A Bionic-Intelligent Scheduling Algorithm for Distributed Power Generation System

  • Zhili Ma State Grid Gansu Electric Power Company, Lanzhou 730030 China
  • Zhenzhen Wang School of Information Science and Engineering, Lanzhou University Lanzhou 730030 China
  • Yuhong Zhang State Grid Gansu Electric Power Company, Lanzhou 730030 China
Keywords: DWMFO; Dynamic adjustment; Bionic-Intelligent; Adaptive; Distributed energy

Abstract

With the introduction of the new power system concept, diversified distributed power generation systems, such as wind power, photovoltaics, and pumped storage, account for an increasing proportion of the energy supply side. Facing objective issues such as distributed energy decentralization and remote location, exploring what kind of algorithm to use to dispatch nearby distributed energy has become a hot spot in the current electric power field. In view of the current situation, this paper proposes a Bionic Intelligent Scheduling Algorithm (DWMFO) for distributed power generation systems. On the basis of the Moth Flame Algorithm (MFO), in order to solve the problem of low accuracy and slow convergence speed of the algorithm in scheduling distributed energy, we use the adaptive dynamic change factor strategy to dynamically adjust the weighting factor of the MFO. The purpose is to assist the power dispatching department to dispatch diversified distributed energy sources such as wind power, photovoltaics, and pumped storage in a timely manner during the peak power consumption period. In the experiment, we compared with 4 algorithms. The simulation results of 9 test functions show that the optimization performance of DWMFO is significantly improved, the convergence speed is faster, the solution accuracy is higher, and the global search capability is stronger. Experimental test results show that the proposed bionic intelligent scheduling algorithm can expand the effective search space of distributed energy. To a certain extent, the possibility of searching for the global optimal solution is also increased, and a better flame solution can be found.

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Author Biographies

Zhili Ma, State Grid Gansu Electric Power Company, Lanzhou 730030 China

Zhili Ma, male, 38 years old, master’s degree, graduated from Lanzhou University, majoring in computer application technology, senior engineer, mainly engaged in security supervision and management and technical research. The main research directions include network security protection and intrusion detection, big data mining and analysis, Internet of Things information collection and perception.

Zhenzhen Wang, School of Information Science and Engineering, Lanzhou University Lanzhou 730030 China

Zhenzhen Wang (1987–), female, Han nationality, from Yicheng County, Shanxi Province. He graduated from the School of Information Science and Engineering of Lanzhou University in July 2010 with a bachelor’s degree in computer science. Since 2019, he is currently studying for a master’s degree in computer science from the School of Information Science and Engineering of Lanzhou University.

Yuhong Zhang, State Grid Gansu Electric Power Company, Lanzhou 730030 China

Yuhong Zhang, male, 55 years old, bachelor’s degree, graduated from Chongqing University with a major in power system automation, engineer, mainly engaged in safety supervision and management and technical research. His main research directions include power safety production big data mining analysis, safety online monitoring Internet of things, information Communication system security protection and other aspects.

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Published
2021-10-21
Section
Renewable Power and Energy Systems