scholarly journals A robust approach based on time variable trigger levels for pump control

2017 ◽  
Vol 19 (6) ◽  
pp. 811-822 ◽  
Author(s):  
Stefano Alvisi ◽  
Marco Franchini
Keyword(s):  
Water Level ◽  
Distribution System ◽  
Water Distribution ◽  
Water Distribution System ◽  
Time Variable ◽  
Energy Costs ◽  
Robust Approach ◽  
Multi Objective ◽  
Plant Feeding ◽  
Electricity Tariff

Abstract An approach for the control of a pumping plant feeding a tank at the inlet of a water distribution system is presented. The approach is aimed at minimizing the energy costs by maximizing pumping during off-peak electricity tariff periods. It is based on trigger levels which are variable during the day according to a prefixed pattern in order to ensure that the water level in the elevated tank is at its minimum and maximum values at the end of the peak and off-peak tariff periods, respectively. The pattern of the trigger levels is defined by solving a multi-objective problem aimed at minimizing the energy costs and the number of pump switches. The approach was applied to a couple of real cases with a single tank. The approach was compared with other methodologies typically used for pump control, i.e. fixed trigger levels (FTLs) and pump scheduling (PS). The results show for the two particular cases that the proposed approach achieves energy costs that are lower than those obtainable by using FTLs, and comparable with those obtainable by using PS. This is based on achieving a similar number of pump switches.

A New Energy Optimization Strategy for Pumping Operation in Water Distribution Systems

2012 ◽  
Author(s):  
Dhafar Al-Ani ◽  
Saeid Habibi
Keyword(s):  
Distribution System ◽  
Energy Cost ◽  
Distribution Systems ◽  
Water Distribution ◽  
Water Distribution System ◽  
Water Distribution Systems ◽  
Energy Optimization ◽  
Operating Conditions ◽  
Optimization Strategy ◽  
Multi Objective

As time goes on, more and more operating-modes based on changing demand profiles will be compiled to enrich the range of feasible solutions for a water distribution system. This implies the conservation of energy consumed by a water pumping station and improves the ability for energy optimization. Another important goal was improving safety, reliability, and maintenance cost. In this paper, three important goals were addressed: cost-effectives, safety, and self-sustainability operations of water distribution systems. In this work, the objective functions to optimize were total electrical energy cost, maintenance costs, and reservoir water level variation while preserving the service provided to water clients. To accomplish these goals, an effective Energy Optimization Strategy (EOS) that manages trade-off among operational cost, system safety, and reliability was proposed. Moreover, the EOS aims at improving the operating conditions (i.e., pumping schedule) of an existing network system (i.e., with given capacities of tanks) and without physical changes in the infrastructure of the distribution systems. The new strategy consisted of a new Parallel Multi-objective Particle Swarm optimization with Adaptive Search-space Boundaries (P-MOPSO-ASB) and a modified EPANET. This has several advantages: obtaining a Pareto-front with solutions that are quantitatively equally good and providing the decision maker with the opportunity to qualitatively compare the solutions before their implementation into practice. The multi-objective optimization approach developed in this paper follows modern applications that combine an optimization algorithm with a network simulation model by using full hydraulic simulations and distributed demand models. The proposed EOS was successfully applied to a rural water distribution system, namely Saskatoon West. The results showed that a potential for considerable cost reductions in total energy cost was achieved (approximately % 7.5). Furthermore, the safety and the reliability of the system are preserved by using the new optimal pump schedules.

Risk- and robustness-based solutions to a multi-objective water distribution system rehabilitation problem under uncertainty

2006 ◽  
Vol 53 (1) ◽  
pp. 61-75 ◽  
Author(s):  
Z. Kapelan ◽  
D.A. Savic ◽  
G.A. Walters ◽  
A.V. Babayan
Keyword(s):  
New York ◽  
Distribution System ◽  
Water Distribution ◽  
Water Distribution System ◽  
Sampling Technique ◽  
Latin Hypercube Sampling ◽  
Pressure Head ◽  
Total Risk ◽  
Fitness Evaluation ◽  
Multi Objective

The water distribution system (WDS) rehabilitation problem is defined here as a multi-objective optimisation problem under uncertainty. Two alternative problem formulations are considered. The first objective in both approaches is to minimise the total rehabilitation cost. The second objective is to either maximise the overall WDS robustness or to minimise the total WDS risk. The WDS robustness is defined as the probability of simultaneously satisfying minimum pressure head constraints at all nodes in the network. Total risk is defined as the sum of nodal risks, where nodal risk is defined as the product of the probability of pressure failure at that node and consequence of such failure. Decision variables are the alternative rehabilitation options for each pipe in the network. The only source of uncertainty is the future water consumption. Uncertain demands are modelled using any probability density functions (PDFs) assigned in the problem formulation phase. The corresponding PDFs of the analysed nodal heads are calculated using the Latin Hypercube sampling technique. The optimal rehabilitation problem is solved using the newly developed rNSGAII method which is a modification of the well-known NSGAII optimisation algorithm. In rNSGAII a small number of demand samples are used for each fitness evaluation leading to significant computational savings when compared to the full sampling approach. The two alternative approaches are tested, verified and their performance compared on the New York tunnels case study. The results obtained demonstrate that both new methodologies are capable of identifying the robust (near) Pareto optimal fronts while making significant computational savings.

scholarly journals Sensitivity of algorithm parameters and objective function scaling in multi-objective optimisation of water distribution systems

2015 ◽  
Vol 17 (6) ◽  
pp. 891-916 ◽  
Author(s):  
Helena Mala-Jetmarova ◽  
Andrew Barton ◽  
Adil Bagirov
Keyword(s):  
Sensitivity Analysis ◽  
Objective Function ◽  
Distribution System ◽  
Distribution Systems ◽  
Water Distribution ◽  
Water Distribution System ◽  
Parameter Setting ◽  
Nsga Ii ◽  
Multi Objective ◽  
Optimisation Model

This paper presents an extensive analysis of the sensitivity of multi-objective algorithm parameters and objective function scaling tested on a large number of parameter setting combinations for a water distribution system optimisation problem. The optimisation model comprises two operational objectives minimised concurrently, the pump energy costs and deviations of constituent concentrations as a water quality measure. This optimisation model is applied to a regional non-drinking water distribution system, and solved using the optimisation software GANetXL incorporating the NSGA-II linked with the network analysis software EPANet. The sensitivity analysis employs a set of performance metrics, which were designed to capture the overall quality of the computed Pareto fronts. The performance and sensitivity of NSGA-II parameters using those metrics is evaluated. The results demonstrate that NSGA-II is sensitive to different parameter settings, and unlike in the single-objective problems, a range of parameter setting combinations appears to be required to reach a Pareto front of optimal solutions. Additionally, inadequately scaled objective functions cause the NSGA-II bias towards the second objective. Lastly, the methodology for performance and sensitivity analysis may be used for calibration of algorithm parameters.

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