Long-Term Assessment and Optimization of Wind Energy Potential for Electricity Production along Palestine’s Mediterranean Coast

Abstract

The demand for sustainable and reliable energy sources has intensified the global focus on renewable energy, with wind power emerging as a critical component of low-carbon energy systems. Palestine, particularly along its Mediterranean coast, exhibits promising wind resources, yet systematic, long-term assessments remain scarce. This study presents a comprehensive evaluation of wind energy potential for electricity generation along the Palestinian Mediterranean coast, spanning a 14-year period. The research employs both Weibull and Rayleigh distribution models to characterize wind speed variability, incorporating multiple numerical parameter estimation techniques, including maximum likelihood, method of moments, and least squares regression, to enhance the accuracy and robustness of wind power density calculations (Pishgar-Komleh, 2015; Mohammadi & Mostafaeipour, 2013). Historical wind datasets obtained from the Palestinian Energy and Natural Resources Authority and satellite-derived measurements are analyzed to quantify temporal and seasonal variability, identify prevailing wind patterns, and assess long-term trends in wind resource availability (Data Source, 2019; Data_source_google_earth).
The study further investigates optimal placement and configuration of wind turbines, evaluating the potential electricity output under varying design and operational scenarios. Comparative analysis of numerical methods demonstrates significant differences in Weibull parameter estimation, which in turn affects power density predictions and energy yield optimization (Arslan et al., 2014; Andrade et al., 2014). The results reveal that the Mediterranean coast exhibits high wind energy potential during the winter and transitional seasons, with power densities capable of supporting medium- to large-scale wind farm deployment. Additionally, the study highlights the importance of integrating site-specific wind characteristics with statistical modeling to minimize uncertainty in energy projections, thereby facilitating more effective renewable energy planning and investment decision-making (Badawi, 2013; Albuhairi, 2006).
The findings of this research have practical implications for policymakers, grid operators, and renewable energy developers seeking to enhance energy security, reduce dependence on imported fossil fuels, and contribute to Palestine’s sustainable energy transition. By providing a long-term, data-driven framework for assessing wind energy resources and optimizing turbine deployment, this study contributes to the advancement of scientific methodologies in wind energy research and offers a replicable approach for regions with similar coastal wind regimes. The research underscores the critical role of long-term statistical analysis in identifying reliable renewable energy resources, optimizing system efficiency, and supporting the strategic integration of wind power into national electricity grids.