The Optimal Control of Grid-connected and Isolated Microgrid Using Genetic Operators Based Bat Algorithm

• Published in: Chinese Control Conference pp. 1623 - 1629
• Main Authors: Cao, Zhiao, Wang, Jinkuan, Yin, Chunhui, Han, Yinghua, Zhao, Qiang
• Format: Conference Proceeding
• Language: English
• Published: Technical Committee on Control Theory, Chinese Association of Automation 01.07.2020
• Subjects: Genetic operator based bat algorithm; Genetics; Grid-connected state; Heuristic algorithms; Isolated state; Microgrids; Optimization; Renewable energy; Renewable energy sources; Robustness; Uncertainty
• ISSN: 1934-1768
• DOI: 10.23919/CCC50068.2020.9188569

With the application of renewable energy in microgrid, its inherent uncertainty directly affects the operation of microgrid. Meanwhile, different operating states of microgrid which are grid-connected state and isolated state bring difficulties to the optimal control of microgrid. Aiming at these problems, this paper constructs optimization models for microgrid under different states, with the goal of maximizing the generation profit. The energy storage system and demand response program are utilized as dispatchable energy, and the uncertainty of renewable energy is processed by adopting robust uncertain set. Considering the nonlinear characteristics of the optimization models, a genetic operators based bat algorithm is proposed to obtain the optimal control strategy of microgrid. In the search process of proposed algorithm, crossover and mutation operators of genetic algorithm are introduced to ensure the diversity of offspring population, thus improving the ability of searching global optimal solution. Simulation results verify the validity of the optimization models and the superiority of proposed algorithm.