AI Article Synopsis
- Climate variability impacts both the supply and demand for renewable electricity, affecting system reliability, particularly in Texas where renewable energy sources are widely used.
- The study utilizes a method based on sea surface temperature variations, linked to El Niño-Southern Oscillation (ENSO), to predict wind, solar energy, and heating/cooling demands one to six months ahead.
- Findings indicate significant risks of oversupply or undersupply in energy and unusual heating/cooling demand, depending on ENSO conditions and the time of year, with implications for financial strategies and forecast applications.
Article Abstract
Climate variability influences renewable electricity supply and demand and hence system reliability. Using the hidden states of the sea surface temperature of tropical Pacific Ocean that reflect El Niño-Southern Oscillation (ENSO) dynamics that is objectively identified by a nonhomogeneous hidden Markov model, we provide a first example of the potential predictability of monthly wind and solar energy and heating and cooling energy demand for 1 to 6 months ahead for Texas, United States, a region that has a high penetration of renewable electricity and is susceptible to disruption by climate-driven supply-demand imbalances. We find a statistically significant potential for oversupply or undersupply of energy and anomalous heating/cooling demand depending on the ENSO state and the calendar month. Implications for financial securitization and the potential application of forecasts are discussed.
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|---|---|
| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11529720 | PMC |
| http://dx.doi.org/10.1126/sciadv.ado3517 | DOI Listing |
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