Multi-objective Harmony Search Algorithm for Dynamic Optimal Power Flow with Demand Side Management

Abstract

In modern power systems, efficient methods like demand side management (DSM) are needed for handling the peak load management problem. An intelligent DSM approach not only gives advantages to utilities but also provides indirect benefits to generating companies. This article introduces a combined model of multi-objective dynamic optimal power flow (MODOPF) and a game theory-based DSM technique. In this article, a single utility company and multiple residential energy consumers are considered for the game theory-based DSM technique. Here, the day ahead load shifting DSM technique is implemented with the help of a day-ahead pricing strategy and an energy consumption game. The total generation cost and transmission losses are considered as the main objectives in the proposed MODOPF problem. These two objectives were optimized individually and simultaneously using harmony search (HS) algorithm with different DSM participation levels for the investigation of generation side benefits. The proposed combined model was tested on two different test systems such as IEEE 30 bus and 118 bus. From the simulation results, it is clear that the combined model consisting of MODOPF and DSM is able to achieve a better economic and secure operation when compared to MODOPF alone.