Multi-side shared energy storage optimization configuration and cost allocation method

Abstract

The invention provides a multilateral shared energy storage optimal configuration and cost allocation method. The method comprises the following steps: S1, acquiring historical load data and wind power and photovoltaic power generation data of each microgrid; s2, environment parameters including the total radiation quantity of the inclined plane of the photovoltaic module, the temperature, the wind speed of a wind turbine generator and the wind direction are obtained through detection; s3, establishing a net load demand prediction function; s4, solving the comprehensive net load demand function and the microgrid energy storage cost model; and S5, performing optimal energy storage configuration and cost allocation, and comparing and judging with the optimal energy storage learning model. By acquiring load data and power generation data of each microgrid, establishing a prediction net load demand function and a microgrid energy storage cost model, and finally comparing with an optimal energy storage learning model, flexible scheduling among the microgrids is realized, the use cost is reduced, a feedback model is added for comparison, and the configuration accuracy is improved.

Description

technical field [0001] The invention relates to the field of microgrid energy storage configuration, in particular to a multilateral shared energy storage optimization configuration and a cost allocation method thereof. Background technique [0002] With the rapid development of new energy, the penetration rate of new energy in the microgrid is also increasing, which will increase the impact of new energy power fluctuations on the security and stability of the microgrid and its access system and the difficulty of operation and scheduling. Energy storage can make up for the congenital defects of new energy in terms of random volatility, and fundamentally solve the problem of high proportion of new energy consumption. Microgrid can use the charging and discharging characteristics of energy storage to stabilize system power fluctuations and improve new energy consumption capacity. , reduce the impact frequency of the power fluctuation of the microgrid to its access system, and ...

AI Technical Summary

Problems solved by technology

[0004] The present invention solves the problem that energy storage configuration shared by multiple microgrids often cannot be optimized, resulting in waste of resources and costs. A method for optimal configuration of energy storage shared by multilateral networks and its cost allocation method obtains the load of each microgrid Data and power generation data, establish a forecasted net load demand function and a microgrid energy storage cost model, and finally compare with the best energy storage learning model, realize flexible scheduling between microgrids, reduce use costs, and increase feedback models for comparison , to improve the accuracy of the configuration

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