Load Management Optimization to Reduce the Demand Side Energy Cost

Egyptian government is undergoing an extremely difficult transition where energy subsidies will be lifted gradually. Therefore, demand side management DS M has been of great attraction to most stakeholders for medium and large size enterprises. This paper presents a fully-fledged program that is developed for load shifting and has been implemented with actual load data collected from a case study of granite industry. For this analysis, granite industrial complex is considered, consisting of eight factories, which was discussed in previous literature. The major equipment in granite industries are cutting machine, polishing machine and compressor. To reduce the maximum demand, the operating time of all machines is rescheduled by optimization techniques such as genetic and particle swarm algorithms. The maximum demand costs are calculated before and after rescheduling. In comparison to previous work, the results show that if the machines are optimally operated, the cost is dramatically reduced and also the effect of load reduction per hour on the feeder load and its peak demand.