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DESSI - Distributed Energy System and Security Infrastructure

DESSI is a new infrastructure for modelling, emulation, monitoring and controlling of the electrical grid. DESSI covers simulations, emulations and cybersecurity of power systems, ranging from micro-, macro- to regional energy systems.

DESSI infrastructure at the Department of Technology Systems (ITS) at UiO

Figure 1: DESSI overall infrastructure addressing the physical part, the digital twin and the high-resolution data collection

About the project

DESSI was initiated to see the potential of decentralised energy production, storage and usage. Specific focus is set to the Nordic context, with high usage of electricity, high percentage of electrical vehicles, and the summer (24h sun) and winter (high energy demand for heating) dilemma.

Objectives

DESSI has three main objectives, 
(i) advancing the research on distributed and decentralised energy systems, through real-life installations and high-resolution energy data,
(ii) provide real-life equipment and energy data for education at the Department of Technology Systems (ITS),
(iii) contribute to the energy transition in Norway, based on participatory transition, eNeighbourhoods and smart energy solutions. 

Outcomes

The outcomes of DESSI are threefold, being the real-life infrastructure, the high-resolution energy data and the modelling of residual energy systems.

The DESSI infrastructure will consists of solar panels, thermal and battery-based storage, vehicle to grid (V2G) and the control infrastructure to implement optimisations. 

Physical infrastructure of DESSI with V2G, battery, solar panels
Figure 2: physical DESSI infrastructure as play-field

DESSI is the play-ground for components of future energy systems, aspects the DESSI infrastructure and the DESSI energy data are as follows:​​​​​​
- High-resolution energy data from private households, reporting every 30 s on fuse level the consumed and/or provided energy.

- Assessment on the potential and the costs of smart energy solutions for private households, e.g. the ability to adjust the "high peaks". As data in figure 3 demonstrate, over 80% reduction (84%, 96% from 7-9 h) are seen in the morning, while the reduction is better than 25% (69%, 25% from 17-19 h) in the afternoon just by adjusting the heat pump and the car charger.

Energy data from the DESSI 108x pilot house
Figure 3: Energy data from the DESSI 108x pilot house from 2Mar2025, demonstrating the capability of energy reduction in the busy hours (7-9 and 17-19 h). 
Convenience factor in smart home controlling
Figure 4: Room temperature variations (lower curve) as a result of smart heat pump control (invers logic on/off)

- Smart energy modelling comes with costs, being (i) the costs for installation and operation, and (ii) the reduced convenience in implementing smart control. Figure 4 shows the temperature in the floor heating (upper curve) during 26-29Oct2024, the corresponding heat pump steering, and the resulting indoor temperature (lower curve).  As the building is a TEK17 building with floor heating the temperature in the room needs about 3 hours to raise due to the latency in the floor heating, though even 5 hours of no heat (7-13 h on 29Oct2024) results in only 0.3 deg drop in room temperature. The implications of reduced convenience is essential for the acceptance of smart home solutions.

- Resilience and Societal Security are key research topics, as the energy transition and smart energy control will have implications on our convenience. The smart grid is a critical infrastructure, as our daily life depends on the availability of energy. Thus, resilience against attacks on the smart grid, and the availability of energy for basic needs is a key aspect of our research.

Risk model for IoT based on Impact over Exposure
Figure 5: Risk assessment of centralised vs distributed home control systems

- An integrated security dashboard allows the understanding of the attack surface and the risk of having smart energy control. While traditional risk models focus on the likelihood of a rist appearing, our research suggests to focus on the exposure of infrastructure. Exposure is both physical and IT-related, with both being assessed through connectivity and protection mechanisms. 

Ongoing project work addresses the potential contribution of residential households to contribute to the energy transition, the costs/convenience factors for smart homes, and opportunities for advanced resilience and societal security.

Topics of Master Thesis work work include (Figure 6): 

Components of the smart grid modelling
Figure 6: MSc work related to the edge of the grid

- A. Monitoring of Fuses
- B. Big data and machine learning on household data
- C. Optimization control for weather forecast, price level and "home latency"
- D. Optimise electricity tariffs for prosumer home
- E. Optimising energy usage through appliance control
- F. Co-ownership of batteries in private homes
- G. The effect of Balcony Power Plants to Norwegian households
- H. HAN port reading with AMSleser
- I. Security challenges of the Smart Home
- J. Seasonal storage solutions

Background, Financing and Cooperation

The work with DESSI started in 2023 as an infrastructure project by UiO to address the contribution of decentralised energy solutions to the energy transition. The infrastructure is financed by UiO, with contributions from researchers across the department. 

We have invited a limited number of private households as pilot houses, and will share our results both as academic publications and as recommendations for practical installations. 

 

 

Tags: DESSI, Energy systems, Energy Storage, Energy challenges, seasonal storage, energy transition
Published Mar. 28, 2025 11:08 AM - Last modified Jan. 23, 2026 2:44 PM

Contact

For more information, contact the project leader Josef Noll or any of the participants (see links below)
 

Participants

Detailed list of participants