World Journal of Engineering Research and Technology

*ThankGod Sylvanus Ntem, Iwueze Ifeanyi M., Ihemba Kennedy Uzodimma and Tafida Balarabe Rabiu

ABSTRACT

Distributed power systems, characterized by mixed load patterns, often experience staggered peaks due to varying peak demand periods among residential, commercial, and industrial loads throughout the day. This research evaluates the impact of staggered peak demand in distributed power networks (DPNs) to facilitate effective grid profile reshaping without load disconnections. The research develops comprehensive models to simulate the dynamics of staggered peakdemand and assess their implications for grid stability, energy efficiency, and operational costs. The study models the peak demand periods of an existing distribution network exhibiting staggered peaks, determines the aggregate staggered peak demand across load types, and implements a grid-tied distributed generation (DG) system controlled by a neural network using this aggregated data. Results indicate that staggered peak demand periods across different load types significantly flatten the overall system load profile, reducing the maximum power required from the grid to 600 kW from a possible 1039 kW. This reduction leads to improved system efficiency and cost savings. Furthermore, integrating DG using the staggered peak strategy lowered total power requirements from the grid to approximately 400 kW. This research has investigated managing peak demand in distributed power networks (DPNs) by exploiting the naturally staggered peak demands of residential, commercial, and industrial loads, paving the way for future research and practical applications aimed at optimizing energy consumption patterns and strengthening grid resilience amid evolving energy demands.

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