Energy storage system collocation method and system

Abstract

The invention provides an energy storage system collocation method, which comprises the steps: obtaining target data; utilizing a mixed integral linear programming method and a particle swarm optimization to respectively calculate an energy storage system scheduling objective function and an energy storage system optimizing objective function; utilizing an energy storage system optimizing collocation result to collocate an energy storage system, wherein the building processes of the energy storage system scheduling objective function and the energy storage system optimizing objective function comprise the steps: a distributed generation mathematic model in a virtual power plant is built; a sub-objective function is analyzed and built according to the mathematic model and the effect of the energy storage system in the virtual power plant and comprises an economy sub-objective function, a network supply sub-objective function and a voltage sub-objective function; the energy storage system scheduling objective function and the energy storage system optimizing objective function are respectively built according to the sub-objective functions. According to an optimizing collocation result solved by an energy storage system optimizing collocation model, the energy storage system of each collocation can be in an optimal scheduling state during operation and work.

Description

technical field [0001] The present application relates to the field of electric power, and in particular to an energy storage system configuration method and system. Background technique [0002] With the development of technology, people have higher and higher requirements for energy storage system configuration. [0003] The existing large-scale photovoltaic energy storage system configuration method obtains the charging and discharging control strategy of the energy storage system by using the first-order low-pass filter algorithm to process the photovoltaic output power, and takes the annual average minimum cost as the objective function to establish the energy storage system The (ESS) optimal configuration model is relatively simple, and it does not fully reflect the role of the energy storage system. The optimal configuration results obtained cannot guarantee that each configuration of the energy storage system is in the optimal scheduling state during operation. [0...

AI Technical Summary

Problems solved by technology

[0005] The technical problem to be solved in this application is to provide an energy storage system configuration method and system, which solves the problem that the energy storage system (ESS) optimal configuration model established in the prior art is relatively single, and the effect on the energy storage system is not fully reflected. The optimal configuration results obtained cannot guarantee that the energy storage system of each configuration is in the optimal scheduling state during operation.

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