ºÚÁÏÍø

News

Cities show significant energy flexibility potential

Demand side management and power-to-heat conversion bring more flexibility for solar and wind power
Fig. Electricity consumption in Helsinki with shiftable loads. The time that the loads can shift their consumption is also indicated.

Urban areas cause two-thirds of global energy consumption and the related CO2 emissions, and will become even more important with the rapid urbanization. Clean energy use in cities is therefore instrumental to climate change mitigation. For example Helsinki and Copenhagen have already set ambitious emissions targets, aiming at carbon neutrality by 2050 and 2030.

Solar and wind power are well-suited for clean energy production in urban areas, but they are also variable which requires more flexibility in energy systems. At the same time, urban areas present interesting flexibility opportunities in electricity and heat consumption. Researchers at the New Energy Technologies group at Aalto University have developed new simulation models for quantifying the technical and economic flexibility potential of electricity demand side management, and power-to-heat conversion with electric boilers and heat pumps. The models can be applied for any location and conditions, and could be useful in clean energy planning in cities worldwide. The relevant technical details of the studied systems are modeled diligently.

The models were applied to  Helsinki, Finland. Unique empirical time series data on shiftable electricity consumption was used to quantify the shiftable share more accurately than before in a bottom-up fashion. The shiftable loads included commercial and residential refrigeration, electric heating and wet appliances, totalling at 20% of the total annual electricity consumption. Power-to-heat with thermal storage in district heating could also absorb surplus solar and wind power very effectively. For example, 50% of the electricity consumption in the city could be produced from solar and wind with all the surplus converted to heat, providing 10% of the heat consumption in the city. Electricity demand side management also significantly improved the matching of electricity consumption and solar and wind production. Power-to-heat with heat pumps and thermal storage, as well as shifting electric heating and commercial refrigeration loads were found profitable investments in today's market.

Salpakari, J., Mikkola, J., Lund, P.D., Improved flexibility with large-scale variable renewable power in cities through optimal demand side management and power-to-heat conversion, Energy Conversion and Management 2016, 126, 649-661.

  • Updated:
  • Published:
Share
URL copied!

Read more news

Portrait of Kimmo Järvinen, from the Xiphera team. A man smiling at the camera
Research & Art, University Published:

Researcher-established company Xiphera growing rapidly

Xiphera Oy, which is celebrating its ninth anniversary, has developed hardware-based encryption solutions for the prevention of information security threats. The company is a deep tech company and its products are based on research and produce new technological solutions.
3D brain scan on screen showing colourful neural pathways inside a semi-transparent head model
Research & Art Published:

Applications open for Innovation Postdoc in AI

A fully funded, 12–month career track to turn your doctoral discoveries into a deep-tech startup.
Outdoor wooden daybeds with sheer beige curtains in a ruined courtyard garden with tall plants.
Cooperation, Press releases, Research & Art Published:

A Finnish working group’s artwork brings a cooling garden to Spain, which is sweltering in the heat

Through their garden art installation, a group of Finnish architects and artists proposes vegetation and a sense of community, among other things, as solutions to urban heat islands and the environmental crisis.
Two children play with bright cartoon panels on a grey tiled wall, spinning sections to mix the figures.
Press releases, Research & Art Published:

RealYou AI will develop the next generation of personalized AI decision assistants

Researchers to build cognitive machine learning that will improve decision-making with instantly personalized intelligent assistance.