A Peak Demand Reduction Scheme of Air-Conditioning (AC) Loads Using a New Binary Particle Swarm Optimization (NBPSO) Algorithm

Abstract

Great power should come with high efficiency, otherwise there will be an excessive loss in the system. Managing one's resources could add up to an effective whole, thus this paper applies a Peak Load Reduction scheme using price signals to shave peak demand to avoid any disturbances it may cost. In this paper, forecasted price values are used to provide a Demand Limit on which how many numbers of Air-Conditioning Units (ACUs) can be scheduled together with the New Binary Particle Swarm Optimization (NBPSO). The simulations and optimization were carried out in GridLAB-D and Matlab, respectively. After the simulations, there was an average of 13.54 per cent reduction in power consumption and 15.97 per cent reduction in Total Cost.