Multi-stage and multi-objective optimization for optimal sizing of stand-alone photovoltaic water pumping systems

• Published in: Energy (Oxford) Vol. 252; p. 124048
• Main Authors: Ahmed, Eihab E.E., Demirci, Alpaslan
• Format: Journal Article
• Language: English
• Published: Oxford Elsevier Ltd 01.08.2022; Elsevier BV
• Subjects: Algorithms; computer software; Developing countries; Drinking water; Economic analysis; Economic models; electric power; energy; Excess water; infrastructure; LDCs; Life cycle cost; life cycle costing; Life cycle costs; Life cycles; Loss of load probability; Multi-objective optimization; Multiple objective analysis; Optimization; Particle swarm optimization; Photovoltaic cells; Photovoltaic water pumping system; Photovoltaics; probability; Pumping; Rural areas; Sensitivity analysis; Sizing; solar energy; Solar radiation; Sudan; Transmission lines; Villages; Water demand; Water tanks; Sudan; Photovoltaic water pumping system; Multi-objective optimization; Loss of load probability; Particle swarm optimization; Life cycle cost
• ISSN: 0360-5442; 1873-6785
• DOI: 10.1016/j.energy.2022.124048

Supplying electrical energy and drinking water in developing countries, especially in rural areas, is a challenging issue. The main reasons for this may include faulty grid lines, inability to fulfill the increasing demand, and inadequate coverage of the national transmission lines due to the distance between the remote villages. Photovoltaic water pumping systems (PVPS) can be the solution to the aforementioned problems. However, the high costs of PVPS and the unpredictability of solar radiation complicate the design of PVPS. This study was conducted considering the drinking water needs of a village located near Khartoum, Sudan. Multi-objective optimization (MOO) in the developed techno-economic model was carried out considering the reliability in terms of loss of load probability (LLP) and life cycle cost (LCC). The PVPS has been optimally sized considering the tilt angle, installed and unused PV power, water tank volume, and excess water. The particle swarm optimization (PSO) algorithm and the new python package, pvpumpingsystem, were combined to simulate the proposed PVPS model. Sensitivity analysis was conducted considering system performance, PV capacity, and tank volume. The optimal sizing results of the proposed model would be satisfactory and feasible, especially in developing countries with infrastructure and energy problems. •Several local solutions are offered, considering user comfort preferences.•The optimum tilt angle of PV is determined using the PVlib library and PSO.•The sensitivity analyses are realized considering the tank volume and PV power simultaneously.•A greater PV power or tank capacity reduces the LLP's sensitivity to drop after a certain amount.•The interrupted days last only 8 h, and the deficit water is reduced to two m3/year.