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%.
Abstract:The lands in the northernmost corner of Europe present contradictory aspects in their social and economic development. Urban settlements are relatively few and small-sized, but rich natural resources (minerals, forests, rivers) attract energy-intensive industries. Energy demand is increasing as a result of new investments in mining and industries, while reliable energy supply is threatened by the planned phase out of Swedish nuclear power, the growth of intermittent power supplies and the need to reduce fossil fuel consumption, especially in the Finnish and Norwegian energy sectors. Given these challenges, this paper investigates the potentials of so far unexploited energy resources in the northern counties of Finland, Norway and Sweden by comparing and critically analyzing data from statistic databases, governmental reports, official websites, research projects and academic publications. The criteria for the technical and economic definition of potentials are discussed separately for each resource. It is concluded that, despite the factors that reduce the theoretical potentials, significant sustainable techno-economic potentials exist for most of the resources, providing important insights about the possible strategies to contribute to a positive socio-economic development in the considered regions.
The North Bergen, NJ Municipal Utility Authority was the first municipality in New Jersey to fully implement facilities for Solids and Floatables Control under its CSO Permit in April 1999. The MUA implemented a system of nine Netting TrashTrap® systems and one mechanical screen at a cost of $3,318,056 -7% below the construction estimate and 300% below the next least expensive technology alternative evaluated.The MUA has now had three years of Operation and Maintenance experience with these facilities. Operating and maintenance costs have been approximately $57,000 per year, in line with the original estimate. These systems collect approximately 40 tons of floatables and solids per year that would otherwise have entered the receiving waterbodies. This paper presents the background and planning that led to the selection of the type of facilities, their construction costs and financing, the operating requirements and costs, and lessons learned to date. It also looks ahead to how these facilities fit with the Long Term Control Plan required in the next phase of the CSO program and makes suggestions and recommendations for others.
In Nordic environments the cold climate, largescale industries, and a high share of electric heating drive energy consumption and create significant peak electricity demand in municipal energy systems. Prospects for decarbonizing the transport sector by electrification escalate these challenges, while availability and sustainability concerns limit biofuel use. Local authorities are committed to contributing to national climate goals, while considering local objectives for economic development, increased energy self-sufficiency and affordable energy costs. This research combines these goals into a multiobjective optimization problem (MOOP), and solves the MOOP by interfacing the energy systems simulation tool EnergyPLAN with a multi-objective evolutionary algorithm (MOEA) implemented in Matlab. In this way, the study generates optimal solutions for integrated electricity, heating and transport sectors and valuable insights are offered to decision makers in local authorities. Piteå (Norrbotten County, Sweden) is a typical Nordic municipality and serves as a case study for this research.Results show that CO2 emissions from the integrated system can be reduced up to 60% without a considerable increase of total annual costs, and that in the same range of emission reductions it is economically more convenient to invest in electric personal vehicles, light trucks and busses.
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