PEPSO: Reducing Electricity Usage and Associated Pollution Emissions of Water Pumps

Abstract

Using metaheuristic optimization methods has enabled researchers to reduce the electricity consumption cost of small water distribution systems (WDSs). However, dealing with complicated WDSs and reducing their environmental footprint remains a challenge. In this study a multi-objective version of Pollution Emission Pump Station Optimization tool (PEPSO) is introduced that can reduce the electricity cost and pollution emissions (associated with the energy consumption) of pumps of WDSs. PEPSO includes a user-friendly graphical interface and a customized version of the non-dominated sorting genetic algorithm. A measure that is called "Undesirability Index" (UI) is defined to assist the search for a promising optimization path. The UI also ensures that the final results are desirable and practical. The various features of PEPSO are tested under six scenarios for optimizing the WDS of Monroe City, MI, and Richmond, UK. The test results indicate that in a reasonable amount of time, PEPSO can optimize and provide practical results for both WDSs.

Advanced Hydroinformatic Techniques for the Simulation and Analysis of Water Supply and Distribution Systems

“…This issue contains 18 papers which focus on some of the mentioned problems of water distribution system management. The key points are: (i) design of water system [1][2][3][4]; (ii) optimization of network performance assessment [5][6][7][8]; (iii) monitoring and diagnosis of pressure pipe system [9][10][11]; (iv) optimal water quality management [12][13][14]; and (v) modelling and forecasting of water demand [15][16][17][18].…”

“…Four papers refer to the second key point that is optimization of network performance assessment. First, Sadatiyan and Miller [5] introduce a multiobjective version of the Pollution Emission Pump Station Optimization tool (PEPSO). It can be used to find a pump schedule of a WDS to reduce both the electricity cost and pollution emissions, by measuring the Undesirability Index in a nondominated sorting genetic algorithm.…”

Comparison between Historical and Real-Time Techniques for Estimating Marginal Emissions Attributed to Electricity Generation

“…The LEEM model was adopted in numerous applications such as Home Emissions Read-Out (HERO) [17], energy optimization tools applied to real-life water networks in Monroe [18], and reducing electricity usage cost and the associated pollution emissions of water pumps within water distribution systems by introducing a Pollution Emission Pump Station Optimization tool (PEPSO) [19]. Although Rogers et al, (2013) [14] performed various analyses to improve and evaluate the reliability of LEEM through power system simulations, suggesting that LEEM provides a means of incorporating pollutant emissions into demand side decisions, there has not been any attempt to compare LEEM with the historical-data-oriented approaches.…”

Energy Optimization Using a Pump Scheduling Tool in Water Distribution Systems

“…Alternative representations of pump scheduling may enhance optimization algorithms and are likely to have an impact on the quality of solutions (López-Ibáñez, 2009). A number of decision support tools have recently been developed, each with a particular schedule type, for optimizing the pump operation of water distribution systems (WDSs) including the Pollution Emission Pump Station Optimization tool (Sadatiyan and Miller, 2019); water distribution cost-emission nexus (Stokes, Simpson and Maier, 2014); Darwin Scheduler (Alighalehbabakhani, et al, 2015); and Markov decision processes (Fracasso, Barnes and Costa, 2013).…”