Mbungu, Nsilulu TresorBansal, Ramesh C.Naidoo, RajMiranda, V.Bipath, M.2018-08-172018-08Mbungu, N.T., Bansal, R.C., Naidoo, R. et al 2018, 'An optimal energy management system for a commercial building with renewable energy generation under real-time electricity prices', Sustainable Cities and Society, vol. 41, pp. 392-404.2210-6707 (online)10.1016/j.scs.2018.05.049http://hdl.handle.net/2263/66181This paper presents an approach to the energy management and control of the effective cost of energy in real-time electricity pricing environment. The strategy aims to optimise the overall energy flow in the electrical system that minimises the cost of power consumption from the grid. To substantiate these claims different cases of time-of-use (TOU) and renewable energy electricity tariff, i.e. in summer and winter seasons, and the robustness of system is analysed. A given energy demand for commercial usage in the city of Tshwane (South Africa) is used to investigate the behaviour of the designed method during low and high demand periods. As grid integrated renewable energy resources, photovoltaic (PV) is an important consideration in assuring excellent power supply and environmental issues in the commercial building. An adaptive optimal approach in the framework of model predictive control (MPC) is designed to coordinate the energy flow on the electrical system. The results show that the proposed adaptive MPC strategy can promote the new approach of an optimal electrical system design, which reduces the energy cost to pay the utility grid by about 46% or more depending on the set target.en© 2018 Elsevier Ltd. All rights reserved. Notice : this is the author’s version of a work that was accepted for publication in Sustainable Cities and Society. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. A definitive version was subsequently published in Sustainable Cities and Society, vol. 41, pp. 392-404, 2018. doi : 10.1016/j.scs.2018.05.049.Time-of-use (TOU)Photovoltaic (PV)Model predictive control (MPC)Battery bankEnergy managementSmart gridHouseholdsPerformanceOperationIntegrationOptimizationStorage systemDemand responseModel predictive controlControl strategyPostprint Article