Abstract Off-grid solar/diesel systems have been widely utilized in remote and rural settings. Some of the main challenges for solar-diesel energies are determining the appropriate capacity and location in rural areas. Therefore, an efficient framework is needed for using off-grid solar/diesel systems. For the optimal sizing and location of off-grid photovoltaic (PV)-diesel schemes in rural areas, a new framework is proposed. In this framework, a geographic information system module is utilized to identify the best location based on technical, economic, reliability, social, and environmental criteria. Then, a hybrid optimization algorithm is utilized to determine the appropriate capacity for continuously meeting of the load via total life cycle cost minimization. A real case study in South Khorasan is considered, in order to illustrate the proposed framework and its effectiveness. The effectiveness of the applied approach is investigated by comparing the outcomes with the results obtained by other heuristic methods. Also, the impacts are investigated of fuel cost variations, initial PV and battery costs, and interest rate on the economics of the hybrid scheme. The simulation results demonstrate that the hybrid algorithm obtains results that are more accurate (by 14.1%) than other applied algorithms, and show that the use of solar energy with a diesel generator, compared to the diesel only system, significantly reduces greenhouse gas emissions (by 59.6%) and supply costs (by 22.2%). The results thus demonstrate the benefits of utilizing the proposed framework for the hybrid system. These results are expected to help enhance acceptance and utilization of cleaner production systems.

中文翻译：

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基于经济参数的最佳尺寸和位置，用于具有光伏、电池和柴油技术的混合系统的离网应用

摘要离网太阳能/柴油系统已广泛应用于偏远和农村地区。太阳能柴油能源面临的一些主要挑战是确定农村地区的适当容量和位置。因此，需要一个有效的框架来使用离网太阳能/柴油系统。为了优化农村地区离网光伏 (PV)-柴油计划的规模和位置，提出了一个新的框架。在该框架中，地理信息系统模块用于根据技术、经济、可靠性、社会和环境标准确定最佳位置。然后，使用混合优化算法通过总生命周期成本最小化来确定连续满足负载的合适容量。考虑了南呼罗珊的一个真实案例研究，为了说明所提出的框架及其有效性。通过将结果与其他启发式方法获得的结果进行比较来研究应用方法的有效性。此外，还研究了燃料成本变化、初始光伏和电池成本以及利率对混合方案经济性的影响。仿真结果表明，混合算法获得的结果比其他应用算法更准确（14.1%），并表明与仅使用柴油的系统相比，使用太阳能与柴油发电机相比，显着减少了温室气体排放（ 59.6%）和供应成本（22.2%）。因此，结果证明了将提议的框架用于混合系统的好处。