Power peak shaving method and system in multi-type energy storage system

Abstract

The present invention relates to the field of electrical engineering technology, and provides a method and system for peak-shaving of electric power in a multi-type energy storage system, including: querying the electric power storage device corresponding to the electric power peak-shaving instruction from the pre-constructed electric power storage system, and clarifying the demand power area corresponding to the electric power peak-shaving instruction; dividing the electric power demand data into dynamic demand data and static demand data according to a preset dimension, and constructing the electric power load curves corresponding to the dynamic demand data and the static demand data respectively, and obtaining the dynamic load curve and the static load curve; calculating the dynamic equivalent charge between the demand power area and the electric power storage device, calculating the static equivalent charge between the demand power area and the electric power storage device, and determining the compensation equivalent charge between the demand power area and the electric power storage device; generating a report on peak-shaving of electric power between the demand power area and the electric power storage device. The present invention aims to improve the accuracy of peak-shaving of electric power in a multi-type energy storage system.

Description

Technical Field

[0001] The present invention relates to the field of electrical engineering technology, and in particular to a power peak regulation method and system in a multi-type energy storage system. Background Art

[0002] Power peak regulation in multi-type energy storage systems refers to the use of various types of energy storage devices (such as battery energy storage, supercapacitor energy storage, flywheel energy storage, etc.) to store or release electrical energy according to changes in the load in the power system, thereby achieving regulation of the balance between power supply and demand.

[0003] At present, multi-type energy storage systems have been widely used in the power field. In order to achieve power peak regulation, the existing technology mainly adopts the power prediction method, which predicts the power load and adjusts the charging and discharging power of the energy storage system according to the prediction results to achieve the purpose of peak regulation. However, there are some problems with the power prediction method. On the one hand, its prediction accuracy is affected by many factors, such as meteorological conditions, user behavior, etc., resulting in unstable peak regulation effect. On the other hand, this method requires a large amount of historical data for training, and data acquisition and processing are difficult, which increases the complexity and cost of the system. Therefore, a new power peak regulation method and system in a multi-type energy storage system is needed to improve the peak regulation efficiency and stability. Summary of the invention

[0004] The present invention provides a method and system for peak-shaving of electric power in a multi-type energy storage system, the main purpose of which is to improve the accuracy of peak-shaving of electric power in the multi-type energy storage system.

[0005] To achieve the above object, the present invention provides a method for peak load regulation in a multi-type energy storage system, comprising:

[0006] In response to the power peak shaving instruction, query the power storage device corresponding to the power peak shaving instruction from the pre-built power storage system, and clarify the power demand area corresponding to the power peak shaving instruction;

[0007] Monitor the power demand data of the power demand area in real time, divide the power demand data into dynamic demand data and static demand data according to a preset dimension, and construct power load curves corresponding to the dynamic demand data and the static demand data respectively to obtain a dynamic load curve and a static load curve;

[0008] Collecting energy storage supply data and equipment operation data of the electric energy storage device, and constructing a power supply curve of the electric energy storage device based on the energy storage supply data and the equipment operation data;

[0009] Calculating the dynamic equivalent charge between the power demand area and the power storage device based on the dynamic load curve and the power supply curve, and calculating the static equivalent charge between the power demand area and the power storage device based on the static load curve and the power supply curve, and determining the compensation equivalent charge between the power demand area and the power storage device according to the dynamic equivalent charge and the static equivalent charge;

[0010] According to the compensation equivalent charge, a power compensation method and a power compensation path are constructed between the power storage device and the power demand area, and based on the power compensation method and the power compensation path, a power peak regulation report between the power demand area and the power storage device is generated.

[0011] Furthermore, the clarifying the power demand area corresponding to the power peak load regulation instruction includes:

[0012] Extracting a peak-shaving instruction signal corresponding to the power peak-shaving instruction, performing quality optimization processing on the peak-shaving instruction signal, and obtaining a target instruction signal;

[0013] Decoding the target instruction signal to obtain a decoded instruction signal, and extracting an instruction operand and an instruction operation code from the decoded instruction signal;

[0014] Decoding the instruction operand and the instruction operation code respectively to obtain a decoding product set;

[0015] Analyzing signal information in the target command signal according to the decoding product set, and identifying regional information in the signal information;

[0016] According to the regional information, the power demand area corresponding to the power peak load regulation instruction is clarified.

[0017] Furthermore, the step of performing quality optimization processing on the peak shaving instruction signal to obtain a target instruction signal includes:

[0018] Performing signal filtering processing on the peak shaving instruction signal to obtain a filtered instruction signal;

[0019] The signal energy corresponding to the filtering instruction signal is calculated by the following formula:

[0020] ,

[0021] Wherein, A represents the signal energy corresponding to the filtering instruction signal, a represents the time point of the filtering instruction signal, and r represents the time length of the filtering instruction signal. Indicates the amplitude value corresponding to the ath time point in the filtering instruction signal,

[0022] According to the signal energy, performing energy balancing processing on the filtered instruction signal to obtain a balanced instruction signal;

[0023] The equalization instruction signal is subjected to signal conditioning processing to obtain a target instruction signal.

[0024] Furthermore, dividing the power demand data into dynamic demand data and static demand data according to a preset dimension includes:

[0025] Querying a quality evaluation indicator corresponding to the power demand data, and calculating a quality score corresponding to the power demand data according to the quality evaluation indicator;

[0026] According to the quality score, the power demand data is cleaned to obtain target demand data;

[0027] Extracting data features corresponding to the target demand data, and calculating feature criticality corresponding to the data features;

[0028] According to the feature criticality, extract the key features from the data features, and calculate the approximation between the key features and the preset dimension;

[0029] According to the approximation, the target demand data is divided and processed to obtain dynamic demand data and static demand data.

[0030] Furthermore, the step of respectively constructing power load curves corresponding to the dynamic demand data and the static demand data to obtain a dynamic load curve and a static load curve includes:

[0031] Performing data clustering processing on the dynamic demand data and the static demand data respectively to obtain dynamic clustering data and static clustering data;

[0032] Analyzing dynamic variables in the dynamic clustering data, and extracting dynamic values ​​corresponding to the dynamic variables from the dynamic clustering data;

[0033] Remove discrete values ​​from the dynamic values ​​to obtain target dynamic values, and analyze static variables in the static clustering data;

[0034] Extracting static values ​​corresponding to the static variables from the static clustering data, removing discrete values ​​from the static values, and obtaining target static values;

[0035] In combination with the dynamic variable, the target dynamic value, the static variable and the target static value, power load curves corresponding to the dynamic clustering data and the static clustering data are respectively constructed to obtain a dynamic load curve and a static load curve.

[0036] Furthermore, constructing the power supply curve of the power storage device based on the energy storage supply data and the device operation data includes:

[0037] Extracting normal operation data and equipment failure data from the equipment operation data;

[0038] Respectively determine the cycle durations corresponding to the normal operation data and the equipment failure data to obtain the equipment operation duration and the equipment failure duration;

[0039] Calculate the equipment failure rate of the power storage device based on the equipment operation time and the equipment failure time;

[0040] Combining the energy storage supply data and the equipment failure rate, a power supply curve of the power storage device is constructed.

[0041] Further, extracting the normal operation data and the equipment failure data from the equipment operation data includes:

[0042] Querying the status index and index threshold corresponding to the electric energy storage device;

[0043] Determine the indicator parameter value corresponding to the status indicator in combination with the equipment operation data;

[0044] Combining the indicator parameter value and the indicator threshold, identifying normal indicators and abnormal indicators in the status indicators;

[0045] Analyze the abnormal impact factor corresponding to the abnormal indicator, and determine the hard fault indicator in the abnormal indicator according to the abnormal impact factor;

[0046] The normal operation data and the equipment failure data in the equipment operation data are extracted by combining the normal index and the hard failure index.

[0047] Further, the calculating the dynamic equivalent charge between the power demand area and the power storage device based on the dynamic load curve and the power supply curve includes:

[0048] identifying synchronization points in the dynamic load profile and the power supply profile;

[0049] According to the synchronization time point, performing curve alignment processing on the dynamic load curve and the power supply curve to obtain a load-supply curve set;

[0050] In combination with the synchronization time point, setting an equivalent time step corresponding to the load-supply curve set;

[0051] Calculating the equivalent power difference corresponding to the equivalent time step according to the load-supply curve set;

[0052] The dynamic equivalent charge between the power demand area and the power storage device is calculated according to the equivalent power difference.

[0053] Furthermore, constructing the power compensation mode and power compensation path between the power storage device and the power demand area according to the compensation equivalent charge includes:

[0054] Determine the compensation intervals corresponding to the compensation equivalent charges, and calculate the compensation hysteresis of the compensation equivalent charges in combination with the compensation intervals;

[0055] According to the compensation hysteresis, constructing a power compensation method between the power storage device and the power demand area;

[0056] Acquire a power transmission network between the power storage device and the power demand area, and identify a power transmission device in the power transmission network;

[0057] evaluating the transmission loss rate corresponding to the power transmission device, and calculating the device distance between the power transmission devices;

[0058] In combination with the device distance and the transmission loss rate, a target transmission device is selected from the power transmission devices;

[0059] According to the target transmission device, a power compensation path is constructed between the power storage device and the power demand area.

[0060] A power peak load regulation system in a multi-type energy storage system, characterized in that the system comprises:

[0061] A power demand area determination module is used to query the power storage device corresponding to the power peak shaving instruction from the pre-built power storage system in response to the power peak shaving instruction, and clarify the power demand area corresponding to the power peak shaving instruction;

[0062] A power load curve construction module is used to monitor the power demand data of the power demand area in real time, divide the power demand data into dynamic demand data and static demand data according to a preset dimension, and respectively construct power load curves corresponding to the dynamic demand data and the static demand data to obtain a dynamic load curve and a static load curve;

[0063] A power supply curve building module, used to collect energy storage supply data and equipment operation data of the power storage device, and build a power supply curve of the power storage device based on the energy storage supply data and the equipment operation data;

[0064] a compensation equivalent charge determination module, configured to calculate the dynamic equivalent charge between the power demand area and the power storage device based on the dynamic load curve and the power supply curve, and calculate the static equivalent charge between the power demand area and the power storage device based on the static load curve and the power supply curve, and determine the compensation equivalent charge between the power demand area and the power storage device according to the dynamic equivalent charge and the static equivalent charge;

[0065] The power peak-shaving report generation module is used to construct a power compensation method and a power compensation path between the power storage device and the power demand area according to the compensation equivalent charge, and generate a power peak-shaving report between the power demand area and the power storage device based on the power compensation method and the power compensation path.

[0066] The present invention queries the power storage device corresponding to the power peak-shaving instruction from the pre-built power storage system in response to the power peak-shaving instruction, so as to facilitate the clarification of the power demand area corresponding to the power peak-shaving instruction and provide a basis for the subsequent analysis of the power resources in the power demand area. The present invention can obtain relevant information on the power demand of users in the power demand area by real-time monitoring of the power demand data of the power demand area, and divide the power demand data into dynamic demand data and static demand data according to preset dimensions, so as to facilitate the subsequent processing of data of the same dimension, thereby improving data processing efficiency and accuracy of power analysis. The present invention can understand the power storage device corresponding to the power peak-shaving device by collecting the energy storage supply data and equipment operation data of the power storage device. The energy storage situation and working condition of the power energy storage device are calculated, and the power supply curve of the power energy storage device is constructed, so that the power supply trend of the power energy storage device can be intuitively analyzed. The present invention calculates the dynamic equivalent charge between the power demand area and the power energy storage device based on the dynamic load curve and the power supply curve, so as to obtain the dynamically changing power demand situation between the power demand area and the power energy storage device, and provides a basis for the subsequent determination of the compensation equivalent charge. The present invention constructs the power compensation method and power compensation path between the power energy storage device and the power demand area according to the compensation equivalent charge, and ensures that an effective power compensation mechanism is established between the power energy storage device and the power demand area to cope with possible power shortages or instability. Therefore, a power peak-shaving method and system in a multi-type energy storage system provided in an embodiment of the present invention can improve the accuracy of power peak-shaving in a multi-type energy storage system. BRIEF DESCRIPTION OF THE DRAWINGS

[0067] Figure 1 A schematic flow chart of a method for peak load regulation of electric power in a multi-type energy storage system provided in one embodiment of the present invention;

[0068] Figure 2 A functional module diagram of a power peak load regulation system in a multi-type energy storage system provided in one embodiment of the present invention.

[0069] The realization of the purpose, functional features and advantages of the present invention will be further explained in conjunction with embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0070] It should be understood that the specific embodiments described herein are only used to explain the present invention, and are not used to limit the present invention.

[0071] An embodiment of the present application provides a method for peak-shaving of electricity in a multi-type energy storage system. In an embodiment of the present application, the execution subject of the method for peak-shaving of electricity in a multi-type energy storage system includes but is not limited to at least one of the electronic devices such as a server and a terminal that can be configured to execute the method provided in an embodiment of the present application. In other words, the method for peak-shaving of electricity in a multi-type energy storage system can be executed by software or hardware installed on a terminal device or a server device, and the software can be a blockchain platform. The server includes but is not limited to: a single server, a server cluster, a cloud server or a cloud server cluster, etc. The server can be an independent server, or it can be a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, content delivery networks (Content Delivery Network, CDN), and big data and artificial intelligence platforms.

[0072] Reference Figure 1 FIG. 1 is a flow chart of a method for peak load regulation of electric power in a multi-type energy storage system provided by an embodiment of the present invention. In this embodiment, the method for peak load regulation of electric power in a multi-type energy storage system includes steps S1-S5.

[0073] S1. In response to a power peak shaving instruction, query the power storage device corresponding to the power peak shaving instruction from a pre-built power storage system, and clarify the power demand area corresponding to the power peak shaving instruction.

[0074] The present invention queries the power storage device corresponding to the power peak shaving instruction from the pre-built power storage system in response to the power peak shaving instruction, thereby facilitating the clarification of the power demand area corresponding to the power peak shaving instruction and providing a basis for the subsequent analysis of the power resources in the power demand area.

[0075] Among them, the power peak-shaving instruction is an instruction to balance the supply and demand of the power system and adjust the production, transmission and use of electricity. The pre-constructed power energy storage system refers to a system that is pre-designed and configured for a collection of power equipment. The power energy storage equipment is a device that stores electrical energy and releases it when needed. The demand power area is a specific area that requires power adjustment. Furthermore, the power energy storage equipment corresponding to the power peak-shaving instruction is queried from the pre-constructed power energy storage system.

[0076] As an embodiment of the present invention, the method of clarifying the demand power area corresponding to the power peak-shaving instruction includes: extracting a peak-shaving instruction signal corresponding to the power peak-shaving instruction, performing quality optimization processing on the peak-shaving instruction signal to obtain a target instruction signal, decoding the target instruction signal to obtain a decoded instruction signal, extracting instruction operands and instruction operation codes in the decoded instruction signal, respectively decoding the instruction operands and the instruction operation codes to obtain a set of decoding products, analyzing the signal information in the target instruction signal according to the set of decoding products, identifying the regional information in the signal information, and clarifying the demand power area corresponding to the power peak-shaving instruction according to the regional information.

[0077] Among them, the peak-shaving instruction signal is the electrical signal corresponding to the power peak-shaving instruction, the decoded instruction signal is the executable signal obtained after the target instruction signal is decoded, the instruction operand and the instruction operation code are respectively the data or address used to specify the operation object and the code used to specify the operation type or function in the decoded instruction signal, the decoding product set is the set of specific control signals converted from the instruction operand and the instruction operation code, the signal information is the content carried by the target instruction signal, and the regional information is the address-related information in the signal information.

[0078] Optionally, the extraction of the peak-shaving instruction signal corresponding to the power peak-shaving instruction can be achieved through a signal detection algorithm, such as a square-law detector algorithm; the decoding processing of the target instruction signal can be achieved through a Manchester decoding algorithm; the instruction operand and instruction operation code in the decoded instruction signal can be extracted according to the corresponding signal format, such as the binary expression of the signal, analyzing the meaning represented by each bit or byte of the binary, so as to extract the instruction operand and the instruction operation code; the decoding processing of the instruction operand and the instruction operation code can be achieved by a decoder; the analysis process of the signal information in the target instruction signal is: extracting the part related to the signal information from the decoding product set, analyzing and interpreting the extracted information to determine its specific meaning and function, and processing the information accordingly according to the meaning and function, such as deleting invalid information, so as to obtain the signal information of the target instruction signal; the identification of the regional information in the signal information can be achieved through an OCR recognition algorithm; the demand power area corresponding to the power peak-shaving instruction can be determined according to the description address in the regional information.

[0079] Further, as an optional embodiment of the present invention, the peak shaving instruction signal is subjected to quality optimization processing to obtain a target instruction signal, including: performing signal filtering processing on the peak shaving instruction signal to obtain a filtered instruction signal, and calculating the signal energy corresponding to the filtered instruction signal by the following formula:

[0080] ,

[0081] Wherein, A represents the signal energy corresponding to the filtering instruction signal, a represents the time point of the filtering instruction signal, and r represents the time length of the filtering instruction signal. Indicates the amplitude value corresponding to the ath time point in the filtering instruction signal,

[0082] According to the signal energy, the filtered instruction signal is subjected to energy balancing processing to obtain a balanced instruction signal, and the balanced instruction signal is subjected to signal conditioning processing to obtain a target instruction signal.

[0083] Among them, the filtering command signal is a signal obtained after removing the noise interference in the peak-shaving command signal, the signal energy represents the signal amplitude value corresponding to the filtering command signal, the equalizing command signal is a signal obtained after the low energy in the filtering command signal is increased, and the signal adjustment processing of the equalizing command signal can improve the quality of the signal. Furthermore, the signal filtering processing of the peak-shaving command signal can be achieved by a low-pass filter; according to the signal energy, an energy threshold corresponding to the filtering command signal is set, and the signal energy below the energy threshold is enhanced to obtain the equalizing command signal, wherein the energy threshold can be an average energy value.

[0084] Further, as an optional embodiment of the present invention, the performing signal conditioning processing on the equalization instruction signal to obtain the target instruction signal includes:

[0085] The equalization command signal is conditioned by the following formula:

[0086] ,

[0087] Where D represents the target command signal, Indicates the signal frequency corresponding to the bth signal in the equalization command signal, represents the signal transmission rate of the bth signal in the equalization instruction signal, Q represents the signal period corresponding to the equalization instruction signal, Indicates the duration corresponding to the ath signal in the equalization command signal, It represents the phase constant corresponding to the ath signal in the equalization command signal, such as is 2;

[0088] The signal frequency, the signal transmission rate, and the signal period can be obtained through a spectrum diagram of the equalization instruction signal, and the spectrum diagram can be obtained by performing Fourier transform processing on the equalization instruction signal.

[0089] S2. Monitor the power demand data of the power demand area in real time, divide the power demand data into dynamic demand data and static demand data according to preset dimensions, and construct power load curves corresponding to the dynamic demand data and the static demand data respectively to obtain dynamic load curves and static load curves.

[0090] The present invention can obtain relevant information on the power demand of users in the power demand area by real-time monitoring of the power demand data of the power demand area, and divide the power demand data into dynamic demand data and static demand data according to preset dimensions, so as to facilitate subsequent processing of data of the same dimension, thereby improving data processing efficiency and accuracy of power analysis, wherein the power demand data is relevant information on the power demand corresponding to the power demand area, the preset dimension is a pre-set attribute or feature of the divided data, the power demand data is relevant record data on power usage in the power demand area, the dynamic demand data is data on real-time changes in the power demand data under different times and conditions, and the static demand data is data that remains stable or relatively fixed in the power demand data. Optionally, real-time monitoring of the power demand data in the power demand area can be achieved through power monitoring equipment, such as power monitoring meters, oscilloscopes, etc.

[0091] As an embodiment of the present invention, the power demand data is divided into dynamic demand data and static demand data according to a preset dimension, including: querying a quality evaluation indicator corresponding to the power demand data, calculating a quality score corresponding to the power demand data according to the quality evaluation indicator, performing data cleaning on the power demand data according to the quality score to obtain target demand data, extracting data features corresponding to the target demand data, calculating feature criticality corresponding to the data features, extracting key features from the data features according to the feature criticality, calculating the approximation between the key features and the preset dimension, and dividing the target demand data according to the approximation to obtain dynamic demand data and static demand data.

[0092] Among them, the quality evaluation index is the quality evaluation basis corresponding to the power demand data, the quality score indicates the quality of the power demand data, the data feature is the data representation corresponding to the target demand data, such as the type of power user used, the feature criticality indicates the importance of the data feature, and the approximation indicates the similarity between the key feature and the preset dimension.

[0093] Optionally, the quality evaluation index corresponding to the power demand data can be obtained by querying the power system management platform, and the power system management platform will analyze the relevant power demand data to obtain relevant quality evaluation indicators; extract the index data corresponding to the quality evaluation index from the power demand data, standardize the index data to obtain standard index data, calculate the proportionality coefficient between the index standard values ​​corresponding to the standard index data, and determine the quality score corresponding to the power demand data according to the proportionality coefficient. For example, if the proportionality coefficient is 0.7, the quality score can be set to 70 points; compare the quality score with the reference value corresponding to the quality evaluation index. If the quality score is lower than the reference value, the power demand data is The target demand data can be obtained by cleaning the data; the extraction of data features corresponding to the target demand data can be achieved through a deep learning model, such as a convolutional neural network; the feature criticality can be obtained by calculating the feature Gini coefficient corresponding to the data feature; based on the numerical value of the feature criticality, the key features in the data features are extracted, and the feature with the largest feature criticality is extracted from each type of the data features as the key feature; the calculation of the approximation between the key feature and the preset dimension can be achieved through a cosine similarity algorithm; the approximation is compared with the preset similarity, and when the approximation is greater than the preset similarity, the target demand data is divided and processed to obtain dynamic demand data and static demand data.

[0094] The present invention constructs power load curves corresponding to the dynamic demand data and the static demand data respectively, so as to understand the changing trends of the dynamic demand data and the static demand data within a certain period of time, thereby facilitating the subsequent determination of equivalent charge, wherein the dynamic load curve and the static load curve are distribution curves describing the changing trends corresponding to the dynamic demand data and the static demand data respectively.

[0095] As an embodiment of the present invention, the power load curves corresponding to the dynamic demand data and the static demand data are respectively constructed to obtain dynamic load curves and static load curves, including: performing data clustering processing on the dynamic demand data and the static demand data to obtain dynamic clustering data and static clustering data, analyzing the dynamic variables in the dynamic clustering data, and extracting dynamic values ​​corresponding to the dynamic variables from the dynamic clustering data, eliminating discrete values ​​in the dynamic values, and obtaining target dynamic values, analyzing the static variables in the static clustering data, and extracting static values ​​corresponding to the static variables from the static clustering data, eliminating discrete values ​​in the static values, and obtaining target static values, and combining the dynamic variables, the target dynamic values, the static variables and the target static values ​​to respectively construct the power load curves corresponding to the dynamic clustering data and the static clustering data to obtain dynamic load curves and static load curves.

[0096] Among them, the dynamic clustering data and the static clustering data are respectively data obtained by clustering similar data in the dynamic demand data and the static demand data together, such as similar data structure or type, the dynamic variable is the variable factor in the dynamic clustering data, which is divided into independent variables and dependent variables, the dynamic value is the descriptive value of the dynamic variable in the dynamic clustering data, and the target dynamic value is the value obtained after eliminating abnormal values ​​in the dynamic value. Optionally, the data clustering processing of the dynamic demand data and the static demand data can be implemented by a clustering algorithm, such as the K-Means algorithm; the analysis of the dynamic variables in the dynamic clustering data can be implemented by principal component analysis; the extraction of the dynamic values ​​corresponding to the dynamic variables can be implemented by an extraction function, and the extraction function is compiled by a scripting language, such as JS scripting language; the variance value between each value in the dynamic value can be used to eliminate discrete values ​​in the dynamic value according to the variance value; the construction of the power load curve corresponding to the dynamic clustering data and the static clustering data can be implemented by a drawing tool, such as the Visio drawing tool.

[0097] S3. Collecting energy storage supply data and equipment operation data of the electric energy storage device, and constructing a power supply curve of the electric energy storage device based on the energy storage supply data and the equipment operation data.

[0098] By collecting the energy storage supply data and equipment operation data of the electric energy storage device, the present invention can understand the energy storage situation and working condition corresponding to the electric energy storage device, and construct a power supply curve of the electric energy storage device, which can intuitively analyze the power supply trend of the electric energy storage device. Furthermore, the collection of the energy storage supply data and equipment operation data of the electric energy storage device can be achieved through a data recorder, such as a sensor.

[0099] As an embodiment of the present invention, constructing the power supply curve of the power storage device based on the energy storage supply data and the equipment operation data includes: extracting normal operation data and equipment failure data from the equipment operation data, respectively determining the cycle durations corresponding to the normal operation data and the equipment failure data, obtaining the equipment operation duration and the equipment failure duration, calculating the equipment failure rate of the power storage device in combination with the equipment operation duration and the equipment failure duration, and constructing the power supply curve of the power storage device in combination with the energy storage supply data and the equipment failure rate.

[0100] Among them, the normal operating data and the equipment failure data are respectively the data of the normal operating of the equipment and the data when an abnormality occurs in the equipment operating data; the equipment operating duration and the equipment failure duration are respectively the length of time of stable operation of the equipment in the normal operating data and the duration when an abnormality occurs in the equipment; the equipment failure rate represents the probability of failure of the power storage device.

[0101] Optionally, the cycle duration can be obtained by counting the timestamps corresponding to each data in the normal operating data and the equipment failure data, and the corresponding duration is calculated according to the timestamp to obtain the equipment operating duration and the equipment failure duration; the equipment failure rate of the power storage device is calculated as follows: equipment failure rate = (equipment failure duration / equipment operating duration + equipment failure duration) × 100%, and the initial power supply curve corresponding to the power storage device can be constructed through the energy storage supply data, and the slope of the initial power supply curve can be adjusted using the equipment failure rate. For example, if the equipment failure rate in the morning time period is higher, the slope of the curve corresponding to the morning time period in the initial power supply curve is set to be flat to obtain the final power supply curve. The specific setting parameters can be determined by combining the previous historical failure data and the historical power supply curve, and the relationship between the historical failure rate and the curve slope is established through a polynomial model, and the degree of adjustment of the curve slope is determined based on this relationship.

[0102] Further, as an optional embodiment of the present invention, the extracting normal operation data and equipment fault data from the equipment operation data includes: querying the state index and index threshold corresponding to the power storage device, determining the index parameter value corresponding to the state index in combination with the equipment operation data, identifying the normal index and the abnormal index in combination with the index parameter value and the index threshold, analyzing the abnormal influencing factor corresponding to the abnormal index, determining the hard fault index in the abnormal index according to the abnormal influencing factor, and extracting the normal operation data and equipment fault data from the equipment operation data in combination with the normal index and the hard fault index.

[0103] Among them, the state indicator is an indicator of the stability of the operating state of the electric energy storage device, such as current, power and temperature, the indicator threshold is a reference value corresponding to the state indicator, the indicator parameter value is a specific numerical value corresponding to the state indicator, the abnormal influencing factor is the abnormal cause corresponding to the abnormal indicator, and the hard fault indicator is an indicator of permanent fault among the abnormal indicators.

[0104] Furthermore, the corresponding status indicators and indicator thresholds can be queried through the industry standards and specifications corresponding to the power energy storage equipment; the indicator parameter value and the indicator threshold are compared, and the normal indicators and abnormal indicators in the status indicators are identified according to the comparison results. For example, if the indicator parameter value is greater than the indicator threshold, the corresponding status indicator is an abnormal indicator; the abnormal influencing factor can be obtained by analyzing the various parameters of the abnormal indicator; according to the type corresponding to the abnormal influencing factor, the hard fault indicator in the abnormal indicator is determined. For example, if the equipment is damaged, it means that the fault is a permanent fault, and the abnormal indicator is a hard fault indicator.

[0105] S4. Based on the dynamic load curve and the power supply curve, the dynamic equivalent charge between the power demand area and the power storage device is calculated, and based on the static load curve and the power supply curve, the static equivalent charge between the power demand area and the power storage device is calculated, and according to the dynamic equivalent charge and the static equivalent charge, the compensating equivalent charge between the power demand area and the power storage device is determined.

[0106] The present invention calculates the dynamic equivalent charge between the power demand area and the power storage device based on the dynamic load curve and the power supply curve, so as to obtain the dynamically changing power demand between the power demand area and the power storage device, and provides a basis for the subsequent determination of the compensating equivalent charge, wherein the dynamic equivalent charge is the charge amount of the dynamically changing power demand between the power demand area and the power storage device.

[0107] As an embodiment of the present invention, the dynamic equivalent charge between the demand power area and the power storage device is calculated based on the dynamic load curve and the power supply curve, including: identifying the synchronization time point in the dynamic load curve and the power supply curve, and according to the synchronization time point, performing curve alignment processing on the dynamic load curve and the power supply curve to obtain a load-supply curve set, setting an equivalent time step corresponding to the load-supply curve set in combination with the synchronization time point, and calculating the equivalent power difference corresponding to the equivalent time step according to the load-supply curve set, and calculating the dynamic equivalent charge between the demand power area and the power storage device according to the equivalent power difference.

[0108] Among them, the synchronization time point is the same time point in the dynamic load curve and the power supply curve, the load-supply curve set is a curve obtained by aligning the dynamic load curve and the power supply curve according to the synchronization time point, the equivalent time step is the time interval of electricity consumption in the load-supply curve set, for example, one hour can be set as the equivalent time step, and the equivalent power difference is the difference in power on the load-supply curve set within the equivalent time step.

[0109] Optionally, the synchronization time points in the dynamic load curve and the power supply curve can be identified by a corresponding time identification tool, and the time identification tool is compiled in JAVA language; the equivalent time step corresponding to the load-supply curve set can be set in combination with the unit or total time length between the synchronization time points, for example, if the unit is hours, it can be set to one hour, or two hours as an equivalent time step, which is set specifically in combination with the actual application scenario; the equivalent power difference corresponding to the equivalent time step can be obtained by calculating the power difference on the load-supply curve set within the step and summing them up; the average equivalent power difference corresponding to the equivalent power difference is calculated to obtain the dynamic equivalent charge between the demand power area and the power storage device.

[0110] The present invention calculates the static equivalent charge between the power demand area and the power storage device based on the static load curve and the power supply curve, thereby obtaining a relatively stable power demand situation between the power demand area and the power storage device, and determines the compensating equivalent charge between the power demand area and the power storage device according to the dynamic equivalent charge and the static equivalent charge, so as to obtain a specific regulated power value. Furthermore, the calculation principle of the static equivalent charge is the same as that of the dynamic equivalent charge, which will not be elaborated herein; the compensating equivalent charge between the power demand area and the power storage device can be obtained by the difference between the dynamic equivalent charge and the static equivalent charge.

[0111] S5. According to the compensation equivalent charge, a power compensation method and a power compensation path are constructed between the power storage device and the power demand area. According to the power compensation method and the power compensation path, the power compensation effect between the power storage device and the power demand area is analyzed. When the power compensation effect meets the preset conditions, a power peak regulation report between the power demand area and the power storage device is generated based on the power compensation method and the power compensation path.

[0112] The present invention constructs a power compensation method and a power compensation path between the power storage device and the power demand area based on the compensated equivalent charge, ensuring that an effective power compensation mechanism is established between the power storage device and the power demand area to cope with possible power shortages or instability, wherein the power compensation method is a method of regulating the amount of electricity between the power storage device and the power demand area, and the power compensation path is a power transmission channel between the power storage device and the power demand area.

[0113] As an embodiment of the present invention, the power compensation method and power compensation path between the power storage device and the power demand area are constructed based on the compensation equivalent charge, including: determining the compensation interval corresponding to the compensation equivalent charges, calculating the compensation hysteresis of the compensation equivalent charge in combination with the compensation interval, constructing the power compensation method between the power storage device and the power demand area according to the compensation hysteresis, obtaining the power transmission network between the power storage device and the power demand area, identifying the power transmission devices in the power transmission network, evaluating the transmission loss rate corresponding to the power transmission devices, and calculating the device distance between the power transmission devices, combining the device distance and the transmission loss rate, screening out the target transmission device from the power transmission devices, and constructing the power compensation path between the power storage device and the power demand area according to the target transmission device.

[0114] Among them, the compensation interval is the time interval between the compensation equivalent charges, the compensation hysteresis represents the compensation change speed between the compensation equivalent charges, the power transmission network is the device and power transmission channel for transmitting power between the power storage equipment and the power demand area, the transmission loss rate represents the degree of energy loss caused by the power transmission device during transmission, and the target transmission device is the device corresponding to the power transmission device with the smallest device distance and the transmission loss rate.

[0115] Furthermore, the compensation interval corresponding to the compensated equivalent charges can be obtained by calculating the time difference between the compensated equivalent charges; the compensated charge difference between the compensated equivalent charges is calculated, and the compensation hysteresis is obtained by dividing the compensated charge difference by the compensation interval; according to the compensation hysteresis, a power compensation method between the power storage device and the power demand area is constructed. For example, if the compensation hysteresis is small, it means that the change is slow, and a distributed method can be used for step-by-step compensation, such as slow charging and discharging; the power transmission network between the power storage device and the power demand area can be obtained from the database of the power supply department; the power transmission device in the power transmission network can be realized by OCR recognition technology to identify the description information in the power transmission network, and determine the corresponding device name according to the description information; the power transmission device is dispatched The historical power transmission data corresponding to the device is determined, and the final transmission power and the initial transmission power of the power transmission device are determined according to the historical power transmission data, then the transmission loss rate = (initial transmission power-final transmission power) ÷ initial transmission power × 100%; the device distance between the power transmission devices can be calculated by the Euclidean distance algorithm; in combination with the device distance and the numerical value corresponding to the transmission loss rate, a target transmission device is screened out from the power transmission devices, for example, if the transmission loss rate is small and the device distance is short, then the device can be used as the final transmission device; the device capacity of the target transmission device is determined, and according to the device capacity, the compensation equivalent charge is distributed and processed to obtain the device transmission charge, and in combination with the target transmission device and the device transmission charge, a power compensation path between the power storage device and the power demand area is constructed.

[0116] The present invention generates a power peak-shaving report between the power demand area and the power storage device based on the power compensation method and the power compensation path, thereby improving the accuracy of power peak-shaving between the power demand area and the power storage device, wherein the power peak-shaving report is a comprehensive and systematic summary and analysis of the peak-shaving situation between the power demand area and the power storage device, and further, the generation of the power peak-shaving report between the power demand area and the power storage device can be achieved by writing a corresponding programming program.

[0117] The present invention queries the power storage device corresponding to the power peak-shaving instruction from the pre-built power storage system in response to the power peak-shaving instruction, so as to facilitate the clarification of the power demand area corresponding to the power peak-shaving instruction and provide a basis for the subsequent analysis of the power resources in the power demand area. The present invention can obtain relevant information on the power demand of users in the power demand area by real-time monitoring of the power demand data of the power demand area, and divide the power demand data into dynamic demand data and static demand data according to preset dimensions, so as to facilitate the subsequent processing of data of the same dimension, thereby improving data processing efficiency and accuracy of power analysis. The present invention can understand the power storage device corresponding to the power peak-shaving device by collecting the energy storage supply data and equipment operation data of the power storage device. The energy storage situation and working condition of the power energy storage device are calculated, and the power supply curve of the power energy storage device is constructed, so that the power supply trend of the power energy storage device can be intuitively analyzed. The present invention calculates the dynamic equivalent charge between the power demand area and the power energy storage device based on the dynamic load curve and the power supply curve, so as to obtain the dynamically changing power demand situation between the power demand area and the power energy storage device, and provides a basis for the subsequent determination of the compensation equivalent charge. The present invention constructs the power compensation method and power compensation path between the power energy storage device and the power demand area according to the compensation equivalent charge, and ensures that an effective power compensation mechanism is established between the power energy storage device and the power demand area to cope with possible power shortages or instability. Therefore, a power peak-shaving method in a multi-type energy storage system provided in an embodiment of the present invention can improve the accuracy of power peak-shaving in a multi-type energy storage system.

[0118] like Figure 2 , is a functional module diagram of a power peak load regulation system in a multi-type energy storage system provided by an embodiment of the present invention.

[0119] The power peak shaving system 100 in a multi-type energy storage system described in the present invention can be installed in an electronic device. According to the functions to be implemented, the power peak shaving system 100 in a multi-type energy storage system can include a demand power area determination module 101, a power load curve construction module 102, a power supply curve construction module 103, a compensation equivalent charge determination module 104 and a power peak shaving report generation module 105. The module described in the present invention can also be referred to as a unit, which refers to a series of computer program segments that can be executed by an electronic device processor and can complete fixed functions, which are stored in the memory of the electronic device.

[0120] In this embodiment, the functions of each module / unit are as follows:

[0121] The power demand area determination module 101 is used to query the power storage device corresponding to the power peak shaving instruction from the pre-built power storage system in response to the power peak shaving instruction, and clarify the power demand area corresponding to the power peak shaving instruction;

[0122] The power load curve construction module 102 is used to monitor the power demand data of the power demand area in real time, divide the power demand data into dynamic demand data and static demand data according to a preset dimension, and respectively construct power load curves corresponding to the dynamic demand data and the static demand data to obtain a dynamic load curve and a static load curve;

[0123] The power supply curve building module 103 is used to collect energy storage supply data and device operation data of the power storage device, and build a power supply curve of the power storage device based on the energy storage supply data and the device operation data;

[0124] The compensation equivalent charge determination module 104 is used to calculate the dynamic equivalent charge between the power demand area and the power storage device based on the dynamic load curve and the power supply curve, and calculate the static equivalent charge between the power demand area and the power storage device based on the static load curve and the power supply curve, and determine the compensation equivalent charge between the power demand area and the power storage device according to the dynamic equivalent charge and the static equivalent charge;

[0125] The power peak shaving report generating module 105 is used to construct a power compensation method and a power compensation path between the power storage device and the power demand area according to the compensation equivalent charge, and generate a power peak shaving report between the power demand area and the power storage device based on the power compensation method and the power compensation path.

[0126] In detail, each module described in the power peak load regulation system 100 in the multi-type energy storage system described in the embodiment of the present application is used in the same manner as described above. Figure 1 The technical means are the same as the power peak regulation method in a multi-type energy storage system described in, and can produce the same technical effects, so they will not be repeated here.

[0127] Finally, it should be noted that the above embodiments are only used to illustrate the technical solution of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solution of the present invention can be modified or replaced by equivalents without departing from the spirit and scope of the technical solution of the present invention.

Claims

1. A method for peak load regulation in a multi-type energy storage system, characterized in that: The method comprises: In response to the power peak shaving instruction, query the power storage device corresponding to the power peak shaving instruction from the pre-built power storage system, and clarify the power demand area corresponding to the power peak shaving instruction; Monitor the power demand data of the power demand area in real time, divide the power demand data into dynamic demand data and static demand data according to a preset dimension, and construct power load curves corresponding to the dynamic demand data and the static demand data respectively to obtain a dynamic load curve and a static load curve; Collecting energy storage supply data and equipment operation data of the electric energy storage device, and constructing a power supply curve of the electric energy storage device based on the energy storage supply data and the equipment operation data; Calculating the dynamic equivalent charge between the power demand area and the power storage device based on the dynamic load curve and the power supply curve, and calculating the static equivalent charge between the power demand area and the power storage device based on the static load curve and the power supply curve, and determining the compensation equivalent charge between the power demand area and the power storage device according to the dynamic equivalent charge and the static equivalent charge; According to the compensation equivalent charge, a power compensation method and a power compensation path are constructed between the power storage device and the power demand area, and based on the power compensation method and the power compensation path, a power peak regulation report between the power demand area and the power storage device is generated.

2. A method for peak load regulation in a multi-type energy storage system according to claim 1, characterized in that: The clarifying the power demand area corresponding to the power peak load regulation instruction includes: Extracting a peak-shaving instruction signal corresponding to the power peak-shaving instruction, performing quality optimization processing on the peak-shaving instruction signal, and obtaining a target instruction signal; Decoding the target instruction signal to obtain a decoded instruction signal, and extracting an instruction operand and an instruction operation code from the decoded instruction signal; Decoding the instruction operand and the instruction operation code respectively to obtain a decoding product set; Analyzing signal information in the target command signal according to the decoding product set, and identifying regional information in the signal information; According to the regional information, the power demand area corresponding to the power peak load regulation instruction is clarified.

3. A method for peak load regulation in a multi-type energy storage system according to claim 2, characterized in that: The step of performing quality optimization processing on the peak shaving instruction signal to obtain a target instruction signal includes: Performing signal filtering processing on the peak shaving instruction signal to obtain a filtered instruction signal; The signal energy corresponding to the filtering instruction signal is calculated by the following formula: ， Wherein, A represents the signal energy corresponding to the filtering instruction signal, a represents the time point of the filtering instruction signal, and r represents the time length of the filtering instruction signal. Indicates the amplitude value corresponding to the ath time point in the filtering instruction signal, According to the signal energy, performing energy balancing processing on the filtered instruction signal to obtain a balanced instruction signal; The equalization instruction signal is subjected to signal conditioning processing to obtain a target instruction signal.

4. The power peak regulation method in a multi-type energy storage system according to claim 1, characterized in that: The dividing the power demand data into dynamic demand data and static demand data according to a preset dimension includes: Querying a quality evaluation indicator corresponding to the power demand data, and calculating a quality score corresponding to the power demand data according to the quality evaluation indicator; According to the quality score, the power demand data is cleaned to obtain target demand data; Extracting data features corresponding to the target demand data, and calculating feature criticality corresponding to the data features; According to the feature criticality, extract the key features from the data features, and calculate the approximation between the key features and the preset dimension; According to the approximation, the target demand data is divided and processed to obtain dynamic demand data and static demand data.

5. The power peak regulation method in a multi-type energy storage system according to claim 1, characterized in that: The step of respectively constructing power load curves corresponding to the dynamic demand data and the static demand data to obtain a dynamic load curve and a static load curve includes: Performing data clustering processing on the dynamic demand data and the static demand data respectively to obtain dynamic clustering data and static clustering data; Analyzing dynamic variables in the dynamic clustering data, and extracting dynamic values ​​corresponding to the dynamic variables from the dynamic clustering data; Remove discrete values ​​from the dynamic values ​​to obtain target dynamic values, and analyze static variables in the static clustering data; Extracting static values ​​corresponding to the static variables from the static clustering data, removing discrete values ​​from the static values, and obtaining target static values; In combination with the dynamic variable, the target dynamic value, the static variable and the target static value, power load curves corresponding to the dynamic clustering data and the static clustering data are respectively constructed to obtain a dynamic load curve and a static load curve.

6. The method for peak load regulation in a multi-type energy storage system according to claim 1, characterized in that: The step of constructing a power supply curve of the power energy storage device based on the energy storage supply data and the device operation data comprises: Extracting normal operation data and equipment failure data from the equipment operation data; Respectively determine the cycle durations corresponding to the normal operation data and the equipment failure data to obtain the equipment operation duration and the equipment failure duration; Calculate the equipment failure rate of the power storage device based on the equipment operation time and the equipment failure time; Combining the energy storage supply data and the equipment failure rate, a power supply curve of the power storage device is constructed.

7. A method for peak load regulation in a multi-type energy storage system according to claim 6, characterized in that: The extracting the normal operation data and the equipment failure data from the equipment operation data includes: Querying the status index and index threshold corresponding to the electric energy storage device; Determine the indicator parameter value corresponding to the status indicator in combination with the equipment operation data; Combining the indicator parameter value and the indicator threshold, identifying normal indicators and abnormal indicators in the status indicators; Analyze the abnormal impact factor corresponding to the abnormal indicator, and determine the hard fault indicator in the abnormal indicator according to the abnormal impact factor; The normal operation data and the equipment failure data in the equipment operation data are extracted by combining the normal index and the hard failure index.

8. The method for peak load regulation in a multi-type energy storage system according to claim 1, characterized in that: The calculating, based on the dynamic load curve and the power supply curve, the dynamic equivalent charge between the power demand area and the power storage device comprises: identifying synchronization points in the dynamic load profile and the power supply profile; According to the synchronization time point, performing curve alignment processing on the dynamic load curve and the power supply curve to obtain a load-supply curve set; In combination with the synchronization time point, setting an equivalent time step corresponding to the load-supply curve set; Calculating the equivalent power difference corresponding to the equivalent time step according to the load-supply curve set; The dynamic equivalent charge between the power demand area and the power storage device is calculated according to the equivalent power difference.

9. The method for peak load regulation in a multi-type energy storage system according to claim 1, characterized in that: The step of constructing a power compensation method and a power compensation path between the power storage device and the power demand area according to the compensation equivalent charge includes: Determine the compensation intervals corresponding to the compensation equivalent charges, and calculate the compensation hysteresis of the compensation equivalent charges in combination with the compensation intervals; According to the compensation hysteresis, constructing a power compensation method between the power storage device and the power demand area; Acquire a power transmission network between the power storage device and the power demand area, and identify a power transmission device in the power transmission network; evaluating the transmission loss rate corresponding to the power transmission device, and calculating the device distance between the power transmission devices; In combination with the device distance and the transmission loss rate, a target transmission device is selected from the power transmission devices; According to the target transmission device, a power compensation path is constructed between the power storage device and the power demand area.

10. A power peak load regulation system in a multi-type energy storage system, characterized in that: The system comprises: A power demand area determination module is used to query the power storage device corresponding to the power peak shaving instruction from the pre-built power storage system in response to the power peak shaving instruction, and clarify the power demand area corresponding to the power peak shaving instruction; A power load curve construction module is used to monitor the power demand data of the power demand area in real time, divide the power demand data into dynamic demand data and static demand data according to a preset dimension, and respectively construct power load curves corresponding to the dynamic demand data and the static demand data to obtain a dynamic load curve and a static load curve; A power supply curve building module, used to collect energy storage supply data and equipment operation data of the power storage device, and build a power supply curve of the power storage device based on the energy storage supply data and the equipment operation data; a compensation equivalent charge determination module, configured to calculate the dynamic equivalent charge between the power demand area and the power storage device based on the dynamic load curve and the power supply curve, and calculate the static equivalent charge between the power demand area and the power storage device based on the static load curve and the power supply curve, and determine the compensation equivalent charge between the power demand area and the power storage device according to the dynamic equivalent charge and the static equivalent charge; The power peak-shaving report generation module is used to construct a power compensation method and a power compensation path between the power storage device and the power demand area according to the compensation equivalent charge, and generate a power peak-shaving report between the power demand area and the power storage device based on the power compensation method and the power compensation path.

Images