Accounting for extreme weather to boost energy system reliability
A computer model that factors in extreme weather events offers insights to improve the design of NEOM’s integrated renewable power, water and heating sectors.
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Saudi Arabia’s government aims to generate more than half of the country’s electricity from renewable sources by 2030. This goal is particularly pertinent in the NEOM region, where an ambitious large-scale project is underway to build a community powered entirely by renewable energy sources.
KAUST researchers have developed a clustering-optimization model that could help to design an integrated multisector energy system for NEOM. Crucially, their model factors in days when weather conditions are such that the demand for total electricity becomes extreme in that part of the world. For example, when limited solar irradiation or no wind means the system comes close to being unable to supply the required electricity.
“Existing optimization models use weather input data, but usually ignore outliers, which is unhelpful when it comes to determining reliability in renewable power generation,” says Ricardo Lima at KAUST. Lima worked on the project with colleagues including Jefferson Riera and Justin Ezekiel, under the supervision of KAUST faculty members Omar Knio and Martin Mai.
“The inherent intermittency of wind and solar power means that it is vital to factor in weather pattern variability, including extreme events,” continues Lima. “Integrating renewable technologies across sectors is another important consideration. We took a novel multisector approach to optimize the proposed system.”
The researchers used past weather data (2008-2018) from the NEOM region in their model. Their approach incorporates the interactions between electricity generation, water desalination and heating generation, allowing for the exchange of information about demand and generation throughout the system.
