Short-term optimal energy management in stand-alone microgrid with battery energy storage

• Published in: Archives of Electrical Engineering (Online) Vol. 67; no. 3; p. 499
• Main Authors: Paliwal, Navin Kumar, Singh, Asheesh Kumar, Singh, Navneet Kumar
• Format: Journal Article
• Language: English
• Published: Warsaw Polish Academy of Sciences 01.01.2018
• Subjects: artificial bee colony; battery energy storage; Clean energy; clean energy sources; Distributed generation; Energy management; Energy storage; Genetic algorithms; Operating costs; optimal energy management; Particle swarm optimization; Photovoltaic cells; Search algorithms; stand-alone microgrid; System reliability; Weather; Wind turbines
• ISSN: 1427-4221; 2300-2506
• DOI: 10.24425/123659

The optimal energy management (OEM) in a stand-alone microgrid (SMG) is a challenging job because of uncertain and intermittent behavior of clean energy sources (CESs) such as a photovoltaic (PV), wind turbine (WT). This paper presents the effective role of battery energy storage (BES) in optimal scheduling of generation sources to fulfill the load demand in an SMG under the intermittency of theWT and PV power. The OEM is performed by minimizing the operational cost of the SMG for the chosen moderate weather profile using an artificial bee colony algorithm (ABC) in four different cases, i.e. without the BES and with the BES having a various level of initial capacity. The results show the efficient role of the BES in keeping the reliability of the SMG with the reduction in carbon-emissions and uncertainty of the CES power. Also, prove that the ABC provides better cost values compared to particle swarm optimization (PSO) and a genetic algorithm (GA). Further, the robustness of system reliability using the BES is tested for the mean data of the considered weather profile.