Class Topper Optimizer for Multi-Objective Cost Optimization in Smart Grid Using Demand Side Management Program

Demand side management (DSM) is widely utilized in Smart Grid for its reliable features, flexibility, and cost benefits that it offers to customers in the reduction of the energy bill. In smart grid, all participants of the electricity market i.e., electricity users, demand response aggregator, and utility operator wish to improve individual economic benefits. It is quite challenging to simultaneously ensure financial advantage for all participants. In the current paper, a multi-objective problem is formulated considering all objectives of all the participants using the DSM program. The multi-objective DSM problem is optimized by a meta-heuristic optimization algorithm: Class Topper optimization (CTO). The goal is to schedule power production and load demand optimally for a given day in order to reduce peak loads, raise load factors, reduce operational costs of power generation, and simultaneously optimize advantages for all market participants in the electrical sector. The simulation's findings show that the ongoing methodology is capable of minimizing the cost of electricity generation and ensuring optimal benefit to all entities of the power market simultaneously. The outcomes are contrasted with other optimization strategy to demonstrate the viability of the current approach to deal with the IEEE 39-bus test framework.