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Intelligence Technique Based Design and Assessment of Photovoltaic-Battery-Diesel for Distributed Generation System in Campus Area

Subiyanto Subiyanto(1*), Mohamad Almas Prakasa(2), Pramudyo Wicaksono(3), Mega Ardisa Hapsari(4)

(1) Department of Electrical Engineering, Universitas Negeri Semarang, Indonesia
(2) Department of Electrical Engineering, Universitas Negeri Semarang, Indonesia
(3) Department of Electrical Engineering, Universitas Negeri Semarang, Indonesia
(4) Department of Electrical Engineering, Universitas Negeri Semarang, Indonesia
(*) Corresponding author



Several studies have discussed the optimal designing methods of distributed generation (DG) based on intelligent algorithms. However, the feasibility of an intelligent algorithm-based DG system has not been investigated further, especially for DG in the campus area. Moreover, the DG that operates in two modes (grid-connected and micro-grid mode) has unique characteristics. This paper presents a design and assessment of the PV-battery-diesel DG system in the campus area based on a powerful intelligence technique. The designed DG consists of a PV system (PV array, battery, and inverter) and a diesel generator is used as backup power supplies to cover the loads during grid blackouts. The intelligence technique is used to determine the optimal size and configuration of PV array. In this work, a new variant modified AHP with fuzzy logic is developed to solve the problem. The developed algorithm is implemented by using MATLAB software. Then, the optimal size and configuration results have been evaluated and assessed in HOMER software. HOMER simulation results show that DG can operate in both grid-connected and micro-grid mode properly. Based on the case study site data, the net present cost of DG system is $291.073,43. The energy cost of the DG system is $0,12 for E6+E8 building system and $0,06 for E11 building system. The DG system has produced some pollutants from fuel consumption.
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Analytical Hierarchy Process; Fuzzy Logic; Intelligence Technique; Distributed Generation; Renewable Energy

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