Abstract In this study, an interval-fuzzy full-infinite programming (IFFIP) method is developed for planning regional energy system (RES) under multiple uncertainties. IFFIP extends upon the existing full-infinite programming (FIP) by allowing uncertainties expressed as crisp intervals, functional intervals and dual-functional intervals to be effectively incorporated within a general framework. Then, an IFFIP-RES model is formulated for planning RES of Hebei province (China) through considering energy transitions in industrial, transport, and residential sectors. Scenarios related to coal/oil reduction and electricity/nature gas growth in final energy demand are designed to evaluate the impact of final energy substitution on RES. The results reveal that (i) final energy substitution would bring about 7.0% increase in clean energy (including nature gas and renewable energy) and 8.9% reduction in coal over the planning horizon; (ii) electricity demand would increase 38.4% with final energy substitution, and the increased electricity would be converted by coal (57.2%) and renewable resources (26.1%); (iii) pollutants (including sulfur dioxide, nitrogen oxide, and particulate matter) from RES would reduce 20.1%; pollutants discharged from industrial, transport and residential sectors would decrease 32.6%, 39.9% and 62.1%, respectively; (iv) nature gas demand would raise rapidly with the energy substitution, and the proportion of imported nature gas would reach up to 97.4%. The results can help the local government explore the relationship among energy transition, electricity generation, as well as environmental emission mitigation under multiple uncertainties, and identify desired policies for RES to achieve cleaner production and sustainable development.