Components sizing of photovoltaic stand-alone system based on loss of power supply probability

Ayop, Razman; Isa, Normazlina Mat; Tan, Chee Wei

doi:10.1016/j.rser.2017.06.079

Cited by 90 publications

(42 citation statements)

References 69 publications

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“…However, the reliability level is kept to 0.01. These results confirm those obtained in [15] which show that the increase of the PV capacity can lead to a decrease of the storage system without compromising the system reliability level. Furthermore, the reduction of 78% of the number of the battery banks leads to a significant reduction of the TLCC.…”

Section: Resultssupporting

confidence: 90%

A comparative study based on the Genetic Algorithm (GA) method for the optimal sizing of the standalone photovoltaic system in the Ngoundiane site

Sadio¹,

Mbodji²,

Fall³

et al. 2018

EAI Endorsed Transactions on Energy Web

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We study a sizing method using Artificial Intelligence Techniques (AI) to find the optimal sizes of a standalone photovoltaic system in Ngoundiane, Senegal. The sizing of the PV system is considered here as a mono-objective problem and the Total Life Cycle Cost (TLCC) is the « Objective » function to minimize. Based on some constraints and after 10 simulations, the optimisation gives, as a result, an optimal value of TLCC corresponding to the combination of 225750 WC/8100 Ah. This result show that the method using Genetic Algorithm (GA) increases considerably the photovoltaic capacity compared to the intuitive and numerical methods used in our previous works. The GA method better covers the load demand, with more long time, when compared with those obtained with numerical method. These results confirm that this method is effective and reliable because it allows the design of a PV system that satisfies the load demand of the Ngoundiane site with a lower cost.

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Section: Resultssupporting

confidence: 90%

A comparative study based on the Genetic Algorithm (GA) method for the optimal sizing of the standalone photovoltaic system in the Ngoundiane site

Sadio¹,

Mbodji²,

Fall³

et al. 2018

EAI Endorsed Transactions on Energy Web

View full text Add to dashboard Cite

show abstract

“…Then, the lower cost from the set of configurations is selected on the basis of the objective function as an optimal solution [39]. Daily meteorological data and simple PV modules were used in these research works [13][14][15][16][17][18][19]40] to find the current-voltage (I-V) data curve at different operation conditions. The daily meteorological data were used in [13][14][15][16][17][18]40] lead to give unsatisfactory performance of the system.…”

Section: Optimization Methodsmentioning

confidence: 99%

Optimum Design of a Standalone Solar Photovoltaic System Based on Novel Integration of Iterative-PESA-II and AHP-VIKOR Methods

et al. 2020

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Solar energy is considered one of the most important renewable energy resources, and can be used to power a stand-alone photovoltaic (SAPV) system for supplying electricity in a remote area. However, inconstancy and unpredictable amounts of solar radiation are considered major obstacles in designing SAPV systems. Therefore, an accurate sizing method is necessary to apply in order to find an optimal configuration and fulfil the required load demand. In this study, a novel hybrid sizing approach was developed on the basis of techno-economic objectives to optimally size the SAPV system. The proposed hybrid method consisted of an intuitive method to estimate initial numbers of PV modules and storage battery, an iterative approach to accurately generate a set of wide ranges of optimal configurations, and a Pareto envelope-based selection algorithm (PESA-II) to reduce large configuration by efficacy obtaining a set of Pareto front (PF) solutions. Subsequently, the optimal configurations were ranked by using an integrated analytic hierarchy process (AHP) and vlsekeriterijumskaoptimizacija i kompromisonoresenje (VIKOR). The techno-economic objectives were loss of load probability, life cycle cost, and levelized cost of energy. The performance analysis results demonstrated that the lead–acid battery was reliable and more cost-effective than the other types of storage battery.

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“…Ever-raising energy load demands, the depletion of the fossil fuel resources, and the global warming encourage energy system designers to optimize their designs. Photovoltaic (PV) systems can be categorized into three types based on the approach of utilization, namely, SAPV system, grid-connected PV system, and hybrid PV system, respectively [1][2][3]. The use of standalone PV (SAPV) systems can lead to a transformation of technology in terms of "leaving the grid" or "living in off-grid".…”

Section: Introductionmentioning

confidence: 99%

Optimal Design of Standalone Photovoltaic System Based on Multi-Objective Particle Swarm Optimization: A Case Study of Malaysia

et al. 2020

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This paper presents a multi-objective particle swarm optimization (MOPSO) method for optimal sizing of the standalone photovoltaic (SAPV) systems. Loss of load probability (LLP) analysis is considered to determine the technical evaluation of the system. Life cycle cost (LCC) and levelized cost of energy (LCE) are treated as the economic criteria. The two variants of the proposed PSO method, referred to as adaptive weights PSO ( A W P S O c f ) and sigmoid function PSO ( S F P S O c f ) , are implemented using MATLAB software to the optimize the number of PV modules in (series and parallel) and number of the storage battery. The case study of the proposed SAPV system is executed using the hourly meteorological data and typical load demand for one year in a rural area in Malaysia. The performance outcomes of the proposed A W / S F P S O c f methods give various configurations at desired levels of LLP values and the corresponding minimum cost. The performance results showed the superiority of S F P S O c f in terms of accuracy is selecting an optimal configuration at fitness function value 0.031268, LLP value 0.002431, LCC 53167 USD, and LCE 1.6413 USD. The accuracy of A W / S F P S O c f methods is verified by using the iterative method.

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Components sizing of photovoltaic stand-alone system based on loss of power supply probability

Cited by 90 publications

References 69 publications

A comparative study based on the Genetic Algorithm (GA) method for the optimal sizing of the standalone photovoltaic system in the Ngoundiane site

A comparative study based on the Genetic Algorithm (GA) method for the optimal sizing of the standalone photovoltaic system in the Ngoundiane site

Optimum Design of a Standalone Solar Photovoltaic System Based on Novel Integration of Iterative-PESA-II and AHP-VIKOR Methods

Optimal Design of Standalone Photovoltaic System Based on Multi-Objective Particle Swarm Optimization: A Case Study of Malaysia

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