Hybrid Renewable Energy System (HRES) has become a popular alternative for locations restricted to national grid connection due to geographical limitations. The study investigates the available renewable resources of a remote village in Mymensingh district of Bangladesh to propose and evaluate optimal sizing and cost of a grid independent HRES. The intermittency of solar irradiance and uncertain variation in load demand are taken into account by adopting probabilistic scenario-based analysis (SBA). Beta distribution and Gaussian distribution are considered for solar irradiance and load uncertainties, respectively, and Roulette Wheel mechanism generates multiple probabilistic scenarios. Objective function is formulated to minimize the total system cost (TSC) under defined constraints. Dandelion optimizer (DO), a relatively recent and unexplored metaheuristic algorithm along with two other popular optimization algorithms, Slime Mould Algorithm (SMA) and Real Coded Genetic Algorithm (RCGA) are applied to size the components for different probabilistic scenarios generated by Roulette Wheel. DO outperformed SMA and RCGA providing the solution set with 18.4 % and 3.2 % reduction in simulation time and system cost, respectively, in comparison with RCGA, whereas, 11.3 % and 16.7 % reduction in simulation time and system cost, respectively, in contrast to SMA. DO’s computation of cost margin (1.17 million dollars to 1.46 million dollars), PV allocation (minimum 7 modules to maximum 218 modules), biomass power allocation (maximum of 70.34215 kW) and optimized battery allocation computed by the algorithms (24 units) provide authorities a margin of cost-efficient estimation with conservative preparedness for developing HRES in the selected region. The study also provides a scientific framework to account for the uncertain parameters while proposing and analyzing HRES for off-grid localities, where inadequate literary exploration is evident in the context of Bangladesh.

中文翻译：

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具有不确定性概率建模的 HRES 的最佳规模——技术经济分析框架


混合可再生能源系统（HRES）已成为由于地理限制而无法连接国家电网的地区的流行替代方案。该研究调查了孟加拉国迈门辛区一个偏远村庄的可用可再生资源，以提出和评估独立于电网的 HRES 的最佳规模和成本。采用概率情景分析（SBA），考虑了太阳辐照度的间歇性和负荷需求的不确定变化。太阳辐照度和负载不确定性分别考虑贝塔分布和高斯分布，轮盘赌机制生成多种概率场景。制定目标函数是为了在定义的约束下最小化总系统成本（TSC）。蒲公英优化器 (DO) 是一种相对较新且未经探索的元启发式算法，它与另外两种流行的优化算法史莱姆霉菌算法 (SMA) 和实数编码遗传算法 (RCGA) 一起用于调整轮盘赌轮生成的不同概率场景的组件大小。 DO 的性能优于 SMA 和 RCGA，提供的解决方案集与 RCGA 相比，仿真时间和系统成本分别减少了 18.4% 和 3.2%，而与 RCGA 相比，仿真时间和系统成本分别减少了 11.3% 和 16.7% SMA。 DO对成本利润（117万美元到146万美元）、光伏分配（最少7个组件到最多218个组件）、生物质发电分配（最大70.34215kW）以及算法计算出的优化电池分配（24台）的计算提供了权威性成本效益估计的余量，并为在选定区域发展 HRES 做好保守准备。 该研究还提供了一个科学框架来解释不确定参数，同时提出和分析离网地区的 HRES，在孟加拉国的背景下，文学探索明显不足。