Combination of PSO and TS-F for Electricity Load Management Optimization: A Case Study of Poultry Sector

Abstract

Malaysia's energy consumption is quickly growing as the country advances along the path of the Industrial Revolution 4.0. Peak periods necessitate greater energy generation, and as a result, the cost is higher than during off-peak periods. It is for this reason that the demand side management (DSM) approach, utilizing the demand response (DR) scheme, was created in order to adjust the demand profile via the implementation of various strategies of actions. The goal of this proposed work is to enhance the power consumption profile of the industrial sector, and perhaps to examine the relevance of energy cost savings using an optimization approach in this sector. In this study, Particle Swarm Optimization (PSO), a bio-inspired approach, was used to optimize the demand profile pattern of the load shifting technique under the Enhance Time of Use (ETOU) tariff scheme. The results of the tests have been endorsed by the use of six (6) cases, which are follows: (1) conventional method for establishing baseline the existing E1 flat tariff rate; (2) baseline of the existing E1 flat tariff rate with Time Series Forecasting (TS-F); (3) E1 ETOU tariff rate without any optimization technique; (4) E1 ETOU tariff rate with TS-F data without optimization technique; (5) E1 ETOU tariff rate with PSO optimization technique without TS-F data; and (6) Combination of PSO optimization technique and TS-F data, respectively. Following that, the statistically significant simulation result of operating profit increase through 24-hour power usage has been thoroughly examined. It was discovered that the proposed strategy resulted in a reduction in the cost of electrical energy consumption across all price zones. Manufacturers are expected to gain from the findings of this study, which will aid them in transitioning to the ETOU tariff and will also help the national Demand Side Management (DSM) initiative programme.