A new energy power transaction collaborative operation method of light storage integration

Abstract

The application relates to the technical field of light storage transaction, and discloses a light storage integrated new energy power transaction collaborative operation method, which comprises the following steps: collecting multi-source data required for light storage transaction collaborative operation, forming access data, performing quality checking, data cleaning, data completion and standardization processing on the access data, constructing a history library, generating operation day prediction results, market conditions and light storage combined available capacity data based on the processed data, forming a medium and long-term time-sharing transaction basic curve and a pre-adjustment holding basic data according to a typical decomposition curve, a transaction time-sharing account, a medium and long-term holding amount, a power generation plan power and a holding plan power, and generating a recommended position, a to-be-adjusted power and a light storage combined day-ahead declaration power. The application unifies the multi-source data caliber, and uses the operation day prediction results, the market conditions and the light storage combined available capacity data for generating the recommended position, the to-be-adjusted power and the light storage combined day-ahead declaration power, so that the adjustment declaration and real-time correction form a processing process.

Description

Technical Field

[0001] This invention relates to the field of photovoltaic-storage trading technology, specifically to a collaborative operation method for integrated photovoltaic-storage new energy power trading. Background Technology

[0002] As the scale of distributed photovoltaic (PV) projects and energy storage systems connected to power users increases, PV and energy storage resources are gradually participating in medium- and long-term transactions, day-ahead transactions, and real-time clearing. In the existing PV and energy storage trading operations, power trading data, grid metering data, PV operation data, energy storage operation data, and external environmental data typically come from different sources, and their collection cycles, data fields, and time granularities are not entirely consistent. If these are directly incorporated into daily forecasting and trading strategy calculations, it can easily lead to inconsistencies in the data definitions of daily load forecasts, electricity price forecasts, combined PV and energy storage availability data, and trading position data.

[0003] In the current trading decision-making process, medium- and long-term holdings, planned power generation, and planned holdings are often treated separately as basic data on the trading side. The amount of photovoltaic power available for trading and the adjustable capacity of energy storage are often treated separately as operational data on the resource side. There is a lack of continuous and coordinated calculation between market conditions, daily forecasts, combined photovoltaic and energy storage capacity data, and pre-adjustment holdings data. Consequently, the resulting suggested positions, pending adjustments, and adjusted holdings data fail to simultaneously reflect trading-side holding demand, daily load changes, electricity price changes, and the adjustable capacity of photovoltaic and energy storage resources, affecting the matching of pre-dated photovoltaic and energy storage joint power generation and joint operation plans.

[0004] In the clearing feedback process, day-ahead clearing results, actual execution data for the operating day, real-time clearing results, deviation data, and settlement trial calculation results are often processed in a fragmented manner. Day-ahead reported deviations, actual execution deviations, and real-time deviations are difficult to promptly feed back to the strategy correction process for subsequent operating days. Due to the lack of a closed-loop method covering data governance, forecasting calculations, photovoltaic-storage capacity calculations, rebalancing applications, real-time corrections, and settlement feedback, insufficient coordination between reported electricity volume, cleared electricity volume, and actual execution electricity volume is prone to occur when photovoltaic and energy storage jointly participate in power trading. Therefore, constructing a collaborative operation method for integrated photovoltaic and energy storage new energy power trading that can unify multi-source data standards, collaboratively generate rebalancing application results, and provide feedback corrections based on clearing and execution results is a problem that needs to be solved in this field. Summary of the Invention

[0005] To address the shortcomings of existing technologies, this invention provides a collaborative operation method for integrated photovoltaic and energy storage new energy power trading, which solves the problems of inconsistent data standards from multiple sources, insufficient connection between rebalancing declarations and the combined availability of photovoltaic and energy storage capacity, and difficulty in using clearing feedback for subsequent daily strategy adjustments in existing photovoltaic and energy storage trading operations.

[0006] To address the above problems, the present invention provides the following technical solution:

[0007] This invention provides a method for collaborative operation of photovoltaic-storage integrated new energy power trading, employing the following technical solution:

[0008] A collaborative operation method for integrated photovoltaic and energy storage renewable energy power trading includes the following steps:

[0009] Collect multi-source data required for the collaborative operation of photovoltaic and energy storage transactions to form access data. Perform quality verification, data cleaning, data completion and standardization on the access data, and build a historical database to obtain the processed data.

[0010] Based on the treated data, daily operation forecasts, market conditions, and combined photovoltaic and energy storage availability data are generated.

[0011] Based on the typical decomposition curve, the time-sharing trading ledger, the medium- and long-term open positions, the planned power generation and the planned open positions, the basic curve for medium- and long-term time-sharing trading and the basic data of open positions before the adjustment are formed.

[0012] Based on the market conditions, the forecast results for the operating day, the available capacity data of the photovoltaic and energy storage joint operation, the medium- and long-term time-sharing trading base curve, and the basic data of the holdings before the adjustment, a suggested position is generated. Based on the suggested position, the amount of electricity to be adjusted is generated. Based on the amount of electricity to be adjusted, the adjusted holdings data, the declared amount of electricity for the photovoltaic and energy storage joint operation, and the photovoltaic and energy storage joint operation plan are generated.

[0013] Based on the day-ahead declared electricity volume of the photovoltaic-storage joint project, the photovoltaic-storage joint operation plan, the day-ahead clearing results, the actual execution data of the operation day, and the real-time clearing results, real-time corrections are made to generate deviation data and settlement trial calculation results, and the deviation data and the settlement trial calculation results are used for strategy correction on subsequent operation days.

[0014] By adopting the above technical solutions, multi-source data governance, operation day forecasting, photovoltaic and energy storage resource capacity calculation, medium- and long-term time-sharing transaction processing, portfolio adjustment declaration and clearing feedback are incorporated into the same methodology, so that transaction-side data, forecast-side data and resource-side data are processed in a unified manner according to the time-sharing period of the operation day.

[0015] Meanwhile, it is recommended that the position, pending power volume, jointly declared power volume, and operation plan be generated in the same link, and that corrections and feedback be made after the day-ahead clearing, the operation day execution, and the real-time clearing. This can reduce the data disconnect between the declaration results and the actual execution results, and improve the collaborative operation capability of photovoltaic and energy storage joint participation in power trading.

[0016] Furthermore, the multi-source data required for the collaborative operation of photovoltaic and energy storage transactions includes:

[0017] The access data is formed by integrating power trading business data, power grid metering data, photovoltaic operation data, energy storage operation data, and external environmental data.

[0018] Configure the data source, service type, collection time, time period, data unit, and data value fields for the access data;

[0019] The access data is collected according to the time period of the operating day.

[0020] By adopting the above technical solutions, power trading business data, power grid metering data, photovoltaic operation data, energy storage operation data, and external environment data can be organized according to unified fields and time periods, avoiding inconsistencies in data caliber caused by different collection cycles and different data sources being directly entered into subsequent calculations.

[0021] Furthermore, the quality verification, data cleaning, data completion, standardization processing, and construction of the historical database include:

[0022] The access data is subjected to integrity verification, continuity verification, consistency verification, value range verification, and abnormal fluctuation verification to obtain data quality verification results;

[0023] Based on the data quality verification results, missing data, out-of-bounds data, and abnormal data are corrected to obtain corrected data values;

[0024] The corrected data value is standardized, and the original data value, the corrected data value, and the standardized data value are written into the historical database.

[0025] By adopting the above technical solution, the access data undergoes quality verification and correction processing before entering the prediction and strategy calculations. The historical database simultaneously retains the original data values, corrected data values, and standardized data values, enabling subsequent daily forecasting, photovoltaic storage capacity calculations, and settlement feedback to access a traceable data foundation.

[0026] Furthermore, the generation of the daily forecast results and the market conditions includes:

[0027] Retrieved load data, electricity price data, transaction data, market disclosure data, and external environment data after the governance process from the historical database;

[0028] Combine daily input data to form predicted input data;

[0029] Based on the predicted input data, generate daily load forecast results, electricity price forecast results, and similar day data;

[0030] The market situation is generated based on the load forecast results for the operating day, the electricity price forecast results, and the similar day data.

[0031] By adopting the above technical solution, the load forecast results, electricity price forecast results, and similar day data can be used together to generate market conditions, so that the subsequent recommended positions do not only rely on static position data, but are calculated by combining the load changes, electricity price changes, and characteristics of historical similar trading days.

[0032] Furthermore, the generation of the combined optical and energy storage availability data includes:

[0033] The amount of photovoltaic power that can be traded is determined based on the power generation metering data, grid connection metering data, and self-consumption metering data of distributed photovoltaic projects.

[0034] Based on the energy storage state of charge, maximum energy storage charging power, maximum energy storage discharging power, energy storage charging efficiency, energy storage discharging efficiency, upper limit of energy storage state of charge, and lower limit of energy storage state of charge, determine the rechargeable energy storage capacity and the rechargeable energy storage capacity, and form the energy storage adjustable capability.

[0035] The combined photovoltaic and energy storage availability data is generated based on the photovoltaic power available for trading and the energy storage adjustable capacity.

[0036] By adopting the above technical solutions, the photovoltaic power available for trading and the energy storage adjustable capacity can be transformed into photovoltaic and energy storage combined available capacity data that can be called upon for trading decisions. This makes subsequent suggested position calculations, allocation of power to be adjusted, and joint applications simultaneously subject to the constraints of photovoltaic output capacity and energy storage charging and discharging capacity.

[0037] Furthermore, the formation of the medium-to-long-term intraday trading baseline curve and the pre-adjustment position baseline data includes:

[0038] Read the typical decomposition curve, peak-to-valley ratio, and transaction time-sharing ledger to form time-sharing transaction parameters;

[0039] The basic electricity volume for medium- and long-term time-of-use trading is generated based on the monthly trading volume and the time-of-use allocation ratio.

[0040] The pre-adjustment position data is formed based on the medium- and long-term holdings, the planned power generation, and the planned power generation.

[0041] By adopting the above technical solution, the monthly trading volume can be converted into the medium- and long-term time-sharing trading base volume in the time-sharing time period dimension according to the typical decomposition curve, peak-to-valley ratio and trading time-sharing ledger, and form the basis for rebalancing calculation with the medium- and long-term open positions, the planned power generation volume and the planned open positions volume.

[0042] Furthermore, the generation of the suggested position, the amount of electricity to be adjusted, and the adjusted position data includes:

[0043] The organization adjusts its portfolio input data, which includes the medium- and long-term holdings, the planned power generation, the planned power holdings, the daily load forecast results, the electricity price forecast results, the photovoltaic power available for trading, the energy storage rechargeable capacity, and the energy storage dischargeable capacity.

[0044] The suggested position is generated based on the rebalancing input data;

[0045] The proposed position is used to generate the power volume to be adjusted and the adjusted position data.

[0046] By adopting the above technical solution, the input data for rebalancing simultaneously includes the trading side's holding plan, the forecast side's load electricity price results, and the resource side's photovoltaic and energy storage capacity data. The recommended holdings can reflect the synergistic relationship between holding demand, daily forecasts, and photovoltaic and energy storage regulation capabilities, and form the amount of electricity to be rebalanced and the adjusted holding data.

[0047] Furthermore, the generation of the day-ahead electricity declaration for the photovoltaic-storage joint project and the photovoltaic-storage joint operation plan includes:

[0048] Based on the power to be adjusted, the photovoltaic power available for trading, the energy storage rechargeable capacity, and the energy storage dischargeable capacity, allocate the photovoltaic grid connection power, the energy storage charging power, and the energy storage discharging power.

[0049] When the amount of electricity to be adjusted is greater than 0, the amount of photovoltaic electricity that can participate in the trading will be used first, and the insufficient part will be made up by the amount of electricity arranged by the energy storage discharge within the range of the energy storage discharge capacity;

[0050] When the amount of energy to be adjusted is less than 0, the energy storage charging arrangement amount is formed within the range of the energy storage rechargeable amount.

[0051] When the amount of electricity to be adjusted is 0, no warehouse adjustment requirement will be generated in the corresponding time period.

[0052] The photovoltaic-storage joint day-ahead declaration of electricity is generated based on the medium- and long-term holdings, the photovoltaic grid connection arrangement of electricity, the energy storage discharge arrangement of electricity, and the energy storage charging arrangement of electricity, and the photovoltaic-storage joint operation plan is generated.

[0053] By adopting the above technical solution, the power to be adjusted can be allocated according to the photovoltaic power available for trading, the energy storage rechargeable capacity, and the energy storage dischargeable capacity. The power declared by the photovoltaic and energy storage joint day-ahead is generated based on the medium and long-term holdings and the photovoltaic and energy storage execution arrangements, avoiding duplicate inclusion of suggested positions and resource arrangements.

[0054] Furthermore, the real-time correction includes:

[0055] Receive the day-ahead clearing result and compare the day-ahead cleared electricity with the day-ahead declared electricity of the photovoltaic-storage joint project to obtain the day-ahead declaration deviation;

[0056] The photovoltaic and energy storage joint operation plan will be revised based on the aforementioned reported deviations.

[0057] The actual execution power is generated based on the actual grid-connected power of photovoltaic power, the actual discharge power of energy storage, and the actual charging power of energy storage.

[0058] The actual executed electricity volume is compared with the day-ahead cleared electricity volume to obtain the actual executed deviation;

[0059] The real-time correction charging capacity and real-time correction discharging capacity are determined based on the actual execution deviation.

[0060] By adopting the above technical solution, the day-ahead clearing power, the day-ahead declared power of photovoltaic-storage joint operation, and the actual executed power can be continuously compared within the operating day. The system corrects the photovoltaic-storage joint operation plan based on the day-ahead declaration deviation and the actual execution deviation, so that the energy storage charging and discharging correction can participate in deviation control.

[0061] Furthermore, the deviation data, the settlement trial calculation results, and the strategy corrections for subsequent operating days include:

[0062] Calculate the real-time deviation power based on the real-time clearing results and the day-ahead clearing power;

[0063] Calculate the two-part trial result and the three-part trial result based on the adjusted position data, the day-ahead clearing result and the real-time clearing result;

[0064] The photovoltaic operation settlement result is calculated based on the actual on-grid power of the photovoltaic system, and the energy storage operation settlement result is calculated based on the actual discharge power of the energy storage system and the actual charging power of the energy storage system.

[0065] The reported deviation, actual execution deviation, real-time deviation electricity, two-part trial calculation result, three-part trial calculation result, photovoltaic operation settlement result, and energy storage operation settlement result are written into the historical database and used for strategy correction on subsequent operating days.

[0066] By adopting the above technical solutions, real-time deviation electricity, two-part trial calculation results, three-part trial calculation results, photovoltaic operation settlement results, and energy storage operation settlement results can be written back into the historical database together with the day-ahead reported deviation and actual execution deviation, providing feedback basis for data governance, forecast calculation, and rebalancing application for subsequent operating days.

[0067] This invention provides a method for collaborative operation of integrated photovoltaic and energy storage renewable energy power trading. It has the following beneficial effects:

[0068] 1. This invention collects multi-source data required for the collaborative operation of photovoltaic and energy storage transactions to form access data. The access data undergoes quality verification, data cleaning, data completion, and standardization. A historical database is constructed, enabling the generation of daily forecast results, market conditions, and photovoltaic and energy storage joint availability data based on the regulated data. It also provides a data source for generating suggested positions, pending power adjustments, and daily reported power for photovoltaic and energy storage joint operations.

[0069] 2. This invention generates suggested positions based on market conditions, daily forecast results, combined photovoltaic and energy storage capacity data, medium- and long-term time-sharing trading curves, and pre-adjustment position data. It then generates the power to be adjusted and the adjusted position data based on the suggested positions, enabling medium- and long-term positions, planned power generation, planned power holdings, and combined photovoltaic and energy storage capacity data to participate in the position adjustment.

[0070] 3. This invention generates deviation data and settlement trial results by making real-time corrections based on the day-ahead declared electricity volume of the photovoltaic-storage joint operation plan, day-ahead clearing results, actual execution data of the operation day, and real-time clearing results. The deviation data and settlement trial results are then used for strategy correction on subsequent operation days. Attached Figure Description

[0071] Figure 1 This is a framework diagram of the photovoltaic-storage integrated new energy power trading and collaborative operation system according to an embodiment of the present invention;

[0072] Figure 2 This is a flowchart of the photovoltaic-storage integrated new energy power trading and collaborative operation method according to an embodiment of the present invention;

[0073] Figure 3 This is a flowchart illustrating the multi-source data acquisition and management process according to an embodiment of the present invention.

[0074] Figure 4 This is a flowchart illustrating the prediction of operating days and the generation of adjustable photovoltaic-storage capabilities according to an embodiment of the present invention.

[0075] Figure 5 This is a flowchart illustrating the generation process of the medium-to-long-term intraday trading base curve and rebalancing base data in an embodiment of the present invention.

[0076] Figure 6 This is a flowchart illustrating the generation process of photovoltaic-storage collaborative inventory adjustment suggestions and joint application strategies in an embodiment of the present invention.

[0077] Figure 7 This is a flowchart illustrating the clearing response, real-time correction, and settlement feedback process according to an embodiment of the present invention.

[0078] Figure 8 This is a comparison chart of the net execution deviation amplitude spectrum of embodiments of the present invention;

[0079] Figure 9This is a comparison chart of the energy storage correction power amplitude spectrum according to an embodiment of the present invention. Detailed Implementation

[0080] The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0081] The specific embodiments of the present invention will be further described below with reference to the accompanying drawings. These specific embodiments are used to illustrate the technical solutions of the present invention and do not limit the scope of protection of the present invention. Under non-conflicting conditions, the technical features in the specific embodiments can be combined with each other.

[0082] See attached document Figure 1 The integrated photovoltaic and energy storage new energy power trading collaborative operation system includes a data governance module, an intelligent forecasting module, a photovoltaic and energy storage operation module, a trading decision module, and a clearing feedback module.

[0083] The photovoltaic-storage integrated new energy power trading collaborative operation system is deployed on the power user distributed service platform or industrial internet platform, and connects to photovoltaic side metering and acquisition equipment, energy storage side metering and acquisition equipment, platform server, database and external business system interfaces.

[0084] Photovoltaic-side metering and acquisition equipment is used to collect electricity generation and consumption metering data from distributed photovoltaic projects. Energy storage-side metering and acquisition equipment is used to collect charging and discharging metering data and operational status data from energy storage systems.

[0085] The platform server runs data processing programs, forecasting programs, trading strategy calculation programs, and settlement trial programs. The database stores basic business data, forecasting results data, trading strategy data, clearing results data, settlement results data, and historical operational data.

[0086] The external business system interface is used to connect to the grid-side system, trading center system, group marketing system, spot trading auxiliary decision-making system, industrial internet platform, and external information data sources. The system obtains power trading business data, grid metering data, market disclosure data, and external environmental data through the external business system interface.

[0087] The data governance module is used to complete multi-source data access, data quality processing, and historical data accumulation. The data governance module includes a data acquisition unit, a data verification unit, and a data storage unit.

[0088] The data acquisition unit is used to access power trading business data, power grid metering data, photovoltaic operation data, energy storage operation data and external environmental data, and to form data to be verified according to data source, business type and time granularity.

[0089] The data verification unit is used to check the integrity, continuity, consistency, value range and abnormal fluctuations of the data to be verified, and outputs data to be put into the database that meets the unified data caliber.

[0090] The data entry unit is used to write the data to be entered into the corresponding historical database, so that subsequent prediction calculations, resource capacity calculations, transaction strategy calculations and settlement trials are performed based on a unified data standard.

[0091] The intelligent forecasting module generates forecast results and market analysis results required for collaborative transaction decisions based on the data output by the data governance module. The intelligent forecasting module includes a load forecasting unit, an electricity price forecasting unit, a similar day unit, and a strategy support unit.

[0092] The load forecasting unit generates load forecast results for each time period of the operating day. The electricity price forecasting unit generates medium- and long-term forecast electricity prices, day-ahead forecast electricity prices, real-time forecast electricity prices, and day-ahead real-time price difference forecast results.

[0093] The Similar Day unit is used to select similar day data from historical trading days based on the characteristics of the operating day. The Strategy Assist unit is used to generate input data for strategy calculation based on the forecast results, similar day data, and market information.

[0094] The photovoltaic (PV) and energy storage (ESD) operation module manages distributed PV and ESD resources and calculates the trading capacity of these resources for each time period of the operating day. The module includes a PV operation unit, an ESD operation unit, and a capacity calculation unit.

[0095] The photovoltaic operation unit is used to maintain the photovoltaic project ledger, photovoltaic commissioning information, photovoltaic equipment ledger and photovoltaic operation data, and to determine the amount of photovoltaic power that can be traded based on the power generation and consumption metering data of distributed photovoltaic projects.

[0096] The energy storage operation unit is used to maintain the energy storage project ledger, energy storage power monitoring data, energy storage equipment operation data and energy storage performance data, and to determine the energy storage adjustability based on the current energy storage power status, charge and discharge metering data and equipment operation status.

[0097] The capacity calculation unit is used to generate combined photovoltaic and energy storage available capacity data based on the photovoltaic power available for trading and the energy storage adjustable capacity.

[0098] The transaction decision module is used to generate portfolio adjustment suggestions, position adjustment results, and joint application strategies for photovoltaic and energy storage based on the output data of the intelligent prediction module and the photovoltaic and energy storage operation module, combined with medium- and long-term time-sharing transaction data.

[0099] The trading decision module includes a parameter processing unit, a position processing unit, a position rebalancing calculation unit, a position adjustment unit, and a report generation unit.

[0100] The parameter processing unit is used to process typical decomposition curves, peak-to-valley ratios, and time-of-day transaction ledgers, and to generate medium- and long-term time-of-day transaction base data for each time period of the operating day. The time-of-day transaction ledger records monthly electricity consumption, daily decomposed electricity consumption, and electricity consumption for each time period.

[0101] The position processing unit is used to process medium- and long-term position volume, power generation plan, position plan, adjusted position and position summary data, and form the basic position data before position adjustment.

[0102] The portfolio adjustment calculation unit generates suggested positions based on market conditions, forecasts, combined solar and energy storage capacity data, and pre-adjustment position data. The position adjustment unit calculates the amount of electricity to be adjusted based on the suggested positions and current medium- to long-term positions, and generates adjusted position data.

[0103] The declaration generation unit is used to generate the day-ahead declaration of photovoltaic-storage combined electricity volume and the photovoltaic-storage combined operation plan based on the adjusted holding data, photovoltaic-storage combined available capacity data and electricity price forecast results.

[0104] The clearing feedback module processes day-ahead clearing results, real-time clearing results, settlement trial results, and strategy feedback data. The clearing feedback module includes a day-ahead response unit, a real-time response unit, a settlement trial unit, a strategy feedback unit, and a dashboard archiving unit.

[0105] The day-ahead response unit is used to revise the photovoltaic-storage joint operation plan based on the day-ahead clearing results and generate day-ahead reported deviation data. The real-time response unit is used to calculate the real-time deviation power based on the real-time clearing results and the actual execution data of the operation day, and to revise the actual photovoltaic operation data and the actual energy storage operation data.

[0106] The settlement trial calculation unit is used to calculate the two-part trial calculation results and the three-part trial calculation results based on medium- and long-term position data, day-ahead clearing results and real-time clearing results, as well as to calculate the photovoltaic operation settlement results and the energy storage operation settlement results.

[0107] The strategy feedback unit is used to feed back the prediction deviation, declaration deviation, real-time deviation electricity and settlement results to the intelligent prediction module, the photovoltaic and energy storage operation module and the transaction decision module.

[0108] The dashboard archiving unit is used to display operational dashboard data and archive transaction strategy data, clearing data, settlement calculation data, photovoltaic operation data, and energy storage operation data.

[0109] See attached document Figure 2 The integrated photovoltaic and energy storage new energy power trading and collaborative operation method includes the following steps:

[0110] S100: Collect and manage multi-source data required for the collaborative operation of photovoltaic and energy storage transactions, and perform quality verification, data cleaning, data completion, standardization processing, and historical database construction on the access data;

[0111] S200: Based on the treated data, generate daily forecast results and adjustable photovoltaic and energy storage capacity, and obtain daily load forecast results, electricity price forecast results, similar day data, photovoltaic power available for trading, energy storage adjustable capacity, and photovoltaic and energy storage combined availability data.

[0112] S300: Construct medium- and long-term intraday trading basic curves and generate basic data for position adjustment. Based on typical decomposition curves, intraday trading ledgers, medium- and long-term open positions, power generation plans and open position plans, form medium- and long-term intraday trading basic curves and basic data for open positions before position adjustment for each intraday period of the operating day.

[0113] S400 generates suggestions for coordinated photovoltaic and energy storage rebalancing and joint application strategies. Based on market conditions, forecast results, data on the combined availability of photovoltaic and energy storage capacity, and the basic data on the holdings before rebalancing, it generates suggested positions, the amount of electricity to be adjusted, the holdings data after adjustment, the amount of electricity to be applied for before the photovoltaic and energy storage joint application, and the photovoltaic and energy storage joint operation plan for each time period of the operation day.

[0114] S500 performs real-time corrections, settlement calculations, and feedback optimizations based on the clearing results. It corrects the photovoltaic-storage joint operation plan based on the clearing results of the day before, calculates deviation data and settlement calculation results based on the actual execution data and real-time clearing results of the operation day, and uses the deviation data and settlement calculation results for strategy corrections on subsequent operation days.

[0115] The specific implementation process of S100 to S500 is explained below.

[0116] See attached document Figure 3 In step S100, external business data, metering data, and internal platform business data involved in the collaborative operation of photovoltaic and energy storage transactions are processed into data with unified time granularity, unified business caliber, and quality status records. The data processed by S100 is used to support subsequent daily forecasting, photovoltaic and energy storage capacity calculation, transaction strategy generation, clearing analysis, and settlement feedback.

[0117] S101 The data governance module accesses power trading business data, power grid metering data, photovoltaic operation data, energy storage operation data and external environment data, and configures the data source, business type, collection time, time period, data unit and data value fields for the accessed data.

[0118] Data sources are distinguished by different business systems or collection devices; business types are distinguished by the business links corresponding to the data; collection time records the data generation time; time-segmentation is aligned with the transaction period of the operating day; data units participate in dimensional verification; and data value fields record the numerical values ​​obtained from collection.

[0119] For data collected over different periods, the data governance module aggregates the data according to the time period of the operating day, so that data within the same operating day can participate in subsequent processing according to the same time period.

[0120] S102. The data governance module performs data quality verification on the accessed data. Data quality verification includes integrity verification, continuity verification, consistency verification, value range verification, and abnormal fluctuation verification.

[0121] The integrity check determines whether required fields have empty values; the continuity check determines whether there are gaps in the time periods of the running day; and the consistency check determines whether the correspondence of the same business object is consistent in different data sources.

[0122] Value range verification determines whether the original data value is within the business-permitted range, and abnormal fluctuation verification determines whether the original data value deviates from historical statistical characteristics.

[0123] The data governance module calculates anomaly detection values ​​based on raw data values, historical mean, and historical standard deviation:

[0124] ;

[0125] in, Index for data types; For time-segment indexes; Indexing data types Time-segmented index The corresponding anomaly detection value; Indexing data types Time-segmented index The corresponding original data value; Indexing data types The corresponding historical average; Indexing data types Corresponding historical standard deviation; This is the absolute value operator.

[0126] The data governance module determines the data validity flag by combining the business-permissible range and the anomaly judgment threshold. When the original data value is within the business-permissible range and the anomaly judgment value is not higher than the anomaly judgment threshold, the data validity flag is set to 1; when the original data value exceeds the business-permissible range, or the anomaly judgment value is higher than the anomaly judgment threshold, the data validity flag is set to 0.

[0127] S103. The data governance module corrects missing, out-of-bounds, and abnormal data based on the data quality verification results. For data that passes the verification, the data governance module retains the original data values.

[0128] For data that fails validation but passes validation in both the preceding and following time slots, the data governance module uses the average of the original data values ​​from the adjacent time slots. For data that fails validation and does not meet the correction conditions in adjacent time slots, the data governance module uses the average of historical samples of the same data type and the same time slot.

[0129] After data correction, the data governance module retains the original data value, the corrected data value, and the data validity marker, enabling the data processing process to be traced.

[0130] S104. The data governance module standardizes the corrected data values ​​and writes the original data values, corrected data values, standardized data values, data validity markers, data sources, business types, and time periods into the historical database.

[0131] Corrected data values ​​are used in business calculations, standardized data values ​​are used in forecasting and strategy calculations, and data quality status is effectively marked and recorded. The historical database organizes data according to transaction business, load power, photovoltaic operation, energy storage operation, clearing results, and strategy results.

[0132] Subsequent steps retrieve data from the historical database based on the operating day, time period, and business type. If the historical standard deviation is 0, the data governance module retains the corrected data value for business calculation and records a preset standard value for the standardized data value.

[0133] For data interface communication, authorization authentication, database writing, and historical database table structure management, those skilled in the art can implement these functions using conventional data integration methods based on the deployment platform. The specific implementations are well-known technologies in this field and will not be elaborated upon here.

[0134] See attached document Figure 4 In step S200, based on historical data after treatment and input data for operating days, the system generates forecast results for operating days, similar day data, photovoltaic power available for trading, energy storage adjustable capacity, and combined photovoltaic and energy storage availability data. The data generated in S200 provides input for subsequent construction of medium- and long-term time-sharing trading baseline curves, calculation of portfolio adjustment suggestions, and generation of joint application strategies.

[0135] S201 The intelligent forecasting module reads the post-treatment load data, electricity price data, transaction business data, market disclosure data and external environment data from the historical database, and combines them with the daily input data to form forecast input data.

[0136] The forecast input data includes historical load, historical electricity price, generation capacity, electricity demand, meteorological factors, maintenance plans, corridor constraints, market supply and demand, and external economic factors related to the trading day.

[0137] The intelligent forecasting module calculates the forecast input data using time-of-use (TOU) granularity, generating load forecast results, medium- and long-term forecast electricity prices, day-ahead forecast electricity prices, and real-time forecast electricity prices for each TOU on the operating day. The generated forecast results are incorporated into subsequent load adjustment input data and participate in the calculation of suggested load positions and the generation of joint photovoltaic-storage application strategies.

[0138] S202. The intelligent forecasting module generates similar day data based on the characteristics of the operating day and historical trading days. The characteristics of the operating day include weather characteristics, date attributes, load characteristics, supply and demand characteristics, and historical price characteristics.

[0139] Historical trading day characteristics use the same data caliber as operational day characteristics. The intelligent prediction module calculates the similarity between operational day characteristics and historical trading day characteristics, and uses historical trading days with similarity reaching the screening threshold as similar day data. Similar day data is used for operational day prediction result verification, market situation analysis, and subsequent reporting strategy generation.

[0140] The intelligent prediction module calculates similarity using the following formula:

[0141] ;

[0142] in, Index for historical trading days; For feature index; The number of features; Index of historical trading days Corresponding similarity; For feature index The corresponding feature weights; The first day corresponding to the running day One eigenvalue; Index of historical trading days The corresponding number One eigenvalue; This is the summation operator.

[0143] When similarity When the number of days is not less than the similarity day screening threshold, the intelligent prediction module will index the historical trading days. The corresponding historical transaction day records are considered similar day data. When the similarity is normalized to 0-1, the similar day screening threshold ranges from 0.70 to 0.90.

[0144] S203, the photovoltaic and energy storage operation module determines the photovoltaic power available for trading in each time period of the operating day based on the power generation metering data, grid connection metering data and self-consumption metering data of the distributed photovoltaic project.

[0145] During time-of-use periods, the amount of photovoltaic (PV) electricity eligible for trading is based on PV grid connection metering data. When grid connection metering data for the operating day has not yet been generated, the PV-storage operation module calculates the amount of PV electricity eligible for trading based on the predicted PV power generation and the predicted PV self-consumption.

[0146] The amount of photovoltaic power available for trading is calculated using the following formula:

[0147] ;

[0148] in, Time-based index The corresponding photovoltaic power that can be traded; For time-segment index Corresponding photovoltaic power generation forecast; Time-based index The corresponding photovoltaic power generation and self-consumption forecast; It is a function for maximizing the value.

[0149] S204. The photovoltaic-storage operation module calculates the adjustable capacity of energy storage based on the energy storage power status, maximum energy storage charging power, maximum energy storage discharging power, energy storage charging efficiency, energy storage discharging efficiency, and the upper and lower limits of energy storage power status.

[0150] Energy storage adjustable capacity includes both rechargeable and dischargeable energy storage capacity. The photovoltaic-energy storage operation module combines the tradeable photovoltaic power with the adjustable energy storage capacity to form photovoltaic-energy storage transmission capacity and energy storage absorption capacity. The photovoltaic-energy storage transmission capacity is obtained by combining the tradeable photovoltaic power with the dischargeable energy storage capacity, while the energy storage absorption capacity is determined by the rechargeable energy storage capacity.

[0151] The energy storage rechargeable capacity of the photovoltaic-storage operation module is calculated using the following formula:

[0152] ;

[0153] in, For time-segment index The corresponding rechargeable energy storage capacity; This represents the maximum charging power for energy storage. The duration is divided into time slots; This represents the upper limit of the energy storage capacity. For time-segment index The energy storage status corresponding to the previous time period; To improve energy storage charging efficiency; It is a minimum value function.

[0154] The energy storage operation module can be calculated for its energy storage discharge capacity using the following formula:

[0155] ;

[0156] in, For time-segment index The corresponding energy storage discharge capacity; This represents the maximum discharge power of the energy storage. The duration is divided into time slots; For time-segment index The energy storage status corresponding to the previous time period; This is the minimum energy storage capacity. This refers to the energy storage and discharge efficiency.

[0157] For load forecasting models, electricity price forecasting models, similar day screening algorithms, and energy storage adjustability calculations, those skilled in the art can implement them using conventional neural network models, regression models, time series models, or rule models, depending on the data scale and deployment environment. The specific training process and model deployment methods are well-known technologies in this field and will not be elaborated here.

[0158] See attached document Figure 5 In the S300 step, based on trading parameters, monthly trading volume, medium- and long-term open positions, power generation plans, and open position plans, the basic medium- and long-term time-sharing trading curves for each time period of the operating day and the basic open position data before position adjustment are generated. The data generated by S300 provides trading-side input for subsequent suggested position calculations, calculations of the volume to be adjusted, and generation of joint reporting strategies.

[0159] S301 The transaction decision module reads typical decomposition curves, peak-to-valley ratios, and transaction time-sharing ledgers, and generates time-sharing transaction parameters according to the operating day and time period.

[0160] A typical decomposition curve represents the distribution of monthly traded electricity volume across different time periods on a given operating day. The peak-to-valley ratio determines the decomposition weight for different electricity price periods. The time-of-use transaction ledger records monthly electricity volume, daily decomposed electricity volume, and time-of-use electricity volume.

[0161] The transaction decision module matches typical decomposition curves, peak-to-valley ratios, and transaction time-sharing ledgers according to the same operating day and the same time period, so that each time period of the operating day has corresponding time-sharing transaction parameters.

[0162] S302. The transaction decision module generates the basic medium- and long-term time-of-use transaction volume for each time period of the operating day based on the monthly transaction volume and the time-of-use breakdown ratio.

[0163] For transaction contracts with a fixed monthly trading volume, the transaction decision module decomposes the monthly trading volume to the corresponding time period of the operating day based on the time-sharing decomposition ratio of each time period in the typical decomposition curve.

[0164] The time-of-use allocation ratio is normalized across all time periods on the operating day to ensure that the sum of the electricity obtained from each time period is consistent with the monthly transaction electricity.

[0165] The trading decision module calculates the basic electricity volume for medium- and long-term time-of-use trading using the following formula:

[0166] ;

[0167] in, For time-segment index The corresponding medium- and long-term time-of-use trading base electricity volume; Monthly transaction volume; For time-segment index The corresponding time-sharing breakdown ratio. The time-sharing breakdown ratio on the operating day. The total value within each time period is 1. This refers to the number of time slots on a given day.

[0168] S303, the trading decision module integrates medium- and long-term holdings, planned power generation, and planned power holdings, and forms basic holding data before rebalancing according to the operating day and time period.

[0169] The trading decision module associates the medium- and long-term open positions, planned power generation, planned open positions, and basic power volume for medium- and long-term time-of-use trading. The association process is executed on the same operating day and in the same time period.

[0170] S304. The trading decision module calculates the basic deviation based on the pre-adjustment position data. The basic deviation includes the power generation plan deviation and the position plan deviation. The power generation plan deviation is obtained by subtracting the medium- and long-term position from the planned power generation, and the position plan deviation is obtained by subtracting the medium- and long-term position from the planned position.

[0171] The trading decision module uses the basic deviation, trading parameters, forecast results, and combined photovoltaic and energy storage availability data as inputs for subsequent recommended position calculations. When the power generation plan deviation is greater than 0, the planned power generation for the corresponding time period is higher than the medium- and long-term holdings; when the holding plan deviation is greater than 0, the planned power generation for the corresponding time period is higher than the medium- and long-term holdings.

[0172] For data reading from the transaction time-sharing ledger, maintenance of typical decomposition curves, import of monthly transaction volume, and time-sharing matching, those skilled in the art can achieve this using conventional data processing methods based on the transaction center's data format and platform database structure. The specific interface configuration and field mapping are well-known technologies in this field and will not be elaborated here.

[0173] See attached document Figure 6 In the S400 step, based on market conditions, forecast results, available capacity data of photovoltaic and energy storage combined, and basic data of holding positions before rebalancing, the recommended positions, the amount of electricity to be adjusted, the adjusted holding data, the amount of electricity declared before the photovoltaic and energy storage combined operation day and the photovoltaic and energy storage combined operation plan are generated for each time period of the operation day.

[0174] S401, the trading decision module organizes the rebalancing input data according to the operating day and time period. The rebalancing input data includes medium- and long-term open positions, planned power generation, planned power holdings, load forecast results, medium- and long-term forecasted electricity prices, day-ahead forecasted electricity prices, real-time forecasted electricity prices, photovoltaic power available for trading, energy storage rechargeable capacity, and energy storage dischargeable capacity.

[0175] The transaction decision module links transaction-side data, prediction-side data, and photovoltaic-storage resource-side data within the same time period, so that each time period corresponds to a complete set of strategy input data.

[0176] For data lacking records for the same time period, the trading decision module uses corrected data values ​​generated by the data governance module for calculation. Data exceeding its validity period is not used as strategy input data for the current trading day.

[0177] S402, the trading decision module generates suggested positions based on the rebalancing input data. The suggested positions are based on the medium- to long-term holdings and are adjusted in conjunction with the planned power generation, the planned power holdings, the load forecast results, and the day-ahead real-time price difference.

[0178] The current real-time price difference is converted into an electricity volume adjustment amount using a price difference adjustment factor. The upper limit of the recommended position is defined by the amount of photovoltaic (PV) electricity available for trading and the amount of energy storage that can be discharged; the lower limit is defined by the amount of energy storage that can be charged. These boundary limitations ensure that the recommended position is matched with the operational capacity of solar and energy storage resources.

[0179] The trading decision module calculates the reference position using the following formula:

[0180] ;

[0181] in, For time-segment index Corresponding reference position; This is a correction factor for the power generation plan; This is the adjustment factor for the position holding plan; This is the load forecast correction factor; This is the price difference correction factor; For time-segment index Corresponding medium- to long-term holdings; For time-segment index The corresponding planned power generation volume; For time-segment index Corresponding holding plan electricity volume; For time-segment index The corresponding load forecast results; For time-segment index Corresponding real-time predicted electricity price; For time-segment index The corresponding day-ahead forecast electricity price.

[0182] The trading decision module calculates the recommended position size using the following formula:

[0183] ;

[0184] in, For time-segment index Corresponding recommended position size; For time-segment index Corresponding medium- to long-term holdings; For time-segment index The corresponding photovoltaic power that can be traded; For time-segment index The corresponding energy storage discharge capacity; For time-segment index The corresponding rechargeable energy storage capacity; For time-segment index Corresponding reference position; It is a function for maximizing the value; It is a minimum value function.

[0185] Inner layer Used to determine the lower boundary of the recommended position, outer layer Used to set reference position Not lower than the lower limit of the recommended position size. This is used to ensure that the recommended position does not exceed the upper boundary formed by combining the medium- and long-term holdings, the tradable electricity volume of photovoltaic power, and the discharge volume of energy storage power.

[0186] S403 The trading decision module calculates the amount of electricity to be adjusted based on the suggested position and the medium- and long-term holdings, and determines the buy or sell demand for each time period of the operating day based on the amount of electricity to be adjusted.

[0187] When the amount of electricity to be adjusted is greater than 0, there is a need to increase holdings or buy electricity during the corresponding time period; when the amount of electricity to be adjusted is less than 0, there is a need to decrease holdings or sell electricity during the corresponding time period; when the amount of electricity to be adjusted is equal to 0, there is no need to adjust holdings during the corresponding time period.

[0188] The trading decision module updates the adjusted position data for the current time period based on the amount of electricity to be adjusted. The adjusted position data is consistent with the recommended position and serves as the trading basis for the joint reporting strategy.

[0189] S404 The transaction decision module allocates photovoltaic grid connection arrangement power, energy storage charging arrangement power and energy storage discharging arrangement power according to the power to be adjusted, the photovoltaic power available for trading, the energy storage chargeable power and the energy storage dischargeable power.

[0190] When the amount of electricity to be adjusted is greater than 0, the transaction decision module will prioritize the use of photovoltaic electricity that can be traded, and any shortfall will be made up by the energy storage discharge within the range of the energy storage's discharge capacity.

[0191] When the amount of electricity to be adjusted is less than 0, the trading decision module generates the energy storage charging arrangement amount within the range of available energy storage chargeable capacity. The trading decision module generates the day-ahead declaration amount of the photovoltaic-storage joint project based on the medium- and long-term holdings, the photovoltaic grid-connected arrangement amount, the energy storage discharge arrangement amount, and the energy storage charging arrangement amount.

[0192] The transaction decision module calculates the photovoltaic grid connection allocation electricity using the following formula:

[0193] ;

[0194] in, For time-segment index The corresponding photovoltaic grid connection arrangement electricity volume; For time-segment index The corresponding photovoltaic power that can be traded; For time-segment index Corresponding recommended position size; For time-segment index The corresponding medium- to long-term holdings.

[0195] The transaction decision module calculates the energy storage discharge arrangement power using the following formula:

[0196] ;

[0197] in, For time-segment index The corresponding energy storage discharge arrangement capacity; For time-segment index The corresponding energy storage discharge capacity; For time-segment index Corresponding recommended position size; For time-segment index Corresponding medium- to long-term holdings; For time-segment index The corresponding photovoltaic grid connection power generation.

[0198] The transaction decision module calculates the energy storage charging schedule using the following formula:

[0199] ;

[0200] in, For time-segment index The corresponding energy storage charging capacity; For time-segment index The corresponding rechargeable energy storage capacity; For time-segment index Corresponding medium- to long-term holdings; For time-segment index The corresponding recommended position size.

[0201] The transaction decision module calculates the day-ahead declared electricity volume of the photovoltaic-storage joint project using the following formula:

[0202] ;

[0203] in, For time-segment index The corresponding photovoltaic and energy storage joint day-ahead declaration of electricity volume; For time-segment index Corresponding medium- to long-term holdings; For time-segment index The corresponding photovoltaic grid connection arrangement electricity volume; For time-segment index The corresponding energy storage discharge arrangement capacity; For time-segment index The corresponding energy storage charging capacity.

[0204] The photovoltaic and energy storage joint venture recently declared electricity volume based on medium- and long-term holdings, plus the execution arrangements for photovoltaic and energy storage, to avoid double counting of recommended positions and resource arrangements.

[0205] The photovoltaic-storage joint operation plan includes the suggested storage capacity, pending power adjustment, photovoltaic grid connection arranged power, energy storage charging arranged power, energy storage discharging arranged power, and photovoltaic-storage joint day-ahead declared power for each time period of the operation day.

[0206] The transaction decision module writes the photovoltaic-storage joint operation plan into the transaction strategy record and uses the day-ahead declaration of photovoltaic-storage joint electricity volume for day-ahead declaration.

[0207] The configuration of correction coefficients, the format of declaration curve generation, and the submission of transaction declaration data in the suggested position calculation can be achieved by those skilled in the art using conventional parameter maintenance and data submission methods based on the rules of the trading center and the platform business configuration. The specific implementation is a well-known technology in the field and will not be elaborated here.

[0208] See attached document Figure 7 In step S500, the photovoltaic-storage joint operation plan is revised based on the day-ahead clearing results, the actual execution data of the operation day, and the real-time clearing results. The settlement trial results are calculated, and the deviation data and settlement trial results are used as the data basis for subsequent operation day strategy revisions.

[0209] S501 The clearing feedback module receives the day-ahead clearing results and compares the day-ahead cleared electricity with the day-ahead declared electricity of the photovoltaic and energy storage joint project to obtain the day-ahead declaration deviation.

[0210] When the daily cleared electricity volume is higher than the electricity volume declared by the photovoltaic and energy storage joint day before, the clearing feedback module increases the photovoltaic and energy storage execution electricity volume arrangement for the corresponding time period; when the daily cleared electricity volume is lower than the electricity volume declared by the photovoltaic and energy storage joint day before, the clearing feedback module decreases the photovoltaic and energy storage execution electricity volume arrangement for the corresponding time period.

[0211] The clearing feedback module uses the cleared electricity from the previous day as the revised planned electricity for the operating day, so that the execution data for the operating day is based on the clearing results from the previous day.

[0212] S502, the clearing feedback module obtains the actual grid-connected power of photovoltaic power, the actual charging power of energy storage, and the actual discharging power of energy storage on the operating day, and calculates the actual executed power based on the actual grid-connected power of photovoltaic power, the actual discharging power of energy storage, and the actual charging power of energy storage.

[0213] The actual executed electricity volume reflects the net execution result of the operating day, which is jointly generated by photovoltaic grid connection, energy storage discharge, and energy storage charging. The clearing feedback module compares the actual executed electricity volume with the cleared electricity volume of the previous day to obtain the actual execution deviation.

[0214] When the actual executed electricity volume is higher than the day-ahead cleared electricity volume, the actual execution deviation is greater than 0; when the actual executed electricity volume is lower than the day-ahead cleared electricity volume, the actual execution deviation is less than 0.

[0215] S503, the clearing feedback module determines the real-time correction charging amount and the real-time correction discharging amount based on the actual execution deviation, the rechargeable amount of stored energy, and the discharging amount of stored energy.

[0216] When the actual execution deviation is greater than 0, the clearing feedback module adds energy storage charging arrangements within the range of rechargeable energy storage capacity; when the actual execution deviation is less than 0, the clearing feedback module adds energy storage discharging arrangements within the range of rechargeable energy storage capacity.

[0217] The clearing feedback module adds the actual charging amount of the energy storage to the real-time corrected charging amount to obtain the corrected energy storage charging amount; it also adds the actual discharging amount of the energy storage to the real-time corrected discharging amount to obtain the corrected energy storage discharging amount. The corrected energy storage charging and discharging amounts are then used in the subsequent settlement trial calculation process.

[0218] S504 The clearing feedback module receives the real-time clearing results and calculates the two-part trial calculation results, the three-part trial calculation results, and the photovoltaic storage operation settlement results based on the day-ahead clearing results, the real-time clearing results, and the actual execution data.

[0219] The real-time clearing result includes the real-time cleared electricity volume and the real-time cleared electricity price. The clearing feedback module calculates the real-time deviation electricity volume based on the real-time cleared electricity volume and the day-ahead cleared electricity volume.

[0220] The clearing feedback module calculates the real-time deviation power using the following formula:

[0221] ;

[0222] in, For time-segment index The corresponding real-time deviation power; For time-segment index The corresponding real-time clearing power; For time-segment index The corresponding amount of electricity cleared up the day before.

[0223] The two-part settlement trial results are calculated based on the medium- and long-term settlement prices, recommended positions, day-ahead clearing electricity prices, and day-ahead clearing volumes.

[0224] The clearing feedback module calculates the two-part trial result using the following formula:

[0225] ;

[0226] in, The results are from a two-part trial calculation. This refers to the number of time slots on a given day. For time-segment index The corresponding medium- and long-term settlement prices; For time-segment index Corresponding recommended position size; For time-segment index The corresponding day-ahead clearing electricity price; For time-segment index The corresponding day-to-day cleared volume; This is the summation operator.

[0227] The three-part trial calculation results are superimposed with the real-time deviation settlement results on the two-part trial calculation results.

[0228] The clearing feedback module calculates the three-part trial result using the following formula:

[0229] ;

[0230] in, This is the result of a three-part system trial calculation; The results are from a two-part trial calculation. This refers to the number of time slots on a given day. For time-segment index The corresponding real-time clearing electricity price; For time-segment index The corresponding real-time deviation in power consumption.

[0231] The photovoltaic operation settlement result is calculated based on the photovoltaic settlement price and the actual on-grid electricity generated by the photovoltaic system.

[0232] The clearing feedback module calculates the photovoltaic operation settlement results using the following formula:

[0233] ;

[0234] in, For photovoltaic operation settlement results; This refers to the number of time slots on a given day. For time-segment index The corresponding photovoltaic settlement price; For time-segment index The corresponding actual on-grid electricity generated by photovoltaic power generation.

[0235] The settlement results for energy storage operations are calculated based on the real-time clearing price, the adjusted energy storage discharge volume, the day-ahead clearing price, and the adjusted energy storage charging volume.

[0236] The clearing feedback module calculates the energy storage operation settlement results using the following formula:

[0237] ;

[0238] in, For energy storage operation settlement results; This refers to the number of time slots on a given day. For time-segment index The corresponding real-time clearing electricity price; For time-segment index The corresponding corrected energy storage discharge capacity; For time-segment index The corresponding day-ahead clearing electricity price; For time-segment index The corresponding corrected energy storage charging capacity.

[0239] The clearing feedback module writes the day-ahead reported deviation, actual execution deviation, real-time deviation electricity, two-part trial calculation results, three-part trial calculation results, photovoltaic operation settlement results, and energy storage operation settlement results into the historical database.

[0240] The deviation data and settlement trial results in the historical database are incorporated into the data governance, forecast calculation, suggested position calculation, and energy storage charging and discharging arrangement processes for subsequent operating days. The intelligent forecasting module corrects the forecast input data based on historical deviation data, the trading decision module adjusts the position correction coefficient based on historical settlement results, the photovoltaic-storage operation module corrects the energy storage adjustable capacity calculation parameters based on energy storage execution deviations, and the clearing feedback module corrects the plan adjustment rules for subsequent operating days based on historical clearing deviations, forming a feedback loop between forecasting, trading, photovoltaic-storage operation, and clearing settlement.

[0241] Importing clearing results, configuring settlement rules, generating trial balances, and displaying dashboards can be achieved by those skilled in the art using conventional data processing methods based on the clearing statement format of the trading center and the platform's business configuration. The specific implementation is a well-known technology in this field and will not be elaborated here.

[0242] Specific application examples:

[0243] To better understand the technical solution of this invention, the following description, in conjunction with specific application scenarios and accompanying drawings, further illustrates the invention. This specific application embodiment is built upon an integrated photovoltaic-storage new energy power trading collaborative operation system in an industrial park. This system operates within a distributed service platform for power users, connecting a 6MW distributed photovoltaic system, a 2MW / 5.6MWh energy storage system, photovoltaic-side metering and acquisition equipment, energy storage-side metering and acquisition equipment, the trading center system, and the grid-side system. It is responsible for acquiring time-of-use transaction ledgers, photovoltaic operation data, energy storage operation data, historical load data, electricity price data, and clearing result data. It also performs data governance, predictive calculations, photovoltaic-storage capacity calculations, rebalancing applications, clearing corrections, and a closed-loop settlement feedback process.

[0244] During the phase of generating photovoltaic (PV) electricity eligible for trading, the PV operating unit extracts the predicted PV power generation and predicted self-consumption PV power for the 48th time-of-use period of the operating day. The parameters are set as follows: Predicted PV power generation. The projected self-consumption capacity of photovoltaic power is 1.800 MWh. The value is 0.550 MWh. The photovoltaic operating unit substitutes the values ​​into the formula to calculate the photovoltaic power available for trading. :

[0245] ;

[0246] Substitute the values ​​into the calculation:

[0247] ;

[0248] The results show that the system obtained 1.250 MWh of photovoltaic (PV) electricity available for trading. Since the calculated result is greater than 0, the PV operating unit determined that there was tradable PV electricity during this time period and wrote 1.250 MWh into the PV operation data record. This result is then incorporated into the PV-storage joint availability capacity calculation process for subsequent recommendations on allocation limits and PV grid connection power allocation.

[0249] During the energy storage adjustability generation phase, the energy storage operation unit extracts the energy storage state of being (SSO), maximum charging power, maximum discharging power, upper limit of SSO, lower limit of SSO, charging efficiency, and discharging efficiency. The parameters are set as follows: Maximum charging power... The maximum discharge power of the energy storage is 2.000MW. It is 2.000MW, with time-of-use durations. The upper limit of the energy storage state is 0.25h. The energy storage capacity is 5.600MWh, which is the minimum capacity limit. The energy storage capacity is 0.800MWh, corresponding to the previous time period. It has a capacity of 4.200MWh and an energy storage charging efficiency of [missing information]. The energy storage discharge efficiency is 0.950. The value is 0.940. The energy storage operating unit substitutes the values ​​into the formula to calculate the rechargeable energy storage capacity. :

[0250] ;

[0251] Substitute the values ​​into the calculation:

[0252] ;

[0253] The energy storage operating unit is substituted into the formula to calculate the discharge capacity of the energy storage. :

[0254] ;

[0255] Substitute the values ​​into the calculation:

[0256] ;

[0257] The results show that the system obtained a chargeable and dischargeable energy storage capacity of 0.500 MWh. Since the calculation results are within the constraints of the energy storage rated power and energy storage state of being, the energy storage operation unit determines that it has bidirectional adjustment capability during this time period and transmits the calculation results to the transaction decision module.

[0258] During the pre-declaration generation phase of the photovoltaic-storage joint declaration, the trading decision module calculates the pre-declared electricity volume for the photovoltaic-storage joint declaration by combining medium- and long-term holdings, recommended positions, photovoltaic grid connection arrangements, energy storage discharge arrangements, and energy storage charging arrangements. The parameters are set as follows: medium- and long-term holdings. The recommended position size is 2.000MWh. The grid-connected power generation is 2.270 MWh. The energy storage discharge capacity is 0.270 MWh. The energy storage charging capacity is 0MWh. The value is 0 MWh. The transaction decision module uses the formula to calculate the day-ahead declared electricity volume of the photovoltaic-storage joint project. :

[0259] ;

[0260] Substitute the values ​​into the calculation:

[0261] ;

[0262] The results show that the combined photovoltaic and energy storage day-ahead declaration volume obtained by the system is 2.270 MWh. This result is based on medium- to long-term holdings plus the execution arrangements for photovoltaic and energy storage, and does not double-count the suggested positions and resource arrangements, which is consistent with the declaration volume generation logic in the specific implementation method. The trading decision module writes 2.270 MWh into the trading strategy record and uses it for day-ahead declaration.

[0263] To verify the accuracy and stability of the photovoltaic-storage coordinated slack-off and real-time deviation correction mechanism in system operation, the system selected historical data from 30 consecutive operating days of the industrial park for comparison. The comparison scheme did not employ photovoltaic-storage coordinated slack-off and real-time deviation correction; it only used the medium- and long-term holdings and the predicted on-grid electricity generation of photovoltaic power to form the day-ahead declaration.

[0264] This specific application example follows a process of data governance, predictive calculation, photovoltaic storage capacity calculation, suggested position calculation, day-ahead reporting, clearing response, and real-time correction. Experimental results show that the average absolute execution deviation of the comparative scheme is 0.184 MWh, while the average absolute execution deviation of this specific application example is 0.073 MWh; the maximum execution deviation of the comparative scheme is 0.510 MWh, while the maximum execution deviation of this specific application example is 0.220 MWh; the 30-day settlement trial profit of the comparative scheme is 1.846 million yuan, while the 30-day settlement trial profit of this specific application example is 1.972 million yuan.

[0265] See attached document Figure 8 , Figure 8 The horizontal axis represents frequency, in Hz. -1The vertical axis represents the deviation amplitude, in MWh. The gray dashed line represents the net execution deviation amplitude spectrum without the collaborative method, and the black solid line represents the net execution deviation amplitude spectrum after applying the method of this specific application embodiment. The gray dashed line is at 0.0417h. -1 A main peak of approximately 0.22 MWh forms nearby, at 0.1667 h. -1 A secondary peak of approximately 0.10 MWh forms nearby, at 0.31 h. -1 A fluctuation peak of approximately 0.055 MWh still exists nearby. The black solid line retains the corresponding fluctuation components in the same frequency band, but the corresponding peak values ​​decrease to approximately 0.07 MWh, 0.03 MWh, and 0.012 MWh, respectively. This result demonstrates that the method in this specific application embodiment can reduce the net execution deviation corresponding to daily cycle fluctuations, intraday short-cycle fluctuations, and higher-frequency deviation components.

[0266] Based on the completion of the net execution deviation verification, in order to verify the execution effectiveness of the real-time energy storage correction process, the system compared the frequency domain distribution of the planned energy storage correction amount and the actual energy storage correction amount.

[0267] See attached document Figure 9 , Figure 9 The horizontal axis represents frequency, in Hz. -1 The vertical axis represents the corrected energy storage amplitude, in MWh. The gray dashed line represents the planned corrected energy storage amplitude spectrum, and the black solid line represents the actual corrected energy storage amplitude spectrum. The gray dashed line is at 0.0417h. -1 The energy level reached approximately 0.16 MWh in the vicinity, at 0.1667 h. -1 The actual energy storage correction power reaches approximately 0.096 MWh in the vicinity; the solid black line reaches approximately 0.13 MWh and 0.072 MWh in the corresponding frequency bands, respectively. This distribution indicates that the actual energy storage correction power follows the main frequency position of the planned energy storage correction power, and is constrained by the energy storage state and charging / discharging power, resulting in amplitude convergence.

[0268] Figure 9 The solid black line in the middle is at 0.31h. -1 A small response was maintained nearby, with Figure 8 The specific application embodiment method still exhibits a low-amplitude deviation in this frequency band. Combined with... Figure 8 and Figure 9 It can be seen that the real-time correction action of energy storage is concentrated on the main deviation frequency band, and the net execution deviation amplitude after adopting the method of this specific application embodiment is lower than the net execution deviation amplitude without adopting the collaborative method, which verifies the application effect of the present invention in the application of photovoltaic-storage joint transaction declaration, operation day deviation correction and settlement revenue improvement.

[0269] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A method for collaborative operation of photovoltaic-storage integrated new energy power trading, characterized in that, Includes the following steps: Collect multi-source data required for the collaborative operation of photovoltaic and energy storage transactions to form access data. Perform quality verification, data cleaning, data completion and standardization on the access data, and build a historical database to obtain the processed data. Based on the treated data, daily operation forecasts, market conditions, and combined photovoltaic and energy storage availability data are generated. Based on the typical decomposition curve, the time-sharing trading ledger, the medium- and long-term open positions, the planned power generation and the planned open positions, the basic curve for medium- and long-term time-sharing trading and the basic data of open positions before the adjustment are formed. Based on the market conditions, the forecast results for the operating day, the available capacity data of the photovoltaic and energy storage joint operation, the medium- and long-term time-sharing trading base curve, and the basic data of the holdings before the adjustment, a suggested position is generated. Based on the suggested position, the amount of electricity to be adjusted is generated. Based on the amount of electricity to be adjusted, the adjusted holdings data, the declared amount of electricity for the photovoltaic and energy storage joint operation, and the photovoltaic and energy storage joint operation plan are generated. Based on the day-ahead declared electricity volume of the photovoltaic-storage joint project, the photovoltaic-storage joint operation plan, the day-ahead clearing results, the actual execution data of the operation day, and the real-time clearing results, real-time corrections are made to generate deviation data and settlement trial calculation results, and the deviation data and the settlement trial calculation results are used for strategy correction on subsequent operation days.

2. The integrated photovoltaic and energy storage new energy power trading and collaborative operation method according to claim 1, characterized in that, The multi-source data required for the collaborative operation of photovoltaic and energy storage transactions includes: The access data is formed by integrating power trading business data, power grid metering data, photovoltaic operation data, energy storage operation data, and external environmental data. Configure the data source, service type, collection time, time period, data unit, and data value fields for the access data; The access data is collected according to the time period of the operating day.

3. The method for collaborative operation of photovoltaic-storage integrated new energy power trading according to claim 2, characterized in that, The quality verification, data cleaning, data completion, standardization processing, and construction of the historical database include: The access data is subjected to integrity verification, continuity verification, consistency verification, value range verification, and abnormal fluctuation verification to obtain data quality verification results; Based on the data quality verification results, missing data, out-of-bounds data, and abnormal data are corrected to obtain corrected data values; The corrected data value is standardized, and the original data value, the corrected data value, and the standardized data value are written into the historical database.

4. The method for collaborative operation of photovoltaic-storage integrated new energy power trading according to claim 1, characterized in that, The generation of the operational day forecast results and the market conditions includes: Retrieved load data, electricity price data, transaction data, market disclosure data, and external environment data after the governance process from the historical database; Combine daily input data to form predicted input data; Based on the predicted input data, generate daily load forecast results, electricity price forecast results, and similar day data; The market situation is generated based on the load forecast results for the operating day, the electricity price forecast results, and the similar day data.

5. The method for collaborative operation of photovoltaic-storage integrated new energy power trading according to claim 4, characterized in that, The generation of the combined availability data for optical and energy storage includes: The amount of photovoltaic power that can be traded is determined based on the power generation metering data, grid connection metering data, and self-consumption metering data of distributed photovoltaic projects. Based on the energy storage state of charge, maximum energy storage charging power, maximum energy storage discharging power, energy storage charging efficiency, energy storage discharging efficiency, upper limit of energy storage state of charge, and lower limit of energy storage state of charge, the rechargeable energy storage capacity and the rechargeable energy storage capacity are determined, and the energy storage adjustable capacity is formed. The combined photovoltaic and energy storage availability data is generated based on the photovoltaic power available for trading and the energy storage adjustable capacity.

6. The method for collaborative operation of photovoltaic-storage integrated new energy power trading according to claim 1, characterized in that, The formation of the aforementioned medium-to-long-term intraday trading baseline curve and the aforementioned pre-rebalancing position data includes: Read the typical decomposition curve, peak-to-valley ratio, and transaction time-sharing ledger to form time-sharing transaction parameters; The basic electricity volume for medium- and long-term time-of-use trading is generated based on the monthly trading volume and the time-of-use allocation ratio. The pre-adjustment position data is formed based on the medium- and long-term holdings, the planned power generation, and the planned power generation.

7. The method for collaborative operation of photovoltaic-storage integrated new energy power trading according to claim 5, characterized in that, The generation of the suggested position, the power supply to be adjusted, and the adjusted position data includes: The organization adjusts its portfolio input data, which includes the medium- and long-term holdings, the planned power generation, the planned power holdings, the daily load forecast results, the electricity price forecast results, the photovoltaic power available for trading, the energy storage rechargeable capacity, and the energy storage dischargeable capacity. The suggested position is generated based on the rebalancing input data; The proposed position is used to generate the power volume to be adjusted and the adjusted position data.

8. The method for collaborative operation of photovoltaic-storage integrated new energy power trading according to claim 7, characterized in that, The generation of the day-ahead electricity declaration for the photovoltaic-storage joint project and the photovoltaic-storage joint operation plan includes: Based on the power to be adjusted, the photovoltaic power available for trading, the energy storage rechargeable capacity, and the energy storage dischargeable capacity, allocate the photovoltaic grid connection power, the energy storage charging power, and the energy storage discharging power. When the amount of electricity to be adjusted is greater than 0, the amount of photovoltaic electricity that can participate in the trading will be used first, and the insufficient part will be made up by the amount of electricity arranged by the energy storage discharge within the range of the energy storage discharge capacity; When the amount of energy to be adjusted is less than 0, the energy storage charging arrangement amount is formed within the range of the energy storage rechargeable amount. When the amount of electricity to be adjusted is 0, no warehouse adjustment requirement will be generated in the corresponding time period. The photovoltaic-storage joint day-ahead declaration of electricity is generated based on the medium- and long-term holdings, the photovoltaic grid connection arrangement of electricity, the energy storage discharge arrangement of electricity, and the energy storage charging arrangement of electricity, and the photovoltaic-storage joint operation plan is generated.

9. The method for collaborative operation of photovoltaic-storage integrated new energy power trading according to claim 8, characterized in that, The real-time correction includes: Receive the day-ahead clearing result and compare the day-ahead cleared electricity with the day-ahead declared electricity of the photovoltaic-storage joint project to obtain the day-ahead declaration deviation; The photovoltaic and energy storage joint operation plan will be revised based on the aforementioned reported deviations. The actual execution power is generated based on the actual grid-connected power of photovoltaic power, the actual discharge power of energy storage, and the actual charging power of energy storage. The actual executed electricity volume is compared with the day-ahead cleared electricity volume to obtain the actual executed deviation; The real-time correction charging capacity and real-time correction discharging capacity are determined based on the actual execution deviation.

10. The method for collaborative operation of photovoltaic-storage integrated new energy power trading according to claim 9, characterized in that, The deviation data, the settlement trial results, and the strategy adjustments for subsequent operating days include: Calculate the real-time deviation power based on the real-time clearing results and the day-ahead clearing power; Calculate the two-part trial result and the three-part trial result based on the adjusted position data, the day-ahead clearing result and the real-time clearing result; The photovoltaic operation settlement result is calculated based on the actual on-grid power of the photovoltaic system, and the energy storage operation settlement result is calculated based on the actual discharge power of the energy storage system and the actual charging power of the energy storage system. The reported deviation, actual execution deviation, real-time deviation electricity, two-part trial calculation result, three-part trial calculation result, photovoltaic operation settlement result, and energy storage operation settlement result are written into the historical database and used for strategy correction on subsequent operating days.

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