Enhanced Slack Time based Price Driven Demand Response for Future Effectual Smart Communities

Abstract

Evolution of smart grid concept aims to address the imbalance between electricity demand and supply. Owing to consideration on sustainable energy, user comfort, and cost efficiency, residential Demand Response (DR) has gained a remarkable popularity over the past few years. To further enhance these benefits, herein we propose a residential appliance scheduling algorithm inspired by Least Slack Time (LST) algorithm. The conventional LST algorithm is amended with consumption thresholds and waiting factor constraints to derive proposed Minimum Slack Time (MST) algorithm, which increase cost and comfort efficiency during DR. Proposed algorithm was experimented in a simulated residential community consists of 50 houses. Further experiments were conducted by aggregating renewable energy sources using aggregated MST (AMST) algorithm. All instances were compared with an existing scheduling mechanism to assure superiority of proposed MST and AMST algorithms, in terms of grid electricity consumption, cost, Peak-to-Average Ratio (PAR), and waiting time.