Design of IoT-oriented demand side management model in microgrid via improved metaheuristic framework

Abstract

The amplified use of power applications by customers is a rising concern in the energy field every day, which leads to an imbalanced ratio of supply and demand. The integration of renewable energy sources and increasing greenhouse gas emission leads to power demand and affects the climate. Shortage of power supply is the major issue in remote areas, to rectify this issue microgrids have become the best solution. Demand side management (DSM) is a very important means for avoiding major deficits from the supply side and improving energy efficiency (EE). The development in the management of energy mainly focuses on minimizing the entire cost of electricity with no limitation in the utilization part and instead, it chooses to lessen the power utilization at peak hours. This paper intends to introduce a sophisticated DSM and controlling scheme for an Efficient Energy Management system (EMS) in Smart Microgrids (SMG). Initially, an optimal cost-efficient EMS operation is established depending on Modified Cat Swarm Algorithm (M-CSA) model and is augmented via time-of-use pricing (ToU) theory. Subsequently, the SMG frequency and voltage are optimally controlled via an improved PID-based Mixed Sensitivity H-infinity (PID-MSH∞) model while functioning in islanded mode. Thus, the developed approach exploits the massive IoT (Internet of Things) aptitudes for ensuring a secure and economic operation of SMG. The energy cost value of the proposed method is 8138.9 which is 33.67%, 37.94%, 35.42%, and 32.27% superior than the traditional approaches such as CSA, IDE, GA and JA. Thus, several analyses are used to demonstrate the created approach's superiority.