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首页> 外文期刊>Journal of Cleaner Production >Modelling and optimisation of a hybrid PV-wind turbine-pumped hydro storage energy system for mini-grid application in coastline communities
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Modelling and optimisation of a hybrid PV-wind turbine-pumped hydro storage energy system for mini-grid application in coastline communities

机译：用于海岸线社区小型电网的混合光伏-风轮机-抽水蓄能系统的建模和优化

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This study proposes a clean, reliable and affordable hybrid energy conversion technology that is based on sunlight and wind, with a hydro based energy storage system. The proposed system comprises Photovoltaic arrays, wind turbine (WT) and Pumped Hydro Energy Storage (PHES). The study was focused on satisfying energy demand of a typical coastline community, Patani (Lat. 5.23 degrees N and Long. 6.17 degrees E) - a Local Government Area (LGA). Genetic algorithm was adopted to optimise the PHES of the proposed hybrid plant to minimise the difference between energy demand and energy generated. Economic models were developed to ascertain the economic feasibility of the hybrid plant. High fidelity software (HOMER (R), MATLAB (R) and MS Excel (R) spreadsheet) were utilised for the analysis and optimisation. The peak rated power of PV and WT required to satisfy the energy demand of the LGA are 217 kW(p) and 226050 kW, respectively. The minimum storage capacity of the PHES was estimated at about 3,930,615 kWh, with the upper reservoir volume of 43170.06 m(3). The value of 0.27 $/kWh was obtained for the Levelised Cost of Energy (LCOE); while the loss of load probability of the proposed energy system was estimated at 0.1086. The proposed energy system supports the Sustainable Development Goal 7 - affordable and clean energy, with climate change mitigation potential. (C) 2019 Elsevier Ltd. All rights reserved.
机译：这项研究提出了一种清洁，可靠且价格合理的混合能源转换技术，该技术基于阳光和风能，并具有基于水的能源存储系统。拟议的系统包括光伏阵列，风力涡轮机（WT）和抽水蓄能电站（PHES）。这项研究的重点是满足典型海岸线社区北大年府（北纬5.23度和东经6.17度）的能源需求。采用遗传算法对拟建混合植物的PHES进行优化，以最大程度地减少能源需求和产生的能源之间的差异。开发经济模型以确定混合植物的经济可行性。高保真软件（HOMER（R），MATLAB（R）和MS Excel（R）电子表格）用于分析和优化。满足LGA能源需求所需的PV和WT的峰值额定功率分别为217 kW（p）和226050 kW。 PHES的最小存储容量估计约为3,930,615 kWh，上部水库容量为43170.06 m（3）。平均能源成本（LCOE）的值为0.27 $ / kWh；而所提议的能源系统的负载概率损失估计为0.1086。拟议的能源系统支持可持续发展目标7-负担得起的清洁能源，具有缓解气候变化的潜力。 （C）2019 Elsevier Ltd.保留所有权利。

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