A novel peak shaving algorithm for islanded microgrid using battery energy storage system. (1st April 2020)

• Record Type: Journal Article
• Authors: Uddin, Moslem; Romlie, M.F.; Abdullah, M.F.; Tan, ChiaKwang; Shafiullah, GM; Bakar, A.H.A.
• Is Part Of: Energy. Volume 196(2020)
• Publication Date: 2020-04-01
• Subjects: Peak-load demand -- Peak-shaving -- Microgrid -- Islanded microgrid -- BESS; Power resources -- Periodicals; Power (Mechanics) -- Periodicals; Energy consumption -- Periodicals; 333.7905
• DOI: 10.1016/j.energy.2020.117084
• Languages: English
• ISSNs: 0360-5442

Abstract

Abstract: The objective of this study is to propose a decision-tree-based peak shaving algorithm for islanded microgrid. The proposed algorithm helps an islanded microgrid to operate its generation units efficiently. Effectiveness of the proposed algorithm was tested with a BESS-based MATLAB/Simulink model of an actual microgrid under realistic load conditions which were recorded. To evaluate the performance, simulation case studies were conducted under various load conditions and results were compared with conventional techniques. Results showed that the proposed algorithm offers a simple and effective way of peak load shaving without heavy computational burdens often needed in other methods. The comparison analysis verified that the proposed algorithm can effectively mitigate the peak load demand regardless of the schedule of the generators, where conventional methods were limited. The financial benefit investigation shows that microgrid utility can enjoy substantial savings, while reducing of the peak demand of the microgrid. Thus, the islanded microgrid that include fuel-based generation can implement the proposed technique to reduce the consumption of fuel and increase the efficiency of fuel-based generation through peak load mitigation. Highlights: A novel peak shaving algorithm is presented for the islanded microgrid. The proposed algorithm is tested for a real microgrid under various load conditions. A comparative analysis is carried out with conventional peak shaving methods. Results show the proposed algorithm successfully supplied peak shaving services. The proposed algorithm shows a robust behavior under the realistic circumstance.