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采用各种电池技术的独立光伏/风能/生物质能混合微电网的综合技术环境评估:一项对比分析。

Comprehensive techno-environmental evaluation of an isolated PV/wind/biomass hybrid microgrid employing various battery technologies: A comparative analysis.

作者信息

Alqahtani Mohammed, Alhajri Saeed, S Menesy Ahmed, Maher Mohammed Ali, M Sultan Hamdy, Khalid Muhammad

机构信息

Industrial Engineering Department, King Khalid University, Abha, Saudi Arabia.

Electrical Engineering Department, King Fahd University of Petroleum & Minerals (KFUPM), Dhahran, Saudi Arabia.

出版信息

PLoS One. 2025 Feb 20;20(2):e0317757. doi: 10.1371/journal.pone.0317757. eCollection 2025.

Abstract

Renewable energy technologies offer promise for addressing energy access and environmental concerns, especially in remote off-grid areas. This paper presents a comprehensive techno-economic analysis of an off-grid PV/wind/biomass hybrid system. Employing optimization techniques including the osprey optimization algorithm (OOA), zebra optimization algorithm (ZOA), and flying foxes optimization (FFO) algorithm, the study aims to determine the optimal sizing of solar PV, wind, biomass, and battery components. Using data from Tabuk, Saudi Arabia (28.38° N, 36.56° E), the study seeks to achieve optimal sizing for solar PV, wind, biomass, and battery storage components to minimize the net present cost (NPC) and ensure reliable power supply, adhering to specified loss of power supply probability (LPSP) and excess energy thresholds. Three battery types, namely, flooded lead-acid, lithium iron phosphate (LFP), and nickel iron (Ni-Fe), were analyzed. Results reveal that ZOA outperformed other algorithms, supplying electricity at a minimum cost of 0.1285 $/kWh in one configuration, with the LFP battery achieving the lowest NPC of 3.8 M$ in case studies with constrained LPSP. Across multiple simulations, ZOA displayed superior stability and convergence characteristics, evidenced by its tight objective function range and lower relative error metrics. These findings underscore the potential of this integrated approach to enhance the economic viability and operational resilience of off-grid hybrid microgrid systems, particularly in arid and semi-arid regions.

摘要

可再生能源技术为解决能源获取和环境问题带来了希望,特别是在偏远的离网地区。本文对一个离网光伏/风能/生物质混合系统进行了全面的技术经济分析。该研究采用了包括鱼鹰优化算法(OOA)、斑马优化算法(ZOA)和狐蝠优化(FFO)算法在内的优化技术,旨在确定太阳能光伏、风能、生物质和电池组件的最佳规模。利用沙特阿拉伯塔布克(北纬28.38°,东经36.56°)的数据,该研究力求实现太阳能光伏、风能、生物质和电池储能组件的最佳规模,以最小化净现值成本(NPC)并确保可靠的电力供应,同时符合指定的供电概率损失(LPSP)和过剩能量阈值。分析了三种电池类型,即铅酸蓄电池、磷酸铁锂(LFP)电池和镍铁(Ni-Fe)电池。结果表明,ZOA算法优于其他算法,在一种配置下以最低成本0.1285美元/千瓦时供电,在LPSP受限的案例研究中,LFP电池实现了最低的NPC,为380万美元。在多次模拟中,ZOA算法表现出卓越的稳定性和收敛特性,其目标函数范围紧凑且相对误差指标较低,证明了这一点。这些发现强调了这种综合方法在提高离网混合微电网系统的经济可行性和运营弹性方面的潜力,特别是在干旱和半干旱地区。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3f4f/11841891/02fe33940597/pone.0317757.g001.jpg

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