Browsing by Author "Makbul, A.M. Ramli"

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    Optimal sizing of grid-connected photovoltaic energy system in Saudi Arabia
    (Renewable Energy, 2015) Makbul, A.M. Ramli; Ayong, Hiendro; Khaled, Sedraoui; Ssennoga, Twaha
    Resource optimization is a major factor in the assessment of the effectiveness of renewable energy systems. Various methods have been utilized by different researchers in planning and sizing the gridconnected PV systems. This paper analyzes the optimal photovoltaic (PV) array and inverter sizes for a grid-connected PV system. Unmet load, excess electricity, fraction of renewable electricity, net present cost (NPC) and carbon dioxide (CO2) emissions percentage are considered in order to obtain optimal sizing of the grid-connected PV system. An optimum result, with unmet load and excess electricity of 0%, for serving electricity in Makkah, Saudi Arabia is achieved with the PV inverter size ratio of R ¼ 1 with minimized CO2 emissions. However, inverter size can be downsized to 68% of the PV nominal power to reduce the inverter cost, and hence decrease the total NPC of the system.
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    A review of optimization approaches for hybrid distributed energy generation systems: off-grid and grid-connected systems
    (Sustainable Cities and Society, 2018) Ssennoga, Twaha,; Makbul, A.M. Ramli
    Distributed generation is a collective term that covers the generation of energy at micro level, distributed in a location near the end user by using renewable and nonrenewable distributed energy generation (DEG) resources including among others, solar, wind, hydro, geothermal and diesel generators. This paper presents a review on the optimization approaches for hybrid DEG systems, considering both stand-alone and grid-connected systems. There are several optimization techniques used on DEG systems, comprising of analytical and artificial intelligent (AI) and hybrid techniques. This work encompasses the selected journal papers published especially in the last five A review of optimization approaches for hybrid distributed energy generation systems: off-grid and grid-connected systems years. A brief background of the optimization approaches been highlighted, particularly identifying the most common techniques to give the basis for analysis of the approaches currently applied on hybrid DEG systems. The analysis shows that AI techniques are still dominating the techniques used for optimization of DEG systems, with particle swarm optimization (PSO) recognized as the most used AI method. The objective functions in the optimization of hybrid DEG systems are currently defined to maximize the reliability, to minimize the expected interruption cost, and to optimize operation schedule of DEG resources.