Multi-Objective Optimization of a Hybrid Nanogrid/Microgrid: Application to Desert Camps in Hafr Al-Batin

Houssem Rafik Al-Hana Bouchekara, Mohammad Shoaib Shahriar, Muhammad Sharjeel Javaid, Yusuf Abubakar Sha’aban and Makbul Anwari Muhammad Ramli
Additional contact information
Houssem Rafik Al-Hana Bouchekara: Department of Electrical Engineering, University of Hafr Al-Batin, Hafr Al-Batin 31991, Saudi Arabia
Mohammad Shoaib Shahriar: Department of Electrical Engineering, University of Hafr Al-Batin, Hafr Al-Batin 31991, Saudi Arabia
Muhammad Sharjeel Javaid: Department of Electrical Engineering, University of Hafr Al-Batin, Hafr Al-Batin 31991, Saudi Arabia
Yusuf Abubakar Sha’aban: Department of Electrical Engineering, University of Hafr Al-Batin, Hafr Al-Batin 31991, Saudi Arabia
Makbul Anwari Muhammad Ramli: Department of Electrical and Computer Engineering, King Abdulaziz University, Jeddah 21589, Saudi Arabia

Energies, 2021, vol. 14, issue 5, 1-24

Abstract: This paper presents an optimal design for a nanogrid/microgrid for desert camps in the city of Hafr Al-Batin in Saudi Arabia. The camps were designed to operate as separate nanogrids or to operate as an interconnected microgrid. The hybrid nanogrid/microgrid considered in this paper consists of a solar system, storage batteries, diesel generators, inverter, and load components. To offer the designer/operator various choices, the problem was formulated as a multi-objective optimization problem considering two objective functions, namely: the cost of electricity (COE) and the loss of power supply probability (LPSP). Furthermore, various component models were implemented, which offer a variety of equipment compilation possibilities. The formulated problem was then solved using the multi-objective evolutionary algorithm, based on both dominance and decomposition (MOEA/DD). Two cases were investigated corresponding to the two proposed modes of operation, i.e., nanogrid operation mode and microgrid operation mode. The microgrid was designed considering the interconnection of four nanogrids. The obtained Pareto front (PF) was reported for each case and the solutions forming this front were discussed. Based on this investigation, the designer/operator can select the most appropriate solution from the available set of solutions using his experience and other factors, e.g., budget, availability of equipment and customer-specific requirements. Furthermore, to assess the quality of the solutions found using the MOEA/DD, three different methods were used, and their results compared with the MOEA/DD. It was found that the MOEA/DD obtained better results (nondominated solutions), especially for the microgrid operation mode.

Keywords: desert camps; diesel generator; nanogrid; microgrid; multi-objective evolutionary algorithm; multi-objective optimization; solar energy (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
https://www.mdpi.com/1996-1073/14/5/1245/pdf (application/pdf)
https://www.mdpi.com/1996-1073/14/5/1245/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jeners:v:14:y:2021:i:5:p:1245-:d:505232

Access Statistics for this article

Energies is currently edited by Ms. Agatha Cao

More articles in Energies from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().