A wolf pack hunting strategy based virtual tribes control for automatic generation control of smart grid
- 1. College of Electrical Engineering and New Energy, China Three Gorges University, Yichang 443002 (China)
- 2. School of Electric Power, South China University of Technology, Guangzhou 510641 (China)
- 3. Faculty of Electric Power Engineering, Kunming University of Science and Technology, Kunming 650504 (China)
Description
Highlights: • A novel distributed autonomous virtual tribes control system is proposed. • WPH-VTC strategy is designed to solve the distributed virtual tribes control. • Stochastic consensus game on mixed homogeneous and heterogeneous multi-agent are resolved. • The optimal total power reference and its dispatch are resolved simultaneously in a dynamic way. • The utilization rate of renewable energy is increased with a reduced carbon emissions. - Abstract: This paper proposes a novel electric power autonomy to satisfy the requirement of power generation optimization of smart grid and decentralized energy management system. A decentralized virtual tribes control (VTC) is developed which can effectively coordinate the regional dispatch centre and the distributed energy. Then a wolf pack hunting (WPH) strategy based VTC (WPH-VTC) is designed through combining the multi-agent system stochastic game and multi-agent system collaborative consensus, which is called the multi-agent system stochastic consensus game, to achieve the coordination and optimization of the decentralized VTC, such that different types of renewable energy can be effectively integrated into the electric power autonomy. The proposed scheme is implemented on a flexible and dynamic multi-agent stochastic game-based VTC simulation platform, which control performance is evaluated on a typical two-area load–frequency control power system and a practical Guangdong power grid model in southern China. Simulation results verify that it can improve the closed-loop system performances, increase the utilization rate of the renewable energy, reduce the carbon emissions, and achieve a fast convergence rate with significant robustness compared with those of existing schemes.
Availability note (English)
Available from http://dx.doi.org/10.1016/j.apenergy.2016.06.041Additional details
Identifiers
- DOI
- 10.1016/j.apenergy.2016.06.041;
- PII
- S0306-2619(16)30816-9;
Publishing Information
- Journal Title
- Applied Energy
- Journal Volume
- 178
- Journal Page Range
- p. 198-211
- ISSN
- 0306-2619
- CODEN
- APENDX
INIS
- Country of Publication
- United Kingdom
- Country of Input or Organization
- International Atomic Energy Agency (IAEA)
- INIS RN
- 48001646
- Subject category
- S29: ENERGY PLANNING, POLICY AND ECONOMY;
- Descriptors DEI
- CARBON; CHINA; COMPARATIVE EVALUATIONS; COMPUTERIZED SIMULATION; DESIGN; ELECTRIC POWER; ENERGY MANAGEMENT; ENERGY MANAGEMENT SYSTEMS; FREQUENCY CONTROL; GRIDS; OPTIMIZATION; POWER GENERATION; RENEWABLE ENERGY SOURCES; SMART GRIDS; STOCHASTIC PROCESSES
- Descriptors DEC
- ASIA; CONTROL; CONTROL SYSTEMS; ELECTRODES; ELEMENTS; ENERGY SOURCES; ENERGY SYSTEMS; EVALUATION; MANAGEMENT; NONMETALS; POWER; POWER SYSTEMS; SIMULATION
Optional Information
- Copyright
- Copyright (c) 2016 Elsevier Science B.V., Amsterdam, The Netherlands, All rights reserved.