208 results about "Coulombmeter" patented technology

The invention relates to an electric quantity detection method and device for an energy storage system, and the method comprises the steps: obtaining the electric energy data and temperature data of the energy storage system, and carrying out the real-time measurement processing, and obtaining a corresponding real-time measurement result; based on the real-time measurement result, accumulated electric quantity calculation and correction processing are carried out, and corrected electric quantity data are obtained; acquiring open-circuit voltage data of the energy storage system, and performing table look-up estimation on the open-circuit voltage data based on a preset voltage SOC corresponding relation to obtain a corresponding SOC estimated value; comprehensively analyzing the corrected electric quantity data and the SOC estimated value to obtain corresponding electric quantity display information; carrying out data recording on the electric quantity display information and the real-time measurement result to obtain corresponding comprehensive record data; and performing safety comprehensive detection on the comprehensive record data based on a preset safety threshold to obtain a corresponding comprehensive detection result, and generating a corresponding system state early warning report according to the comprehensive detection result. According to the method, the actual capacity and the use condition of the energy storage system can be accurately grasped.

The invention provides a low-voltage transformer area line loss calculation method and device, electronic equipment and a medium, and the method is applied to a three-phase Internet of Things meter of a target low-voltage transformer area, and comprises the steps: reading the electric quantity of the three-phase Internet of Things meter and the electric quantity of each single-phase meter, and obtaining the electrical characteristic quantity of the target low-voltage transformer area; calculating a first line loss result based on the electric quantity of the three-phase Internet of Things meter and the electric quantity of each single-phase meter; inputting the electrical characteristic quantity into a pre-trained line loss calculation model to obtain a second line loss result; wherein the line loss calculation model is obtained by training a random forest model based on an improved bat algorithm; and performing weighted calculation on the first line loss result and the second line loss result to obtain a line loss result of the target low-voltage transformer area. According to the invention, the line loss calculation precision is improved.

The invention provides an electric energy meter correction electric quantity calculation method and device, electronic equipment and a storage medium. The method comprises the steps of obtaining metering historical data of a target electric energy meter; analyzing the metering historical data by adopting a phase angle feature portrait algorithm, and identifying a wiring error type corresponding to the target electric energy meter; determining a corresponding correction transformation matrix based on the wiring error type; and calculating the corrected electric quantity of the target electric energy meter based on the corrected transformation matrix. The invention provides a novel calculation scheme for the corrected electric quantity of the electric energy meter, the corrected electric quantity of the electric energy meter is calculated more accurately by adopting an advanced algorithm and a mathematical model, the interference of human factors is reduced, various complex wiring error conditions can be adapted, and the calculation efficiency is improved. Therefore, the accuracy and reliability of the correction electric quantity calculation method of the electric energy meter of the power system are improved.

The invention relates to a virtual power plant regulation and control method and system for realizing new energy consumption. The method comprises the steps of performing statistics according to a wind and light power generation module to obtain predicted power generation amount E1 in each time period; according to an electric vehicle scheduling module, predicting the actual charging demand electric quantity QS1 of the electric vehicle in each time period; predicting actual load demand electric quantity QS2 in each time period according to a load prediction module; according to the energy storage module, calculating the storable electric quantity C and the standby residual capacity CS of each time period in real time; and according to the virtual power plant global scheduling module, the electric quantity difference value E difference required by each time period is calculated according to the predicted electric quantity E1 of each time period, the actual charging demand electric quantity QS1, the actual load demand electric quantity QS2 and the storable electric quantity C, and according to the electric quantity difference value E difference, a scheduling power generation instruction is issued to the heat power unit module for time-phased power generation. The distributed new energy consumption can be realized, and the stability and economy of grid-connected scheduling operation of the distributed new energy equipment can be improved at the same time.

The invention discloses a single-phase charge-control intelligent electric energy meter and an intelligent metering system thereof, relates to the technical field of electric variable measurement, and aims to solve the technical problem of inaccurate metering of the existing intelligent electric energy meter, and the single-phase charge-control intelligent electric energy meter comprises a working electric quantity calculation module which is connected to a power grid and is used for counting the electric quantity when the electric energy meter works and storing the electric quantity in a memory; the non-working electric quantity calculation module is used for calculating the electric quantity when the electric meter does not work; the working electric quantity calculation module further comprises a first processing unit which is used for calculating the working electric quantity consumed when the electric meter works according to the working duration of the electric meter; the first calculation unit is used for receiving the working electric quantity from the first processing unit, calculating corrected electric quantity according to the working electric quantity and historical electric quantity data stored in the memory, and transmitting the corrected electric quantity to the correction unit; and the correction unit is used for receiving the correction electric quantity transmitted by the first calculation unit and correcting the working electric quantity. The method has the advantage of improving the electricity metering accuracy of the electricity meter.

The invention discloses a voltameter monitoring method and device, electronic equipment and a storage medium, and belongs to the technical field of charging. The method is applied to electronic equipment and comprises the steps that monitoring measurement parameters for monitoring the voltameter through all preset burying points are obtained, the monitoring measurement parameters comprise measurement results collected at all the preset burying points, and all the preset burying points are set for the voltameter through burying point driving; and according to the monitoring measurement parameters, the operation state of the voltameter is determined, and the operation state comprises a normal state and an error state. In the running process of the electronic equipment, the voltameter is monitored in a buried point presetting mode, the monitoring and measuring parameters for monitoring the voltameter are obtained in time, whether the voltameter is in the normal state or the error state is determined based on the monitoring and measuring parameters, the effect of monitoring the voltameter in the electronic equipment is achieved, and the safety of the electronic equipment is improved. The measurement result of the voltameter at the preset burying point can be collected in time, and the efficiency of monitoring the voltameter of the electronic equipment is improved.

The invention relates to an issued electric quantity prediction method based on electric quantity big data, and the method comprises the following steps: S1, obtaining and collecting the power utilization property and network structure data of a load supplied by a transformer area, and carrying out the analysis and control, and improving the quality of line loss basic data in the same period; s2, constructing an electricity sale quantity prediction model, and predicting future electricity sale quantity; s3, establishing a feedback loop, continuously self-calibrating the electricity sale quantity prediction model by using an error correction method, and carrying out future electricity sale quantity prediction correction by incorporating an event, updating and error correction means; s4, according to the corrected future electricity sale quantity, predicting line transformer loss electricity quantity based on a line transformer loss electricity quantity prediction model, and calculating issued electricity quantity based on the predicted line transformer loss electricity quantity and the future electricity sale quantity; and S5, displaying the historical electricity sale quantity, the historical power supply quantity, the predicted future electricity sale quantity and the predicted issued electricity quantity in a chart form. According to the method, complex time dependency and nonlinear fluctuation can be captured, and the accuracy and fine granularity of issued electric quantity prediction are improved.

The invention relates to a method and a system for detecting abnormal electricity consumption of an electric energy meter, and relates to the technical field of electric power detection. According to the method for detecting abnormal power consumption of the electric energy meter, the data of the electric energy meter is collected and analyzed, so that the accuracy of wiring of the electric energy meter can be preliminarily judged through an instrument, the electric quantity needing to be compensated during a fault period is automatically calculated, the manual calculation processing time is shortened, and the field operation and maintenance working efficiency can be greatly improved; the electric quantity calculation method can be immediately corrected by analyzing acquired data of the electric energy meter, finding a wrong wiring condition, so that the device can acquire a real-time power consumption condition and automatically calculate the electric quantity needing to be compensated in a wrong wiring state and in abnormal operation, the operation and maintenance work difficulty of an electric power department is reduced, and the working efficiency is improved. And the efficiency of field operation and the timeliness of electric quantity compensation are improved.

The invention discloses a method for evaluating the health state of a LiFePO4 battery, and belongs to the field of prediction of the health state of a battery of a peak regulation energy storage system. The implementation method comprises the following steps: acquiring initial electric quantity according to open-circuit voltage of a battery, and calculating SOH by combining full-charge charging capacity; a differential voltage curve is obtained by performing differential processing on a charging curve, an inflection point between a high-voltage platform and a low-voltage platform in the charging curve is accurately positioned by using valley voltage between high-voltage characteristic peaks and low-voltage characteristic peaks, and SOH is calculated by accumulating electric quantity before and after the inflection point. Under the same multiplying power and electric quantity interval, an average charging and discharging voltage value is taken to construct an average charging and discharging curve, an inflection point is positioned through differential processing, and SOH is estimated through accumulation of electric quantity before and after the inflection point. And intelligently distributing weight coefficients of the three groups of SOH estimation results based on a fuzzy theory to obtain a final SOH value of the battery. According to the method, the accuracy and the reliability of LiFePO4 battery health state evaluation can be remarkably improved, and fault diagnosis and service life prediction of a battery system are facilitated.

The invention relates to the technical field of phase change energy storage wall body detection, in particular to a phase change energy storage wall body energy saving rate and comfort degree testing method which is used for solving the problem that in the prior art, the energy saving rate and comfort degree of a phase change energy storage component are not easy to detect. The comfort level and the energy-saving effect are tested through sine wave temperature change. Firstly, the temperature comfort degree is tested without constant temperature control, and the time period difference of the two in a comfort area is compared; secondly, testing electricity consumption under constant-temperature control, calculating energy-saving quantity and energy-saving rate, and taking an average value of three test periods as a final result; by means of the testing method, the energy-saving rate and the comfort degree of the phase change energy storage component in the application process can be directly tested, and the problem that the energy-saving rate and the comfort degree of the phase change energy storage component are not easy to detect in the prior art is solved.

The invention provides a metering box electricity larceny detection method, system, equipment and medium under carrier communication, and relates to the field of metering box electricity larceny prevention, and the method comprises the following steps: collecting the three-phase current ICCO, voltage UCCO and freezing electric quantity QCCO of a split-phase protection intelligent circuit breaker, and the current Ij, voltage Uj and freezing electric quantity Qj of an electric energy meter in real time; calculating a correlation coefficient and an average distance between the voltage sequence {Uj} of the electric energy meter and the three-phase voltage sequence {UA, UB, UC} of the circuit breaker, and determining a connection phase of each electric energy meter; the deviation value delta I of the sum of the current ICCO of the circuit breaker and the current Ij of the connected electric energy meter under the same phase is calculated, a line loss model is constructed by combining the freezing electric quantity Qj and the QCCO, and the line loss rate p is solved; and performing three-level electricity stealing judgment, positioning an electricity stealing point and generating an electricity stealing probability Ptheft. Through multi-source data fusion, edge-side autonomous efficient electricity stealing closed-loop judgment and split-phase protection and electricity stealing prevention collaborative optimization, the accuracy of electricity stealing identification and the reliability of power supply are remarkably improved.

The invention discloses a heavy load transformer area technology loss abnormity diagnosis method and system based on a characteristic cutaway view, and belongs to the technical field of line loss management. The method comprises the following steps: acquiring the power supply quantity and the line loss rate of the transformer area in the automatic meter reading system; calculating a transformer area average load rate according to the transformer area power supply amount, and screening out a heavy load transformer area by using the transformer area average load rate; drawing a characteristic cutaway view of the heavy load area according to the power supply quantity of the heavy load area and the line loss rate of the heavy load area; fitting the heavy load area characteristic cutaway view, and calculating the slope of the heavy load area characteristic cutaway view; and obtaining a technical loss abnormity diagnosis result of the heavy load transformer area according to the slope of the heavy load transformer area characteristic section view and the slope threshold value of the same type of heavy load transformer area. According to the heavy load area characteristic cutaway view provided by the invention, accurate judgment of the line loss abnormity of the heavy load area can be realized only through image analysis and data fitting.

The invention belongs to the technical field of charging pile electric quantity metering, and particularly relates to a charging pile error prediction method, system and device based on a particle swarm optimization long short-term memory neural network and a computer readable storage medium. The data required for prediction comprises metering errors of a part of charging piles in the charging station in a to-be-measured time period; the data required for prediction further comprises one, two or more of factory errors of all the charging piles in the charging station, voltage fluctuation conditions of the power distribution network in the to-be-detected time period, product batch failure rates corresponding to all the charging piles and accumulated operation time of all the charging piles; and 2) data required by prediction are input into the trained machine learning algorithm model, the whole station metering error of the charging station in the to-be-measured time period is predicted, the model inputs more data, the precision is higher, and the finally predicted whole station metering error of the charging station is more accurate and more reliable.

The invention discloses an electricity larceny time judgment and electric quantity calculation method, which comprises the following steps of: analyzing an electricity larceny type after finding electricity larceny, correspondingly judging the electricity larceny time and calculating the electric quantity, judging whether an electric energy meter event record is triggered or not, calculating according to an electric energy meter event recording method, judging whether typical load characteristics exist or not, and calculating according to a load data characteristic method. Judging whether line loss change is obvious or not, calculating according to a transformer area or line loss change method, judging whether a metering reference point exists or not, and calculating according to the metering reference point; according to the method, the electricity stealing quantity affirmation accuracy and standardization degree are greatly improved, the divergence of electricity stealing quantity affirmation of power supply enterprises, electricity stealing users, judicial offices and the like is reduced, the electricity loss of the power supply enterprises is effectively retrieved, and compared with a traditional algorithm, the per-household compensation amount is remarkably increased; by restoring the actual electricity stealing quantity, an electricity stealing user cannot pay less electricity fee by using the vulnerability of a traditional algorithm, the attempt of electricity stealing is effectively restrained, and the order of power supply and consumption is maintained.

The invention provides an ammeter metering abnormity identification method and system based on multi-mode power utilization data fusion, and relates to the technical field of electric power metrology, and the method comprises the steps: collecting an actual power consumption set of intelligent power utilization equipment of a target user in a preset time zone, and carrying out the matching to obtain an equipment association degree set; according to the actual power consumption set and the equipment association degree set, predicting to obtain predicted total power consumption; performing analysis based on the intelligent electric equipment type set and the equipment association degree set to obtain prediction confidence; calculating a threshold adjustment coefficient according to the load fluctuation characteristics, the environment fluctuation characteristics and the prediction confidence in the preset time zone, correcting the initial error threshold, and outputting an adaptive error threshold; and calculating the electric quantity deviation amplitude according to the meter display consumed electric quantity of the electric energy meter of the target user in the preset time zone and the predicted total consumed electric quantity, and if the electric quantity deviation amplitude exceeds an adaptive error threshold, executing abnormal early warning. The technical problems of high false alarm rate and poor reliability of electricity meter metering abnormity identification in the prior art are solved.

A single-phase fee-controlled electric energy meter based on the Internet of Things, the electric energy meter comprising a meter body (1) and an intelligent working system, wherein a mounting base (2) is provided on a back face of the meter body (1), and fixing holes (23) are uniformly provided on the mounting base (2); a display screen (11) is provided on a front face of the meter body (1), and connecting wires (12) are mounted at the bottom of the meter body (1); and the intelligent working system comprises: an intelligent processor, an electricity quantity calculation module, an electricity fee calculation module, a display module, an information transmission module, an alarm module and a security module. By means of the information transmission module, calculated electricity consumption information and electricity fee information are instantly transmitted to a power supply department by means of a transmitting device via a data network.

The invention provides a POS machine detection method and a POS machine, a voltameter is arranged in the POS machine, a voltameter chip is arranged in the voltameter, and the detection method comprises the steps that when a voltameter driver is loaded, the voltameter chip is verified; if the chip of the voltameter is abnormal, reporting abnormal information to the Android system; if the voltameter chip is normal, loading a voltameter chip driver, and reading battery data of the POS machine; according to the battery data, different states of the POS machine are processed, and the states of the POS machine comprise the state that the POS machine is only connected with a charger to be started, the state that the POS machine is connected with a battery again after being started, and different batteries are replaced when the POS machine is in the standby state. According to the invention, the situation that the newly accessed battery and the accessed battery are possibly detached after the POS machine is started is considered, and different states of the POS machine can be processed.

To provide an information processing apparatus, a system, and a method for determining procurement of electric power whose environmental value is certified.SOLUTION: A method executed by an information processing apparatus, the method including: acquiring a desired condition related to procurement power and a required amount of power from each tenant of a customer; calculating a desired amount of power and an environmental value based on the desired amount of power for each demand having the same desired condition; temporarily assigning, for each demand, a predicted value of an amount of power generation of renewable energy with a proven environmental value to the desired amount of power; and externally procuring, when the predicted value of the amount of power generation is insufficient for the desired amount of power for each demand, differential between the predicted value of the amount of power generation and the desired amount of power for each demand such that a procurement cost is minimized.SELECTED DRAWING: Figure 3

The present invention relates to the field of power trading risk assessment, and specifically to a power spot trading risk assessment method, comprising the following steps: S1, obtaining photovoltaic impact information and wind power impact information of the area where the target power spot supplier is located; S2, calculating the total predicted power generation of the target power generator in the target time period based on the photovoltaic impact information and the wind power impact information; S3, obtaining the power consumption impact information and historical power consumption information of the power grid; S4, calculating the first total power consumption of the power grid in the target time period based on the power consumption impact information and the historical power consumption information; the present invention takes into account that the common power grid power consumption calculation method only calculates the individual effects of season, GDP growth rate, industry type and population density on the total power consumption, and does not take into account the mutual influence between these factors, resulting in an inaccurate calculation result of the power grid power consumption, so four coupling influence coefficients are introduced, and the accuracy of the total power generation of the power grid finally calculated is higher.

The invention discloses an electric power metering and electric charge accounting system based on multi-source data and an intelligent algorithm, and relates to the technical field of intelligent power grids, and the system comprises the following steps: S1, constructing a multi-source power credibility weighted fusion model, and outputting multi-source credibility weighted fusion power; s2, performing section-level correction and equivalent electric quantity calculation on electric energy flow in the current settlement time slice; s3, constructing a user side clearing electric quantity model, and dynamically calculating the clearing electric quantity of the user; s4, constructing an electric charge cardinal model, and dynamically pricing the sorted electric quantity; s5, the obtained electricity charge cardinal number is optimized; and S6, establishing an anomaly identification and dynamic verification mechanism. According to the invention, a credible fusion mechanism of multi-source heterogeneous data is constructed, self-calibration modeling of a metering point topological structure is realized, a precise clearing method oriented to user contracts and line loss is introduced, and a full-link intelligent system is formed in combination with a strategy-driven electricity charge accounting model and a cross-cycle consistency anomaly detection mechanism.

The invention provides a household electric quantity loss calculation method and device, a storage medium and a product, belongs to the technical field of power systems, is applied to each household distributed photovoltaic single household, and comprises the following steps: determining a single household of which the electric quantity loss is to be calculated; counting all normal household samples in a preset area to which the single household of which the power loss is to be calculated belongs in the abnormal duration; according to all normal household samples in the preset area, the theoretical generating capacity of a to-be-calculated household in the abnormal duration is calculated, and the to-be-calculated household is a single household of which the power loss is to be calculated; and according to the actual generating capacity and the theoretical generating capacity of the to-be-calculated user in the abnormal duration, obtaining the lost electric quantity of the to-be-calculated user in the abnormal duration. The benchmark generating capacity of the to-be-calculated user is calculated according to the normal user sample in the preset area to which the to-be-calculated user belongs when the to-be-calculated user is abnormal, the lost electric quantity of the to-be-calculated user when the to-be-calculated user is abnormal is obtained by combining the theoretical generating capacity, and the method is simple and high in calculation accuracy.

The present invention relates to the technical field of batteries, and particularly to a battery power detection method, an electronic device, and a computer-readable storage medium, including: reading an original voltage value of the battery through the ADC module and calculating an actual voltage value; judging whether the battery is in a charging state according to the actual voltage value, obtaining a corrected voltage value according to a judgment result, obtaining a compensation value according to the corrected voltage value and a power supply state of the SOC main control chip, and further calculating a compensated voltage value; using the compensated voltage value to update the sliding window so as to determine a remaining power of the battery according to an average voltage value of the updated sliding window. By combining a voltage correction and compensation mechanism with a sliding window technique, the stability and accuracy of battery remaining power detection can be ensured, and no additional external coulometer or other peripheral circuits are required, thereby significantly reducing the production cost of the product.

The invention discloses a carbon reduction optimization method for a transformer substation, and relates to the technical field of transformer substation optimization, and the method comprises the following steps: obtaining the power distribution quantity of the transformer substation and the load power consumption of different regions, and calculating the matching degree of the power distribution quantity of the transformer substation and the load power consumption according to the power distribution quantity of the transformer substation and the total load power consumption; obtaining a load peak-valley difference rate according to the load electricity consumption of different areas, and calculating first optimization data by combining the load electricity consumption with the matching degree of the distribution quantity of the transformer substation; obtaining the power loss of the transformer substation, correcting the first optimization data based on a preset second optimization data calculation formula according to the power loss of the transformer substation to obtain second optimization data, and performing energy-saving optimization on the transformer substation according to the second optimization data; the energy consumption problem of the transformer substation is optimized, so that the carbon emission of the transformer substation is reduced, and the influence on the environment is reduced.

The present invention discloses a method for designing an excitation inductor to ensure soft switching of a CLLC resonant converter, comprising a qualitative analysis of the dead-zone equivalent circuit of the CLLC resonant converter and a Laplace coordinate transformation. The electric quantity values ​​of the capacitor and the inductor at the dead-zone moment are obtained according to the fixed-frequency analysis principle of the CLLC resonant converter. The time-domain expression of the resonant current during the dead-zone is obtained by using the mesh current method. The period of the resonant current is calculated according to the parasitic capacitance value of the primary and secondary side switching tubes. The discharge time of the parasitic capacitance is calculated taking into account the electric quantity of the capacitor. The excitation inductance value required when the resonant current just drops to zero at the end of the dead-zone time is calculated. The present invention can effectively ensure the soft switching of the resonant converter, reduce the amplitude of the resonant current, improve the efficiency of the resonant converter, and has strong versatility.

The invention provides an ammeter matching method and system, an electronic device, a storage medium and a program product. The method comprises the following steps: obtaining the daily collection electric quantity of a TMR system ammeter of any device in a plant station; obtaining the daily integral electric quantity of the EMS system of the equipment; acquiring the daily acquisition electric quantity and the daily integral electric quantity of the equipment for multiple consecutive days; calculating a correlation coefficient of the daily collection electric quantity and the daily integration electric quantity of the equipment according to the obtained daily collection electric quantity and the daily integration electric quantity of the multiple days; calculating the deviation ratio of the daily collection electric quantity and the daily integration electric quantity of the equipment according to the obtained daily collection electric quantity and the daily integration electric quantity of the multiple days; and judging the equipment, and if the correlation coefficient of the equipment is greater than a first preset threshold value and the deviation rate of the equipment is smaller than a second preset threshold value, matching the TMR system electric meter of the equipment with the EMS system of the equipment. According to the invention, automatic matching of the TMR system ammeter and the EMS system can be realized.

The present invention discloses a method and device for estimating the life of a power battery, comprising: obtaining the temperature of each power battery cell in a whole pack of power batteries; calculating the cell SOH value corresponding to each power battery cell based on the cell attenuation model according to the temperature; calculating the power of each power battery cell according to the temperature; calculating the initial whole pack SOH value of the whole pack of power batteries according to the cell SOH value and the power, and obtaining the ampere-hour value of each initial whole pack SOH value; calculating the corrected whole pack SOH value of the whole pack of power batteries according to the initial whole pack SOH value and the obtained measured whole pack SOH value; performing parameter identification on the cell attenuation model according to the corrected whole pack SOH value and the ampere-hour value of each corrected whole pack SOH value, and generating a whole pack attenuation model; estimating the estimated whole pack SOH value of the whole pack of power batteries based on the whole pack attenuation model. The application of the present invention can improve the accuracy of the estimated whole pack SOH value of the whole pack of power batteries.

The invention discloses an abnormal transformer area diagnosis method and device, and the method comprises the steps: 1, collecting the power consumption and power supply of a transformer area, calculating the predicted power consumption and residual error of a diagnosis day according to the power consumption and power supply of the transformer area, and judging whether the power supply or power consumption of the day is abnormal or not according to the residual error; step 2, if the power supply quantity or the power consumption quantity of the day is judged to be abnormal in the step 1, calculating abnormal loss-reducible power quantity, and trying to calculate the loss-reducible power quantity and the line loss rate of the transformer area based on the abnormal loss-reducible power quantity; and step 3, outputting a calculation result in the step 2 in a list mode. According to the method, whether the power supply quantity or the electricity consumption is abnormal or not is judged by analyzing the electricity consumption and the power supply quantity, and when the electricity consumption is abnormal, the transformer area abnormality diagnosis is realized through the loss-reducible electricity quantity, the trial calculation transformer area loss-reducible electricity quantity and the line loss rate so as to maintain the stability of the transformer area.

A charging apparatus includes a charging module, where the charging module is connected to a first terminal of a first selection module; a second terminal of the first selection module is connected to a first terminal of a first battery module, a third terminal of the first selection module is connected to a first terminal of a second battery module, in a case in which a first condition is satisfied, the first terminal of the first selection module is connected to the second terminal of the first selection module, and in a case in which a second condition is satisfied, the first terminal of the first selection module is connected to the third terminal of the first selection module; and a coulometer management module, connected to the first battery module and the second battery module.

The invention provides a photovoltaic power station multi-data-source electric quantity correction module and correction method. The correction module comprises a multi-source data acquisition module, a priority ranking module, a slicing module and a data source selection module. The multi-source data acquisition module, the priority ranking module, the slicing module and the data source selection module are connected in sequence. According to the method, by introducing a logic isolation mechanism of a time window and combining the characteristics of multiple data sources, time-sharing fusion calculation for different configurations and data sources is realized, the problem of data inconsistency can be effectively solved, and the accuracy of electric quantity calculation is remarkably improved.

The application provides a power meter correction electric quantity calculation method and device, electronic equipment and a storage medium. The method comprises the following steps: acquiring metering history data of a target power meter; analyzing the metering history data by using a phase angle feature portrait algorithm, and identifying a wiring error type corresponding to the target power meter; determining a corresponding correction transformation matrix based on the wiring error type; and calculating the correction electric quantity of the target power meter based on the correction transformation matrix. The application provides a novel power meter correction electric quantity calculation scheme. By using an advanced algorithm and a mathematical model, the correction electric quantity of the power meter can be more accurately calculated, the interference of human factors is reduced, various complex wiring error conditions can be adapted to, and therefore the accuracy and reliability of the power system power meter correction electric quantity calculation method are improved.