Power field integrated office system and method based on RPA technology

Abstract

The invention discloses a power field integrated office system and method based on an RPA technology. The system comprises a power energy transaction and data analysis module, a distributed photovoltaic operation and electric charge calculation module, a financial comprehensive management and risk assessment module and an enterprise operation management and market development module. By automatically processing a large amount of business work which is simple in logic and mechanically repeated, the time and error rate of manual operation are reduced, and the working efficiency is remarkably improved. Through integration of monitoring, transmission, calculation, operation and application functions, cross-system seamless operation is realized, information islands are broken, and the overall cooperative capability of the system is improved. Aiming at new characteristics and new requirements in a novel electric power system with'double-high 'as typical characteristics, the solution provided by the invention is beneficial to promoting digital transformation and intelligent upgrading of the electric power energy industry, and has an important industry demonstration effect.

Description

Technical Field

[0001] The present invention relates to the field of integrated office technology, and specifically to an integrated office system and method in the electric power field based on RPA technology. Background Art

[0002] As the power and energy industry transforms to a new clean and low-carbon energy system, large-scale renewable energy has gradually replaced the dominant position of traditional coal-fired power, leading to major changes in the original planning pattern of the power and energy industry. As a result, the traditional fossil energy business model is difficult to meet the needs of new scenarios, and the office system with new businesses such as "distributed energy planning, procurement of green electricity and green certificates, and power data analysis and forecasting" as the main body has become a new model, which urgently needs to promote the digitalization, automation and intelligent upgrading of enterprise management models and business processing.

[0003] Currently, invention patents in this field tend to focus on independent monitoring and early warning, data acquisition, and financial management, etc. They have single functions and simple systems and cannot fully meet the marketing business needs under the current new power system. Summary of the invention

[0004] In view of the above-mentioned problems, the present invention is proposed.

[0005] In order to solve the above technical problems, the present invention provides the following technical solutions: an integrated office system in the power field based on RPA technology, including: power energy trading and data analysis module, distributed photovoltaic operation and electricity fee calculation module, financial comprehensive management and risk assessment module, enterprise operation management and market development module;

[0006] The power energy trading and data analysis module includes a 96-point power consumption detection and analysis unit for enterprise users, a medium- and long-term power trading unit, a green power green certificate trading unit, and a power spot trading unit;

[0007] The distributed photovoltaic operation and electricity fee calculation module includes a photovoltaic system online monitoring and full-cycle management unit, a power consumption collection and data analysis unit, an electricity fee calculation and benefit analysis unit, and a customer service and technical support unit;

[0008] The comprehensive financial management and risk assessment module includes a financial data collection and analysis unit, a cost calculation and investment return unit, and a capital structure optimization and capital chain management unit;

[0009] The enterprise operation management and market development module includes a daily marketing business management unit, a technology development and intellectual property unit, a market analysis and strategic planning unit, and a market development and customer relationship management unit.

[0010] As a preferred solution of the integrated office system in the power field based on RPA technology described in the present invention, the 96-point power consumption detection and analysis unit of the enterprise user includes: the RPA robot monitors the enterprise's power consumption in real time, checks data integrity and abnormal values, and performs data deduplication and formatting; uses algorithms to identify abnormal fluctuations in power consumption patterns, sets power consumption thresholds based on past data, and triggers alarms; sets different levels of warnings, verifies warning levels, and ensures timely notification of relevant personnel; automatically generates daily, weekly and monthly power consumption reports, and provides graphical power consumption data display;

[0011] The medium- and long-term electricity trading unit includes using RPA robots to collect and analyze market data, understand market demand and price dynamics, analyze historical transaction data, assess potential risks, and formulate risk control measures; automatically generate standardized electricity purchase and sales contracts based on preset templates and rules, and automatically check the integrity and compliance of contract terms; automatically match the needs of buyers and sellers on the electricity trading platform, execute transactions, and automatically record detailed transaction data; automatically use optimization algorithms to distribute electricity, improve energy efficiency, regularly monitor electricity distribution, and adjust deviations in a timely manner to ensure supply and demand balance; automatically complete financial settlement after the transaction, including invoice processing and payment transfer, and automatically check the accounts of all parties to the transaction;

[0012] The green electricity and green certificate trading unit includes: automatically collecting market demand information for green electricity and green certificates, analyzing user needs, and providing data support for trading strategies; automatically matching buyers and sellers on the trading platform, executing transactions, automatically recording transaction details, and providing data support; tracking and managing the generation and trading of green certificates, real-time monitoring of the validity period of green certificates, and reminding renewal or redemption; automatically performing financial settlement after the transaction is completed, performing benefit accounting, and evaluating the economic and environmental benefits of the transaction; real-time updating of compliance with green electricity trading regulations, regular transaction audits, and generating compliance reports;

[0013] The electricity spot trading unit includes: automatically collecting factors that affect electricity prices, such as historical trading data, weather forecasts, etc., and using machine learning algorithms to predict electricity price trends; simulating different trading strategies based on market and electricity price forecast results, evaluating returns and risks, and adjusting strategies to minimize risks and maximize returns; automatically quoting and inquiring on the electronic trading platform, and automatically recording key information such as transaction volume and price after the transaction is concluded; real-time monitoring of market prices and news events, and quickly adjusting trading strategies according to market changes; and automatically settling with the power exchange after the transaction is completed, and calculating the transaction results according to financial standards.

[0014] As a preferred solution of the integrated office system in the power field based on RPA technology described in the present invention, the photovoltaic system online monitoring and full-cycle management unit includes: real-time automatic collection of photovoltaic panel operation data, preliminary data verification, and elimination of anomalies or errors; analysis of operation data, automatic identification of faults or performance degradation signs, generation of early warning information, notification of operation and maintenance personnel, and prediction of potential faults using historical data; regular evaluation of the power generation efficiency and component performance of the photovoltaic system, analysis of performance trends, identification of degradation patterns, and generation of performance analysis reports; automatic creation and dispatch of maintenance tasks based on maintenance plans and fault detection results, real-time tracking of task execution, and intelligent deployment of maintenance resources; monitoring of the use of photovoltaic components and equipment, recording replacement and maintenance requirements, managing the entire life cycle of equipment, and automatically updating configuration and performance parameters; automatic generation of daily operation and maintenance reports based on collected data and analysis results, providing customized reports, and automatically distributing them to relevant personnel;

[0015] The power consumption collection and data analysis unit includes: automatically collecting real-time power generation data, including current, voltage, temperature, etc., verifying data format and content, and integrating data from different sources or formats; calculating power generation in real time according to inverter, gateway table and grid cabinet data, screening abnormal data and marking; calculating system loss, adjusting power generation efficiency according to loss trend; collecting and comparing gateway table and grid cabinet data, evaluating operation effect, and recording net power generation; automatically matching applicable electricity prices, adjusting electricity price data in real time, saving historical electricity price data, and supporting long-term cost-benefit analysis; calculating direct economic benefits of photovoltaic projects, analyzing income trends, identifying factors affecting income, and generating income reports; calculating operating costs, combining income and cost data, and evaluating economic benefits; automatically compiling comprehensive reports on electricity calculation, income analysis, and cost analysis, and system management and archiving report files;

[0016] The electricity fee accounting and benefit analysis includes: automatically collecting power generation data and performing quality control, eliminating inaccurate data, and summarizing power data of different time periods; automatically determining applicable electricity prices based on real-time electricity prices and contract terms, identifying time periods corresponding to power generation, and applying corresponding electricity prices; establishing an electricity fee calculation model, executing batch electricity fee calculations, and performing internal logic verification after the calculations are completed; automatically deducting operating and maintenance costs, and updating financial records; automatically determining applicable tax rates, calculating tax payable, and generating tax reports and documents; analyzing electricity prices, simulating electricity fee benefits, predicting benefits under different strategies, and automatically adjusting strategies; automatically generating electricity bills based on accounting results, automatically reviewing bills and ensuring accuracy, and sending them to customers electronically; automatically tracking customer payment status, confirming on-time payments, sending reminders to customers who have not paid on time, and after confirming the recovery, confirming the receipt and updating financial records in the system;

[0017] The customer service and technical support include: automatic updating and verification of customer and PV system information; automatic response to customer inquiries through multiple channels, provision of system information, and referral of complex issues; automatic receipt and recording of fault reports, preliminary analysis and notification of maintenance teams; recording of service requests, automatic execution of approval processes, and provision of real-time progress updates; automatic reminders to customers according to maintenance plans, recording of maintenance activities and update status; and regular generation and delivery of customized performance reports to customers.

[0018] As a preferred solution of the integrated office system in the power field based on RPA technology described in the present invention, the financial data collection and analysis unit automatically collects data from data sources such as accounting, sales, and bank accounts, performs data verification and cleaning, and eliminates errors and duplicate data; automatically records accounts based on data, automatically generates accounting vouchers, and identifies and adjusts accounting anomalies; collects and analyzes cost data, compares it with the budget, calculates deviations, and automatically warns management when costs exceed thresholds; tracks and records all income streams, automatically matches contract terms, analyzes income trends, and provides business development decision support; automatically calculates taxes and fees according to tax laws, completes tax declarations, and prepares documents and data required for tax audits; automatically generates standard financial reports and customized analysis reports, and automatically sends reports to shareholders, management, and other stakeholders; automatically checks the compliance of financial activities, maintains audit tracking records, runs risk assessment procedures, identifies and reports financial risks; monitors cash inflows and outflows, maintains funding status, conducts financial and business forecast analysis, and puts forward funding and investment recommendations;

[0019] The cost calculation and investment return unit includes: automatically collecting cost data from multiple systems, classifying it, analyzing historical trends, and identifying cost saving opportunities; automatically generating budgets based on historical and forecast data, monitoring actual expenditures, and identifying deviations; automatically calculating the rates of return on different investment projects, comparing the ROI of multiple projects, evaluating risks, and assisting investment decisions; automatically executing cost reduction strategies, tracking implementation results, and regularly generating cost control reports for management decision-making; analyzing contract terms, identifying savings points, reminding renewal time, monitoring contract execution, and ensuring that suppliers fulfill their commitments; evaluating supplier quotations, recommending the best procurement options, and automating procurement processes; monitoring energy consumption, analyzing usage efficiency, and evaluating the cost-effectiveness of energy-saving measures; tracking capital expenditure project status and budget usage, sorting investment priorities based on project urgency and returns, and providing funding allocation and expenditure recommendations;

[0020] The capital structure optimization and capital chain management include: regularly checking the balance of each account, automatically collecting funds into the main account, generating reports on abnormal or unauthorized transactions and notifying relevant personnel; collecting historical cash flow data, predicting short-term cash flow, and automatically generating cash flow analysis reports for decision-making; setting budget parameters based on historical performance, automatically allocating budgets and initiating approval processes, and tracking status; real-time monitoring of budget execution, comparing actual expenditures, identifying deviations, and automatically notifying relevant departments to take measures; automatically analyzing cost data, proposing cost reduction measures, tracking the effectiveness of measures, and ensuring the achievement of budget goals; evaluating the returns on investment projects, prioritizing expenditure projects, and recommending funding allocation plans based on priorities and funding conditions; identifying potential risks in cash flows, such as liquidity and credit risks, quantifying and analyzing the impact of risks, and proposing risk management strategies.

[0021] As a preferred solution of the integrated office system in the power field based on RPA technology described in the present invention, the daily marketing business management unit includes: automatically executing data entry and report generation tasks; automatically collecting key data from different data sources, cleaning, formatting and verifying data, and establishing a central data warehouse; real-time tracking of key operating indicators, automatic generation of operating reports and abnormal situation reports; automatic monitoring of risk factors and compliance changes; automatic response to customer inquiries, providing information and answers, analyzing customer data, identifying needs, and automatically recommending products or services; analyzing resource needs and utilization efficiency, automatically adjusting resource allocation, and giving priority to high-return projects; quickly obtaining market data, identifying investment trends, automatically tracking investment performance, and evaluating risks and returns; automatically reviewing contract terms to ensure compliance, tracking supplier performance, and automating procurement processes;

[0022] The technology development and intellectual property unit includes: regularly collecting technology research reports and industry trends, automatically analyzing potential technology trends, and generating analysis reports; automatically creating project plans based on demand, including timetables and budgets, tracking project progress in real time, and reporting deviations and potential risks; automatically tracking R&D costs, analyzing and proposing savings opportunities; using RPA tools to automatically archive and manage R&D documents to ensure information consistency; the automation platform collects employees' innovative ideas, screens potential ideas, and provides tools and resource support;

[0023] The market analysis and strategic planning unit includes: automatically collecting market data, including industry reports and consumer behavior, using data analysis tools to generate market trend reports; collecting and analyzing consumer feedback and social media comments, using natural language processing technology to refine consumer insights; automatically collecting internal and external risk data, assessing strategic decision-making risks, and formulating risk management plans; monitoring resource usage, automatically reallocating resources according to demand, tracking resource allocation effects, and optimizing configuration strategies; automatically collecting investment project data, using quantitative models for evaluation, providing investment analysis reports, and assisting decision-making; regularly collecting competitor data, analyzing market performance, adjusting company strategies, and formulating countermeasures;

[0024] The market development and customer relationship management unit includes automatically collecting customer information from multiple channels, integrating and building customer profiles, analyzing customer behavior, identifying needs and purchasing patterns; collecting industry reports and market data, analyzing market trends, generating target customer group descriptions, and assisting in market positioning; designing personalized marketing activities, automatically executing promotions, collecting performance data in real time, and adjusting marketing strategies; automatically processing common inquiries, improving response speed, regularly collecting customer feedback, and evaluating satisfaction; screening high-probability sales opportunities, updating sales pipelines, generating sales forecast reports, and assisting in sales strategy formulation; analyzing purchase history, identifying loyal customers, designing differentiated reward plans, and automatically executing reward distribution; monitoring competitor activities, collecting market feedback, and proposing market strategy adjustment suggestions; summarizing sales and market activity data, generating performance reports, and using machine learning to predict market trends and guide business direction.

[0025] An integrated office method in the electric power field based on RPA technology using the system of the present invention is characterized by: extracting and processing information data through information collection technology of the front-end monitoring layer;

[0026] The collected information data is sent to the computing layer through the transmission layer to complete the data calculation of the application layer;

[0027] The operation layer connects to the application layer to clarify specific task requirements; the computing layer connects to the bottom layer to drive the RPA digital workforce underlying processing system for analysis, calculation and feedback.

[0028] The application layer is responsible for implementing specific business functions and automated processes. Its functions are completed through four major modules and fifteen sub-functional units, namely power energy trading and data analysis, distributed photovoltaic operation and electricity fee calculation, comprehensive financial management and risk assessment, and enterprise operation management and market development.

[0029] As a preferred solution of the integrated office method in the power field based on RPA technology described in the present invention, wherein: in the computing layer, logs are generated according to the functional requirements of the application layer, and historical logs are periodically extracted and reviewed;

[0030] When extracting logs, select the log content generated between the last extracted log and the current time and perform random extraction; at the same time, add random perturbation ∈ during extraction, where the value range of ∈ is between 0 and θ. Each time an extraction is performed, there is a probability of ∈×100% to randomly extract all historical records;

[0031] Wherein, θ represents the preset disturbance threshold, which is greater than 0 and less than 1; the number of extractions is the preset number U;

[0032] The extracted logs are classified through decision trees, and the completeness and content analysis of the logs of each classification result are performed;

[0033] The completeness evaluation includes setting mandatory and optional parts for each type of log. If a mandatory part is blank, the log is judged to be incomplete, and the incomplete log is marked as mark 1;

[0034] When analyzing the log content, the logs judged to be abnormal are marked as mark 2;

[0035] After completing the content analysis and completeness assessment of the onboarding log, all tags are identified and the tagged logs are output, while the tag type is displayed.

[0036] As a preferred solution of the integrated office method in the power field based on RPA technology described in the present invention, the log content analysis includes: assuming that each log contains multiple records, firstly, each record is segmented and POS tagged, stop words are removed and stems are extracted to obtain the pre-processed result i;

[0037] Using the bag-of-words model and TF-IDF, features are extracted from the preprocessed text:

[0038] L i =TF-IDF(BagOfWords(Preprocess(i)))

[0039] Among them, i represents the i-th log, BagOfWords represents the bag-of-words model, and L i represents the features of the i-th log, TF-IDF represents the term frequency-inverse document frequency model;

[0040] A bidirectional long short-term memory network is introduced to analyze the relationship between the previous and next log contents, and a Gaussian mixture model is used to perform probability distribution analysis.

[0041] BiLSTM(Lt-1 ,L t ,L t+1 )

[0042] =Concat(LSTM forward (L t-1 ,L t ,L t+1 ),LSTM backward (L t+1 ,L t ,L t+1 ))

[0043] Use GMM to perform probability distribution analysis on the output of BiLSTM to determine the rationality of the log content;

[0044]

[0045] Among them, π k is the weight of the kth Gaussian component, μ k and Σ k are the mean and covariance matrices respectively; LSTM forward and LSTM backward are forward and backward LSTM, L t Represents the characteristics of the current moment, L t-1 Indicates the previous log feature of the same record target, L t+1 Indicates the next log feature of the same record target. is a Gaussian distribution, K is the number of Gaussian components;

[0046] An adaptive analysis model based on Bayesian optimization is introduced to dynamically adjust the rationality of log content:

[0047]

[0048] Among them, x is the input variable; θ is the model parameter, and the model is optimized by maximizing the probability distribution of the log content;

[0049] Combining the various parts together, we get a comprehensive rationality analysis formula:

[0050] R′(L t )=BO(P(L t ))

[0051] Among them, R′(L t ) is the rationality evaluation result, and its value range is real number; if R′(L t )>0, then the content is judged to be normal; if R′(L t )≤0, the log content is considered abnormal.

[0052] A computer device comprises: a memory and a processor; the memory stores a computer program, wherein: the processor implements the steps of any one of the methods of the present invention when executing the computer program.

[0053] A computer-readable storage medium stores a computer program, wherein: when the computer program is executed by a processor, the steps of any one of the methods of the present invention are implemented.

[0054] Beneficial effects of the present invention: The integrated office system in the power field based on RPA technology provided by the present invention improves work efficiency: by automating the processing of a large number of logically simple and mechanically repetitive business tasks, the time and error rate of manual operations are reduced, and work efficiency is significantly improved.

[0055] Optimize resource allocation: Free employees from tedious and repetitive tasks, allowing them to focus on higher value-added and more complex work, thereby optimizing human resource allocation.

[0056] Enhanced data processing capabilities: The information collection and processing capabilities of RPA technology have improved the accuracy and timeliness of data, providing strong support for energy layout planning, energy sales strategies, sales business, and electricity data analysis and forecasting.

[0057] Promote system integration: By integrating monitoring, transmission, calculation, operation and application functions, seamless operation across systems is achieved, breaking down information silos and improving the overall coordination capabilities of the system.

[0058] Improve decision-making quality: Through comprehensive analysis of data in key business areas such as power energy trading and analysis, distributed photovoltaic management and billing, financial management and risk assessment, corporate operations and market development, more comprehensive and accurate decision-making support is provided to management.

[0059] Promote industry development: In response to the new features and new demands emerging in the new power system with "double highs" as the typical characteristics, the solution proposed by this patent will help promote the digital transformation and intelligent upgrading of the electric power energy industry, and has an important industry demonstration role. BRIEF DESCRIPTION OF THE DRAWINGS

[0060] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0061] Figure 1A framework diagram of an integrated office system in the power field based on RPA technology provided in the first embodiment of the present invention;

[0062] Figure 2 An integrated office platform architecture diagram in an integrated office method in the electric power field based on RPA technology provided in the second embodiment of the present invention;

[0063] Figure 3 A technical step diagram of front-end information collection in an integrated office method in the power field based on RPA technology is provided for the second embodiment of the present invention. DETAILED DESCRIPTION

[0064] In order to make the above-mentioned purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the drawings of the specification. Obviously, the described embodiments are part of the embodiments of the present invention, but not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary persons in the art without creative work should fall within the scope of protection of the present invention.

[0065] Example 1, reference Figure 1 , which is an embodiment of the present invention, provides an integrated office system in the power field based on RPA technology, including:

[0066] Electric energy trading and data analysis module, distributed photovoltaic operation and electricity fee calculation module, comprehensive financial management and risk assessment module, enterprise operation management and market development module.

[0067] The electric energy trading and data analysis module includes a 96-point electricity consumption detection and analysis unit for corporate users, a medium- and long-term electricity trading unit, a green electricity and green certificate trading unit, and a spot electricity trading unit.

[0068] The distributed photovoltaic operation and electricity fee calculation module includes a photovoltaic system online monitoring and full-cycle management unit, a power consumption collection and data analysis unit, an electricity fee calculation and benefit analysis unit, and a customer service and technical support unit.

[0069] The comprehensive financial management and risk assessment module includes a financial data collection and analysis unit, a cost calculation and investment return unit, and a capital structure optimization and capital chain management unit.

[0070] The enterprise operation management and market development module includes a daily marketing business management unit, a technology development and intellectual property unit, a market analysis and strategic planning unit, and a market development and customer relationship management unit.

[0071] The 96-point electricity consumption detection and analysis unit for enterprise users includes: RPA robots monitor the enterprise's electricity consumption in real time, check data integrity and outliers, and perform data deduplication and formatting; use algorithms to identify abnormal fluctuations in electricity consumption patterns, set electricity consumption thresholds based on past data, and trigger alarms; set different levels of warnings, verify warning levels, and ensure timely notification of relevant personnel; automatically generate daily, weekly and monthly electricity consumption reports, and provide graphical electricity consumption data display.

[0072] The medium- and long-term electricity trading unit includes using RPA robots to collect and analyze market data, understand market demand and price trends, analyze historical transaction data, assess potential risks, and formulate risk control measures; automatically generate standardized electricity purchase and sales contracts based on preset templates and rules, and automatically check the integrity and compliance of contract terms; automatically match the needs of buyers and sellers on the electricity trading platform, execute transactions, and automatically record detailed transaction data; use optimization algorithms to automatically allocate electricity, improve energy efficiency, regularly monitor electricity distribution, and adjust deviations in a timely manner to ensure supply and demand balance; automatically complete post-transaction financial settlement, including invoice processing and payment transfers, and automatically check the accounts of all parties to the transaction.

[0073] The green electricity and green certificate trading unit includes: automatically collecting market demand information on green electricity and green certificates, analyzing user needs, and providing data support for trading strategies; automatically matching buyers and sellers on the trading platform, executing transactions, automatically recording transaction details, and providing data support; tracking and managing the generation and trading of green certificates, real-time monitoring of the validity period of green certificates, and reminding renewal or redemption; automatically conducting financial settlement after the transaction is completed, performing benefit accounting, and evaluating the economic and environmental benefits of the transaction; real-time updating of compliance with green electricity trading regulations, regular transaction audits, and generation of compliance reports.

[0074] The electricity spot trading unit includes: automatically collecting factors that affect electricity prices, such as historical trading data, weather forecasts, etc., and using machine learning algorithms to predict electricity price trends; simulating different trading strategies based on market and electricity price forecast results, evaluating returns and risks, and adjusting strategies to minimize risks and maximize returns; automatically quoting and inquiring on the electronic trading platform, and automatically recording key information such as transaction volume and price after the transaction is concluded; real-time monitoring of market prices and news events, and quickly adjusting trading strategies according to market changes; and automatically settling with the power exchange after the transaction is completed, and calculating the transaction results according to financial standards.

[0075] The photovoltaic system online monitoring and full-cycle management unit includes: real-time automatic collection of photovoltaic panel operation data, preliminary data verification, and elimination of anomalies or errors; analysis of operation data, automatic identification of faults or performance degradation signs, generation of early warning information, notification of operation and maintenance personnel, and use of historical data to predict potential faults; regular evaluation of the photovoltaic system's power generation efficiency and component performance, analysis of performance trends, identification of degradation patterns, and generation of performance analysis reports; automatic creation and dispatching of maintenance tasks based on maintenance plans and fault detection results, real-time tracking of task execution, and intelligent deployment of maintenance resources; monitoring of the usage status of photovoltaic components and equipment, recording replacement and maintenance needs, managing the entire life cycle of equipment, and automatically updating configuration and performance parameters; automatic generation of daily operation and maintenance reports based on collected data and analysis results, providing customized reports, and automatically distributing them to relevant personnel.

[0076] The electricity consumption collection and data analysis unit includes: automatically collecting real-time power generation data, including current, voltage, temperature, etc., verifying data format and content, and integrating data from different sources or formats; calculating power generation in real time according to inverter, gateway table and grid cabinet data, screening abnormal data and marking; calculating system loss, and adjusting power generation efficiency according to loss trend; collecting and comparing gateway table and grid cabinet data, evaluating operation effect, and recording net power generation; automatically matching applicable electricity prices, adjusting electricity price data in real time, saving historical electricity price data, and supporting long-term cost-benefit analysis; calculating direct economic benefits of photovoltaic projects, analyzing income trends, identifying factors affecting income, and generating income reports; calculating operating costs, combining income and cost data, and evaluating economic benefits; automatically compiling comprehensive reports on electricity calculation, income analysis, and cost analysis, and systematically managing and archiving report files.

[0077] The electricity fee accounting and benefit analysis include: automatically collecting power generation data and performing quality control, eliminating inaccurate data, and summarizing power data for different time periods; automatically determining applicable electricity prices based on real-time electricity prices and contract terms, identifying time periods corresponding to power generation, and applying corresponding electricity prices; establishing an electricity fee calculation model, executing batch electricity fee calculations, and performing internal logic verification after the calculations are completed; automatically deducting operating and maintenance costs, and updating financial records; automatically determining applicable tax rates, calculating tax payable, and generating tax reports and documents; analyzing electricity prices, simulating electricity fee benefits, predicting benefits under different strategies, and automatically adjusting strategies; automatically generating electricity bills based on accounting results, automatically reviewing bills and ensuring accuracy, and sending them to customers electronically; automatically tracking customer payment status, confirming on-time payments, sending reminders to customers who have overdue payments, and after confirming the recovery, confirming the collection and updating financial records within the system.

[0078] The customer service and technical support include: automatic updating and verification of customer and PV system information; automatic response to customer inquiries through multiple channels, provision of system information, and referral of complex issues; automatic receipt and recording of fault reports, preliminary analysis and notification of maintenance teams; recording of service requests, automatic execution of approval processes, and provision of real-time progress updates; automatic reminders to customers according to maintenance plans, recording of maintenance activities and update status; and regular generation and delivery of customized performance reports to customers.

[0079] The financial data collection and analysis unit automatically collects data from accounting, sales, bank accounts and other data sources, performs data verification and cleaning, and eliminates errors and duplicate data; automatically records accounts based on the data, automatically generates accounting vouchers, identifies and adjusts accounting anomalies; collects and analyzes cost data, compares it with the budget, calculates deviations, and automatically warns management when costs exceed thresholds; tracks and records all income streams, automatically matches contract terms, analyzes income trends, and provides business development decision support; automatically calculates taxes and fees according to tax laws, completes tax returns, and prepares documents and data required for tax audits; automatically generates standard financial reports and customized analysis reports, and automatically sends reports to shareholders, management and other stakeholders; automatically checks the compliance of financial activities, maintains audit tracking records, runs risk assessment procedures, identifies and reports financial risks; monitors cash inflows and outflows, maintains funding status, conducts financial and business forecast analysis, and makes funding and investment recommendations.

[0080] The cost calculation and return on investment unit includes automatically collecting cost data from multiple systems, classifying it, analyzing historical trends, and identifying cost saving opportunities; automatically generating budgets based on historical and forecast data, monitoring actual expenditures, and identifying deviations; automatically calculating the rates of return on different investment projects, comparing the ROI of multiple projects, evaluating risks, and assisting investment decisions; automatically executing cost reduction strategies, tracking implementation results, and regularly generating cost control reports for management decision-making; analyzing contract terms, identifying savings points, reminding renewal time, monitoring contract execution, and ensuring that suppliers fulfill their commitments; evaluating supplier quotations, recommending the best procurement options, and automating procurement processes; monitoring energy consumption, analyzing usage efficiency, and evaluating the cost-effectiveness of energy-saving measures; tracking capital expenditure project status and budget usage, sorting investment priorities based on project urgency and returns, and providing funding allocation and expenditure recommendations.

[0081] The capital structure optimization and capital chain management include: regularly checking the balance of each account, automatically collecting funds into the main account, generating reports on abnormal or unauthorized transactions and notifying relevant personnel; collecting historical cash flow data, predicting short-term cash flow, and automatically generating cash flow analysis reports for decision-making; setting budget parameters based on historical performance, automatically allocating budgets and initiating approval processes, and tracking status; real-time monitoring of budget execution, comparing actual expenditures, identifying deviations, and automatically notifying relevant departments to take measures; automatically analyzing cost data, proposing cost reduction measures, tracking the effectiveness of measures, and ensuring the achievement of budget goals; evaluating the returns on investment projects, prioritizing expenditure projects, and recommending funding allocation plans based on priorities and funding conditions; identifying potential risks in cash flows, such as liquidity and credit risks, quantifying and analyzing the impact of risks, and proposing risk management strategies.

[0082] The daily marketing business management unit includes automatically executing tasks such as data entry and report generation; automatically collecting key data from different data sources, cleaning, formatting and verifying data, and establishing a central data warehouse; tracking key operating indicators in real time, automatically generating operating reports and exception reports; automatically monitoring risk factors and compliance changes; automatically responding to customer inquiries, providing information and answers, analyzing customer data, identifying needs, and automatically recommending products or services; analyzing resource needs and utilization efficiency, automatically adjusting resource allocation, and giving priority support to high-return projects; quickly acquiring market data, identifying investment trends, automatically tracking investment performance, and evaluating risks and returns; automatically reviewing contract terms to ensure compliance, tracking supplier performance, and automating procurement processes.

[0083] The technology development and intellectual property unit includes: regularly collecting technology research reports and industry trends, automatically analyzing potential technology trends, and generating analysis reports; automatically creating project plans based on demand, including schedules and budgets, tracking project progress in real time, and reporting deviations and potential risks; automatically tracking R&D costs, analyzing and proposing savings opportunities; using RPA tools to automatically archive and manage R&D documents to ensure information consistency; the automation platform collects employees' innovative ideas, screens potential ideas, and provides tools and resource support.

[0084] The market analysis and strategic planning unit includes: automatically collecting market data, including industry reports and consumer behavior, using data analysis tools to generate market trend reports; collecting and analyzing consumer feedback and social media comments, and using natural language processing technology to refine consumer insights; automatically collecting internal and external risk data, evaluating strategic decision-making risks, and formulating risk management plans; monitoring resource usage, automatically reallocating resources according to demand, tracking resource allocation effects, and optimizing configuration strategies; automatically collecting investment project data, using quantitative models for evaluation, providing investment analysis reports, and assisting decision-making; regularly collecting competitor data, analyzing market performance, adjusting company strategies, and formulating countermeasures.

[0085] The market development and customer relationship management unit includes automatically collecting customer information from multiple channels, integrating and building customer profiles, analyzing customer behavior, identifying needs and purchasing patterns; collecting industry reports and market data, analyzing market trends, generating target customer group descriptions, and assisting in market positioning; designing personalized marketing activities, automatically executing promotions, collecting performance data in real time, and adjusting marketing strategies; automatically processing common inquiries, improving response speed, regularly collecting customer feedback, and evaluating satisfaction; screening high-probability sales opportunities, updating sales pipelines, generating sales forecast reports, and assisting in sales strategy formulation; analyzing purchase history, identifying loyal customers, designing differentiated reward plans, and automatically executing reward distribution; monitoring competitor activities, collecting market feedback, and proposing market strategy adjustment suggestions; summarizing sales and market activity data, generating performance reports, and using machine learning to predict market trends and guide business direction.

[0086] Example 2, reference Figure 2 , 3 , which is an embodiment of the present invention, provides an integrated office method in the power field based on RPA technology.

[0087] The main purpose of the hierarchical structured framework design of the software system is to achieve independence and high cohesion and low coupling at each level, so as to facilitate the expansion and maintenance of the system. Figure 2 As shown, the specific design is as follows:

[0088] The monitoring layer is mainly responsible for data collection and preliminary processing. This layer uses a variety of equipment and technologies such as smart meters, sensors, surveillance cameras, satellite remote sensing and third-party data sources to obtain relevant business data of the power energy industry in real time. The monitoring equipment should have high precision, high reliability and good environmental adaptability to ensure the accuracy and timeliness of the data.

[0089] The transport layer is mainly responsible for data transmission and communication. This layer achieves efficient data access and interaction through mobile terminals, fiber-optic private networks, and operator Internet. The transmission protocol uses the TCP / IP protocol to ensure the stability and security of data transmission. In addition, encryption technology (such as SSL / TLS) can be used to protect data privacy and prevent data from being stolen or tampered with during transmission.

[0090] The computing layer is mainly responsible for data storage, computing and analysis. This layer uses the computing, storage and network resources of the cloud platform, combines "two libraries and one platform" (i.e. database, knowledge base and computing platform), and realizes efficient data processing through intelligent components such as graphical user interface (GUI) and application programming interface (API). The computing layer also supports RPA process design and management, provides service support, and ensures the flexibility and scalability of data processing.

[0091] The operation layer is mainly responsible for specific business operations and process automation. This layer includes substantive operations such as data collection, statistical analysis, report generation, and resource downloading. The operation layer connects to the application layer to clarify specific task requirements; it connects to the computing layer to drive the RPA digital workforce underlying processing system for analysis, calculation, and feedback. The design of the operation layer should focus on efficiency and accuracy to ensure the smooth operation of business processes.

[0092] The application layer is mainly responsible for realizing specific business functions and automated processes. This layer includes four modules and fifteen sub-functions: power energy trading and data analysis, distributed photovoltaic operation and electricity fee calculation, financial comprehensive management and risk assessment, and enterprise operation management and market development. The design of the application layer should focus on user experience and functional integrity to ensure that users can use the services provided by the system conveniently and quickly.

[0093] S1: Extract and process information data through the information collection technology of the front-end monitoring layer. The steps of the front-end information collection technology are as follows: Figure 3 shown.

[0094] Specifically including: 1. Setting of integrated development environment (IDE).

[0095] Install and configure IDE: Select a suitable RPA development tool. This system selects UiPath development and installs the corresponding IDE in the development environment.

[0096] Create a project: Create a new project in the IDE and define the project name, path, and other related configurations.

[0097] Develop automation scripts: Use the visual design tools or programming languages ​​(Python, C#, etc.) provided by the IDE to write automation scripts to simulate user interaction with the application.

[0098] 2. Application of user interface automation technology.

[0099] Element positioning: Positioning elements on the screen, such as buttons, text boxes, menus, etc., through user interface automation technology.

[0100] Simulate user operations: Write scripts to simulate user clicks, text input, option selection and other operations to achieve basic functions of automated operations.

[0101] Automatic form filling: Automatically fill in various items in the form, including text boxes, drop-down menus, check boxes, etc.

[0102] 3. Extraction and processing of information data.

[0103] Screen scraping technology: Use screen scraping technology to capture elements on the screen, such as tables, lists, etc.

[0104] Image recognition technology: Use image recognition technology to extract information from images, such as QR codes, barcodes, etc.

[0105] OCR technology: Use OCR technology to extract text information from documents in different formats (such as PDF, pictures, etc.).

[0106] Regular expression technology: Use regular expression technology to clean and verify the extracted data to ensure data accuracy and consistency. Regular expression is a pattern composed of common characters (such as letters and numbers) and special characters or symbols (called metacharacters). This pattern can be used to check whether a string contains a certain substring, replace the matching substring, or extract the part that meets certain conditions from a string.

[0107] 4. Mouse and keyboard processing driven by command information.

[0108] Parse instruction information: Parse the instruction information that needs to be executed from the automation script, such as clicking a button, entering text in a text box, etc.

[0109] Drive mouse and keyboard operations: According to the parsed command information, drive mouse clicks, movements, keyboard input and other operations to realize the operation and entry of user interface information.

[0110] 5. Implementation of application program interface (API) calling technology.

[0111] Define API interface: Define the API interface to be called according to business needs, and specify the interface URL, request method (GET / POST / PUT / DELETE, etc.) and request parameters.

[0112] Initiate API request: Use network communication technology to initiate API request and exchange data with external systems or services.

[0113] Process API responses: Receive API responses and process them, such as parsing JSON data, handling error responses, etc.

[0114] 6. Application of database interaction technology.

[0115] Establish a database connection: Use interactive technologies such as the database (Python's pymysql library, JavaScript's mysql library, etc.) to establish a connection with the database, and define the connection string and database operation commands.

[0116] Execute database operations: perform database query, insert, update, and delete operations according to business needs, and support complex business logic processing and data management.

[0117] Database result conversion: Process database query results and convert them into data structures suitable for subsequent processing.

[0118] 7. Use of network communication technology.

[0119] Process HTTP requests: Use network communication technology to process HTTP requests and support API calls and data exchange.

[0120] Data transmission and parsing: Implement data transmission and parsing to ensure the correct transfer and processing of data between different systems and services.

[0121] S2: Send the collected information data to the computing layer through the transport layer to complete the data calculation at the application layer.

[0122] In the computing layer, logs are generated according to the functional requirements of the application layer, and historical logs are periodically extracted and reviewed.

[0123] When extracting logs, select the log content generated between the last extracted log and the current time for random extraction; at the same time, add random perturbation ∈ during extraction, the value range of ∈ is between 0 and θ, and each time extraction occurs, there is a probability of ∈×100% to randomly extract all historical records.

[0124] Wherein, θ represents a preset disturbance threshold value, which is greater than 0 and less than 1; the number of extractions is the preset number U.

[0125] The extracted logs are classified through decision trees, and the completeness and content analysis of the logs of each classification result are performed.

[0126] The completeness evaluation includes setting mandatory and optional parts for each type of log. If a mandatory part is blank, the log is judged to be incomplete, and the incomplete log is marked as mark 1.

[0127] When analyzing the log content, the logs judged to be abnormal are marked as mark 2.

[0128] After completing the content analysis and completeness assessment of the onboarding log, all tags are identified and the tagged logs are output, while the tag type is displayed.

[0129] The log content analysis includes: assuming that each log contains multiple records, firstly performing word segmentation and part-of-speech tagging on each record, removing stop words and performing stem extraction to obtain a preprocessed result i.

[0130] Using the bag-of-words model and TF-IDF, features are extracted from the preprocessed text:

[0131] L i=TF-IDF(BagOfWords(Preprocess(i)))

[0132] Among them, i represents the i-th log, BagOfWords represents the bag-of-words model, and L i represents the features of the i-th log, and TF-IDF represents the term frequency-inverse document frequency model.

[0133] A bidirectional long short-term memory network is introduced to analyze the relationship between the previous and next log contents, and a Gaussian mixture model is used to perform probability distribution analysis.

[0134] BiLSTM(L t-1 ,L t ,L t+1 )

[0135] =Concat(LSTM forward (L t-1 ,L t ,L t+1 ),LSTM backward (L t+1 ,L t ,L t+1 ))

[0136] GMM is used to perform probability distribution analysis on the output of BiLSTM to determine the rationality of the log content.

[0137]

[0138] Among them, π k is the weight of the kth Gaussian component, μ k and Σ k are the mean and covariance matrices respectively; LSTM forward and LSTM backward are forward and backward LSTM, L t Represents the characteristics of the current moment, L t-1 Indicates the previous log feature of the same record target, L t+1 Indicates the next log feature of the same record target. is a Gaussian distribution, and K is the number of Gaussian components.

[0139] An adaptive analysis model based on Bayesian optimization is introduced to dynamically adjust the rationality of log content:

[0140]

[0141] Among them, x is the input variable; θ is the model parameter, and the model is optimized by maximizing the probability distribution of the log content;

[0142] Combining the various parts together, we get a comprehensive rationality analysis formula:

[0143] R′(L t )=BO(P(L t ))

[0144] Among them, R′(L t ) is the rationality evaluation result, and its value range is real number; if R′(L t )>0, then the content is judged to be normal; if R′(L t )≤0, the log content is considered abnormal.

[0145] S3: Connect the operation layer to the application layer to clarify specific task requirements; connect to the computing layer to drive the underlying processing system of the RPA digital workforce to perform analysis, calculation and feedback.

[0146] The information feedback is completed through the back-end information feedback technology. Specifically including:

[0147] ①Report generation

[0148] Functional requirements: The system should be able to generate different types of reports based on the input data.

[0149] System operation: Design report templates, support custom fields and formats. Implement report generation engine to extract data according to different business needs. Provide report export function, support multiple formats such as PDF and Excel.

[0150] ②Data analysis

[0151] Functional requirements: Conduct in-depth analysis of input data and generate analysis results.

[0152] System operation: Integrate the data mining tool SciPy to implement operations such as data classification and clustering. Develop a forecasting analysis module to use historical data to predict future trends. Implement trend analysis functions to identify data change patterns.

[0153] ③Chart display

[0154] Functional requirements: Provide a variety of chart types and support real-time updates and dynamic display.

[0155] System operation: Select the chart library Matplotlib, which supports line charts, bar charts, pie charts, etc. Realize dynamic binding between data and charts to ensure that charts can reflect data changes in real time. Provide interactive chart operations such as zooming, dragging, etc.

[0156] ④Automated operation

[0157] Functional requirements: Provide powerful automated operation functions to ensure that tasks are executed according to priorities and rules, and support task monitoring, suspension, continuation, and cancellation.

[0158] System operation: Design a task configuration interface to allow users to define task parameters and execution conditions. Implement a task scheduler to automatically execute tasks according to the configuration.

[0159] ⑤Real-time monitoring

[0160] Functional requirements: Provide real-time monitoring function to view currently running tasks and their status.

[0161] System operation: Develop a monitoring dashboard to display real-time data of system operation. Implement a task status update mechanism to ensure the real-time nature of monitoring data. Provide a task log function to record detailed information on task execution.

[0162] ⑥ Early warning mechanism

[0163] Functional requirements: Set up an early warning mechanism to promptly notify relevant personnel of system abnormalities.

[0164] System operation: define abnormal situations and warning rules. Implement warning system, monitor key indicators, trigger warning notifications. Integrate notification services such as email, SMS or real-time message push.

[0165] ⑦System Integration

[0166] Functional requirements: Ensure that the backend system can be seamlessly integrated with other systems or modules (such as process design and execution modules).

[0167] System operation: Design a unified API interface to realize the interaction between data and services. Implement a data synchronization mechanism to ensure data consistency between systems. Provide developer documentation and SDK to facilitate the integration of third-party systems or modules.

[0168] Through the design of back-end information feedback technology, the final result is presented in the system application layer, such as the relevant statistical tables and analysis reports for power energy trading and data analysis, full-cycle power generation monitoring and early warning of photovoltaic systems, etc.

[0169] If the above functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk and other media that can store program codes.

[0170] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute instructions), or in conjunction with such instruction execution systems, devices or apparatuses. For the purposes of this specification, "computer-readable medium" can be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in conjunction with such instruction execution systems, devices or apparatuses.

[0171] More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection with one or more wires (electronic device), a portable computer disk case (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be a paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, deciphering or, if necessary, processing in another suitable manner, and then stored in a computer memory.

[0172] It should be understood that the various parts of the present invention can be implemented by hardware, software, firmware or a combination thereof. In the above-mentioned embodiments, a plurality of steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0173] Example 3, the following is an embodiment of the present invention, which provides an integrated office system in the power field based on RPA technology. In order to verify the beneficial effects of the present invention, scientific demonstration is carried out through economic benefit calculation and simulation experiments.

[0174] Table 1 is a statistical table of the performance test of some functions of the system, among which function 1 is medium- and long-term electricity trading, function 2 is electricity consumption collection and data analysis, function 3 is financial data collection and analysis, and function 4 is daily marketing business management.

[0175] Table 1 Statistics of some functional performance tests of the system

[0176]

[0177] As shown in Table 1, all test functions achieved 100% accuracy, ensuring the reliability of task execution. The average response time was maintained at about 5 seconds, showing the system's ability to respond quickly to user requests. The average throughput index shows that the system has efficient data processing and data transmission capabilities. The system also performed well in resource utilization, with the CPU utilization rate remaining below 30%, which not only reflects the system's efficient use of computing resources, but also means that the system has enough margin to cope with higher workloads. In addition, the system achieved a good balance between performance and resource consumption, ensuring fast response and high throughput while effectively controlling resource utilization. Overall, the system's test results highlight its excellent performance in accuracy, response speed, throughput, resource utilization, and stability. It is a well-designed and efficient system.

[0178] System Benefit Analysis:

[0179] In order to deeply demonstrate the actual benefits of the four major functional modules and their 15 sub-functions implemented by this system, this paper conducts a detailed functional benefit comparison analysis between manual operation and RPA technology. Table 2 shows the statistical comparison of system functional benefits. The cost savings consider the percentage reduction between the labor remuneration that three people should pay for working eight hours a day until the work is completed and the average cost of the RPA system development and maintenance costs allocated to each module.

[0180] Table 2 System function and benefit comparison

[0181]

[0182]

[0183] As can be seen from the table above, the average time for manual calculation of the four modules of power energy trading and data analysis, distributed photovoltaic operation and electricity fee calculation, financial comprehensive management and risk assessment, and enterprise operation management and market development is 1951h, 1322h, 431h and 227.25h respectively, while the average time for RPA technology processing is 91.25h, 72.5h, 26.3h and 5.25h respectively. The average efficiency of each module is improved by 2886.75%, 1640.75%, 1532.67% and 3695.75% respectively, and the cost savings are 30.5%, 33.5%, 24.33% and 23.5% respectively. From the perspective of the entire system, the average time for manual calculation is 1019.6h, while the average time for RPA technology processing is 50.3h, the average efficiency improvement is 2499.4%, and the cost savings are 28.2%. From the perspective of individual functions, the 96-point electricity consumption monitoring and analysis function for enterprise users saves the most time, with an efficiency improvement of 8198%. The two functions of medium- and long-term electricity trading and photovoltaic system online monitoring and full-cycle management save the most costs, both by 43%. These data fully demonstrate the excellent performance of this system in improving enterprise operating efficiency and reducing operating costs.

[0184] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. An integrated office system in the power field based on RPA technology, characterized in that: include: Power energy trading and data analysis module, distributed photovoltaic operation and electricity fee calculation module, comprehensive financial management and risk assessment module, enterprise operation management and market development module; The power energy trading and data analysis module includes a 96-point power consumption detection and analysis unit for enterprise users, a medium- and long-term power trading unit, a green power green certificate trading unit, and a power spot trading unit; The distributed photovoltaic operation and electricity fee calculation module includes a photovoltaic system online monitoring and full-cycle management unit, a power consumption collection and data analysis unit, an electricity fee calculation and benefit analysis unit, and a customer service and technical support unit; The financial comprehensive management and risk assessment module includes a financial data collection and analysis unit, a cost calculation and investment return unit, and a capital structure optimization and capital chain management unit; The enterprise operation management and market development module includes a daily marketing business management unit, a technology development and intellectual property unit, a market analysis and strategic planning unit, and a market development and customer relationship management unit.

2. The integrated office system for the electric power field based on RPA technology according to claim 1, characterized in that: The enterprise user's 96-point electricity consumption detection and analysis unit includes an RPA robot that monitors the enterprise's electricity consumption in real time, checks data integrity and abnormal values, and performs data deduplication and formatting; Use algorithms to identify abnormal fluctuations in power consumption patterns, set power consumption thresholds based on past data, and trigger alarms; set different levels of warnings, verify warning levels, and ensure timely notification of relevant personnel; automatically generate daily, weekly, and monthly power consumption reports, and provide graphical power consumption data displays; The medium- and long-term electricity trading unit includes using RPA robots to collect and analyze market data, understand market demand and price dynamics, analyze historical transaction data, assess potential risks, and formulate risk control measures; automatically generate standardized electricity purchase and sales contracts based on preset templates and rules, and automatically check the integrity and compliance of contract terms; automatically match the needs of buyers and sellers on the electricity trading platform, execute transactions, and automatically record detailed transaction data; automatically use optimization algorithms to distribute electricity, improve energy efficiency, regularly monitor electricity distribution, and adjust deviations in a timely manner to ensure supply and demand balance; automatically complete financial settlement after the transaction, including invoice processing and payment transfer, and automatically check the accounts of all parties to the transaction; The green electricity and green certificate trading unit includes: automatically collecting market demand information for green electricity and green certificates, analyzing user needs, and providing data support for trading strategies; automatically matching buyers and sellers on the trading platform, executing transactions, automatically recording transaction details, and providing data support; tracking and managing the generation and trading of green certificates, real-time monitoring of the validity period of green certificates, and reminding renewal or redemption; automatically performing financial settlement after the transaction is completed, performing benefit accounting, and evaluating the economic and environmental benefits of the transaction; real-time updating of compliance with green electricity trading regulations, regular transaction audits, and generating compliance reports; The power spot trading unit includes automatically collecting factors that affect power prices, such as historical trading data, weather forecasts, etc., and using machine learning algorithms to predict power price trends; Based on the market and electricity price forecast results, simulate different trading strategies, evaluate benefits and risks, and adjust strategies to minimize risks and maximize benefits; automatically quote and inquire on the electronic trading platform, and automatically record key information such as transaction volume and price after the transaction is completed; monitor market prices and news events in real time, and quickly adjust trading strategies according to market changes; after the transaction is completed, automatically settle with the power exchange and calculate the transaction results according to financial standards.

3. The integrated office system for the electric power field based on RPA technology as claimed in claim 2, characterized in that: The photovoltaic system online monitoring and full-cycle management unit includes: real-time automatic collection of photovoltaic panel operation data, preliminary data verification, and elimination of anomalies or errors; analysis of operation data, automatic identification of faults or performance degradation signs, generation of early warning information, notification of operation and maintenance personnel, and prediction of potential faults using historical data; regular evaluation of photovoltaic system power generation efficiency and component performance, analysis of performance trends, identification of degradation patterns, and generation of performance analysis reports; automatic creation and dispatching of maintenance tasks based on maintenance plans and fault detection results, real-time tracking of task execution, and intelligent deployment of maintenance resources; monitoring of the use of photovoltaic components and equipment, recording replacement and maintenance requirements, managing the entire life cycle of equipment, and automatically updating configuration and performance parameters; automatic generation of daily operation and maintenance reports based on collected data and analysis results, providing customized reports, and automatically distributing them to relevant personnel; The power consumption collection and data analysis unit includes: automatically collecting real-time power generation data, including current, voltage, temperature, etc., verifying the data format and content, and integrating data from different sources or formats;: calculating power generation in real time based on the inverter, gateway table and grid cabinet data, screening abnormal data and marking; Calculate system losses and adjust power generation efficiency according to loss trends; collect and compare gateway meters and grid-connected cabinet data, evaluate operating results, and record net power generation; automatically match applicable electricity prices, adjust electricity price data in real time, save historical electricity price data, and support long-term cost-benefit analysis; calculate direct economic benefits of photovoltaic projects, analyze revenue trends, identify factors affecting revenue, and generate revenue reports; calculate operating costs, combine revenue and cost data, and evaluate economic benefits; Automatically compile comprehensive reports of power calculation, revenue analysis, and cost analysis, and systematically manage and archive report files; The electricity cost accounting and benefit analysis includes automatically collecting power generation data and performing quality control, eliminating inaccurate data, and summarizing power data in different time periods; automatically determining the applicable electricity price based on the real-time electricity price and contract terms, identifying the time period corresponding to the power generation, and applying the corresponding electricity price; Establish an electricity fee calculation model, perform batch electricity fee calculation, and perform internal logic verification after the calculation is completed; automatically deduct operation and maintenance costs and update financial records; automatically determine the applicable tax rate, calculate the tax payable, and generate tax reports and documents; analyze electricity prices, simulate electricity fee benefits, predict the benefits under different strategies, and automatically adjust strategies; automatically generate electricity bills based on the calculation results, automatically review the bills and ensure accuracy, and send them to customers electronically; automatically track customer payment status, confirm on-time payment, send reminders to customers who have not paid on time, and after confirming the recovery, confirm the collection and update financial records in the system; Said customer service and technical support includes automatic updating and verification of customer and PV system information; Automatically respond to customer inquiries through multiple channels, provide system information, and refer complex issues; automatically receive and record fault reports, conduct preliminary analysis, and notify the maintenance team; Record service requests, automate approval processes, and provide real-time progress updates; automatically remind customers according to maintenance plans, record maintenance activities and update status; regularly generate and send customized performance reports to customers.

4. The integrated office system for the electric power field based on RPA technology as claimed in claim 3, characterized in that: The financial data collection and analysis unit automatically collects data from data sources such as accounting, sales, and bank accounts, performs data verification and cleaning, and eliminates errors and duplicate data; automatically records accounts based on data, automatically generates accounting vouchers, and identifies and adjusts accounting anomalies; collects and analyzes cost data, compares it with the budget, calculates deviations, and automatically warns management when costs exceed thresholds; tracks and records all income streams, automatically matches contract terms, analyzes income trends, and provides support for business development decisions; automatically calculates taxes and fees according to tax laws, completes tax returns, and prepares documents and data required for tax audits; automatically generates standard financial reports and customized analysis reports, and automatically sends reports to shareholders, management, and other stakeholders; automatically checks the compliance of financial activities, maintains audit tracking records, runs risk assessment procedures, and identifies and reports financial risks; monitors cash inflows and outflows, maintains funding status, conducts financial and business forecast analysis, and makes funding and investment recommendations; The cost calculation and investment return unit includes: automatically collecting cost data from multiple systems, classifying it, analyzing historical trends, and identifying cost saving opportunities; automatically generating budgets based on historical and forecast data, monitoring actual expenditures, and identifying deviations; automatically calculating the rate of return on different investment projects, comparing the ROI of multiple projects, assessing risks, and assisting investment decisions; automatically executing cost reduction strategies, tracking implementation results, and regularly generating cost control reports for management decision-making; analyzing contract terms, identifying savings points, reminding renewal time, monitoring contract execution, and ensuring that suppliers fulfill their commitments; evaluating supplier quotations, recommending the best procurement options, and automating procurement processes; Monitor energy consumption, analyze usage efficiency, and evaluate the cost-effectiveness of energy-saving measures; Track capital expenditure project status and budget usage, prioritize investments based on project urgency and returns, and provide funding allocation and spending recommendations; The capital structure optimization and capital chain management include: regularly checking the balance of each account, automatically collecting funds to the main account, generating reports on abnormal or unauthorized transactions and notifying relevant personnel; collecting historical cash flow data, predicting short-term cash flow, and automatically generating cash flow analysis reports for decision-making; setting budget parameters based on historical performance, automatically allocating budgets and starting approval processes, and tracking status; real-time monitoring of budget execution, comparing actual expenditures, identifying deviations, and automatically notifying relevant departments to take measures; automatically analyzing cost data, proposing cost reduction measures, tracking the effectiveness of measures, and ensuring the achievement of budget goals; evaluating the return on investment projects, prioritizing expenditure projects, and recommending funding allocation plans based on priorities and funding conditions; Identify potential risks in capital flows, such as liquidity and credit risks, quantify and analyze the risk impact, and propose risk management strategies.

5. The integrated office system for the electric power field based on RPA technology as claimed in claim 4, characterized in that: The daily marketing business management unit includes automatically performing tasks such as data entry and report generation; Automatically collect key data from different data sources, clean, format and verify data, and establish a central data warehouse; track key operating indicators in real time, automatically generate operating reports and exception reports; automatically monitor risk factors and compliance changes; automatically respond to customer inquiries, provide information and answers, analyze customer data, identify needs, and automatically recommend products or services; analyze resource needs and utilization efficiency, automatically adjust resource allocation, and give priority to high-return projects; quickly obtain market data, identify investment trends, automatically track investment performance, and evaluate risks and returns; automatically review contract terms to ensure compliance, track supplier performance, and automate procurement processes; The technology development and intellectual property unit includes regularly collecting technology research reports and industry trends, automatically analyzing potential technology trends, and generating analysis reports; Automatically create project plans based on demand, including timetables and budgets, track project progress in real time, and report deviations and potential risks; automatically track R&D costs, analyze and propose savings opportunities; use RPA tools to automatically archive and manage R&D documents to ensure information consistency; The automated platform collects employees’ innovative ideas, screens potential ideas, and provides tools and resource support; The market analysis and strategic planning unit includes automatically collecting market data, including industry reports and consumer behavior, and using data analysis tools to generate market trend reports; Collect and analyze consumer feedback and social media comments, and use natural language processing technology to extract consumer insights; Automatically collect internal and external risk data, assess strategic decision-making risks, and develop risk management plans; Monitor resource usage, automatically reallocate resources according to demand, track resource allocation results, and optimize allocation strategies; automatically collect investment project data, use quantitative models for evaluation, provide investment analysis reports, and assist in decision-making; regularly collect competitor data, analyze market performance, adjust company strategies, and formulate countermeasures; The market development and customer relationship management unit includes automatically collecting customer information from multiple channels, integrating and building customer profiles, analyzing customer behavior, identifying needs and purchasing patterns; collecting industry reports and market data, analyzing market trends, generating target customer group descriptions, and assisting in market positioning; designing personalized marketing activities, automatically executing promotions, collecting effect data in real time, and adjusting marketing strategies; automatically processing common inquiries, improving response speed, regularly collecting customer feedback, and evaluating satisfaction; screening high-probability sales opportunities, updating sales pipelines, generating sales forecast reports, and assisting in sales strategy formulation; Analyze purchase history, identify loyal customers, design differentiated reward plans, and automatically execute reward distribution; monitor competitor activities, collect market feedback, and make suggestions for market strategy adjustments; Aggregate sales and marketing activity data, generate performance reports, and use machine learning to predict market trends and guide business direction.

6. An integrated office method in the electric power field based on RPA technology using the system as claimed in any one of claims 1 to 5, characterized in that: Extract and process information data through the information collection technology of the front-end monitoring layer; The collected information data is sent to the computing layer through the transmission layer to complete the data calculation of the application layer; The operation layer connects to the application layer to clarify specific task requirements; the computing layer connects to the bottom layer to drive the RPA digital workforce underlying processing system for analysis, calculation and feedback. The application layer is responsible for implementing specific business functions and automated processes. Its functions are completed through four major modules and fifteen sub-functional units, namely power energy trading and data analysis, distributed photovoltaic operation and electricity fee calculation, comprehensive financial management and risk assessment, and enterprise operation management and market development.

7. The integrated office method in the electric power field based on RPA technology as claimed in claim 6, characterized in that: In the computing layer, logs are generated according to the functional requirements of the application layer, and historical logs are periodically extracted and reviewed; When extracting logs, select the log content generated between the last extracted log and the current time and perform random extraction; at the same time, add random perturbation ∈ during extraction, where the value range of ∈ is between 0 and θ. Each time an extraction is performed, there is a probability of ∈×100% to randomly extract all historical records; Wherein, θ represents the preset disturbance threshold, which is greater than 0 and less than 1; the number of extractions is the preset number U; The extracted logs are classified through decision trees, and the completeness and content analysis of the logs of each classification result are performed; The completeness evaluation includes setting mandatory and optional parts for each type of log. If a mandatory part is blank, the log is judged to be incomplete, and the incomplete log is marked as mark 1; When analyzing the log content, the logs judged to be abnormal are marked as mark 2; After completing the content analysis and completeness assessment of the onboarding log, all tags are identified and the tagged logs are output, while the tag type is displayed.

8. The integrated office method in the electric power field based on RPA technology as claimed in claim 7, characterized in that: The log content analysis includes: assuming that each log contains multiple records, firstly, performing word segmentation and part-of-speech tagging on each record, removing stop words and performing stem extraction to obtain a preprocessed result i; Using the bag-of-words model and TF-IDF, features are extracted from the preprocessed text: L i =TF-IDF(BagOfWords(Preprocess(i))) Among them, i represents the i-th log, BagOfWords represents the bag-of-words model, and L i represents the features of the i-th log, TF-IDF represents the term frequency-inverse document frequency model; A bidirectional long short-term memory network is introduced to analyze the relationship between the previous and next log contents, and a Gaussian mixture model is used to perform probability distribution analysis. BiLSTM(L t-1 ,L t ,L t+1 )=Concat(LSTM forward (L t-1 ,L t ,L t+1 ),LSTM backward (L t+1 ,L t ,L t+1 )) Use GMM to perform probability distribution analysis on the output of BiLSTM to determine the rationality of the log content; Among them, π k is the weight of the kth Gaussian component, μ k and Σ k are the mean and covariance matrices respectively; LSTM forward and LSTM backward are forward and backward LSTM, L t Represents the characteristics of the current moment, L t-1 Indicates the previous log feature of the same record target, L t+1 Represents the next log feature of the same record target, N is the Gaussian distribution, and K is the number of Gaussian components; An adaptive analysis model based on Bayesian optimization is introduced to dynamically adjust the rationality of log content: Among them, x is the input variable; θ is the model parameter, and the model is optimized by maximizing the probability distribution of the log content; Combining the various parts together, we get a comprehensive rationality analysis formula: R′(L t )=BO(P(L t )) Among them, R′(L t ) is the rationality evaluation result, and its value range is real number; if R′(L t )>0, then the content is judged to be normal; if R′(L t )≤0, the log content is considered abnormal.

9. A computer device comprising: Memory and processor; The memory stores a computer program, characterized in that: when the processor executes the computer program, the steps of an integrated office method in the power field based on RPA technology are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of an integrated office method in the power field based on RPA technology are implemented.

Images