Economic valuation of heat pumps and electric boilers in the Danish energy system

Maria Grønnegaard Nielsen, Juan Miguel Morales González, Marco Zugno, Thomas Engberg Pedersen, Henrik Madsen

Research output: Contribution to journalJournal articleResearchpeer-review


Heat pumps (HP) and electric immersion boilers (EB) have great potential to increase flexibility in energy systems. In parallel, decreasing taxes on electricity-based heat production are creating a more favorable economic environment for the deployment of these units in Denmark. In this paper, the economic value of heat pumps and electric boilers is assessed by simulating their day-to-day market performance using a novel operational strategy based on two-stage stochastic programming. This stochastic model is employed to optimize jointly the daily operation of HPs and EBs along with the Combined Heat and Power (CHP) units in the system. Uncertainty in the heat demand and power price is modeled via scenarios representing different plausible paths for their future evolution. A series of case-studies are performed using real-world data for the heat and power systems in the Copenhagen area during four representative weeks of 2013. We show that the use of stochastic operational models is critical, as standard deterministic models provide an overestimation of the added benefits from the installation of HPs and EBs, thus leading to over-investment in capacity. Furthermore, we perform sensitivity studies to investigate the effect on market performance of varying capacity and efficiency for these units, as well as of different levels of prices in the electricity market. We find that these parameters substantially affect the profitability of heat pumps and electric boilers, hence, they must be carefully assessed by potential investors.
Original languageEnglish
JournalApplied Energy
Pages (from-to)189–200
Number of pages12
Publication statusPublished - 2016


  • Heat marke
  • Electricity market
  • Heat pump
  • Electric boiler
  • Combined heat and power
  • Stochastic programming


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