Decision support tools for improving land footprint and power generation of a photovoltaic field by the deployment of wind turbines in the same designated area: Eilat district as a case study

Sharon Gat (), Ran Ben-Arie and Adam Liberman-Shalev
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Sharon Gat: Afeka College of Engineering
Ran Ben-Arie: Afeka College of Engineering
Adam Liberman-Shalev: Afeka College of Engineering

Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, 2023, vol. 25, issue 11, No 16, 12495-12526

Abstract: Abstract The deployment of wind turbines in a photovoltaic field resulted in a reduced land footprint and CO2 emissions while increasing power production per unit area. When land is limited, the model optimizes the placement of wind turbines in the PV field while accounting for energy losses owing to the shadow produced by wind turbines on PV modules. The two tools developed provide the decision maker a basis for a tender outlining a 100% renewable energy district’s total area and annual solar/wind power requirements. The entrepreneur tool offers three alternative configurations: PV system, PV/circumferential wind turbine deployment, and fully integrated PV/wind field. The model incorporates storage capacity and GT backup to meet the demand criterion. Levelized cost of energy (LCOE) and CO2 avoidance were key parameters to evaluate the performance of each configuration. The Eilat case study demonstrated a 3.9% decrease in area requirements, improved power generation, and a substantial reduction in CO2 emissions of up to 24%. However, the estimated LCOE is 40–57% higher than the Israel Electric Company standard tariff. Sensitivity analysis shows that an improved wind regime significantly decreases the LCOE (0.08$/kWh). Suggesting that, depending on location, policy reform is required to promote the transition to sustainable energy systems.

Keywords: Wind turbine shadow model; PV/Wind integrated field; PV/Wind hybrid field; PV land footprint (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1007/s10668-022-02576-0

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