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Planning and operation of an integrated energy system in a Swedish building
KTH Royal Inst Technol, Div Energy Proc, SE-10044 Stockholm, Sweden..
Mälardalen University, School of Business, Society and Engineering, Future Energy Center. KTH Royal Inst Technol, Div Energy Proc, SE-10044 Stockholm, Sweden.; Malardalen Univ, Sch Business Soc & Engn, SE-72123 Vasteras, Sweden..ORCID iD: 0000-0002-1351-9245
RISE Res Inst Sweden, Div Safety & Transport Elect, SE-50462 Boras, Sweden..
Tianjin Univ, Sch Environm Sci & Technol, Tianjin 300072, Peoples R China..
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2019 (English)In: Energy Conversion and Management, ISSN 0196-8904, E-ISSN 1879-2227, Vol. 199, article id 111920Article in journal (Refereed) Published
Abstract [en]

More flexibility measures are required due to the increasing capacities of variable renewable energies (VRE). In buildings, the integration of energy supplies forms integrated energy systems (IES). IESs can provide flexibility and increase the VRE penetration level. To upgrade a current building energy system into an IES, several energy conversion and storage components are needed. How to decide the component capacities and operate the IES were investigated separately in studies on system planning and system operation. However, a research gap exists that the system configuration from system planning is not validated by actual operation conditions in system operation. Meanwhile, studies on system operation assume that IES configurations are predetermined. This work combines system planning and system operation. The IES configuration is determined by mixed integer linear programming in system planning. Actual operation conditions and forecast errors are considered in system operation. The actual operation profiles are obtained through year-round simulations of different energy management systems. The results indicate that the system configuration from system planning can meet energy demands in system operation. Among different energy management systems, the combination of robust optimization and receding horizon optimization achieves the lowest yearly operation cost. Meanwhile, two scenarios that represent high and low forecast accuracies are studied. Under the high and low forecast accuracy scenarios, the yearly operation costs are about 4% and 6% higher than that obtained from system planning.

Place, publisher, year, edition, pages
PERGAMON-ELSEVIER SCIENCE LTD , 2019. Vol. 199, article id 111920
Keywords [en]
Building, Integrated energy system, Planning and operation, MILP, Robust optimization
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
URN: urn:nbn:se:mdh:diva-46199DOI: 10.1016/j.enconman.2019.111920ISI: 000494884000016OAI: oai:DiVA.org:mdh-46199DiVA, id: diva2:1373911
Available from: 2019-11-28 Created: 2019-11-28 Last updated: 2019-11-28Bibliographically approved

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Campana, Pietro EliaYan, Jinyue

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