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Investigation of the Techno-Economic Viability of A Hybrid Renewable Energy System (HRES) in Rural Malaysian Islands

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This study evaluates the feasibility of a hybrid renewable energy system (HRES) for rural Malaysian regions, specifically Pulau Carey and Pulau Ketam. This research employs a three-pronged approach: Multi-Criteria Decision Making (MCDM): This method selects the most suitable HRES configuration for the target islands. Criteria Analysis: Economic, environmental, energy security and technical aspects are considered. PSO (Particle Swarm Optimization) Validation: This technique validates the accuracy of HRES sizing simulations. The MCDM analysis identifies wind and solar energy as the most suitable choices, with scores of 0.8138 and 0.7877, respectively. The study identifies Configuration 5, which includes solar PV, wind turbines, a diesel generator, and battery storage, as the most effective HRES. It balances cost-efficiency, energy security, and renewable integration, achieving the lowest Levelized Cost of Energy (LCOE) and Net Present Cost (NPC) with a 99.99% renewable energy fraction. MATLAB-based PSO optimization closely matches results from Homer Pro software, showing minimal errors. This configuration is particularly beneficial for remote communities like Kampung Orang Asli Sungai Bumbun, offering significant cost savings over current energy solutions.
Title: Investigation of the Techno-Economic Viability of A Hybrid Renewable Energy System (HRES) in Rural Malaysian Islands
Description:
This study evaluates the feasibility of a hybrid renewable energy system (HRES) for rural Malaysian regions, specifically Pulau Carey and Pulau Ketam.
This research employs a three-pronged approach: Multi-Criteria Decision Making (MCDM): This method selects the most suitable HRES configuration for the target islands.
Criteria Analysis: Economic, environmental, energy security and technical aspects are considered.
PSO (Particle Swarm Optimization) Validation: This technique validates the accuracy of HRES sizing simulations.
The MCDM analysis identifies wind and solar energy as the most suitable choices, with scores of 0.
8138 and 0.
7877, respectively.
The study identifies Configuration 5, which includes solar PV, wind turbines, a diesel generator, and battery storage, as the most effective HRES.
It balances cost-efficiency, energy security, and renewable integration, achieving the lowest Levelized Cost of Energy (LCOE) and Net Present Cost (NPC) with a 99.
99% renewable energy fraction.
MATLAB-based PSO optimization closely matches results from Homer Pro software, showing minimal errors.
This configuration is particularly beneficial for remote communities like Kampung Orang Asli Sungai Bumbun, offering significant cost savings over current energy solutions.

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