Abstract:
One of the key contributions of the smart grid is demand-side management (DSM). DSM allows
a consumer to schedule its energy consumption pattern to reduce electricity cost, and to benefit
the utility grid by reducing peak load demand. However, while doing so it jeopardizes the user
comfort. In the present thesis, authors have proposed an efficient demand-side management
system (EDSMS) for a single household to minimize the electricity cost and peak to average
ratio (PAR) while simultaneously minimizing user discomfort. Additionally, the impact of load
scheduling on environmental emissions has also been investigated along with the integration of a
PV system. The artificial bee colony (ABC) algorithm is applied to minimize objectives in this
multi-objective optimization problem. Two types of tariffs including real-time electricity pricing
(RTEP) and critical peak pricing (CPP) are considered. Results reveal that the proposed ABC
algorithm shows greater minimization of objectives as compared to other standard algorithms.
