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Energies 2017, 10(10), 1664; doi:10.3390/en10101664

Multi-Objective Optimal Design of Stand-Alone Hybrid Energy System Using Entropy Weight Method Based on HOMER

Department of Electrical Engineering, Army Logistics University of PLA, Chongqing 401331, China
Department of Electrical Engineering, Chongqing Communication Institute, Chongqing 400036, China
Authors to whom correspondence should be addressed.
Received: 15 September 2017 / Revised: 10 October 2017 / Accepted: 16 October 2017 / Published: 20 October 2017
(This article belongs to the Section Electrical Power and Energy System)
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Implementation of hybrid energy system (HES) is generally considered as a promising way to satisfy the electrification requirements for remote areas. In the present study, a novel decision making methodology is proposed to identify the best compromise configuration of HES from a set of feasible combinations obtained from HOMER. For this purpose, a multi-objective function, which comprises four crucial and representative indices, is formulated by applying the weighted sum method. The entropy weight method is employed as a quantitative methodology for weighting factors calculation to enhance the objectivity of decision-making. Moreover, the optimal design of a stand-alone PV/wind/battery/diesel HES in Yongxing Island, China, is conducted as a case study to validate the effectiveness of the proposed method. Both the simulation and optimization results indicate that, the optimization method is able to identify the best trade-off configuration among system reliability, economy, practicability and environmental sustainability. Several useful conclusions are given by analyzing the operation of the best configuration. View Full-Text
Keywords: hybrid energy system; optimal design; HOMER; entropy weight method hybrid energy system; optimal design; HOMER; entropy weight method

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Lu, J.; Wang, W.; Zhang, Y.; Cheng, S. Multi-Objective Optimal Design of Stand-Alone Hybrid Energy System Using Entropy Weight Method Based on HOMER. Energies 2017, 10, 1664.

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