Optimal Coordination of Home Energy Management Systems in a Distribution Grid
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Involving end-users in Demand Side Management (DSM) programs with home energy management systems (HEMS) is an important requirement in realizing a smart grid. One of the main advantages of smart grids is the presence of advanced communication technologies that facilitate grid operators and local distribution companies (LDCs) to communicate directly with customers. Thus, there is a need to evaluate the potential impact of the application of Demand Response (DR) programs on both customers and utilities. The thesis presents a comprehensive mathematical model of an HEMS including the interrelationships between various entities such as the rooftop solar photovoltaic panel (PV) with its associated battery, energy storage device (ESD), and the LDC. The HEMS comprises a set of essential household appliances such as refrigerator, water heater, washer and dryer, and lighting system. The thesis also presents the application of model predictive control (MPC) on an HEMS model in order to arrive at the optimal operational decisions when the inputs are subject to variations. Case studies have been carried out to illustrate the advantages of applying the MPC approach on HEMS. The results show an improvement in the HEMS operation which can potentially lead to an increase in the customers' revenue from selling the generated and stored energy to the LDC. The thesis further proposes the formulation of a bi-level optimization framework wherein multiple HEMSs simultaneously optimize their respective energy consumption profi les, while the LDC aggregates the controllable demand from each HEMS to optimize its operational performance. A coordination scheme between multiple HEMS and the LDC is proposed to determine the optimal DR signals for each HEMS. The results show that the proposed approach helps regulate the total load pro file of the LDC in addition to bringing about signfi cant improvements in the voltage pro file at each bus. However, it was noted that the customers would incur a slight increase in their daily energy cost.