A Multi-Criteria Decision Maker for Grid-Connected Hybrid Renewable Energy Systems Selection Using Multi-Objective Particle Swarm Optimization

David Abdul Konneh, Harun Or Rashid Howlader, Ryuto Shigenobu, Tomonobu Senjyu, Shantanu Chakraborty and Narayanan Krishna
Additional contact information
David Abdul Konneh: Department of Electrical and Electronics Engineering, University of the Ryukyus, Okinawa 903-0213, Japan
Harun Or Rashid Howlader: Department of Electrical and Electronics Engineering, University of the Ryukyus, Okinawa 903-0213, Japan
Ryuto Shigenobu: Department of Electrical and Electronics Engineering, University of the Ryukyus, Okinawa 903-0213, Japan
Tomonobu Senjyu: Department of Electrical and Electronics Engineering, University of the Ryukyus, Okinawa 903-0213, Japan
Shantanu Chakraborty: Energy Transition Hub, University of Melbourne, Melbourne 3053, Australia
Narayanan Krishna: Department of Electrical and Electronics Engineering, SASTRA Deemed University, Thanjavur-613401, India

Sustainability, 2019, vol. 11, issue 4, 1-36

Abstract: Combating climate change issues resulting from excessive use of fossil fuels comes with huge initial costs, thereby posing difficult challenges for the least developed countries in Sub-Saharan Africa (SSA) to invest in renewable energy alternatives, especially with rapid industrialization. However, designing renewable energy systems usually hinges on different economic and environmental criteria. This paper used the Multi-Objective Particle Swarm Optimization (MOPSO) technique to optimally size ten grid-connected hybrid blocks selected amongst Photo-Voltaic (PV) panels, onshore wind turbines, biomass combustion plant using sugarcane bagasse, Battery Energy Storage System (BESS), and Diesel Generation (DG) system as backup power, to reduce the supply deficit in Sierra Leone. Resource assessment using well-known methods was done for PV, wind, and biomass for proposed plant sites in Kabala District in Northern and Kenema District in Southern Sierra Leone. Long term analysis was done for the ten hybrid blocks projected over 20 years whilst ensuring the following objectives: minimizing the Deficiency of Power Supply Probability (DPSP), Diesel Energy Fraction (DEF), Life Cycle Costs (LCC), and carbon dioxide (CO 2 ) emissions. Capacity factors of 27.41 % and 31.6 % obtained for PV and wind, respectively, indicate that Kabala district is the most feasible location for PV and wind farm installations. The optimum results obtained are compared across selected blocks for DPSP values of 0–50% to determine the most economical and environmentally friendly alternative that policy makers in Sierra Leone and the region could apply to similar cases.

Keywords: wind energy; solar energy; biomass energy; battery energy storage; grid-connected hybrid energy system; diesel energy fraction; CO 2 emissions; reliability and sustainability; MOPSO (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (13)

Downloads: (external link)
https://www.mdpi.com/2071-1050/11/4/1188/pdf (application/pdf)
https://www.mdpi.com/2071-1050/11/4/1188/ (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:jsusta:v:11:y:2019:i:4:p:1188-:d:208600

Access Statistics for this article

Sustainability is currently edited by Ms. Alexandra Wu

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