Application of Particle Swarm Optimization to a Scheduling Strategy for Microgrids Coupled with Natural Gas Networks

• Published in: Energies (Basel) Vol. 11; no. 12; p. 3499
• Main Authors: Yousif, Muhammad, Ai, Qian, Gao, Yang, Wattoo, Waqas Ahmad, Jiang, Ziqing, Hao, Ran
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01.12.2018
• Subjects: Air pollution; Alternative energy sources; Computer engineering; distribution networks; Electric power grids; Electricity; Electricity distribution; Energy management; Energy resources; Genetic algorithms; International conferences; Methods; Natural gas; natural gas and electricity integrated energy system; optimal power dispatch; Optimization; power scheduling strategy; PSO; renewable energy sources; Researchers; Smart grid technology; United States > US; China
• ISSN: 1996-1073; 1996-1073
• DOI: 10.3390/en11123499

This article focuses on the minimization of operational cost and optimal power dispatch associated with microgrids coupled with natural gas networks using particle swarm optimization (PSO). Introducing a natural gas turbine in a microgrid to overcome the drawbacks of renewable energy resources is a recent trend. This results in increased load and congestion in the gas network. To avoid congestion and balance the load, it is necessary to coordinate with the electric grid to plan optimal dispatch of both interactive networks. A modification is done in applying PSO to solve this coupled network problem. To study the proposed approach, a 7-node natural gas system coupled with the IEEE bus 33 test system is used. The proposed strategy provides the optimal power dispatch. Moreover, it indicates that power sharing between the main grid and microgrid is reduced in such a way that it may help the main grid to shave the load curve peaks.