Economic optimisation of microgrid based on improved quantum genetic algorithm

Abstract

The optimal dispatch of a microgrid is a complex issue with both important economic benefits and social benefits. To ensure the microgrid with distributed power to operate in a more economical, flexible and environmental way, and the advantages of distributed generation can be fully utilised, according to the problem of optimal scheduling of the microgrid, this study proposes a multi-objective optimisation function model of the microgrid with an electric vehicle, which is used as a load and power generation unit at the same time, which aims to maximise the economic benefit and minimise the environmental cost of multi-objective optimisation of the microgrid. In the process of optimisation, this study introduces the structure of a double chain and the adjustment strategy of the dynamical rotation angle, proposes a new modified quantum genetic algorithm, and compares with the traditional genetic algorithm and the fundamental quantum genetic algorithm. Finally, numerical examples are provided to verify the effectiveness and feasibility of the proposed model, strategy and algorithm.

Keywords

• distributed power generation
• genetic algorithms
• power generation economics
• power generation scheduling
• cost reduction
• power generation dispatch
• traditional genetic algorithm
• fundamental quantum genetic algorithm
• improved quantum genetic algorithm
• optimal dispatch
• social benefits
• distributed power
• distributed generation
• optimal scheduling
• multiobjective optimisation function model
• power generation unit
• economic benefit
• modified quantum genetic algorithm
• microgrid economic optimisation
• electric vehicle
• load generation unit
• double chain structure
• dynamical rotation angle adjustment strategy
• environmental cost minimization