A review on sizing methodologies of photovoltaic array and storage battery in a standalone photovoltaic system

Khatib, Tamer; Ibrahim, Ibrahim A.; Mohamed, Azah

doi:10.1016/j.enconman.2016.05.011

Cited by 218 publications

(124 citation statements)

References 77 publications

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“…To avoid system economic losses while providing charging at a fixed price, it is crucial to determine the optimum size of the ESU and PV array. There are several approaches that can be taken for this purpose, as elaborated in the previous studies . Although these approaches are widely used for power system sizing, the concept can be used as the guidelines in choosing the appropriate methodology for the proposed charging system.…”

Section: The System Sizing Approachesmentioning

confidence: 99%

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Optimized sizing of photovoltaic grid‐connected electric vehicle charging system using particle swarm optimization

et al. 2018

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Summary In this paper, the particle swarm optimization (PSO) is used to find optimum size of the photovoltaic (PV) array and energy storage unit (ESU) for PV grid‐connected charging system (in office workplace) for electric vehicles (EV). It is designed in such a way that the EVs are charged at a fixed price (rather than time‐of‐use price) without incurring economic losses to the station owner. The simulation is modeled using the single diode model (for PV) and the state of charge of Li‐ion battery (for ESU and EV). The objective function of the PSO is formulated based on a financial model that comprises of the grid tariff, EV demand, and the purchasing as well as selling prices of the energy from PV and ESU. By integrating the financial model with energy management algorithm (EMA), the PSO computes the minimum number of PV modules (Npv) and ESU batteries (Nbat) for a various number of vehicles and office holidays. The resiliency of the proposed system is validated under different weather conditions, EV fleet, parity levels, energy prices, and operating period. Furthermore, the performance of the proposed system is compared with the standard grid charging system. The results suggest that with the computed Npv and Nbat, the charging price is decreased by approximately 16%, while the EV charging burden on the grid is reduced by 94% to 99%. It is envisaged that this work provides the guidance for the installers to precisely determine the optimum size of the components prior to the physical construction of the charging station.

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Section: The System Sizing Approachesmentioning

confidence: 99%

“…Since the PV‐ESU grid charging concept is relatively new, there are limited literature that discuss the component (PV and ESU) sizing and its effects on the utility grid and EV users . Majority of the present and past works deal with the grid charging only.…”

Section: Introductionmentioning

confidence: 99%

Optimized sizing of photovoltaic grid‐connected electric vehicle charging system using particle swarm optimization

et al. 2018

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“…HOMER, HYBRID2, HOGA, and PHOTOV-III are the most widely used commercial software [8]. In SAPV designs, meteorological data and load demand values can be used by considering daily or monthly averages [1,9]. In this section, the path that is followed in sizing and determining the cost of all the equipment that makes up the designed SAPV system is explained.…”

Section: Methodsmentioning

confidence: 99%

“…Because of these reasons, PV systems with a quick settling time, long life, and lower risk of failure are preferred. SAPV systems typically have installed powers between 0.5 kW and 20 kW [1]. They can supply loads such as rural homes, homes or surveillance centers for various purposes in forested areas, telecom radar stations, irrigation pumps, and lighting devices.…”

Section: Introductionmentioning

confidence: 99%

Comparison of Turkey’s Geographical Regions in terms of Stand-Alone PV System Design and Cost Parameters

Onat

2017

International Journal of Photoenergy

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Stand-alone photovoltaic (SAPV) systems are widely used in rural areas where there is no national grid or as a precaution against power outages. In this study, technical and economic analysis of a SAPV system was carried out using meteorological data for 75 province centers in seven geographical regions of Turkey. Obtained results for each province center were separated by geographical area. The averages of the centers for each region are taken as output. A calculation algorithm based on MsExcel has been established for these operations. The analyses made with the developed algorithm are repeated for five different scenarios that they cover periods of time when a constant strong load is active for all seasons (winter, spring, summer, and autumn) and all year round. The developed algorithm calculates the life-cycle cost, the unit energy cost, the electrical capacity utilization rate, the amount of generated/excess energy per month, the initial investment/replacement, and operating and maintenance (O&M) costs of each element. As a result, geographical regions of Turkey are compared in terms of these outputs graphically. Further investigations may include the sale of excess energy generated, small-scale PV system cost factors parallel to the grid, and the effects of government incentives.

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“…However, the drawback of standalone PV systems is the high capital cost as compared with conventional energy sources. To reduce the capital cost, an optimal sizing process of a standalone PV system is necessary so as to achieve a relatively reliable system at minimum cost [2]. Standalone PV system size depends on meteorological variables, such as solar radiation and ambient temperature.…”

Section: Introductionmentioning

confidence: 99%

Impact of Battery’s Model Accuracy on Size Optimization Process of a Standalone Photovoltaic System

Ibrahim

Khatib

Mohamed³

2016

Sustainability

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This paper presents a comparative study between two proposed size optimization methods based on two battery's models. Simple and complex battery models are utilized to optimally size a standalone photovoltaic system. Hourly meteorological data are used in this research for a specific site. Results show that by using the complex model of the battery, the cost of the system is reduced by 31%. In addition, by using the complex battery model, the sizes of the PV array and the battery are reduced by 5.6% and 30%, respectively, as compared to the case which is based on the simple battery model. This shows the importance of utilizing accurate battery models in sizing standalone photovoltaic systems.

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A review on sizing methodologies of photovoltaic array and storage battery in a standalone photovoltaic system

Cited by 218 publications

References 77 publications

Optimized sizing of photovoltaic grid‐connected electric vehicle charging system using particle swarm optimization

Optimized sizing of photovoltaic grid‐connected electric vehicle charging system using particle swarm optimization

Comparison of Turkey’s Geographical Regions in terms of Stand-Alone PV System Design and Cost Parameters

Impact of Battery’s Model Accuracy on Size Optimization Process of a Standalone Photovoltaic System

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