This paper reports a study on how hourly temperature variations of different heat sources influence the seasonal coefficient of performance (SCOP) of heat pumps (HPs) when supplying district heating. The considered heat sources were: groundwater, seawater, air and a combination of the three. The system included HPs, an electric peak load boiler and short-term storage. Linear programming was used to minimize annual electricity consumption of the system. This process also determined the optimum capacities of the HPs using different heat sources. The study was based on data for the area of Copenhagen, Denmark. The results showed that the SCOP of seawater and air HPs, considering heat demand variations, was 11 % and 15 % lower, respectively, than their arithmetic mean performances. For a combination of heat sources, the optimum proportions of HP capacities were: 63 %, 14 % and 23 % for the groundwater, seawater and air HP, respectively. The SCOP of such system was found to be 3 %, 6 % and 11 % greater than the SCOP of a system using the heat sources individually. The results indicate that a maximum system performance may be achieved for HPs based on a combination of different heat sources.
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Excess heat is present in many sectors, and its utilization could reduce the primary energy use and emission of greenhouse gases. This work presents a geographical mapping of excess heat, in which excess heat from the industry and utility sector was distributed to specific geographical locations in Denmark. Based on this mapping, a systematic approach for identifying cases for the utilization of excess heat is proposed, considering the production of district heat and process heat, as well as power generation. The technical and economic feasibility of this approach was evaluated for six cases. Special focus was placed on the challenges for the connection of excess heat sources to heat users. To account for uncertainties in the model input, different methods were applied to determine the uncertainty of the results and the most important model parameters. The results show how the spatial mapping of excess heat sources can be used to identify their utilization potentials. The identified case studies show that it can be economically feasible to connect the heat sources to the public energy network or to use the heat to generate electricity. The uncertainty analysis suggests that the results are indicative and are particularly useful for a fast evaluation, comparison and prioritization of possible matches. The excess heat temperature and obtainable energy price were identified as the most important input parameters.
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