Sizing and Techno-Economic Analysis of Utility-Scale PV Systems with Energy Storage Systems in Factory Buildings: An Application Study

In recent years, PV power plants have been widely used on the roofs of commercial buildings with grid connections, primarily to enhance self-consumption in distributed energy systems. In addition, installing PV plants on commercial buildings’ roofs is becoming increasingly important, especially in crowded cities where land is limited. Since the Sun is an intermittent energy source, PV power plants cause frequency and voltage fluctuations in the grid. The way to avoid this problem is to install PV plants together with battery storage systems. Battery storage systems prevent frequency and voltage fluctuations in the grid and provide economic benefits. This article presents the sizing and techno-economic analysis of a factory building’s rooftop PV system with a battery. The amount of energy produced by the PV plant, PV temperature, and irradiation were recorded in a data logger obtained by various sensors. These real-time measurements were continuously collected and analyzed to evaluate system performance and assess seasonal variations.Load demand data were collected through an automatic meter reading system. The installed capacity of the PV power plant is 645 kW. The optimum battery capacity determined for this factory is 130 kW for 5 h. Techno-economic analysis was carried out using metrics such as the payback period, net present value, and levelized cost of energy. As a result of the analysis using various input variables, LCOE, NPV, and PBP were determined as 0.1467 $/kWh, 4918.3 $, and 7.03 years, respectively.

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Publication Details

Journal
Applied Sciences
Published
2025-04-01
DOI
https://doi.org/10.3390/app15073876
Citations
10
Primary Topic
Smart Grid Energy Management
Type
article
Field-Weighted Citation Impact
7.30
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article

Sizing and Techno-Economic Analysis of Utility-Scale PV Systems with Energy Storage Systems in Factory Buildings: An Application Study

Mahmut Temel Özdemir, Gökay Bayrak, Kıvanç Başaran
10 citations
Applied Sciences
Smart Grid Energy Management
7.30
article

Sizing and Techno-Economic Analysis of Utility-Scale PV Systems with Energy Storage Systems in Factory Buildings: An Application Study

Mahmut Temel Özdemir, Gökay Bayrak, Kıvanç Başaran
article en
10 citations

Abstract

In recent years, PV power plants have been widely used on the roofs of commercial buildings with grid connections, primarily to enhance self-consumption in distributed energy systems. In addition, installing PV plants on commercial buildings’ roofs is becoming increasingly important, especially in crowded cities where land is limited. Since the Sun is an intermittent energy source, PV power plants cause frequency and voltage fluctuations in the grid. The way to avoid this problem is to install PV plants together with battery storage systems. Battery storage systems prevent frequency and voltage fluctuations in the grid and provide economic benefits. This article presents the sizing and techno-economic analysis of a factory building’s rooftop PV system with a battery. The amount of energy produced by the PV plant, PV temperature, and irradiation were recorded in a data logger obtained by various sensors. These real-time measurements were continuously collected and analyzed to evaluate system performance and assess seasonal variations.Load demand data were collected through an automatic meter reading system. The installed capacity of the PV power plant is 645 kW. The optimum battery capacity determined for this factory is 130 kW for 5 h. Techno-economic analysis was carried out using metrics such as the payback period, net present value, and levelized cost of energy. As a result of the analysis using various input variables, LCOE, NPV, and PBP were determined as 0.1467 $/kWh, 4918.3 $, and 7.03 years, respectively.

Applied SciencesVol. 15(7)
Fırat University (TR), Manisa Celal Bayar University (TR), Bursa Technical University (TR), Renewable Energy Systems (United Kingdom) (GB)
Openalex Percentile: Top 3%
Smart Grid Energy Management
7.30
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