Conceived by an international research team, the model can also be utilized for hybrid wind-solar projects. According to its creators, it provides a practical solutions for land-use optimization and renewable energy planning.

A group of researchers led by Saudi Arabia’s King Fahd University of Petroleum & Minerals (KFUPM) has developed a novel spatio-temporal decision-making model for the development of hybrid photovoltaic-wind power plants, as well as individual wind and PV projects, in Saudi Arabia.

“Our new model can identify the optimal locations for utility-scale solar PV, onshore wind farms, and hybrid systems in Saudi Arabia,” the research’s lead author, Mohamed R. Elkadeem, told pv magazine. “Unlike traditional approaches that rely on long-term averaged data or single energy sources, we introduced a novel spatio-temporal decision-making model (STDMM) that leverages the ERA5 hourly reanalysis dataset along with high-accuracy spatial models of over twenty constraints and evaluation criteria. The model provides a practical solution for land-use optimization and renewable energy (RE) planning.”

ERA5 is a reanalysis dataset providing hourly estimates of a large number of atmospheric, land and oceanic climate variables. It can calculate a project’s capacity factor (CF), annual technical potential generation (ATPG), and levelized cost of electricity (LCOE) while also estimating power infrastructure costs.

To identify the best sites for wind and solar deployment, the method uses 1 km² grid-level analysis based on a multi-layered hybrid GIS-Bayesian Best Worst Method (BWM) model, which is a multi-criteria decision-making method to find the optimal weights of a set of criteria based on the preferences of only one decision-maker (DM). An energetic complementarity model is utilized to analyze hybrid wind-solar plants.

“The combination of GIS and Bayesian BWM modeling ensures that site selection is comprehensive and balanced, incorporating expert-driven criteria to optimize decision-making of the site selection process,” the scientists said, noting that ERA5 tends to perform better for solar resource assessments compared to wind resources.

Through the new model, the researchers found that around 32% of the country is suitable for solar energy development and 36% for wind

“The study proposes that approximately 4.81 % of land be allocated for solar projects and 4.74 % for wind projects to meet 50 % of Saudi Arabia’s 2030 energy needs, translating to the development of 95.12 GW of solar PV and 74.45 GW of wind turbines,” the team stated. “Techno-economic analysis reveals solar resources are relatively homogeneous across the country, while wind resources show greater spatial variability, affecting project costs and efficiency.”

Their analysis also showed that the LCOE for solar power ranges between $43/MWh and $78.6/MWh, with the average value reaching $52.6/MWh. As for wind, the LCOE was found to have a wider range from $34.8/MWh to $125/MWh.

The novel methodology was introduced in the study “A spatio-temporal decision-making model for solar, wind, and hybrid systems – A case study of Saudi Arabia,” published in Applied Energy. The research team included academics from Egypt’s Kafrelsheikh University and the Wrocław University of Science and Technology in Poland.

According to the research team, the proposed method could open new markets for renewable energy planning and optimization tools, serving developers, governments, and utility companies in Saudi Arabia. “The model not only reduces costs but also accelerates the efficient installation of utility-scale renewable energy systems, contributing to Saudi Arabia’s goals for 50% renewables share in electricity generation by 2030 and 50% natural gas-fired power generation and reach Net-Zero Emissions by 2060,” Elkadeem said.