Optimization of wind/solar energy microgrid by division algorithm considering human health and environmental impacts for power-water cogeneration

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27740%2F22%3A10249812" target="_blank" >RIV/61989100:27740/22:10249812 - isvavai.cz</a>

Result on the web

<a href="https://doi.org/10.1016/j.enconman.2021.115064" target="_blank" >https://doi.org/10.1016/j.enconman.2021.115064</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.enconman.2021.115064" target="_blank" >10.1016/j.enconman.2021.115064</a>

Result language

angličtina

Original language name

Optimization of wind/solar energy microgrid by division algorithm considering human health and environmental impacts for power-water cogeneration

Original language description

Although freshwater is necessary for the well-being of humankind, increasing population growth and limited resources lead to a serious crisis to supply freshwater. Since the Earth is surrounded by seawater, desalination based on electrical power is introduced as a promising technology to provide freshwater. It is well documented that the connection of remote areas that usually do not have access to freshwater into the electricity grid is not affordable and eco-friendly. Hence, the efforts to design and construct high reliability, cost-effective, and eco-friendly stand-alone hybrid renewable energy system in remote areas. In line with this, this paper describes a novel energy management system for the optimized operation of a stand-alone hybrid energy system based on photovoltaic panels, wind turbines, batteries, and diesel generator. For this purpose, a multi-objective optimization problem is formulated by combining three objective functions, i.e., minimum the total life cycle cost as well as environmental impacts on human health and ecosystems and the maximum system reliability that can conflict with each. To solve the multi-objective optimization problem, a division algorithm is proposed that is more flexible and faster compared with conventional algorithms such as genetic algorithm. In order to show the proposed framework, a real case study in Larak Island, Iran, with appropriate solar and wind is considered. The effectiveness of the applied approach compared with optimization results of genetic algorithm and the artificial bee swarm optimization algorithm that was previously used successfully to solve optimization problems related to desalination integrated with the renewable energy system. The optimization is performed based on different diesel fuel price amounts (0.2, 0.5, and 1 $/liter). It is seen that at fuel price set to 0.2 and 0.5 $/liter, the seawater reverses osmosis desalination/photovoltaic/diesel generator/battery is the most cost-effective energy system, and when fuel price is 1 $/liter, the seawater reverses osmosis desalination/photovoltaic/wind turbine/diesel generator/battery is the most cost-effective hybrid system. While at fuel price set to 0.2, 0.5, and 1 $/liter, the seawater reverse osmosis desalination /photovoltaic/wind turbine/diesel generator/battery is the most eco-friendly. Finally, the results of this study show proposed algorithm is faster and more accurate (100 iterations, 98.36% accuracy) than the genetic algorithm (1000 iterations, 83.03% accuracy) and the artificial bee swarm optimization (300 iterations, 95.49% accuracy).

Czech name

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Czech description

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Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

—

OECD FORD branch

20303 - Thermodynamics

Project

<a href="/en/project/EF16_013%2F0001791" target="_blank" >EF16_013/0001791: IT4Innovations national supercomputing center - path to exascale</a><br>

Continuities

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year

2022

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

Energy Conversion and Management

ISSN

0196-8904

e-ISSN

1879-2227

Volume of the periodical

252

Issue of the periodical within the volume

January

Country of publishing house

GB - UNITED KINGDOM

Number of pages

19

Pages from-to

nestrankovano

UT code for WoS article

000744026300002

EID of the result in the Scopus database

2-s2.0-85120494609