Time series of heat demand and heat pump efficiency for energy system modeling

Ruhnau, Oliver; Hirth, Lion; Praktiknjo, Aaron

doi:10.1038/s41597-019-0199-y

Cited by 121 publications

(96 citation statements)

References 11 publications

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“…Lifetime expectancy is used to calculate the existing generation and storage unit development towards 2050, which forces part of the decommissioning that takes place in the model. COP time series are based on [72], where missing Nordic countries are assumed to have the same profile as Poland.…”

Section: Biofuelsmentioning

confidence: 99%

“…The national heat demand split across regions is based on electricity demand of each region. Heating demand time series are based on the methodology in [72], using hourly temperature to get heating demand hourly profile over a year. Using the heating demand profile and annual heat demand, the maximum heat load within a year is found and it is defined as the total installed heating capacity.…”

Section: Biofuelsmentioning

confidence: 99%

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The role of sector coupling in the green transition: A least-cost energy system development in North Europe towards 2050

Bermúdez¹,

Münster²,

Jensen³

et al. 2020

Preprint

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<div>This paper analyses the role of sector coupling towards 2050 in the energy system of North Europe when pursuing the green transition. Impacts of restricted onshore wind potential and transmission expansion are considered. Optimisation of the capacity development and operation of the energy system towards 2050 is performed with the energy system model Balmorel. Generation, storage, transmission expansion, district heating, carbon capture and storage, and synthetic gas units compete with each other. The results show how sector coupling leads to a change of paradigm: The electricity system moves from a system where generation adapts to inflexible demand, to a system where flexible demand adapts to variable generation. Sector coupling increases electricity demand, variable renewable energy, heat storage, and electricity and district heating transmission expansion towards 2050. Allowing investments in onshore wind and electricity transmission reduces emissions and costs considerably (especially with high sector coupling) with savings of 78.7 EUR2016/person/year. Investments in electricity-to-heat units are key to reduce costs and emissions in the heat sector. The scenarios with the highest sector coupling achieve the highest emission reduction by 2045: 76% greenhouse gases reduction with respect to 1990 levels, which highlights the value of sector coupling to achieve the green transition.</div><div><br></div><div><br></div>

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Section: Biofuelsmentioning

confidence: 99%

Section: Biofuelsmentioning

confidence: 99%

The role of sector coupling in the green transition: A least-cost energy system development in North Europe towards 2050

Bermúdez¹,

Münster²,

Jensen³

et al. 2020

Preprint

View full text Add to dashboard Cite

show abstract

“…The building energy analytics community has only just started to use open data sets towards the efforts of creating benchmarking data sets. Several prominent open building energy-related data sets have been released in recent years including applications to building-level office 6 and residential 7 appliances, occupant behavior 8 , heat pump 9 and natural ventilation systems 10 , as well as commercial and residential energy meter data 11 – 13 . The use of open data sets in the built environment enables the analysis of large numbers of buildings in applications such as benchmarking 14 .…”

Section: Background and Summarymentioning

confidence: 99%

The Building Data Genome Project 2, energy meter data from the ASHRAE Great Energy Predictor III competition

et al. 2020

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This paper describes an open data set of 3,053 energy meters from 1,636 non-residential buildings with a range of two full years (2016 and 2017) at an hourly frequency (17,544 measurements per meter resulting in approximately 53.6 million measurements). These meters were collected from 19 sites across North America and Europe, with one or more meters per building measuring whole building electrical, heating and cooling water, steam, and solar energy as well as water and irrigation meters. Part of these data was used in the Great Energy Predictor III (GEPIII) competition hosted by the American Society of Heating, Refrigeration, and Air-Conditioning Engineers (ASHRAE) in October-December 2019. GEPIII was a machine learning competition for long-term prediction with an application to measurement and verification. This paper describes the process of data collection, cleaning, and convergence of time-series meter data, the meta-data about the buildings, and complementary weather data. This data set can be used for further prediction benchmarking and prototyping as well as anomaly detection, energy analysis, and building type classification.

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“…The modeling was further detailed for space heating, and two profiles were constructed to appropriately account for technology specificities between heat pump and electric heater. Following Ruhnau et al [27], the degradation of air-source heat-pump performance with outside air temperature was integrated with the non-linear effects of the coefficient of performance in the end use profile. It turned out to be impossible to directly retrieve a charging profile from historical loads for passenger; profile from the French transmission system operator RTE [28] was then used.…”

Section: Space Heatingmentioning

confidence: 99%

The Role of Electrification in the Decarbonization of Central-Western Europe

d'Aertrycke¹,

Smeers

Peufeilhoux³

et al. 2020

Energies

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Scenario studies of energy transition generally point to the central role of electricity. This notion is ambiguous as its interpretation can range from an electricity-only policy to portfolios of different energy vectors with a dominance of electricity. This ambiguity adds to the uncertainty that already pervades today’s investment environment. This paper examines the centrality of electricity through a so-called “variational scenario” analysis with policies obtained by a mix of electricity-only and green gas penetration while maintaining constant decarbonization objectives. Electricity is a complex product that can only be further complicated by the high penetration of renewables and its interaction with the production and use of synthetic fuels. The variational scenario analysis is conducted with sufficiently fine (hourly) granularity to produce an adequate representation of these phenomena. It shows that tilting the central role of electricity to a mix of electricity and green gas offers several advantages in terms of efficiency, flexibility of investment strategies, and robustness with respect to major uncertainties. It shows that the variational scenario analysis can be extended to more complex mixes of policies.

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Time series of heat demand and heat pump efficiency for energy system modeling

Cited by 121 publications

References 11 publications

The role of sector coupling in the green transition: A least-cost energy system development in North Europe towards 2050

The role of sector coupling in the green transition: A least-cost energy system development in North Europe towards 2050

The Building Data Genome Project 2, energy meter data from the ASHRAE Great Energy Predictor III competition

The Role of Electrification in the Decarbonization of Central-Western Europe

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