Optimal operation of a sustainable water desalination unit integrated a green energy system

Ali Ahmadian; Ali Almansoori; Ali Elkamel

doi:10.1016/B978-0-443-15274-0.50463-7

Optimal operation of a sustainable water desalination unit integrated a green energy system

Ali Ahmadian
, Ali Almansoori
, Ali Elkamel

University of Bonab
Department of Chemical Engineering
University of Waterloo

Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

1 Scopus citations

Abstract

In this paper, an optimization framework is proposed in order to optimal operation of a water desalination unit in a sustainable green energy network. The operation problem is modeled as a mixed integer linear programming (MILP) and optimized using a mathematical based optimization algorithm. In order to increase the flexibility of the studied sustainable energy system, a fuel cell unit and hydrogen-based vehicles have been included in the system. Moreover, the uncertainty of stochastic parameters has been considered and a machine learning based method namely long short term memory (LSTM) algorithm is utilized for forecasting of the parameters. The proposed methodology is applied on a typical case study and the simulation results are extracted and discussed.

Original language	British English
Title of host publication	Computer Aided Chemical Engineering
Publisher	Elsevier B.V.
Pages	2909-2915
Number of pages	7
DOIs	https://doi.org/10.1016/B978-0-443-15274-0.50463-7
State	Published - Jan 2023

Publication series

Name	Computer Aided Chemical Engineering
Volume	52
ISSN (Print)	1570-7946

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 6 Clean Water and Sanitation
SDG 7 Affordable and Clean Energy
SDG 11 Sustainable Cities and Communities

Keywords

smart cities
sustainable green energy
Water desalination unit

Access to Document

10.1016/B978-0-443-15274-0.50463-7

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abstract = "In this paper, an optimization framework is proposed in order to optimal operation of a water desalination unit in a sustainable green energy network. The operation problem is modeled as a mixed integer linear programming (MILP) and optimized using a mathematical based optimization algorithm. In order to increase the flexibility of the studied sustainable energy system, a fuel cell unit and hydrogen-based vehicles have been included in the system. Moreover, the uncertainty of stochastic parameters has been considered and a machine learning based method namely long short term memory (LSTM) algorithm is utilized for forecasting of the parameters. The proposed methodology is applied on a typical case study and the simulation results are extracted and discussed.",

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AU - Almansoori, Ali

AU - Elkamel, Ali

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N2 - In this paper, an optimization framework is proposed in order to optimal operation of a water desalination unit in a sustainable green energy network. The operation problem is modeled as a mixed integer linear programming (MILP) and optimized using a mathematical based optimization algorithm. In order to increase the flexibility of the studied sustainable energy system, a fuel cell unit and hydrogen-based vehicles have been included in the system. Moreover, the uncertainty of stochastic parameters has been considered and a machine learning based method namely long short term memory (LSTM) algorithm is utilized for forecasting of the parameters. The proposed methodology is applied on a typical case study and the simulation results are extracted and discussed.

AB - In this paper, an optimization framework is proposed in order to optimal operation of a water desalination unit in a sustainable green energy network. The operation problem is modeled as a mixed integer linear programming (MILP) and optimized using a mathematical based optimization algorithm. In order to increase the flexibility of the studied sustainable energy system, a fuel cell unit and hydrogen-based vehicles have been included in the system. Moreover, the uncertainty of stochastic parameters has been considered and a machine learning based method namely long short term memory (LSTM) algorithm is utilized for forecasting of the parameters. The proposed methodology is applied on a typical case study and the simulation results are extracted and discussed.

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KW - sustainable green energy

KW - Water desalination unit

UR - https://www.scopus.com/pages/publications/85166291211

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M3 - Chapter

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T3 - Computer Aided Chemical Engineering

SP - 2909

EP - 2915

BT - Computer Aided Chemical Engineering

PB - Elsevier B.V.

ER -

Optimal operation of a sustainable water desalination unit integrated a green energy system

Abstract

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UN SDGs

Keywords

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