Towards the EU Emission Targets of 2050: Cost-Effective Emission Reduction in Finnish Detached Houses

Hirvonen, Janne; Jokisalo, Juha; Heljo, Juhani; Kosonen, Risto

doi:10.3390/en12224395

Cited by 34 publications

(59 citation statements)

References 35 publications

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“…Significant changes in both district heating and electrical power levels were realized with energy retrofits in all the building age categories. In the previous study [13], it was found that switching to electrified heating resulted in significant emission reductions, when monthly average emission factors of Finnish electricity generation were used. However, as the number of retrofitted buildings goes up, the changes in consumption patterns start to influence the national grid.…”

Section: Effect On Building Stockmentioning

confidence: 98%

“…Finally, a few optimally retrofitted building configurations were selected for further study. The calculations are based on previous simulation work of the authors [13], where Finnish single-family houses of various ages were retrofitted to reduce emissions.…”

Section: Simulation and Optimizationmentioning

confidence: 99%

“…This is the average power of the 5% of weekly hours (8 h) with the highest (or lowest) demand. [13]. For ground-source heat pump (GSHP) capacity, the number in parentheses is the ratio of HP thermal capacity to the maximum space heating demand.…”

Section: Buildings With District Heatingmentioning

confidence: 99%

“…To estimate the potential influence of retrofits on a larger scale, assumptions about the retrofit levels were made in reference [13]. Of buildings that use wood or oil boilers for heating, 50% switch to GSHP and the other 50% switch to or keep using a wood boiler, while also doing other improvements.…”

Section: Effect On Building Stockmentioning

confidence: 99%

“…In Finnish office buildings CO 2 emissions could be cost-effectively reduced by 50% while preserving thermal comfort [12]. In Finnish detached houses [13] life cycle costs and CO 2 emissions could be most effectively lowered by deep energy retrofits in buildings with direct electric or oil-based heating. In these studies, dynamic simulation with IDA-ICE was combined with multi-objective optimization by a genetic algorithm, to go through hundreds of retrofit packages.…”

Section: Introductionmentioning

confidence: 99%

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The Effect of Deep Energy Retrofit on The Hourly Power Demand of Finnish Detached Houses

2020

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This study examines how the energy renovation of old detached houses affects the hourly power consumption of heating and electricity in Finland. As electrification of heating through heat pumps becomes more common, the effects on the grid need to be quantified. Increased fluctuation and peak power demand could increase the need for fossil-based peaking power plants or call for new investments to the distribution infrastructure. The novelty in this study is the focus on hourly power demand instead of just annual energy consumption. Identifying the influence of building energy retrofits on the instantaneous power demand can help guide policy and investments into building retrofits and related technology. The work was done through dynamic building simulation and utilized building configurations obtained through multi-objective optimization. Deep energy retrofits decreased both the total and peak heating power consumption. However, the use of air-source heat pumps increased the peak power demand of electricity in district heated and wood heated buildings by as much as 100%. On the other hand, peak power demand in buildings with direct electric heating was reduced by 30 to 40%. On the building stock level, the demand reduction in buildings with direct electric heating could compensate for the increase in the share of buildings with ground-source heat pumps, so that the national peak electricity demand would not increase. This prevents the increase of demand for high emission peaking power plants as heat pump penetration rises. However, a use is needed for the excess solar electricity generated by the optimally retrofitted buildings, because much of the solar electricity cannot be utilized in the single-family houses during summer.

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Section: Effect On Building Stockmentioning

confidence: 98%

Section: Simulation and Optimizationmentioning

confidence: 99%

Section: Buildings With District Heatingmentioning

confidence: 99%

Section: Effect On Building Stockmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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The Effect of Deep Energy Retrofit on The Hourly Power Demand of Finnish Detached Houses

2020

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Carbon emissions index decomposition and carbon emissions prediction in Xinjiang from the perspective of population-related factors, based on the combination of STIRPAT model and neural network

Ziyuan

Yibo

Simayi

et al. 2022

Environ Sci Pollut Res

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In the present study, the STIRPAT model was adopted to examine the impacts of several factors on dioxide emissions using the time series data from 2000 to 2019 in Xinjiang. The said factors included population aging, urbanization, household size, per capita GDP, number of vehicles, per capita mutton consumption, education level, and household direct energy consumption structure. Findings were made that the positive effects of urbanization, per capita GDP, per capita mutton consumption and education on carbon emissions were obvious; the number of vehicles had the biggest positive impact on carbon dioxide emissions; and household size and household direct energy consumption structure had a significantly negative impact on carbon emissions. Based on the aforementioned findings, the GA-BP neural network was introduced to predict the carbon emission trend of Xinjiang in 2020–2050. The results reveal that the peak time of the low-carbon scenario was the earliest, between 2029 and 2033. The peak time of the middle scenario was later than low-carbon scenario, between 2032 and 2037, while the peak time of the high-carbon scenario was the latest and was unlikely to reach the peak before 2050.

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TVP-VAR based time and frequency domain food & energy commodities connectedness an analysis for financial/geopolitical turmoil episodes

Polat,

Ertuğrul,

Sakarya

et al. 2024

Applied Energy

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Towards the EU Emission Targets of 2050: Cost-Effective Emission Reduction in Finnish Detached Houses

Cited by 34 publications

References 35 publications

The Effect of Deep Energy Retrofit on The Hourly Power Demand of Finnish Detached Houses

The Effect of Deep Energy Retrofit on The Hourly Power Demand of Finnish Detached Houses

Carbon emissions index decomposition and carbon emissions prediction in Xinjiang from the perspective of population-related factors, based on the combination of STIRPAT model and neural network

TVP-VAR based time and frequency domain food & energy commodities connectedness an analysis for financial/geopolitical turmoil episodes

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