{"query_echo":{"q":"","filters":{"analysis_type":["computational modelling"]},"warnings":[{"code":"facet_value_not_in_vocabulary","message":"Value 'computational modelling' for facet 'analysis_type' is not in the controlled vocabulary."}]},"total":{"value":1,"relation":"eq"},"page":1,"page_size":20,"self":"https://climateinsightsdirectory.org/api/v1/search?analysis_type=computational+modelling","stability":"beta","ai_marking":{"digital_source_type":{"uri":"http://cv.iptc.org/newscodes/digitalsourcetype/trainedAlgorithmicMedia","name":"Created using Generative AI"},"notice":"Summary and key insights are generated using artificial intelligence."},"results":[{"id":"sei-002059","url":"https://climateinsightsdirectory.org/document/sei-002059","title":"Framework for Decentralized Energy Resilience in Islands","publisher":{"name":"Stockholm Environment Institute","organization":"stockholm-environment-institute"},"document_type":"policy brief","language":"en","date_published":"2024-12-05","source_url":"https://www.sei.org/publications/framework-decentralized-energy-resilience-islands/","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","climate_tags","geography_discussed","analysis_type"],"summary":{"text":"The document introduces a novel five-step modelling framework designed to identify power infrastructure vulnerabilities and design cost-optimal decentralized renewable energy (DRE) solutions for islands and low-lying states. The framework involves identifying disruption hotspots, assessing disruptive potential, designing DRE systems using HOMER Pro, integrating local contextual factors, and evaluating resilience improvements. Testing the framework in Cuba revealed that municipalities with high electricity demand from industries and large buildings are most vulnerable to single-point failures. The results demonstrate that while DRE systems—incorporating solar PV, wind, battery storage, and biomass—improve power supply continuity, their effectiveness and cost are heavily influenced by local contexts, such as the US embargo on Cuba, which increased capital investment costs by 5-40% compared to global scenarios.","ai_generated":true,"unit":"sei-002059#summary","date_modified":"2026-10-23"},"key_insights":[{"text":"The proposed five-step framework enables island states to identify critical network nodes and design decentralized renewable energy (DRE) systems to prevent cascading power failures. The process involves: 1) identifying hotspots via network centrality metrics; 2) assessing disruptive potential by simulating node removal; 3) designing cost-optimal solutions using HOMER Pro; 4) integrating local contextual factors; and 5) evaluating resilience by comparing power supply during disruptive events.","ai_generated":true,"unit":"sei-002059#insight-1","date_modified":"2026-10-23"},{"text":"Application of the framework in Cuba identified that the city of Havana is a major center of vulnerability, containing seven of the ten municipalities with the highest disruption potential. Specifically, areas with high concentrations of electricity demand from industries and large buildings are more susceptible to single-point power system failures.","ai_generated":true,"unit":"sei-002059#insight-2","date_modified":"2026-10-23"},{"text":"Contextual factors significantly impact the cost and feasibility of DRE systems. In Cuba, the US embargo leads to higher investment costs and limited technology access; capital investment costs for DRE systems in the 'Cuban scenario' were approximately 5-40% higher than in the 'global scenario'.","ai_generated":true,"unit":"sei-002059#insight-3","date_modified":"2026-10-23"},{"text":"DRE solutions, particularly ancillary systems (AS), enhance power system resilience by maintaining a more continuous supply during disruptions. In the tested scenarios, supplied loads during disruptive events were up to 66% higher for AS1 (global scenario) and 56% higher for AS2 (Cuban scenario) compared to everyday operations.","ai_generated":true,"unit":"sei-002059#insight-4","date_modified":"2026-10-23"}],"climate_tags":["Resilience (power system)","photovoltaics","wind power","battery energy storage system","energy security"],"geography_discussed":["Cuba","Havana","Regla"],"frame_perspective":[],"analysis_type":["framework development","case study","computational modelling"]}]}