An Integrated Energy Management Approach for the Economic Operation of Industrial Microgrids Under Uncertainty of Renewable Energy

• Published in: IEEE transactions on industry applications Vol. 56; no. 2; pp. 1062 - 1073
• Main Authors: Mohy-ud-din, Ghulam, Vu, Dao Hoang, Muttaqi, Kashem M., Sutanto, Danny
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.03.2020; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Battery energy storage; Distributed generation; Energy conservation; Energy management; Energy storage; industrial microgrids; integrated energy management; Onsite; Operating costs; Optimization; renewable energy uncertainty; Strategy; Uncertainty
• ISSN: 0093-9994; 1939-9367
• DOI: 10.1109/TIA.2020.2964635

Many modern industries are equipped with onsite renewable generation and are normally connected to the grid. A battery energy storage system (BESS) can complement the intermittency of the available onsite renewable generation. The combination of the BESS and the renewable generation can operate as a microgrid. If the microgrid is properly sized and managed, it is possible to reduce the electricity bill to have a huge saving in the electricity cost. This article proposes an energy management system for such an industrial microgrids. The decisions to charge and discharge the BESS in the proposed energy management are usually constrained by the size of the energy storage. The proposed energy management strategy aims to optimize the operation of the industrial microgrids subject to the scalability of the BESS under uncertainties. The proposed optimization involves two stages. In the first stage of optimization, it determines the optimum size of the energy storage taking into account the cost of the BESS, and in the second stage, it minimizes the cost of the microgrid operation based on the decision made in the first stage. This proposed two-stage energy management strategy is formulated as a single-stage linear program that incorporates stochastic scenarios for addressing uncertainties. In addition, the proposed strategy also considers the various operating limits of the energy storage, such as the efficiency and the charging and the discharging rates, and considers the fading effect of the batteries of the BESS. The proposed strategy is then validated using two typical datasets from two different industrial units in New South Wales, Australia. The simulation results show that the proposed strategy effectively calculates the optimum size of the BESS and reduces the operational cost.