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Integrated supply-demand energy management for optimal design of off-grid hybrid renewable energy systems for residential electrification in arid climates

机译:集成供需的能源管理,用于干旱气候住宅电气化的离网混合可再生能源系统的最佳设计

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The growing research interest in hybrid renewable energy systems (HRESs) has been regarded as a natural and yet critical response to address the challenge of rural electrification. Based on a Bibliometric analysis performed by authors, it was concluded that most studies simply adopted supply-side management techniques to perform the design optimization of such a renewable energy system. To further advance those studies, this paper presents a novel approach by integrating demand-supply management (DSM) with particle swarm optimization and applying it to optimally design an off-grid hybrid PV-solar-diesel-battery system for the electrification of residential buildings in arid environments, using a typical dwelling in Adrar, Algeria, as a case study. The proposed HRES is first modelled by an in-house MATLAB code based on a multi-agent system concept and then optimized by minimizing the total net present cost (TNPC), subject to reliability level and renewable energy penetration. After validation against the HOMER software, further techno-economic analyses including sensitivity study are undertaken, considering different battery technologies. By integrating the proposed DSM, the results have shown the following improvements: with RF = 100%, the energy demand and TNPC are reduced by 7% and 18%, respectively, compared to the case of using solely supply-side management. It is found that PV-Li-ion represents the best configuration, with TNPC of $23,427 and cost of energy (COE) of 0.23 $/kWh. However, with lower RF values, the following reductions are achieved: energy consumption (19%) and fuel consumption or CO2 emission (57%), respectively. In contrast, the RF is raised from 15% (without DSM) to 63% (with DSM). It is clear that the optimal configuration consists of wind-diesel, with COE of 0.21 $/kWh, smaller than that obtained with a standalone diesel generator system. The outcomes of this work can provide valuable insights into the successful design and deployment of HRES in Algeria and surrounding regions.
机译:对混合可再生能源系统(返还)的日益增长的研究兴趣被认为是对解决农村电气化挑战的自然而艰巨的回应。基于作者进行的真人计量分析,得出结论,大多数研究只是采用了供应侧管理技术来执行这种可再生能源系统的设计优化。为了进一步推进这些研究,本文通过将需求管理(DSM)与粒子群优化集成并应用以最佳地设计了一种用于最佳设计的用于居住建筑物的电气化的外网混合PV-Solar-电池系统的新方法在干旱的环境中,在阿尔及利亚阿德尔的典型住宅为例。所提出的HRES是由基于多助理系统概念的内部MATLAB代码建模的,然后通过最小化总净目的成本(TNPC)进行优化,以可靠性水平和可再生能源渗透。在验证荷马软件后,考虑不同的电池技术,进行了进一步的技术经济分析,包括敏感性研究。通过整合所提出的DSM,结果表明了以下改进:与使用完全供应侧管理的情况相比,RF = 100%,能量需求和TNPC分别减少了7%和18%。发现PV-Li离子代表最佳配置,TNPC为23,427美元,能源成本(COE)为0.23 $ / kWh。然而,利用较低的RF值,实现了以下还原:能耗(19%)和燃料消耗或二氧化碳排放(57%)。相比之下,RF从15%(没有DSM)升高至63%(DSM)。很明显,最佳配置由风柴油组成,COE为0.21 $ / kWh,小于由独立柴油发电机系统获得的COE。这项工作的结果可以为阿尔及利亚和周围地区的成功设计和部署提供有价值的见解。

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