This study shows the adequacy of power systems that can incorporate renewable energy sources and hydrogen for large-scale power consumption. Using the Analytic Hierarchy Process with a focus on multiple criteria, six grid-scalable energy storage technologies are initially assessed to this end. The most suitable option for grid-scale application is green hydrogen storage technology. Then, an optimization model is developed to advance hydrogen solutions by minimizing the annual cost equivalent to capital and operational expenditures of the systems. The model is used to comprehensively examine the integration and operation of two distinct real-life applications: hybrid power systems that incorporate hydrogen alongside renewable energy sources (i) without natural gas and (ii) with natural gas. In this direction, this study thoroughly examines the crucial role of green hydrogen in achieving a sustainable and clean energy landscape through a multidisciplinary investigation of hydrogen production and storage from a technology management perspective. Through case studies, the practicality of integrating green hydrogen into power systems to meet substantial power demands is shown. By decreasing the systems’ current costs by ∼60% and contributing to an increase in renewable energy penetration, the proposed systems provide cost-effectiveness, carbon reduction potential, and adaptability to existing infrastructure. In response to the imperative to overcome challenges in transitioning to cleaner energy, this research advocates for well-informed decision-making by using the optimization model to attain a robust and ecofriendly energy future.

This paper analyzes the impact of climate change on Turkey’s residential, industrial and commercial electricity demand by applying the Structural Time Series Model. The model consists of explanatory variables and uses annual time series data for the period from 1980 to 2017. The variables included are electricity price, income per capita, urbanization rate, manufacturing added value, population-weighted cooling degree days (as a climate variable) and, finally, stochastic Underlying Energy Demand Trend. The effect of cooling degree days on the residential, industrial and commercial electricity demand is found to be significantly elastic. Moreover, residential, industrial and commercial electricity demands in 2031 are expected to increase considerably, and at different ratios, depending on the chosen climate change scenario. The findings of this study are significant for efforts to establish regulations to shape energy security policies in the presence of climate change.