This paper presents an analysis of energy use and sector coupling in a local energy community using a model based on energy cost centres (ECCs), functional units for decentralised responsibility and optimisation of energy use within defined system boundaries. The ECC model enables structured identification and optimisation of energy and material flows in complex industrial and urban settings. It was applied to a case study involving an energy-intensive steel plant and its integration with the surrounding community. The study assessed the potential for renewable electricity production (7914 MWh annually), green hydrogen generation, battery storage, and the reuse of 11,440 MWh of excess heat. These measures could offset 9598 MWh of grid electricity through local production and savings, reduce natural gas use by 4,116,850 Nm³, and lower CO₂ emissions by 10,984 tonnes per year. The model supports strategic planning by linking sectoral actions to measurable sustainability indicators. It is adaptable to data availability and stakeholder engagement, allowing both high-level overviews and detailed analysis of selected ECCs. Limitations include heterogeneous data sources, uneven stakeholder participation, and the need for refinement of sub-models. Nonetheless, the approach offers a replicable framework for integrated energy planning and supports the transition to sustainable, decentralised energy systems.

The integration of energy sectors and the optimisation of resource use are fundamental elements of sustainable development. This study presents a model for analysing energy use based on the structure of Energy Cost Centres (ECCs). The model facilitates a systematic identification and optimisation of energy flows in industrial and urban environments. The developed methodology was tested on a case study of an energy-intensive industry, where we analysed the potential utilisation of renewable energy sources, hydrogen production, electricity storage, and the use of excess heat for the local community. The results indicate that the systematic application of the model could achieve total electricity savings of 9,598 MWh, alongside 4,116,850 Nm³ of natural gas savings through excess heat utilisation. These measures collectively contribute to an annual CO₂ emissions reduction of 10,984 tonnes. The approach enhances the integration of sustainable energy solutions, strengthens stakeholder collaboration, and increases the economic viability of projects. Moreover, the model can be adapted for use in other industrial and urban settings. Despite potential barriers such as data availability and initial implementation costs, the results confirm the approach´s value in the strategic planning of sustainable energy systems.

National energy planning increasingly needs to account for climate risks, yet adaptation priorities in National Energy and Climate Plans (NECPs) often remain too generic to guide infrastructure, regulatory, and investment decisions. This paper develops a policy-facing framework for translating energy sector climate risk evidence into ranked adaptation priorities. The framework decomposes the national energy system into supply chains and aggregate element types, combines stakeholder-derived system importance weights with multi-hazard exposure and vulnerability scores, and derives a relative impact ranking. Exposure is represented through hazard magnitude, frequency, and spatial prevalence, while vulnerability is assessed through expert-based sensitivity and adaptive capacity scores. The framework is demonstrated for Slovenia, covering electricity, gas, liquid fuels, solid fuels, and district heat as part of the country’s first national sectoral climate vulnerability and risk assessment for energy. The results identify electricity transmission and distribution networks, liquid fuel import and logistics infrastructure, gas imports and transmission, and selected storage and conversion assets as priority areas. In the RCP8.5 climate stress case, exposure rises substantially for floods, heat, landslides, and wildfires. Monte Carlo robustness checks indicate that the core set of high-priority element types remains stable. The paper contributes a system-wide screening approach for integrating climate risk knowledge into climate-resilient energy planning, adaptable to different national contexts.