Microgrid group optimization scheduling strategy based on niche chaos particle swarm algorithm

Abstract

The invention discloses a microgrid group optimization scheduling strategy based on a niche chaos particle swarm algorithm, and the strategy comprises the steps: 1, building a dynamic electricity price model and a load model under the dynamic electricity price, building a cost model and an economic benefit model based on the dynamic electricity price model, and building a target function model based on the cost model and the economic benefit model; 2, respectively setting constraint conditions of microgrid power balance, output, controllable unit output, climbing, energy storage battery operation, power interaction between microgrids and power interaction between the microgrids and a power distribution network; 3, taking the target function model under the constraint condition as a scheduling model; and 4, optimizing the scheduling model by adopting a niche chaos particle swarm algorithm, and solving an optimal cost solution of the scheduling model. According to the invention, space complementation among different power supplies of the micro-grid group, bidirectional regulation of electric energy storage and release of the energy storage device and interactive regulation and control of supply and demand balance of the power supplies and loads are realized, which indicates the effectiveness of an optimized scheduling strategy.

Description

technical field [0001] The invention belongs to the technical field of economic and environmental optimization operation of microgrid groups, and more specifically relates to a microgrid group optimal scheduling strategy based on niche chaotic particle swarm optimization algorithm. Background technique [0002] Hybrid microgrids and their clusters have attracted much attention because of their flexible power supply, strong control capabilities, and ability to meet multi-dimensional and multi-level power demands. Therefore, it is very important to deepen the research on the economic and environmental protection operation of the microgrid group and the reasonable energy scheduling. [0003] The traditional particle swarm optimization algorithm is suitable for function optimization in low-dimensional space. When there are many constraints, it is easy to be local optimal and lead to a sudden drop in optimization effect. In order to strengthen the optimization ability of the PSO...

AI Technical Summary

Problems solved by technology

For example, based on two-point estimation and improved particle swarm optimization algorithm, a microgrid considering uncertain rules can be established to randomly distribute the economic load of the microgrid, but this improved particle swarm optimization algorithm cannot realize the interactive regulation of comprehensive energy.

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