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dc.contributor.authorAbokersh, Mohamed Hany
dc.contributor.authorSaikia, Kangkana
dc.contributor.authorCabeza, Luisa F.
dc.contributor.authorBoer, Dieter
dc.contributor.authorVallès Rasquera, J. Manel
dc.description.abstractThe movement toward the 4th generation district heating (4GDH) embraces a great opportunity to support the future smart energy development concept. However, its development calls for addressing technological and economic obstacles aligning with the need for a reformation of the energy market to ensure the quality of service. In this context, our paper presents a comprehensive analysis based on a multi-objective optimization framework incorporating an artificial neural network-based model for the possibility of integrating heat pump (HP) into solar assisted district heating system (SDHS) with seasonal thermal energy storage to support the sustainable transition toward 4GDH. The study evaluates the performance of the proposed system with the help of key performance indicators (KPI) related to the 4GDH characteristics and key stakeholders for possible market growth with consideration for the environmental benefits. The proposed analysis is applied to a small neighbourhood of 10 residential buildings located in Madrid (Spain) to investigate the optimal integration of HP under different control strategies into a SDHS. Inherent the SDHS operator perspective, the results reveal a significant improvement in the stabilization of the SDHS performance due to the HP integration where the solar field temperature never exceeds 80 ◦C, and the seasonal storage tank (SST) temperature stands at 85.4 ◦C. In addition, the share of solar energy stands above 86.1% with an efficiency of 73.9% for the SST, while the seasonal HP performance factor stands above 5.5 for all optimal scenarios. From the investor viewpoint, an energy price of 59.1 Euro/MWh can be achieved for the proposed system with a payback period of 26 years. Finally, from the policymaker perspective, along with the significant economic and sustainable improvement in the SDHS performance, a substantial environmental improvement of 82.5% is achieved when compared to the conventional boiler heating system. The proposed analysis reflects a great motivation for different stakeholders to propose this system as a path toward the 4GDH in the future district energy systems.
dc.description.sponsorshipThe work is funded by the Spanish government RTI2018-093849-B-C31 and RTI2018-093849-B-C33. The authors would like to thank the Catalan Government for the quality accreditation given to their research group (GREiA – 2017 SGR 1537, AGACAPE – 2017 SGR 1409). GREiA is a certified agent TECNIO in the category of technology developers from the Government of Catalonia. This work is partially supported by ICREA under the ICREA Academia programme. This work is partially funded by the Ministerio de Ciencia, Innovación y Universidades – Agencia Estatal de Investigación (AEI) (RED2018-102431-T). This project has received funding from the European Union's Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No. 713679 and from the Universitat Rovira i Virgili (URV).
dc.relation.isformatofVersió postprint del document publicat a:
dc.relation.ispartofEnergy Conversion and Management, 2020, vol. 225, p. 113379-1-113379-18
dc.rightscc-by-nc-nd (c) Elsevier, 2020
dc.subjectSolar assist district heating system
dc.subjectHeat pump
dc.subjectArtificial neural network
dc.subjectMulti-objective optimization
dc.subjectKey performance indicators
dc.subject4th generation district heating
dc.titleFlexible heat pump integration to improve sustainable transition toward 4th generation district heating

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cc-by-nc-nd (c) Elsevier, 2020
Except where otherwise noted, this item's license is described as cc-by-nc-nd (c) Elsevier, 2020