OPTIMIZE ENERGY MANAGEMENT TECHNIQUES TO DECREASE OPERATIONAL COSTS IN WATER TREATMENT PLANTS AT NO INVESTMENT BASED ON IMPROVED PUMPS OPERATION SCHEDULES. | ||||
| Journal of Al-Azhar University Engineering Sector | ||||
| Volume 19, Issue 72, July 2024, Page 270-283 PDF (561.64 K) | ||||
| Document Type: Original Article | ||||
| DOI: 10.21608/auej.2024.255527.1525 | ||||
 View on SCiNiTO | ||||
| Authors | ||||
Nader S. H. Abdelhakeem1; Mohamed I.S. Abodief  2; Mohamed I. Elsayed2
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| 1Electrical Engineering Department, Faculty of Engineering (Shoubra), Benha University | ||||
| 2Electrical Engineering Department, Faculty of Engineering, Al-Azhar University, Nasr City, 11884, Cairo, Egypt | ||||
| Abstract | ||||
| The pump units are the main water treatment plant (WTP) equipment, and their operating and maintenance costs are considerable in their life cycle cost. optimize pump operation is essential and significant for improving the efficiency of asset management and developing an operation strategy. The pump's energy consumption costs share a range of 30–50% of the overall operating cost, with a potential 10% savings by optimizing operation. Energy management is one of the most widely used optimization objectives in pump systems, as it has direct improvements to the whole WTP life cycle, such as environmental impact and operational costs. Our methodology is a combination of using a linear model for forecasting the production of the water plant and optimizing operation costs, where it forecasts the water demand at any given time in parallel with optimization algorithm to generate the proper pump operation schedules for the demand. We have set the energy management parameters related to the WTP operational cost. The Matlab optimizer has defined several different pump schedules based on the input data sets related to the variable water demands throughout the day and in each season, and achieved the main optimization objective of cost reduction. The energy cost of each schedule has been presented according to the main energy management factors, such as cost, maximum demand, and efficiency. This research presents the effects of decreasing pump set operational costs in a conventional WTP in Egypt through improved energy management based on water demand forecasts. Special Issue of AEIC 2024 (Electrical and System & Computer Engineering Session) | ||||
| Keywords | ||||
| Water supply systems; Operational control optimization; Energy and cost efficiency; Improving Energy management; Artificial intelligence in WTP | ||||
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