Residential demand side management in smart grid paradigm

Smart grid (SG) modernizes the aging grid by the introduction of two-way communication between utility and load, power electronics, automation, and control. One prominent application of SG is demand side management (DSM) which can be defined as optimization of the demand side energy consumption pattern for efficient and economic operation and utilization of electrical energy generation system. This paper proposes a DSM strategy for residential customers whose load is comprised of conventional residential load and electric vehicle (EV) charging load. The proposed technique determines suitable size of local solar photovoltaic (PV) generation system and then based upon the available local PV power and day-ahead price of electricity, shifts the load demand to minimize the electricity bill of customers. The optimization problem is formulated and solved using teacher learner based optimization (TLBO) algorithm. A comparison based upon cost per-unit between three case studies, (i) system without local PV generation and DSM, (ii) system without local PV generation but with DSM, and (iii) system with both local PV generation and DSM, is presented. It is found that the proposed methodology is more economical.