Microgrid energy storage SOC estimation method and system based on least square support vector machine

Abstract

The invention discloses a microgrid energy storage SOC estimation method and a system based on a least square support vector machine. Firstly, a microgrid experiment platform comprising an energy storage system is used, and through measurement, voltage, current, temperature and an SOC data sequence of the energy storage system during a charging and discharging process are obtained; according to the measurement data, training set and test set samples for the least square support vector machine are obtained; a cross validation method is then used for selecting the optimal training parameters for the training set of the least square support vector machine, and a training model is further obtained; and the testing set is then used for testing the training model, the result is evaluated, and finally, the training model can be used for SOC estimation determination on the corresponding type of energy storage system in the microgrid. Defects in the traditional SOC calculation method can be overcome, reference is provided for charging and discharging control on the energy storage system, deep charging and discharging of a battery can be prevented, and the service life of the battery and the operation safety of the microgrid can be improved.

Description

technical field [0001] The invention relates to the technical field of microgrid energy storage, in particular to a microgrid energy storage SOC estimation method and system based on a least squares support vector machine suitable for multi-energy microgrids. Background technique [0002] With the gradual implementation of the new round of electricity reform plan, the market on the electricity sales side will be liberalized, which will greatly expand the development space of the microgrid. The microgrid coordinates and balances a variety of distributed energy sources through the control system and energy storage system. It is usually connected in parallel with the large grid, and the surplus power is input into the large grid or energy storage system. In the event of a large power grid failure, it will be quickly disconnected, and the isolated grid will operate to ensure the main load. The cost of energy storage in the microgrid system is relatively high. Considering the ec...

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Problems solved by technology

Among them, the discharge experiment method and the internal resistance measurement method are not applicable in actual engineering; the ampere time method is widely used, but it needs to know the initial SOC size, and as time accumulates, the error will become larger and larger; the open circuit voltage method has high precision and is simple , but it needs to stand for a long time to get a stable open circuit voltage value; the internal resistance measurement method only considers the two basic factors of the battery discharge current and internal resistance, and the calculation accuracy is limited, so it is difficult to accurately estimate the battery capacity; linear The model method is suitable for the situation of low current and SOC changing slowly, and the estimation effect of the variable current situation needs to be further studied; the neural network method is based on empirical risk minimization, and sometimes falls into a local minimum, the structural parameters are difficult to determine, and there is a lack of appropriate theoretical guidance

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