Grid-connected microgrid reliability evaluation method considering peak load shifting

Abstract

The invention relates to a grid-connected microgrid reliability evaluation method considering peak load shifting. The method includes the following steps that: the fuzzy membership degree of a peak period and a valley period is set according to the load curve of a power system; the fuzzy similarity matrix R and equivalence matrix R<^> of various time points of the load curve are determined, dynamic clustering is carried out through a lambda-cut relation, so that the division of the peak period and the valley period can be realized; adjustment is made according to the order of the power market and the actual electricity consumption demands of people, so that a corrected typical load peak period, normal period and valley period can be obtained; a load demand response model is established according to three constraint elements, namely, the total electricity consumption of loads, electricity price and customer' satisfaction, and an objective function described in the descriptions of the invention is provided, and a solution can be obtained through using a particle swarm algorithm, and a corrected load curve is determined; and the reliability of a corrected load curve-based grid-connected microgrid is determined through using a Monte Carlo simulation method. The method of the invention has the advantages of great universality and simple algorithm interface.

Description

technical field [0001] The invention relates to power system reliability evaluation, in particular to a grid-connected micro-grid reliability evaluation method that takes into account peak shaving and valley filling, and belongs to the technical field of electrical engineering. Background technique [0002] The dispatching method of the traditional power system only considers the impact of the power supply side on the system, but the demand response strategy based on user consumer psychology enables the grid manager to optimize the operation of the power system from the user side. The integration of renewable energy in microgrids and the implementation of demand response strategies complicate the reliability assessment of microgrids. In order to ensure the stable operation of the power system, power managers need to stop power supply to some users during peak power consumption. At the same time, when the power consumption is low, the load of the power system is less than th...

AI Technical Summary

Problems solved by technology

However, the existing microgrid reliability evaluation algorithms do not consider the impact of peak load shifting and valley filling on the reliability of microgrids, but only consider the grid structure of microgrids and the randomness and intermittent nature of new energy sources.

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