Municipal energy systems in the northern regions of Finland, Norway, and Sweden face multiple challenges: large-scale industries, cold climate, and a high share of electric heating characterize energy consumption and cause significant peak electricity demand. Local authorities are committed in contributing to national goals on CO₂ emission reductions by improving energy efficiency and investing in local renewable electricity generation, while considering their own objectives for economic development, increased energy self-sufficiency, and affordable energy costs. This paper formulates a multi-objective optimization problem about these goals that is solved by interfacing the energy systems simulation tool EnergyPLAN with a multi-objective evolutionary algorithm implemented in Matlab. A sensitivity analysis on some key economic parameters is also performed. In this way, optimal alternatives are identified for the integrated electricity and heating sectors and valuable insights are offered to decision-makers in local authorities. Piteå (Norrbotten, Sweden) is used as a case study that is representative of Nordic municipalities, and results show that CO₂ emissions can be reduced by 60% without a considerable increase in total costs and that peak electricity import can be reduced by a maximum of 38%.