Geoinformation support for energy resource planning and accounting in communities as a tool for improving energy efficiency and ensuring sustainable development

The article defines the methodological principles of geoinformation support for planning and accounting of energy resources at the level of territorial communities. It proposes the integration of spatial datasets, digital registers of municipal infrastructure, operational monitoring systems and analytical management tools. The capabilities of geoinformation platforms during the inventory of facilities, recording energy resource losses and preparing investment projects are analysed separately. The aim of the work is todevelopan applied model of the use of geoinformation technologies in the planning, monitoring and accounting of energy resources at the community level. Attention is paid to combining information on consumption volumes, the state of engineering networks, local generation reserves and the probability of emergency situations. The study is based on current regulations, official statistics, open geospatial materials, technical characteristics of networks and registers of municipal facilities. The methodological part includes system analysis, spatial modelling, economic prioritisation of measures, scenario calculations and comparative assessment of management options in the field of energy consumption. The authors argue for the need toestablish a unifieddigital database of energy resources of a territorial community. The article presents tools for visualising areas with excessive consumption, calculating technical losses in networks and determining sites for placing solar, wind and bioenergy installations. A method for selecting investment projects is proposed, considering the payback period, technical accessibility and environmental impact. The effectiveness of combining a geographic information system with remote reading meters and a local geoportal is proven.The development of digital twins of municipal infrastructure is considered a promising direction for further research.It is also advisable to explore the possibilities of artificial intelligence in predicting energy loads. An important task remains the creation of industry standards for the exchange of spatial data.Received: 06.05.2026;Accepted: 16.06.2026;