electricity spot market is captured based on the data acquisition interface during a preset monitoring period, the captured data is identified based on the operation characteristics, different types of operation orders are distinguished, and a classified set is obtained as the electricity spot data; wherein the operation characteristics include operation time, operation power, operation unit price, operation system load data, unit operation quotation data and section limit data.

3. The method for monitoring and early warning of power spot market operation risks according to claim 1, characterized in that: The power spot data is preprocessed to obtain preprocessed data, including: Clean the electricity spot data to obtain cleaned data; The cleaned data is formatted according to data standards to obtain preprocessed data.

4. The method for monitoring and early warning of power spot market operation risks according to claim 1, characterized in that: Establish a verification database for the electricity spot market, including: Collect relevant requirements for data verification from relevant laws, policies, standards and market operation rules of the power spot market, organize the relevant requirements, and obtain a verification rule set, including data format verification rules, data range verification rules and data logical relationship verification rules; Classifying the verification rule set to obtain classified data; the classified data includes basic data verification, business logic verification and compliance verification; Encode each rule in the classification data to obtain encoded data; Store the coded data into the database and build a verification database.

5. The method for monitoring and early warning of power spot market operation risks according to claim 1, characterized in that: Perform data verification according to the data verification task list to obtain target data, including: Based on the hardware resources of the monitoring and early warning system and the scale of the data verification tasks in the data verification task list, a data verification task thread pool is constructed; Allocate the data verification tasks in the data verification task list to threads in the data verification task thread pool based on the load balancing strategy; Each thread calls the data verification engine to verify the pre-processed data corresponding to the specified data verification task according to the verification rules; The threads in the data verification task thread pool execute data verification tasks in parallel and return the verification results to the main thread. The main thread summarizes and analyzes the verification results, generates a verification report, and obtains the target data based on the verification report.

6. The method for monitoring and early warning of power spot market operation risks according to claim 5, characterized in that: Each thread calls the data verification engine to verify the pre-processed data corresponding to the specified data verification task according to the verification rules, including: When verifying the operating system load data in the preprocessed data, check the integrity of the operating system load data, whether the change amplitude of the load adjacent points exceeds the set threshold, whether the operating system load forecast is greater than the total bus load after deducting the power supply plan, and whether the deviation percentage between the system load and the total bus load is within the set range; When verifying the unit operation quotation data in the pre-processed data, check whether the unit operation quotation range is within the maximum and minimum technical output range of the unit, whether the unit segment quotation is within the set upper and lower limits, whether the unit quotation segment number is within the set maximum quotation segment number, whether the unit start-up and shutdown costs are complete, and whether the start-up and shutdown costs are within the set upper and lower limits; When verifying the section limit data in the preprocessing data, the section positive limit is non-negative, the section reverse limit is non-positive, and the absolute values ​​of the section positive and reverse limits are verified to be within the set threshold range.

7. The method for monitoring and early warning of power spot market operation risks according to claim 1, characterized in that: Conduct power spot market operation risk monitoring and early warning based on target data, including: Set risk indicators and build a risk assessment system based on risk indicators; Evaluate the target data according to the risk assessment system to obtain the risk assessment results; Conduct electricity spot market operation risk monitoring and early warning based on risk assessment results.

8. The method for monitoring and early warning of power spot market operation risks according to claim 7, characterized in that: Also includes: According to the risk assessment results, query the preset risk assessment results-treatment measures data table to determine the target treatment measures; The corresponding control command signal is generated according to the target processing measures and transmitted to the control module of the power spot market.

9. The method for monitoring and early warning of power spot market operation risks according to claim 8, characterized in that: Also includes: Before transmitting the control command signal to the control module of the power spot market, calculating the transmission reliability value of the control command signal, and transmitting the signal when it is determined that the transmission reliability value is greater than a preset threshold; Calculate the transmission reliability value of the control command signal, including: Calculate the amplitude characteristic value of the control command signal : in, To control the power of the effective signal in the command signal; To control the power of noise in the command signal; is the number of signal nodes in the control command signal; For the The energy at each signal node; is the average energy of the signal node; According to the amplitude characteristic value of the control command signal , calculate the transmission reliability value of the control command signal : in, is the variance of the noise in each signal node; is the estimated transmission time of the control command signal; To control the vibration frequency of the effective signal in the command signal; It is the vibration frequency of the noise in the control command signal.

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