A method for detecting the energy storage margin of an independent microgrid

Abstract

The invention discloses an independent micro-grid energy storage margin detection method. Wind power, photovoltaic output and load random models are built on the basis of a latin hypercube sampling scene generation technology and a probability distance scene reduction technology; a scene generation and reduction technologies-based micro-grid energy storage margin detection model combining with a storage battery charge-discharge optimization technology and a secant method is built by constructing an expected value of island power shortage and the expected value of island power surplus as reliability evaluation indexes; on the basis of considering a micro-source and load stochastic characteristics, due to introduction of energy storage equipment and the ratio of newly increased load carrying capacity to an original load of a system, the micro-grid energy storage margin is detected or calculated to obtain the required minimum capacity of the energy storage equipment when a micro-grid reaches one energy storage margin under the condition of maintaining the reliability of the system unchanged.

Description

technical field [0001] The invention relates to the technical field of micro-grid energy storage, in particular to a method for detecting an independent micro-grid energy storage margin based on reliability and random characteristics. Background technique [0002] In recent years, with the increasingly prominent energy and environmental issues and the deepening of power market reforms, renewable energy power generation has developed rapidly around the world. Due to the fluctuation and random characteristics of intermittent energy sources such as wind and light, it has a great impact on the power balance, voltage and frequency stability of the microgrid. Moreover, the power prediction accuracy of intermittent energy sources such as wind and light is not high, which also increases the randomness of wind and light grid connection. Energy storage equipment, due to its flexible power regulation capability, has become an important device to balance the instantaneous power inside ...

AI Technical Summary

Problems solved by technology

At present, the research on energy storage system mainly focuses on the control strategy and capacity optimization configuration. The common optimization models include: the hybrid energy storage capacity configuration method based on chance constrained programming aiming at the lowest device cost[2], and the method of stabilizing the wind farm The optimal design of capacity allocation based on short-term neural network algorithm for power fluctuation targets [3], and the multi-objective energy storage optimal allocation model based on minimum cost, best power matching, and smoothest output power [4], but less energy storage is involved margin

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