Optimal Design of Water Distribution System Using Demand Forecasting OLED Model

Engineering benchmark problems with specific characteristics have been used to compare the performance and reliability of metaheuristic algorithms, and water distribution system design benchmarks are also widely used. However, only a few benchmark design problems have been considered in the research community. Due to the limited set of previous benchmarks, it is challenging to identify the algorithm with the best performance and the highest reliability among a group of algorithms. Therefore, in this study, a new water distribution system design benchmark problem generation method is proposed considering problem size and complexity modifications of a reference benchmark. The water distribution system design benchmark problems are used for performance and reliability comparison among several reported metaheuristic optimization algorithms. The optimal design results are able to quantify the performance and reliability of the compared algorithms which shows each metaheuristic algorithm has its own strengths and weaknesses. Finally, using the proposed method in this study, guidelines are derived for selecting an appropriate metaheuristic algorithm for water distribution system design.

Download Full-text

IoT-based water demand forecasting and distribution design for smart city

Journal of Water and Climate Change ◽

10.2166/wcc.2019.019 ◽

2019 ◽

Vol 11 (4) ◽

pp. 1411-1428 ◽

Cited By ~ 2

Author(s):

Lakshmi Kanthan Narayanan ◽

Suresh Sankaranarayanan

Keyword(s):

Water Demand ◽

Distribution System ◽

Smart City ◽

Water Distribution ◽

Water Distribution System ◽

Moving Average ◽

Demand Forecasting ◽

Underground Water ◽

Daily Basis ◽

Water Demand Forecasting

Abstract The percentage of fresh water resource availability in the world is diminishing every year. According to a world economic forum survey, the increase in water demand will result in high scarcity globally in the next two decades. The eradication of the water demand increase and reducing the losses during the transportation of water is challenging. Thus accordingly, an Internet of Things (IoT)-based architecture integrated with Fog for underground water distribution system has been proposed. Towards designing an IoT water distribution architecture for a smart city, we need to first forecast the water demand for consumers. Hence, accordingly, water demand forecasting has been carried out on a daily basis for a period of three months as a case study using autoregressive integrated moving average (ARIMA) and regression analysis. Based on water demand forecasting analysis, a water distribution design for an IoT-based architecture has been carried out using hydraulic engineering design for proper distribution of water with minimal losses which would result in the development of a smart water distribution system (SWDS). This has been carried out using EPANET.

Download Full-text

Water Demand Forecasting using Deep Learning in IoT Enabled Water Distribution Network

International Journal of Computers Communications & Control ◽

10.15837/ijccc.2020.6.3977 ◽

2020 ◽

Vol 15 (6) ◽

Author(s):

Lakshmi Kanthan Narayanan ◽

Suresh Sankaranarayanan ◽

Joel J P C Rodrigues ◽

Sergei Kozlov

Keyword(s):

Deep Learning ◽

Water Demand ◽

Distribution System ◽

Water Distribution ◽

Short Term Memory ◽

Water Distribution System ◽

Distribution Network ◽

Demand Forecasting ◽

Water Distribution Network ◽

Water Losses

Most of the water losses occur during water distribution in pipelines during transportation. In order to eradicate the losses, an “IoT based water distribution system” integrated with “Fog and Cloud Computing" proposed for water distribution and underground health monitoring of pipes. For developing an effective water distribution system based on Internet of Things (IoT), the demand of the consumer should be analysed. So, towards predicting the water demand for consumers, Deep learning methodology called Long Short-Term Memory (LSTM) is compared with traditional Time Series methodology called Auto Regressive Integrated Moving Average (ARIMA) in terms of error and accuracy. Now based on demand prediction with higher accuracy, an IoT integrated “Water Distribution Network (WDN)” is designed using hydraulic engineering. This WDN design will ensure minimal losses during transportation and quality of water to the consumers. This will lead to development of a smart system for water distribution.

Download Full-text

Optimal Design of Water Distribution System by Multiobjective Evolutionary Methods

Lecture Notes in Computer Science - Evolutionary Multi-Criterion Optimization ◽

10.1007/3-540-36970-8_48 ◽

2003 ◽

pp. 677-691 ◽

Cited By ~ 13

Author(s):

Klebber T. M. Formiga ◽

Fazal H. Chaudhry ◽

Peter B. Cheung ◽

Luisa F. R. Reis

Keyword(s):

Optimal Design ◽

Distribution System ◽

Water Distribution ◽

Water Distribution System ◽

Evolutionary Methods

Download Full-text

Optimal Design and Analysis of Water Distribution Networking Systemusing EPANET

Journal of Water Engineering and Management ◽

10.47884/jweam.v1i3pp16-25 ◽

2020 ◽

Vol 1 (3) ◽

Author(s):

Bipin Sahu ◽

Ajai Singh

Keyword(s):

Water Management ◽

Optimal Design ◽

Water Demand ◽

Distribution System ◽

Water Distribution ◽

Water Distribution System ◽

Water Distribution Network ◽

Maximum Pressure ◽

Rural Water ◽

Scarce Water

To satisfy the increasingly growing population's water demand, it is necessary to provide adequate and consistent quantities of water across the planned pipeline network. The scarce water resources must be planned scientifically and proper water distribution network can play an important role in managing non-revenue urban and rural water management. In the present work, we have applied the EPANET model for analyzing the water distribution system for a small place in Ranchi, Jharkhand. The results showed that the pressures at all junctions and the flows at all pipes are sufficient to provide adequate water for the design network. The maximum pressure was observed to be 30.04 m and the flow was also quite reasonable for transporting the water to the consumers. The study demonstrated the application of EPANET for analyzing a water distribution system and should be used to check non-revenue urban and rural water management.

Download Full-text