<HashMap><database>biostudies-literature</database><scores/><additional><omics_type>Unknown</omics_type><volume>10(44)</volume><submitter>Zhang M</submitter><pubmed_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 m</pubmed_abstract><journal>Science advances</journal><pagination>eado3517</pagination><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/S-EPMC11529720</full_dataset_link><repository>biostudies-literature</repository><pubmed_title>Potential climate predictability of renewable energy supply and demand for Texas given the ENSO hidden state.</pubmed_title><pmcid>PMC11529720</pmcid><pubmed_authors>Amonkar Y</pubmed_authors><pubmed_authors>Yan L</pubmed_authors><pubmed_authors>Nayak A</pubmed_authors><pubmed_authors>Lall U</pubmed_authors><pubmed_authors>Zhang M</pubmed_authors></additional><is_claimable>false</is_claimable><name>Potential climate predictability of renewable energy supply and demand for Texas given the ENSO hidden state.</name><description>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 m</description><dates><release>2024-01-01T00:00:00Z</release><publication>2024 Nov</publication><modification>2025-04-26T17:02:40.128Z</modification><creation>2025-04-06T15:23:52.425Z</creation></dates><accession>S-EPMC11529720</accession><cross_references><pubmed>39485843</pubmed><doi>10.1126/sciadv.ado3517</doi></cross_references></HashMap>