towards optimal sustainable energy systems in nordic municipalities

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ID: 154594
2020
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Abstract
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%.
Reference Key
fischer2020energiestowards Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors ;Robert Fischer;Erik Elfgren;Andrea Toffolo
Journal acs combinatorial science
Year 2020
DOI
10.3390/en13020290
URL
https://www.mdpi.com/1996-1073/13/2/290
Keywords
renewable energy sources multi-objective optimization

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