Details
| Original language | English |
|---|---|
| Pages (from-to) | 4924-4939 |
| Number of pages | 16 |
| Journal | Energy Reports |
| Volume | 11 |
| Early online date | 3 May 2024 |
| Publication status | Published - Jun 2024 |
Abstract
The novel concept of using hybrid renewable resources to provide clean energy helps to address the unique shortcomings of each renewable source. This study describes an innovative concept about the design of optimal grid PV/biomass 100 % renewable and fully reliable energy systems without considering energy storage devices. By leveraging community solar and biomass resources, the proposed system can power remote villages with a minimum cost of energy. Multi-Objective Genetic Algorithm (MOGA) is employed to perform an optimal procedure. The PV-biomass deployment project's economic viability is assessed using financial metrics such as net present cost (NPC) and cost of energy (COE). In order to install a hybrid system at the chosen site, the optimal configuration (PV 87 kW, biomass1 29 kW, and biomass2 125 kW) was examined. The NPC, COE, and total system cost, in this configuration, are $118,942, $0.02/kWh, and $892,892, respectively. The combined yearly consumption of the biomass1 and biomass2 generators is 704.81 tons of wheat straw. The total annual CO2 emissions of the PV, biomass1, and biomass2 generators in this system are avoided by 729.5 tons. The findings clearly demonstrate that the suggested approach can manage a reliable power flow with a suitable configuration. The solar PV and biomass system examined in this study will probably be a specialized solution in regions with abundant biomass resources; nevertheless, it offers a reliable starting point for the creation of larger-scale bioenergy value chains with the long-term objective of generating electricity from wheat straw biomass materials.
Keywords
- Cost of energy, Hybrid renewable energy system, Renewable energy, Solar energy, Wheat straw
ASJC Scopus subject areas
Sustainable Development Goals
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In: Energy Reports, Vol. 11, 06.2024, p. 4924-4939.
Research output: Contribution to journal › Article › Research › peer review
}
TY - JOUR
T1 - Novel integration and optimization of reliable photovoltaic and biomass integrated system for rural electrification
AU - Irshad, Ahmad Shah
AU - Ueda, Soichiro
AU - Furukakoi, Masahiro
AU - Zakir, Mohammad Naseer
AU - Ludin, Gul Ahmad
AU - Elkholy, M. H.
AU - Yona, Atsushi
AU - Elias, Said
AU - Senjyu, Tomonobu
N1 - Publisher Copyright: © 2024
PY - 2024/6
Y1 - 2024/6
N2 - The novel concept of using hybrid renewable resources to provide clean energy helps to address the unique shortcomings of each renewable source. This study describes an innovative concept about the design of optimal grid PV/biomass 100 % renewable and fully reliable energy systems without considering energy storage devices. By leveraging community solar and biomass resources, the proposed system can power remote villages with a minimum cost of energy. Multi-Objective Genetic Algorithm (MOGA) is employed to perform an optimal procedure. The PV-biomass deployment project's economic viability is assessed using financial metrics such as net present cost (NPC) and cost of energy (COE). In order to install a hybrid system at the chosen site, the optimal configuration (PV 87 kW, biomass1 29 kW, and biomass2 125 kW) was examined. The NPC, COE, and total system cost, in this configuration, are $118,942, $0.02/kWh, and $892,892, respectively. The combined yearly consumption of the biomass1 and biomass2 generators is 704.81 tons of wheat straw. The total annual CO2 emissions of the PV, biomass1, and biomass2 generators in this system are avoided by 729.5 tons. The findings clearly demonstrate that the suggested approach can manage a reliable power flow with a suitable configuration. The solar PV and biomass system examined in this study will probably be a specialized solution in regions with abundant biomass resources; nevertheless, it offers a reliable starting point for the creation of larger-scale bioenergy value chains with the long-term objective of generating electricity from wheat straw biomass materials.
AB - The novel concept of using hybrid renewable resources to provide clean energy helps to address the unique shortcomings of each renewable source. This study describes an innovative concept about the design of optimal grid PV/biomass 100 % renewable and fully reliable energy systems without considering energy storage devices. By leveraging community solar and biomass resources, the proposed system can power remote villages with a minimum cost of energy. Multi-Objective Genetic Algorithm (MOGA) is employed to perform an optimal procedure. The PV-biomass deployment project's economic viability is assessed using financial metrics such as net present cost (NPC) and cost of energy (COE). In order to install a hybrid system at the chosen site, the optimal configuration (PV 87 kW, biomass1 29 kW, and biomass2 125 kW) was examined. The NPC, COE, and total system cost, in this configuration, are $118,942, $0.02/kWh, and $892,892, respectively. The combined yearly consumption of the biomass1 and biomass2 generators is 704.81 tons of wheat straw. The total annual CO2 emissions of the PV, biomass1, and biomass2 generators in this system are avoided by 729.5 tons. The findings clearly demonstrate that the suggested approach can manage a reliable power flow with a suitable configuration. The solar PV and biomass system examined in this study will probably be a specialized solution in regions with abundant biomass resources; nevertheless, it offers a reliable starting point for the creation of larger-scale bioenergy value chains with the long-term objective of generating electricity from wheat straw biomass materials.
KW - Cost of energy
KW - Hybrid renewable energy system
KW - Renewable energy
KW - Solar energy
KW - Wheat straw
UR - http://www.scopus.com/inward/record.url?scp=85192076766&partnerID=8YFLogxK
U2 - 10.1016/j.egyr.2024.04.057
DO - 10.1016/j.egyr.2024.04.057
M3 - Article
AN - SCOPUS:85192076766
VL - 11
SP - 4924
EP - 4939
JO - Energy Reports
JF - Energy Reports
ER -