Performance Analysis of a Semi-Virtual Renewable Energy System and Building Operation

Minyan Lu, Simo Kilpeläinen, Sunliang Cao, Ala Hasan, Shuqin Chen

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review


This paper describes the composition and operation of a semi-virtual energy system and building emulator. The research is part of a joint project between VTT Technical Research Centre of Finland and Aalto University funded by the Academy of Finland.

The system consists of a real part for energy production (PV panels, micro-wind turbine and solar thermal collectors), storage (battery pack and hot water storage tanks) and conversion (ground-source heat pump GSHP and electric heater) combined with a virtual part that models a single-family house in the computer simulation program TRNSYS. A Labview program is used to communicate between the real part and the virtual part.

In this paper, measurement data from six selected studied periods in each month in September 2015 to February 2016 are analysed. The data indicates that during the studied period, the electricity consumption was 1290 kWh, divided to 44/38/18 % between household appliances, GSHP and electric heater, respectively. The local net production was 250 kWh, or 19 % of the demand. 54% of the production came from PV, which was heavily concentrated in September and October. Wind production was winter-centred.

Two indices are used to represent the electrical energy matching aspects of the system: OEFe (on-site electrical energy fraction), the fraction of the building electrical demand covered by local production, and OEMe (on-site electrical energy matching), the ratio of the building’s self-consumption to the total local production. It is found that the matching capability of the energy system is poor, which is due to daily and seasonal mismatches between production and demand. The small net production compared to demand leads to small OEFe and large OEMe values overall. OEFe exhibits strong daily/nightly trends in September and October due to the PV production. OEME is mostly unity except for short times when it drops around noon when PV production is at highest. In wind-dominated winter months, the day/night trends of the indices are not so visible.
Original languageEnglish
Title of host publicationProceedings of SET 2017 International Conference
PublisherUniversita di Bologna
Number of pages10
ISBN (Print)979-12-200-2203-3
Publication statusPublished - 24 Jul 2017
MoE publication typeA4 Article in a conference publication
EventInternational Conference on Sustainable Energy Technologies - Università di Bologna, School of Engineering and Architecture, Bologna, Italy
Duration: 17 Jul 201720 Jul 2017
Conference number: 16


ConferenceInternational Conference on Sustainable Energy Technologies
Abbreviated titleSET
Internet address


  • Nearly zero-energy building
  • Renewables
  • Energy matching
  • Building emulation


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