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How could measuring indoor air quality help households control ventilation and save energy? How could AI be used to operate and predict the yield of residential solar panels? Could heat pumps be controlled based on electricity price data?
These were some of the issues explored in a series of pilot projects funded by Sitra over the winter. Late last autumn Sitra decided to share its expertise to create energy savings by funding eight data-driven pilots. The aim of the pilots was to boost products and services that help small energy users in particular, such as households, small businesses and housing companies, to save on electricity and heating costs.
Data helps save energy
Launched in December, the pilots explored the use of data to save energy and achieve a more balanced energy consumption by shifting some of the demand away from the peak hours.
The pilots showed that new types of mobile applications and cloud services could be produced from open data Open data Data which can be freely used, re-used and re-distributed by anyone. Open term page Open data sources with relatively little effort. These services can be used to control household appliances and heating according to the energy situation and help consumers make smart and flexible energy consumption decisions in their daily lives.
The Finnish energy sector produces high-quality open data, which made building these services for the purpose of the pilots relatively quick and easy. The electricity grid is remarkably smart when compared to other European countries or the United States. Smart grid automation and communication technologies provide accurate information on electricity use for consumers and electricity companies. However, the pilots revealed a lack of innovation by many energy retailers.
Sitra found that the most interesting solutions were offered by three pilots: the projects by Loopshore, Kapacity.io and Turku University of Applied Sciences. They were able to test their product ideas within a short timeframe and obtain preliminary but positive measurement results for their data-driven solutions.
Loopshore: Data-driven optimisation of ventilation efficiency
Loopshore, a Tampere-based company developing indoor air quality sensors, piloted a project to optimise ventilation efficiency to save energy consumption in buildings. This would prevent venting warm air directly outside. Ventilation consumes a lot of energy.
The pilot sites were a hospital and a detached house.
What was the role of data in the solution?
The energy optimisation is based on real time data obtained from continuous measurement. The pilot used ambient sensors in a new way as part of an energy saving scheme for whole buildings. The ambient sensors measured indoor air for carbon dioxide concentration, temperature and relative humidity.
The measurements showed that in one of the pilot sites, ventilation could be reduced by more than 50% without compromising comfort and health.
The measurements showed that ventilation could be reduced by more than 50% without compromising comfort and health.
“The pilot also found that the interfaces for building automation data exchange should be opened up to make it easier to coordinate different systems,” said Janne Edgren, one of Loopshore’s founding partners. There are still barriers to the movement of data. For example, suppliers of ventilation systems have had restrictions to protect their own business, slowing down the development of new solutions and cooperation networks.
“The pilots told us something important: that the data collected can actually generate savings and that energy optimisation is something worth pursuing,” the company said.
Kapacity.io: Heat pump use based on electricity price forecast
The pilot project of Helsinki-based Kapacity.io developed a system for households that controls their heat pumps based on electricity price forecasts. The system makes the heat pump’s electricity consumption more efficient and directs it away from the most expensive peak demand hours, according to the price of electricity.
Because electricity prices fluctuate, heat pumps offer a way of identifying opportunities for demand response. In homes with electric heating, the main energy consumer is the heat pump.
Modern heat pumps are typically connected to a cloud service, allowing residents to control the pump with their mobile phones even when they are not at home.
What was the role of data in the solution?
The AI algorithm developed by Kapacity.io addresses demand response: a property’s appliances such as heat pumps, ventilation or solar panels are controlled based on signals from the electricity market. The signals can include the price of electricity and the carbon intensity of the electricity grid, which indicates whether the electricity comes from renewable or emitting sources at any given moment.
“Based on preliminary results, Kapacity.io’s smart heat pump control can achieve savings of more than 10% in the electricity consumption of the heat pump,” the company said.
The smart control operates the heat pump automatically, provided the property owner has given permission for processing of the heat pump data and controlling the pump.
“By developing open data transfer interfaces for heat pumps, they can be turned into service platforms. Third parties can build their software on top of it for the benefit of the device owner as well as the power grid,” said Johanna Kalli of Kapacity.io.
The smart heat pump control can achieve savings of more than 10% in the electricity consumption of the heat pump.
In the future, heat pump manufacturers will not just sell the device. They will also want to make use of the data sourced from it, often as part of someone else’s service development.
Turku University of Applied Sciences: Getting the most out of solar panels with AI
The pilot project of the Turku University of Applied Sciences developed a machine learning algorithm to calculate more accurate output predictions for solar panels based on their location, weather forecasts and previous output history. The panels were located on the roofs of the university buildings and the student village.
The aim was to use AI to improve household energy management. Energy management systems are important tools for monitoring, managing and optimising energy consumption. They are used in offices, hospitals, industry and increasingly in homes.
In this pilot, a prototype of a mobile app for households to optimise the use of solar panels with data was developed.
The pilot also involved cooperation between Turun Energia and the solar panel manufacturer Solar Finland from Salo.
What was the role of data in the solution?
Energy management systems using AI can learn from user behaviour and predict future electricity consumption. At the same time, they can help balance the grid and avoid overloading.
For the mobile app, both public data and MyData MyData The term MyData refers to: 1) a new approach, a paradigm shift in personal data management and processing that seeks to transform the current organisation-centric system to a human-centric system; 2) personal data as a resource that the individual can access and control. Personal data that is not under the respective individual’s own control cannot be called MyData. Open term page MyData generated by households were collected.
The pilot showed that AI and open data can increase the accuracy and efficiency of energy management systems to benefit users.
“The integration of AI into a larger energy management system was found to be challenging,” said Tero Mäki, who led the student team. Reconciling data from different sensors can also be difficult.
“Our goal is to be able to measure and visualise the impact of users’ actions not only in terms of economic efficiency, but also sustainability and the environment,” the pilot team reported.
Gamification and smart home appliances were also tested in pilots
The other pilots receiving Sitra funding explored the following areas:
- Boosting household energy savings through the Energiarenki service: In Renki Software’s pilot, an accurate analysis of a household’s electricity use was created for the Omasahko.fi service. Users can import their own electricity usage history to the service from the energy grid company Fingrid’s Datahub. The service provides an illustration of personal consumption and advice on how to save electricity at home.
- Flexibility in energy use with a game-like mobile application: Wapice developed a game-like mobile app concept to encourage more flexible energy consumption and savings. Consumers can use the app to monitor their own electricity consumption and shift their electricity consumption away from the peak hours. Success in the game requires avoiding peak hours and completing different energy saving challenges. Within the framework of the pilot, the design reached the user testing phase.
- Energy savings by controlling smart household appliances: The Honkio pilot developed a mobile application controlling smart home appliances to encourage demand response. This allows consumers to see in real time how their daily choices affect energy consumption and achieve savings. The mobile app was developed to the prototype stage and the installation concept was tested.
- Smart home appliances responding to the electricity price forecast The Netgallery pilot focused on the further development of an on-site control device for smart household appliances which responds to energy weather tracking . The unit can control home heating, solar energy and electricity-intensive appliances. It helps time the electricity production and sourcing to the more affordable hours with lower emissions. The required data, for example on electricity prices, will be downloaded from open interfaces. The device description developed in the pilot and its source codes will be mostly open.
- Demand response incentives for fixed-price electricity contracts The MoeGreen pilot aimed to develop a platform service for energy retailers to encourage fixed-price electricity contract customers to take advantage of demand response. However, the project did not go ahead because the desired cooperation with energy retailers did not materialise.
Why are energy savings and new solutions still needed?
The winter energy crisis was predicted to be challenging for households, businesses and society. Many households were looking at how to cut their expensive electricity bills and reduce electricity consumption. The authorities were preparing for a possible power shortages and how to ensure sufficient electricity distribution for everyone.
Although electricity shortages and power cuts were eventually avoided this winter – mainly thanks to the mild weather – there is still a need for solutions. In the future, energy will increasingly be generated by weather-dependent means such as wind, solar and hydropower. Electricity prices are likely to continue to fluctuate next winter. Saving energy is a quick and effective way to mitigate the energy crisis and save money.
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Extensive data repositories in the energy sector should be increasingly exploited and integrated into the development of new services. There is still room for improvement in data availability. For example, consumers should have easier access to their own consumption data in Fingrid’s data exchange system Datahub, so that data can be more easily shared with other services.
There is also a need for free electricity price data for further use by businesses, so that the data can be used to develop new services. The further development of energy-saving services requires data, data analysis and data presentation in a way that is accessible to users so that they can make the most out of it.
The Sitra-funded energy saving pilots presented their lessons learned at the Data Economy Situation Room event on 7 March 2023. A recording of the event is available for viewing in the shared open workspace Howspace.
