Demand Response Based Techno-Socio-Economic Improvements with Time-Varying Incentives at DN using Cuckoo Search Algorithm

The current energy crisis and the negative environmental effects of fossil fuel consumption have prompted a paradigm shift in favor of renewable energy sources. An efficient demand response (DR) scheme is proposed to shift the high load demand during peak load hours to the off-peak hours. High resistance to reactance ratio is a defining characteristic of distribution networks (DNs). With hourly shifting incentives, a price-load elasticity-based demand response method is presented to incentivize participants to redistribute their load utilization profile. This work shows how the combined effects of PV and DR can enhance the benefits of a radial distribution network in terms of technology, economy, and environment. The Cuckoo search algorithm (CSA) has been utilized to determine the optimal hourly PV power to be fed into an IEEE 22 bus test DN. Geographic equations are used to compute the installed capacity of photovoltaic systems (PV) in Jammu and Kashmir, India, while the beta distribution function is used to characterize the uncertainty of PV.