Bygnings Energi Flexibilitet: Sensitivitets Analyse og Sammenligning af Nøgleindikatorer
Studenteropgave: Kandidatspeciale og HD afgangsprojekt
- John Ellingsgaard
4. semester, Bygningers Energidesign, Kandidat (Kandidatuddannelse)
This thesis has two objectives, the first is to analyze the impact of insulation level, thermal
mass, type of heating system, control strategy, outdoor temperature, solar radiation and type of
building (office or single family house), on the flexibility function and the two key performance
indicators developed by IEA EBC Annex 67. This sensitivity analysis is based on raw data from
6 case studies, and to assess the influence on the different parameters, ANOVA tests are used.
The results are then ranked according to their influence on the different flexibility characteristics
and key performance indicators. Furthermore, another sensitivity analysis is performed to more
specifically analyze the impact of insulation level, thermal mass, heating system and control
strategy on the flexibility characteristics.
The results showed that insulation level has the largest influence on all the flexibility
characteristics and key performance indicators, except the total time of increased energy demand.
Thermal mass is also found to have a significant influence on the flexibility characteristics,
especially on low insulated building.
The validity of the sensitivity analysis results on the total time of increase/decrease energy
demand are questionable. Based on analysis and result from other studies, the ranking order
should be different. Insulation level and thermal mass should be the parameters that have the
largest influence.
The results also showed that only insulation level has an influence on the cost/savings by applying
flexibility. This can be more related to the decrease of energy consumption from a low insulated
to a high insulated building.
The second objective of this thesis is so analyze and compare different key performance indicators
to the ones developed by IEA EBC Annex 67. For comparison, a graph with results from both
the respective and key performance indicators developed by IEA EBC Annex 67 is used. In total,
11 key performance indicators were analyzed, and it was found that they can be categorized into
four categories.
The comparison showed that 8 of the 11 analyzed key performance indicators were either
comparable to shifted flexible load or efficiency of flexible operation, or, if only considering
the KPIs that can assess the flexibility potential on a yearly basis, 8 of the 9 analyzed key
performance indicators were comparable to the IEA EBC Annex 67 key performance indicators.
mass, type of heating system, control strategy, outdoor temperature, solar radiation and type of
building (office or single family house), on the flexibility function and the two key performance
indicators developed by IEA EBC Annex 67. This sensitivity analysis is based on raw data from
6 case studies, and to assess the influence on the different parameters, ANOVA tests are used.
The results are then ranked according to their influence on the different flexibility characteristics
and key performance indicators. Furthermore, another sensitivity analysis is performed to more
specifically analyze the impact of insulation level, thermal mass, heating system and control
strategy on the flexibility characteristics.
The results showed that insulation level has the largest influence on all the flexibility
characteristics and key performance indicators, except the total time of increased energy demand.
Thermal mass is also found to have a significant influence on the flexibility characteristics,
especially on low insulated building.
The validity of the sensitivity analysis results on the total time of increase/decrease energy
demand are questionable. Based on analysis and result from other studies, the ranking order
should be different. Insulation level and thermal mass should be the parameters that have the
largest influence.
The results also showed that only insulation level has an influence on the cost/savings by applying
flexibility. This can be more related to the decrease of energy consumption from a low insulated
to a high insulated building.
The second objective of this thesis is so analyze and compare different key performance indicators
to the ones developed by IEA EBC Annex 67. For comparison, a graph with results from both
the respective and key performance indicators developed by IEA EBC Annex 67 is used. In total,
11 key performance indicators were analyzed, and it was found that they can be categorized into
four categories.
The comparison showed that 8 of the 11 analyzed key performance indicators were either
comparable to shifted flexible load or efficiency of flexible operation, or, if only considering
the KPIs that can assess the flexibility potential on a yearly basis, 8 of the 9 analyzed key
performance indicators were comparable to the IEA EBC Annex 67 key performance indicators.
Sprog | Engelsk |
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Udgivelsesdato | 28 jan. 2019 |
Antal sider | 92 |