A FUTURISTIC APPROACH TO SEAMLESS POWER CONTROLLING, MONITORING AND DEMAND MANAGEMENT

Abstract

As renewable energy sources become increasingly integrated and smart grid technologies advance, there
is a critical need for innovative approaches to effectively manage power distribution, while also ensuring efficient
monitoring and responsiveness to fluctuating demands. This paper presents an advanced approach to demand-side
management (DSM) and control strategies within smart microgrids (SMGs) to enhance energy efficiency and
address challenges such as voltage and frequency regulations, CO2 emissions, peak-to-average ratio (PAR), and the
stochastic nature of renewable energy sources (RESs). Leveraging Internet of Things (IoT) capabilities, the
proposed strategy integrates a two-level genetic algorithm (GA) optimization and time-of-use pricing (ToU) for
cost-effective energy management. Additionally, an improved PID-based mixed sensitivity H-infinity (PID-MSH∞)
control scheme is employed to regulate SMG voltage and frequency in islanded mode, ensuring compliance with
IEEE Standard-1547 and enhancing customer service quality while facilitating DSM. Experimental validation on a
lab-scale prototype demonstrates the efficacy of the proposed strategy in reducing energy costs, emissions, and PAR
while achieving optimal DSM and regulatory performance. Furthermore, the paper discusses the necessity for
coordination between renewable power generation units, energy storage systems (ESSs), and the grid to address
intermittency challenges, proposing a smart grid architecture with embedded microgrids and introducing a "Microgrid
Key Elements Model" (MKEM) to facilitate smooth integration and virtualization testing. Simulation results
underscore the benefits of renewable energy integration and the stabilizing role of battery storage systems in grid
operations.