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Solving financial allocation problem in distribution system expansion planning Siti Hajar Mohd Tahar; Shamshul Bahar Yaakob; Ahmad Shukri Fazil Rahman; Amran Ahmed
Bulletin of Electrical Engineering and Informatics Vol 8, No 1: March 2019
Publisher : Institute of Advanced Engineering and Science

This paper introduces a new technique to solve financial allocation in Distribution System Expansion Planning (DSEP) problem. The proposed technique will be formulated by using mean-variance analysis (MVA) approach in the form of mixed-integer programming (MIP) problem. It consist the hybridization of Hopfield Neural Network (HNN) and Boltzmann Machine (BM) in first and second phase respectively. During the execution at the first phase, this model will select the feasible units meanwhile the second phase will restructured until it finds the best solution from all the feasible solution. Due to this feature, the proposed model has a fast convergence and the accuracy of the obtained solution. This model can help planners in decision-making process since the solutions provide a better allocation of limited financial resources and offer the planners with the flexibility to apply different options to increase the profit.

Solving financial allocation problem in distribution system expansion planning Siti Hajar Mohd Tahar; Shamshul Bahar Yaakob; Ahmad Shukri Fazil Rahman; Amran Ahmed
Bulletin of Electrical Engineering and Informatics Vol 8, No 1: March 2019
Publisher : Institute of Advanced Engineering and Science

This paper introduces a new technique to solve financial allocation in Distribution System Expansion Planning (DSEP) problem. The proposed technique will be formulated by using mean-variance analysis (MVA) approach in the form of mixed-integer programming (MIP) problem. It consist the hybridization of Hopfield Neural Network (HNN) and Boltzmann Machine (BM) in first and second phase respectively. During the execution at the first phase, this model will select the feasible units meanwhile the second phase will restructured until it finds the best solution from all the feasible solution. Due to this feature, the proposed model has a fast convergence and the accuracy of the obtained solution. This model can help planners in decision-making process since the solutions provide a better allocation of limited financial resources and offer the planners with the flexibility to apply different options to increase the profit.

Solving financial allocation problem in distribution system expansion planning Siti Hajar Mohd Tahar; Shamshul Bahar Yaakob; Ahmad Shukri Fazil Rahman; Amran Ahmed
Bulletin of Electrical Engineering and Informatics Vol 8, No 1: March 2019
Publisher : Institute of Advanced Engineering and Science

This paper introduces a new technique to solve financial allocation in Distribution System Expansion Planning (DSEP) problem. The proposed technique will be formulated by using mean-variance analysis (MVA) approach in the form of mixed-integer programming (MIP) problem. It consist the hybridization of Hopfield Neural Network (HNN) and Boltzmann Machine (BM) in first and second phase respectively. During the execution at the first phase, this model will select the feasible units meanwhile the second phase will restructured until it finds the best solution from all the feasible solution. Due to this feature, the proposed model has a fast convergence and the accuracy of the obtained solution. This model can help planners in decision-making process since the solutions provide a better allocation of limited financial resources and offer the planners with the flexibility to apply different options to increase the profit.

Assessment of renewable energy sources to generate electricity for remote areas, South Iraq Ali Hadi Kother; Zaidoon Waleed AL-Shammari Waleed Jawad; Safaa Kother; Ihsan Ahmed Taha; Hussam Almukhtar; Muhammad Mokhzaini Azizan; Ahmad Shukri Fazil Rahman; Khairunnisa Hasikin
International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 13, No 4: December 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijpeds.v13.i4.pp2378-2385

With the rising need for utilizing renewable energy instead of traditional energies in electricity generation across the world, a broad assessment of these energies' performance is required to make the most of them everywhere. This paper looks at the techno-economics of renewable energy resources for a distant health clinic in a rural location of southern Iraq. Cost, dependability, and availability are the parameters that were considered in this study, which took into consider the power load in this scenario. Because of its efficacy, the particle swarm optimization (PSO) technique was chosen for the suggested study. Results showed that the respective optimal values for number of photovoltaics (NPV) equal to (10), number of wind turbines (NWT) equal to (5), and number of batteries (NBT) of (33), cost of energy (COE) of (0.518 US$/kWh), loss power supply probability (LPSP) of (0.073%), reliability (REL) of (99.927%) and renewable factors (RF) of (100%) with (66 %) solar energy penetration, and (34%) wind energy penetration. Finally, it was discovered that implementing a hybrid renewable energy system (HRES) is an effective way to address the electrical demands of remote rural regions in Iraq and other developing countries with similar climates.

Optimal sizing of standalone for hybrid renewable energy system by using PSO optimization technique Zaidoon Waleed Jawad Al-Shammari; Muhammad Mokhzaini Azizan; Ahmad Shukri Fazil Rahman; Khairunnisa Hasikin
International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 14, No 1: March 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijpeds.v14.i1.pp426-432

Providing electricity to rural regions is difficult for developing countries, such as Iraq, particularly in remote parts without grid connections. The electrical demands of Zerbattiya, a community in southern Iraq near the Iranian border, are discussed in this paper. The proposed system includes wind turbines, solar panels, diesel engines, batteries, etc. This study suggests a techno-economic viable and optimal size for each component to generate electricity for this area. This research uses particle swarm optimization techniques (PSO). The best hybrid renewable energy system (HRES) design is achieved by balancing the lowest possible cost of energy (COE) with the lowest possible loss of power supply probability (LPSP) and the greatest possible reliability factor value. As a result of the findings, the respective ideal values of number of photovoltaics (NPV), number of wind turbines (NWT), number of diesel generator (NDG), number of batteries (NBT), COE, LPSP, and reliability are 138, 43, 2, 324, US$/KWh 0.129, 0.0508%, and 99.9492%, respectively. Finally, it was discovered that implementing a HRES is an effective way to address the electrical demands of remote rural regions in Iraq and other developing countries with similar climates.

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