An Approach of Load Management and Cost Saving for Industrial Production Line Using Particle Swarm Optimization

EasyChair Preprint 3775

Abstract

The industrial revolution in Egypt and other developing countries needs a huge amount of power, while utility could not be able to provide the needed energy, where both the cost of energy and environmental issues should be also considered. In this paper a granite factory is considered as a case study, where the load shifting technique is applied in order to reduce the running cost. The applied optimization technique cost function mainly depends on three main parameters: electrical cost (which is divided into on-peak and off-peak periods), demand cost (depends on the maximum utilized power), and workers’ wages (based on night or day shifts). Particle Swarm Optimization (PSO) has been introduced and simulated. By comparing the results from different operation conditions and cases, it was found that the load shifting technique can reduce the peak demand and capital cost, while increasing the running cost has been noticed. So, the shut-down period has been then suggested and studied in order to reduce both capital and running cost.

Keyphrases: Demand Side Management, Industrial Production Line, Particle Swarm Optimization, cost saving

@booklet{EasyChair:3775,
  author    = {Esraa M. Abd Elsadek and Hamdy Ashour and Ragy Ali Refaat and Mohamed Moustafa M. Sedky},
  title     = {An Approach of Load Management and Cost Saving for Industrial Production Line Using Particle Swarm Optimization},
  howpublished = {EasyChair Preprint 3775},
  year      = {EasyChair, 2020}}