CN111584952A - Method and system for online evaluation of electrochemical cells of energy storage power station - Google Patents
Method and system for online evaluation of electrochemical cells of energy storage power station Download PDFInfo
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Abstract
Description
技术领域technical field
本发明涉及电化学电池充放电领域，具体涉及一种用于储能电站电化学电池在线评估的方法和系统。The invention relates to the field of charging and discharging of electrochemical cells, in particular to a method and system for on-line evaluation of electrochemical cells in energy storage power stations.
背景技术Background technique
储能技术在电力系统“电能生产、传输、分配和消费”中增加一个“存储”环节，使原本几乎“刚性”的系统变得“柔性”起来。大容量的电池储能具有快速吸收能量并适时释放的特点，可实现能量的时间迁移，解决新能源发电的出力波动性和不确定性引起的系统供电充裕性不足问题。随着电池材料、制造工艺、系统集成及运行维护等方面实现技术突破，储能的制造和运行成本大大降低，储能系统发展潜力巨大。电化学储能以其能量密度高、充放电速率快、使用寿命长的特点成为储能电站电池的首选，但是电化学储能电池的安全性和可靠性一直都是其应用中必须十分关注的问题：Energy storage technology adds a "storage" link to the "electricity production, transmission, distribution and consumption" of the power system, making the almost "rigid" system "flexible". Large-capacity battery energy storage has the characteristics of rapid energy absorption and timely release, which can realize the time migration of energy and solve the problem of insufficient system power supply adequacy caused by the output fluctuation and uncertainty of new energy power generation. With technological breakthroughs in battery materials, manufacturing processes, system integration, and operation and maintenance, the manufacturing and operating costs of energy storage are greatly reduced, and the development potential of energy storage systems is huge. Electrochemical energy storage has become the first choice for energy storage power station batteries due to its high energy density, fast charge and discharge rate, and long service life, but the safety and reliability of electrochemical energy storage batteries have always been the focus of its application. question:
一方面，能量大、电压高且电解液大多为有机易燃物，应用不当有可能导致电池温度升高、着火甚至爆炸；On the one hand, the energy is large, the voltage is high, and the electrolytes are mostly organic flammables. Improper application may cause the battery to rise in temperature, catch fire or even explode;
另一方面，电化学储能电池过充电、过放电会导致电池内部材料特性发生变化，造成不可逆的损失，从而导致性能下降；On the other hand, the overcharge and overdischarge of the electrochemical energy storage battery will lead to changes in the internal material properties of the battery, resulting in irreversible losses, resulting in performance degradation;
再有，由于工艺的差异性，电池内阻往往不一致，随着充放电的循环进行，电池组内单体电池的性能失衡，使电池组的寿命缩短、性能下降。Furthermore, due to the differences in the process, the internal resistance of the battery is often inconsistent. As the cycle of charge and discharge proceeds, the performance of the single cells in the battery pack is unbalanced, which shortens the life of the battery pack and reduces its performance.
综上所述，必须为储能电池配套智能、高效的状态监测、在线评估体系，建立支撑储能健康管理和安全管理的电池储能在线评估系统，融合动态工况的实时运行状态感知、健康状态评估，对电池进行有效的安全性和可靠性管理。To sum up, it is necessary to provide an intelligent and efficient state monitoring and online evaluation system for energy storage batteries, establish an online battery energy storage evaluation system that supports energy storage health management and safety management, and integrate real-time operating state perception and health of dynamic operating conditions. Condition assessment for effective safety and reliability management of batteries.
发明内容SUMMARY OF THE INVENTION
本发明的目的是提供一种用于储能电站电化学电池在线评估的方法和系统，集储能电站大数据分析、可视化维护、精细化管理于一体，能够实现对储能电站每个电池单体全命周期的数据接入、处理与分析，完成对储能电站整体、电池堆、电池模组、电池单体的全生命周期监视、状态分析、在线评估等功能。The purpose of the present invention is to provide a method and system for on-line evaluation of electrochemical cells in energy storage power stations, which integrates big data analysis, visual maintenance, and refined management of energy storage power stations, and can realize the evaluation of each battery cell of energy storage power stations. Data access, processing and analysis of the whole life cycle of the energy storage power station, complete the whole life cycle monitoring, status analysis, online evaluation and other functions of the energy storage power station as a whole, battery stacks, battery modules, and battery cells.
为解决上述问题，本发明的第一方面提供了一种用于储能电站电化学电池在线评估的方法，包括：In order to solve the above problems, a first aspect of the present invention provides a method for on-line evaluation of electrochemical cells in energy storage power stations, including:
实时采集电池状态监测数据。Collect battery status monitoring data in real time.
模型规范化处理所述电池数据，业务化存储采集的电池数据。The model normalizes and processes the battery data, and stores the collected battery data in a business manner.
设定不同的时间阈值，针对不同的时间阈值分析所述电池数据。Different time thresholds are set for which the battery data is analyzed.
根据不同特性电池的“特征指纹”评估电池状态。Evaluate battery status based on "feature fingerprints" of batteries with different characteristics.
根据本发明的一个实施例，所述模型规范化处理所述电池数据，包括：According to an embodiment of the present invention, the model normalizing the battery data includes:
建立各种储能电站业务模型，分类划分电池为电池单体、电池模组、电池堆，规范所述电池业务模型与不同电池类别之间的对应关系。Establish various energy storage power station business models, classify batteries into battery cells, battery modules, and battery stacks, and standardize the correspondence between the battery business models and different battery categories.
将实时采集的电池四遥数据转化为与电池业务模型相关的业务数据，并按照业务模型进行数据存储。Convert the battery remote data collected in real time into business data related to the battery business model, and store the data according to the business model.
根据本发明的一个实施例，所述将实时采集的电池数据转化为与电池业务模型相关的业务数据，包括：用电池采集装置的采集点表建成装置模板。根据电池业务数据的信息模型及编码定义模板中的数据业务信息类型。According to an embodiment of the present invention, converting the battery data collected in real time into service data related to the battery service model includes: building a device template with a collection point table of the battery collection device. The data service information type in the template is defined according to the information model and coding of the battery service data.
根据装置模板实例化装置。将电池设备电池堆、电池模组、电池单体的数据按设备、属性及设备属性值按电池模型建立数据表。Instantiate a device from a device template. The data of the battery equipment battery stack, battery module and battery cell is established according to the device, attribute and device attribute value according to the battery model.
根据本发明的一个实施例，所述设定不同的时间阈值，通过多角度阈值描绘电池运行状态的“特征指纹”，从而利用“特征指纹”来分析所述电池数据，包括：采用统计计算、极差值分析、关联性分析、灰色度分析、概率分析的方法分析电池数据。According to an embodiment of the present invention, different time thresholds are set, and the "feature fingerprint" of the battery operating state is depicted through multi-angle thresholds, so as to use the "feature fingerprint" to analyze the battery data, including: using statistical calculation, The battery data are analyzed by means of range analysis, correlation analysis, grey level analysis and probability analysis.
根据本发明的一个实施例，所述电池数据包括：电池电压、电池内阻、电池容量。According to an embodiment of the present invention, the battery data includes: battery voltage, battery internal resistance, and battery capacity.
根据本发明的一个实施例，所述设定不同的时间阈值，针对不同的时间阈值分析所述电池数据，包括：According to an embodiment of the present invention, the setting of different time thresholds, and the analysis of the battery data for the different time thresholds includes:
设定第一阈值时间，分析电池的一致性，包括：计算并联电池堆的压差与内阻差，判断与电池堆相关的电站荷电状态，得到电池一致性评估结果。The first threshold time is set to analyze the consistency of the batteries, including: calculating the voltage difference and internal resistance difference of the parallel battery stacks, judging the state of charge of the power station related to the battery stacks, and obtaining the battery consistency evaluation results.
设定第二阈值时间，评估电池寿命、修正可用电池容量，包括：利用灰色度法和增量分析法，分析电池堆、电池模组、电池单体的电池全生命周期过程数据，基于电池循环寿命标称数据建立电池容量衰退模型，通过对充放电曲线进行特征提取，根据特征变量不一致性，评估电池寿命是否终止，评估电池组、电池堆的整体寿命以及修正可用电池容量。Set the second threshold time, evaluate the battery life, and correct the available battery capacity, including: using the gray scale method and incremental analysis method to analyze the battery life cycle process data of battery stacks, battery modules, and battery cells, based on battery cycles The nominal life data is used to establish a battery capacity decay model. By extracting the characteristics of the charge-discharge curve, according to the inconsistency of the characteristic variables, to evaluate whether the battery life is terminated, to evaluate the overall life of the battery pack and the battery stack, and to correct the available battery capacity.
本发明的另一方面提供了一种用于储能电站电化学电池在线评估的系统，包括：采集单元，用于实时采集电池数据，存储采集的电池数据。Another aspect of the present invention provides a system for on-line evaluation of an electrochemical battery in an energy storage power station, comprising: a collection unit for collecting battery data in real time and storing the collected battery data.
处理单元，用于模型规范化处理所述电池数据。The processing unit is used for model normalization to process the battery data.
分析单元，用于设定不同的时间阈值，针对不同的时间阈值分析所述电池数据。评估单元，用于根据不同的分析结果评估电池状态。An analysis unit, configured to set different time thresholds, and analyze the battery data for different time thresholds. Evaluation unit for evaluating the battery status based on different analysis results.
根据本发明的一个实施例，所述处理单元，包括：模型规范单元，用于建立各种储能电站业务模型，分类划分电池为电池单体、电池模组、电池堆，规范所述电池业务模型与不同电池类别之间的对应关系。According to an embodiment of the present invention, the processing unit includes: a model specification unit for establishing various business models of energy storage power stations, classifying batteries into battery cells, battery modules, and battery stacks, and regulating the battery business Correspondence between models and different battery classes.
数据转换单元，用于将实时采集的电池数据转化为与电池业务模型相关的业务数据。The data conversion unit is used to convert the battery data collected in real time into business data related to the battery business model.
根据本发明的一个实施例，所述数据转换单元，包括：模板构建模块，用于根据电池采集装置的采集点表建成装置模板。According to an embodiment of the present invention, the data conversion unit includes: a template building module for building a device template according to a collection point table of the battery collection device.
编码定义模块，用于根据电池业务数据的信息模型及编码定义模板中的数据业务信息类型。The coding definition module is used to define the data service information type in the template according to the information model and coding of the battery service data.
实例化模块，用于根据装置模板实例化装置。The instantiation module is used to instantiate the device according to the device template.
数据对应模块，用于将电池设备电池堆、电池模组、电池单体的数据按设备、属性及设备属性值按电池模型建立数据表。The data correspondence module is used to establish a data table according to the battery model according to the data of the battery equipment battery stack, battery module and battery cell according to the equipment, attributes and equipment attribute values.
根据本发明的一个实施例，所述分析单元，包括：According to an embodiment of the present invention, the analysis unit includes:
第一分析单元，用于设定第一阈值时间，分析电池的一致性。The first analysis unit is configured to set a first threshold time and analyze the consistency of the battery.
第二分析单元，用于设定第二阈值时间，评估电池寿命、修正可用电池容量。包括：第一分析模块，用于分析电池堆、电池模组、电池单体的电池全生命周期过程数据；第二分析模块，用于根据电池循环寿命标称数据建立电池容量衰退模型；第三分析模块，用于特征提取充放电曲线数据，评估电池寿命是否终止，评估电池组、电池堆的整体寿命以及修正可用电池容量。The second analysis unit is configured to set a second threshold time, evaluate the battery life, and correct the available battery capacity. It includes: a first analysis module, used to analyze the battery life cycle process data of the battery stack, battery module, and battery cell; a second analysis module, used to establish a battery capacity decay model according to the nominal data of battery cycle life; the third Analysis module for feature extraction of charge-discharge curve data, evaluation of battery life termination, evaluation of battery pack, battery stack overall life, and correction of available battery capacity.
综上所述，本发明提供了一种用于储能电站电化学电池在线评估的方法和系统，该方法包括：首先大数据处理子系统对实时采集的电池数据进行处理和存储；然后基于电池的实时数据和历史数据进行数据分析；最后从短时间尺度和长时间尺度对电池运行状态进行评估。短时间尺度下分析电池堆、电池模组、电池单体的电流、电压、温度等海量实时数据，通过对不同特性电池、温度、内阻、故障等的“特征指纹”数据分析，评估电池一致性，整个储能电站的荷电容量，为储能电站参与电网优化控制和运行管理提供数据；长时间尺度下基于大数据分析的不同工况下电池全寿命周期历史数据中评估电池容量衰退、电池寿命情况，为电池的日常运维管理和电池梯次利用提供参考。In summary, the present invention provides a method and system for on-line evaluation of electrochemical batteries in energy storage power stations, the method includes: first, the big data processing subsystem processes and stores the battery data collected in real time; The real-time data and historical data are used for data analysis; finally, the battery operating state is evaluated from the short time scale and the long time scale. Analyze massive real-time data such as current, voltage, temperature, etc. of battery stacks, battery modules, and battery cells in a short time scale, and evaluate battery consistency by analyzing "feature fingerprint" data of batteries with different characteristics, temperature, internal resistance, and faults. The charging capacity of the entire energy storage power station provides data for the energy storage power station to participate in the optimal control and operation management of the power grid; in the long-term scale based on big data analysis, the battery capacity decline, The battery life situation provides a reference for the daily operation and maintenance management of the battery and the battery utilization.
附图说明Description of drawings
图1是本发明实施例公开的储能电站结构示意图；1 is a schematic structural diagram of an energy storage power station disclosed in an embodiment of the present invention;
图2是本发明实施例公开的电池在线评估系统功能示意图；2 is a functional schematic diagram of a battery online evaluation system disclosed in an embodiment of the present invention;
图3是本发明实施例公开的电池业务模型建立流程示意图；3 is a schematic diagram of a process flow for establishing a battery business model disclosed in an embodiment of the present invention;
图4是本发明实施例公开的用于储能电站电化学电池在线评估的方法流程图；4 is a flowchart of a method for on-line evaluation of an electrochemical cell in an energy storage power station disclosed in an embodiment of the present invention;
图5是本发明实施例公开的用于储能电站电化学电池在线评估的系统方框图。FIG. 5 is a block diagram of a system for on-line evaluation of an electrochemical cell in an energy storage power station disclosed in an embodiment of the present invention.
具体实施方式Detailed ways
为使本发明的目的、技术方案和优点更加清楚明了，下面结合具体实施方式并参照附图，对本发明进一步详细说明。应该理解，这些描述只是示例性的，而并非要限制本发明的范围。此外，在以下说明中，省略了对公知结构和技术的描述，以避免不必要地混淆本发明的概念。In order to make the objectives, technical solutions and advantages of the present invention clearer, the present invention will be further described in detail below with reference to the specific embodiments and the accompanying drawings. It should be understood that these descriptions are exemplary only and are not intended to limit the scope of the invention. Also, in the following description, descriptions of well-known structures and techniques are omitted to avoid unnecessarily obscuring the concepts of the present invention.
MW级大容量储能电站由成千上万支单体电池组成，由多个电池单体经串联后形成电池模组，再将多个电池模组并联/串联成电池堆。单个或多个电池堆并联经PCS进行能量交互后接入电网，储能电站结构图如图1所示。The MW-level large-capacity energy storage power station is composed of thousands of single cells. Multiple battery cells are connected in series to form a battery module, and then multiple battery modules are connected in parallel/series to form a battery stack. Single or multiple battery stacks are connected in parallel to the power grid through PCS for energy exchange. The structure diagram of the energy storage power station is shown in Figure 1.
储能电站电化学电池在线评估系统从电池BMS系统、储能PCS及测控装置等采集储能电站、电池堆、电池模组、电池单体的运行信息及状态数据，由于电池单体数目最大，采集量多且需要存储，对于MW级大容量储能电站来说总数据规模为几十万到百万量级，需在大数据处理子系统、大数据分析子系统的支撑下完成电池的在线评估功能，如图2所示。The electrochemical battery online evaluation system of energy storage power station collects the operation information and status data of energy storage power station, battery stack, battery module and battery cell from battery BMS system, energy storage PCS and measurement and control device. The amount of data collected is large and needs to be stored. For a MW-level large-capacity energy storage power station, the total data scale is in the order of hundreds of thousands to millions. It is necessary to complete the online battery under the support of the big data processing subsystem and big data analysis subsystem. The evaluation function is shown in Figure 2.
储能电站电化学电池在线评估子系统包括短时间尺度(5～15分钟)和长时间尺度(1天)评估储能电站电池状态。不同时间尺度的电池状态评估为储能电站优化控制、运行管理、电池梯次利用等需求提供了数据支撑。The electrochemical battery online evaluation subsystem of the energy storage power station includes short time scale (5-15 minutes) and long time scale (1 day) to evaluate the battery status of the energy storage power station. The battery state assessment at different time scales provides data support for the needs of energy storage power stations such as optimal control, operation management, and battery cascade utilization.
短时间尺度下分析电池堆、电池模组、电池单体的电流、电压、温度等海量实时数据，通过横向数据对比，关联数据分析等方法，评估采集的电池单体、电池模组、电池堆数据的可信度与准确度，采集数据预处理后，通过对不同特性电池、温度、内阻、故障等的“特征指纹”数据分析，评估电池一致性，整个储能电站的SOC，为储能电站参与电网优化控制和运行管理提供数据。长时间尺度下基于大数据分析的不同工况下电池全寿命周期历史数据中评估电池容量衰退、电池寿命情况，为电池的日常运维管理和电池梯次利用提供参考。Analyze massive real-time data such as current, voltage, and temperature of battery stacks, battery modules, and battery cells in a short time scale, and evaluate collected battery cells, battery modules, and battery stacks through horizontal data comparison, correlated data analysis, and other methods. The reliability and accuracy of the data. After preprocessing the collected data, the battery consistency is evaluated by analyzing the "feature fingerprint" data of batteries with different characteristics, temperature, internal resistance, fault, etc. The power station participates in the grid optimization control and operation management to provide data. The battery capacity decline and battery life are evaluated in the historical data of the battery life cycle under different working conditions based on big data analysis on a long-term scale, which provides a reference for the daily operation and maintenance management of the battery and the battery utilization.
本发明中，一种储能电站电化学电池在线评估系统包括以下内容：首先大数据处理子系统对实时采集的电池数据进行处理和存储；然后基于电池的实时数据和历史数据进行数据分析；最后从短时间尺度和长时间尺度对电池运行状态进行评估。In the present invention, an on-line evaluation system for an electrochemical battery of an energy storage power station includes the following contents: first, the big data processing subsystem processes and stores the battery data collected in real time; then conducts data analysis based on the real-time data and historical data of the battery; finally The battery operating state is evaluated from both short and long time scales.
大数据处理子系统的数据处理流程：The data processing flow of the big data processing subsystem:
首先通过配置工具建立各种储能电站业务模型，将电池信息划分为电池单体、电池模组、电池堆，建立上述业务设备之间的关联关系；Firstly, various energy storage power station business models are established through configuration tools, and battery information is divided into battery cells, battery modules, and battery stacks, and the relationship between the above business equipment is established;
将遥信、遥测数据转化为具有电池业务含义的业务信息数据。实现方式：首先，用电池采集装置的采集点表建成装置模板，根据电池业务数据的信息模型及编码定义模板中的数据业务信息类型，根据装置模板实例化装置后，所有的四遥数据就包含点号、装置号、业务信息类型等属性；为了进一步方便上层应用调用数据，大数据处理子系统将四遥数据业务模型化处理，将电池设备电池堆、电池模组、电池单体的数据按设备、属性及设备属性值按电池模型建立数据表，如图3。以电池堆为例：Convert remote signaling and telemetry data into business information data with battery business meaning. Implementation method: First, use the collection point table of the battery collection device to build a device template, define the data service information type in the template according to the information model and code of the battery service data, and instantiate the device according to the device template, all the four remote data include. Point number, device number, business information type and other attributes; in order to further facilitate the upper-layer application to call data, the big data processing subsystem models the four remote data business, and the data of battery equipment battery stack, battery module, battery cell is The equipment, attributes and equipment attribute values establish a data table according to the battery model, as shown in Figure 3. Take the battery stack as an example:
大数据分析子系统根据电池在线评估所用的数据处理方法，提供基本的算法支撑供高级应用调用。主要包括以下方法：The big data analysis subsystem provides basic algorithm support for advanced application calls according to the data processing method used for battery online evaluation. Mainly include the following methods:
1)统计计算，包括最大值、最小值、平均值、排序等；1) Statistical calculation, including maximum value, minimum value, average value, sorting, etc.;
2)极差值分析，用于做两个属性值差值的分析，因为对于电池安全性分析来说，电压差，温度差越限更具有危害性；2) Extreme difference analysis, used to analyze the difference between two attribute values, because for the battery safety analysis, the voltage difference and the temperature difference are more harmful;
3)关联性分析，两个属性值之间具有业务关联性关系或其变化趋势具备关联关系；3) Correlation analysis, there is a business correlation between the two attribute values or its change trend has a correlation;
4)灰色度分析，用已知属性的数据变化时段值，来判断与具有关联关系的未知属性的值的相似关系。4) Gray degree analysis, using the data change period value of the known attribute to judge the similarity relationship with the value of the unknown attribute with the associated relationship.
5)概率分析，根据历史数据分析事件发生的概率。5) Probabilistic analysis, analyzing the probability of events based on historical data.
电池状态在线评估分成短时间尺度评估和长时间尺度评估。首先根据每种状态下的评估指标，然后计算评估参数，最后得出评估结论。The online assessment of battery status is divided into short time scale evaluation and long time scale evaluation. First, according to the evaluation indicators in each state, and then calculate the evaluation parameters, and finally draw the evaluation conclusion.
短时间尺度的评估指标主要是针对储能电站荷电状态SOC状态和电池一致性的评估。对于大型储能电站来说，由多个电池堆构成，在各电池堆上送的各自的SOC值不一致的情况下合理评估整个储能电站的SOC值。为了避免在充放电变化时SOC值跳变，同时减少电池短板效应的影响，基于电池电压、内阻的分布特性和相关性，建立电池一致性快速估计模型，计算电池一致性的综合性能指标。具体实施方法如下：计算并联电池堆的压差与内阻差，根据电池一致性快速估计模型判断电池一致性，电池一致性在BMS均衡范围内以电池堆均值为基准，在BMS均衡范围外根据PCS的充放电状态，充电过程以电压高的电池堆SOC为基准，放电过程中以电压低的电池堆SOC为基准，基准确定后根据容量扩展到该PCS下所有电池的SOC值，然后将所有PCS下的电池SOC值按容量比加和得到整个储能电站的SOC。The short-time-scale evaluation indicators are mainly aimed at the evaluation of the state of charge (SOC) of the energy storage power station and the consistency of the battery. For a large-scale energy storage power station, it is composed of multiple battery stacks, and the SOC value of the entire energy storage power station is reasonably estimated when the respective SOC values sent by each battery stack are inconsistent. In order to avoid the jump of the SOC value when charging and discharging changes, and reduce the influence of the short-board effect of the battery, based on the distribution characteristics and correlation of the battery voltage and internal resistance, a rapid estimation model of the battery consistency is established, and the comprehensive performance index of the battery consistency is calculated. . The specific implementation method is as follows: calculate the voltage difference and internal resistance difference of the parallel battery stacks, and judge the battery consistency according to the battery consistency fast estimation model. The charging and discharging state of PCS, the charging process is based on the SOC of the battery stack with high voltage, and the battery stack SOC with low voltage is used as the benchmark during the discharging process. The SOC value of the battery under PCS is summed according to the capacity ratio to obtain the SOC of the entire energy storage power station.
长时间尺度的评估指标主要是针对电池寿命和电池容量衰减的评估。具体实施方法：利用灰色度法和增量分析法按照从整体到部分的原则，分析电池堆、电池模组、电池单体的电池全生命周期过程数据，基于电池循环寿命标称数据建立电池容量衰退模型，通过对充放电曲线进行特征提取，根据特征变量不一致性在线情况下识别电池组内达到寿命终止状态的单体电池，实现对储能电站整体电池寿命的评估和可用电池容量的修正。The evaluation indicators on the long-term scale are mainly for the evaluation of battery life and battery capacity fading. Specific implementation method: Use the gray scale method and incremental analysis method to analyze the battery life cycle process data of battery stacks, battery modules, and battery cells in accordance with the principle from the whole to the part, and establish battery capacity based on the nominal data of battery cycle life. The decay model, by extracting the characteristics of the charge-discharge curve, identifies the single cells in the battery pack that have reached the end of life state according to the inconsistency of the characteristic variables, and realizes the evaluation of the overall battery life of the energy storage power station and the correction of the available battery capacity.
如图4所示，一种用于储能电站电化学电池在线评估的方法，包括：S101：实时采集电池状态监测数据。As shown in FIG. 4 , a method for on-line evaluation of an electrochemical battery in an energy storage power station includes: S101 : collect battery state monitoring data in real time.
S102：模型规范化处理所述电池数据。包括：建立各种储能电站业务模型，分类划分电池为电池单体、电池模组、电池堆，规范所述电池业务模型与不同电池类别之间的对应关系。将实时采集的电池数据转化为与电池业务模型相关的业务数据，并进行业务化数据的存储。S102: Model normalization to process the battery data. Including: establishing various energy storage power station business models, classifying batteries into battery cells, battery modules, and battery stacks, and standardizing the correspondence between the battery business models and different battery categories. Convert the battery data collected in real time into business data related to the battery business model, and store the business data.
将实时采集的电池数据转化为与电池业务模型相关的业务数据，包括：用电池采集装置的采集点表建成装置模板。根据电池业务数据的信息模型及编码定义模板中的数据业务信息类型。Convert the battery data collected in real time into business data related to the battery business model, including: building a device template with the collection point table of the battery collection device. The data service information type in the template is defined according to the information model and coding of the battery service data.
根据装置模板实例化装置。将电池设备电池堆、电池模组、电池单体的数据按设备、属性及设备属性值按电池模型建立数据表。Instantiate a device from a device template. The data of the battery equipment battery stack, battery module and battery cell is established according to the device, attribute and device attribute value according to the battery model.
S103：设定不同的时间阈值，针对不同的时间阈值分析所述电池数据。所述设定不同的时间阈值，建立针不同特性电池的“特征指纹”，然后通过不同的时间阈值分析所述电池数据，包括：采用统计计算、极差值分析、关联性分析、灰色度分析、概率分析的方法分析电池数据。S103: Set different time thresholds, and analyze the battery data for different time thresholds. The different time thresholds are set to establish "feature fingerprints" for batteries with different characteristics, and then the battery data is analyzed through different time thresholds, including: statistical calculation, range analysis, correlation analysis, and gray level analysis. , Probabilistic analysis method to analyze battery data.
电池数据包括：电池电压、电池内阻、电池容量。Battery data includes: battery voltage, battery internal resistance, battery capacity.
设定不同的时间阈值，针对不同的时间阈值分析所述电池数据，包括：Set different time thresholds, and analyze the battery data for different time thresholds, including:
设定第一阈值时间，分析电池的一致性，包括：计算并联电池堆的压差与内阻差，判断与电池堆相关的电站荷电状态，得到电池一致性评估结果。The first threshold time is set to analyze the consistency of the batteries, including: calculating the voltage difference and internal resistance difference of the parallel battery stacks, judging the state of charge of the power station related to the battery stacks, and obtaining the battery consistency evaluation results.
设定第二阈值时间，评估电池寿命、修正可用电池容量，包括：利用灰色度法和增量分析法按照从整体到部分的原则，分析电池堆、电池模组、电池单体的电池全生命周期过程数据，基于电池循环寿命标称数据建立电池容量衰退模型，通过对充放电曲线进行特征提取，根据特征变量不一致性，评估电池寿命是否终止，评估电池组、电池堆的整体寿命以及修正可用电池容量。Set the second threshold time, evaluate the battery life, and correct the available battery capacity, including: using the gray scale method and the incremental analysis method to analyze the whole life of the battery stack, battery module, and battery cell according to the principle from the whole to the part Cycle process data, establish a battery capacity decay model based on the nominal data of battery cycle life, extract features from the charge-discharge curve, evaluate whether the battery life is terminated according to the inconsistency of characteristic variables, evaluate the overall life of the battery pack and battery stack, and correct the available battery capacity.
S104：根据不同特性电池的“特征指纹”评估电池状态。S104: Evaluate the battery state according to "feature fingerprints" of batteries with different characteristics.
本发明用于储能电站电化学电池在线评估的方法，首先大数据处理子系统对实时采集的电池状态监测数据进行处理；然后基于电池的实时数据和历史数据进行数据分析和存储；最后从短时间尺度和长时间尺度对电池运行状态进行评估。短时间尺度下分析电池堆、电池模组、电池单体的电流、电压、温度等海量实时数据，基于对不同特性电池、温度、内阻、故障等的“特征指纹”数据分析，评估电池一致性，整个储能电站的荷电容量，为储能电站参与电网优化控制和运行管理提供数据；长时间尺度下基于大数据分析的不同工况下电池全寿命周期历史数据中评估电池容量衰退、电池寿命情况，为电池的日常运维管理和电池梯次利用提供参考。The method of the present invention for on-line evaluation of electrochemical batteries in energy storage power stations, first, the big data processing subsystem processes the battery state monitoring data collected in real time; then data analysis and storage are performed based on the real-time data and historical data of the battery; The battery operating state is evaluated on time scales and long time scales. Analyze massive real-time data such as current, voltage, and temperature of battery stacks, battery modules, and battery cells on a short time scale The charging capacity of the entire energy storage power station provides data for the energy storage power station to participate in the optimal control and operation management of the power grid; in the long-term scale based on big data analysis, the battery capacity decline, The battery life situation provides a reference for the daily operation and maintenance management of the battery and the battery utilization.
本发明的另一方面提供了一种用于储能电站电化学电池在线评估的系统500，如图5所示，包括：采集单元501，用于实时采集电池状态监测数据。Another aspect of the present invention provides a
处理单元503，用于模型规范化处理所述电池数据，并进行业务化数据存储。The processing unit 503 is used for model normalization to process the battery data, and to store the business data.
分析单元505，用于设定不同的时间阈值，建立电池状态的“特征指纹”针对不同的时间阈值分析所述电池数据。The analyzing unit 505 is configured to set different time thresholds, and establish a "feature fingerprint" of the battery state to analyze the battery data for different time thresholds.
评估单元507，用于根据不同特性电池的“特征指纹”评估电池状态。The evaluation unit 507 is used to evaluate the battery state according to the "feature fingerprints" of batteries with different characteristics.
根据本发明的一个实施例，所述处理单元，包括：模型规范单元，用于建立各种储能电站业务模型，分类划分电池为电池单体、电池模组、电池堆，规范所述电池业务模型与不同电池类别之间的对应关系。According to an embodiment of the present invention, the processing unit includes: a model specification unit for establishing various business models of energy storage power stations, classifying batteries into battery cells, battery modules, and battery stacks, and regulating the battery business Correspondence between models and different battery classes.
数据转换单元，用于将实时采集的电池数据转化为与电池业务模型相关的业务数据。The data conversion unit is used to convert the battery data collected in real time into business data related to the battery business model.
根据本发明的一个实施例，所述数据转换单元，包括：模板构建模块，用于根据电池采集装置的采集点表建成装置模板。According to an embodiment of the present invention, the data conversion unit includes: a template building module for building a device template according to a collection point table of the battery collection device.
编码定义模块，用于根据电池业务数据的信息模型及编码定义模板中的数据业务信息类型。The coding definition module is used to define the data service information type in the template according to the information model and coding of the battery service data.
实例化模块，用于根据装置模板实例化装置。The instantiation module is used to instantiate the device according to the device template.
数据对应模块，用于将电池设备电池堆、电池模组、电池单体的数据按设备、属性及设备属性值按电池模型建立数据表。The data correspondence module is used to establish a data table according to the battery model according to the data of the battery equipment battery stack, battery module and battery cell according to the equipment, attributes and equipment attribute values.
根据本发明的一个实施例，所述分析单元，包括：According to an embodiment of the present invention, the analysis unit includes:
第一分析单元，用于设定第一阈值时间，分析电池的一致性。The first analysis unit is configured to set a first threshold time and analyze the consistency of the battery.
第二分析单元，用于设定第二阈值时间，评估电池寿命、修正可用电池容量。包括：第一分析模块，用于分析电池堆、电池模组、电池单体的电池全生命周期过程数据；第二分析模块，用于根据电池循环寿命标称数据建立电池容量衰退模型；第三分析模块，用于特征提取充放电曲线数据，评估电池寿命是否终止，评估电池组、电池堆的整体寿命以及修正可用电池容量。The second analysis unit is configured to set a second threshold time, evaluate the battery life, and correct the available battery capacity. It includes: a first analysis module, used to analyze the battery life cycle process data of the battery stack, battery module, and battery cell; a second analysis module, used to establish a battery capacity decay model according to the nominal data of battery cycle life; the third Analysis module for feature extraction of charge-discharge curve data, evaluation of battery life termination, evaluation of battery pack, battery stack overall life, and correction of available battery capacity.
本发明用于储能电站电化学电池在线评估的系统，首先大数据处理子系统对实时采集的电池数据进行处理和存储；然后基于电池的实时数据和历史数据进行数据分析；最后从短时间尺度和长时间尺度对电池运行状态进行评估。短时间尺度下分析电池堆、电池模组、电池单体的电流、电压、温度等海量实时数据，基于对不同特性电池、温度、内阻、故障等的“特征指纹”数据分析，评估电池一致性，整个储能电站的荷电容量，为储能电站参与电网优化控制和运行管理提供数据；长时间尺度下基于大数据分析的不同工况下电池全寿命周期历史数据中评估电池容量衰退、电池寿命情况，为电池的日常运维管理和电池梯次利用提供参考。The system of the present invention is used for the on-line evaluation of the electrochemical battery of the energy storage power station. First, the big data processing subsystem processes and stores the battery data collected in real time; then it performs data analysis based on the real-time data and historical data of the battery; and long-term scales to evaluate the battery operating state. Analyze massive real-time data such as current, voltage, and temperature of battery stacks, battery modules, and battery cells on a short time scale The charging capacity of the entire energy storage power station provides data for the energy storage power station to participate in the optimal control and operation management of the power grid; in the long-term scale based on big data analysis, the battery capacity decline, The battery life situation provides a reference for the daily operation and maintenance management of the battery and the battery utilization.
应当理解的是，本发明的上述具体实施方式仅仅用于示例性说明或解释本发明的原理，而不构成对本发明的限制。因此，在不偏离本发明的精神和范围的情况下所做的任何修改、等同替换、改进等，均应包含在本发明的保护范围之内。此外，本发明所附权利要求旨在涵盖落入所附权利要求范围和边界、或者这种范围和边界的等同形式内的全部变化和修改例。It should be understood that the above-mentioned specific embodiments of the present invention are only used to illustrate or explain the principle of the present invention, but not to limit the present invention. Therefore, any modifications, equivalent replacements, improvements, etc. made without departing from the spirit and scope of the present invention should be included within the protection scope of the present invention. Furthermore, the appended claims of this invention are intended to cover all changes and modifications that fall within the scope and boundaries of the appended claims, or the equivalents of such scope and boundaries.
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