Energy System Operation
In CITIES, we have developed controllers and operational strategies for direct control of system states like temperature control in district heating for short term/operational use.
The controllers are based on probabilistic forecasts and combined with operational strategies, for example, price signals to move end-users’ energy consumption and relieve the energy system through flexibility.
Findings in the CITIES project – possible benefits (CO2 + Costs) from using digitalization in the operation system:
- Up to 800 mill Dkr annually savings in Denmark by data-driven temperature optimization (and tons of CO2 savings) in the district heating system. See the report here
- 10-30 pct savings by predictive control of heat pumps
- 5-15 pct savings by integrating forecasts in smart house controllers
- 10-40 pct improvements in electricity and heat load forecasts
- Up to 10 pct savings by optimal operations of CHP and DH plants
- 5-12 pct savings by smart wastewater treatment
- 10-20 pct savings on cooling for supermarkets
- Up to 90 pct savings on cooling for data centres
See the recommendations and videos below.
Flexibility / virtual storage – a keyword
Flexibility / virtual storage is a keyword to green transition in a cheap and effective way and in planning and operation.
To obtain the Danish climate goals for 2030 and 2050 we need to focus on digitalization and sector coupling. Digitization is the link that enables the coupling of energy sources with real-time matching of energy demands and production through data intelligence and IoT devices in integrated energy systems.
In the CITIEs project, we have investigated how much flexibility can help us achieve climate goals.
We note these characteristics for flexibility:
- Flexibility (or virtual storage) characteristics:
- Wastewater systems can provide storage 0.2-6 hours ahead
- Supermarket refrigeration can provide storage 0.5-2 hours ahead
- Buildings thermal capacity can provide storage up to, say, 2-10 hours ahead
- Buildings with local water storage can provide storage up to, say, 2-18 hours ahead
- District heating/cooling systems can provide storage up to 1-3 days ahead
- DH systems can provide seasonal/long term storage solutions
- Gas systems can provide seasonal/long term storage solutions
Model Predictive Control for Smart Energy Systems
CITIES has developed tools for short term (probabilistic) forecasting and control of integrated energy systems with flexible geographic scope. At CITIES final conference Professor John Bagterp Jørgensen talked about the software solutions for predictive control (MPC). The technology is based on stochastic differential equations (SDEs)
Professor Henrik Madsen: Forecasting for the Green Transition
In future energy forecasting will play a central role in the green transition, when demand follows the renewable power production. In this talk Project Manager at CITIES, Professor Henrik Madsen, describes state-of-the-art methodologies for renewable energy forecasting. He also describes how integrated forecasting across domains (wind, solar, load, prices, …) will become essential.
Characterisation and Integration of Energy Flexibility
Flexibility in electricity consumption will be a keyword for the green transition, in the energy system of the future based on solar and wind. Postdoc Rune Grønborg Junker from DTU Compute talks about how to unlocking consumers flexibility potential.
Demand response solutions and perspectives
CITIES Final conference November 9, 2020: Demand response solutions and perspectives Ben Kroposki, Director, National Renewable Energy Lab, Colorado, US
Smart Cooling - Singapore, Grindsted and the Future
At CITIES final conference November 9, 2020 postdoc Dominik Franjo Dominkovic talked about the research we have done in Singapore to utilized excess waste heat via absorption shillers to generate cold and analyzed the potential of widely adopted district cooling in tropical regions, with steady cooling demand. He has used the same methods on a demo case in Grindsted for cooling meeting rooms and the research continues now in ‘Cool-Data’ – with data centres.
Flexibility concepts in practice; case study on water towers
Rune Grønborg Junker, Postdoc at DTU Compute, together with colleagues and with the help of Grundfos, has found an intuitive way in which mathematical models describe how energy-flexible consumers react to electricity prices. They have used a water tower at Grundfos to investigate price-based management of flexibility.
Using SDEs to understand energy efficiency in buildings
Jaume Palmer Real is a PhD student at DTU COMPUTE – the Technical University of Denmark. In his YouTube-video, he tells about his PhD project: Stochastic Differential Equations (SDE) for Modeling Energy Systems Integration – and about how to use SDEs to understand energy efficiency in buildings. A model we use in CITIES.
Smart Control of Wastewater Treatment Aeration
In a CITIES demo project Krüger-Veolia together with DTU Compute have tested how to use the wastewater plant to increase flexibility in the energy system and to save CO2 and money. At the Green Digitalization conference on November 10, 2020Peter Stentoft Krüger talked about the results.
Data-driven Methods to Characterize the Dynamic of Buildings
At CITIES final conference on November 9, 2020, Carsten Rode, Professor at DTU Byg and Work Package Manager on CITIES & Christoffer Rasmussen, PhD at DTU Compute explained how they have developed a concept whereby they use mathematics/statistics to analyze data collected with high frequency from sensors in the buildings to optimize energy efficiency and to use the buildings as energy flexible storage.
Methods for Optimal Operation and Market Participation of DH
District heating provider with a portfolio of production units including combined heat and power (CHP) plant. A novel bidding method (HURB) has been developed to optimize the daily production of heat to cover the heat demand at minimal cost and to sell the electricity from the CHP, if beneficial for the overall system cost. At CITIES final conference Daniela Guericke (DTU) & Anders Andersen (EMD International) talked about the research.
Impact of Energy Communities on Distribution Grids
In a CITIES demo project, Dansk Energy together with DTU Computes have made a simple analysis of the impact of energy
communities on three different grid layouts to estimate the consequences of different setups of energy communities on the distribution grid. At the Green Digitalization conference on November 10, 2020, Tilman Weckesser, Dansk Energi, presented the results.
Leveraging consumers’ flexibility for the provision of ancillary services
Flexibility in electricity consumption will be a keyword for the green transition, in the energy system of the future based on solar and wind. Giulia de Zotti from the Danish Energy Agency and DTU Compute talks here about how to unlocking consumers flexibility potential.
The green transition calls for the next level of digitization and a need for new tailored methods, i.e. energy system-oriented AI, Big Data Analytics, Grey-Box Modelling, Cloud-Fog-Edge Computing, System-of-Systems, IoT, Resilience, User-involvement, and Data-sharing principles. This special CITIES session provides a number of talks highlighting the status and challenges in achieving an efficient implementation of the future low-carbon society.
Contemporary digital and data-driven methods are key to optimize the operation of buildings and district energy systems such that use of fossil fuels can be minimized without compromising on comfort and functionality of the built environment. The CITIES workshop gives an overview of potentials and state-of-the-art technologies in the field.
Qualitative investigation of the impact of energy communities on distr. grids
The demo project has made a simple analysis of the impact of energy communities on three different grid layouts: urban, suburban and rural areas of Denmark to estimate consequences of different setups of energy communities on distribution grids.
Control of heat pumps
The demonstration project has implemented, tested and demonstrated a fluidborne heating system with a heat pump and a solar collector in a domestic building that makes optimal use of renewable energy from the grid.
In this demo case, the CITIES project wants to assess or activate/utilize the thermal energy storage potential of different building archetypes, calculate the potential of thermal mass as a storage component on the system scale and assess the impact of utilizing this storage capacity in the energy system as a whole.
Optimization under uncertainty heat/power production in DH systems
Dynamic prices for heat delivered to district heating systems
This demo project has studied the dynamic value of heat supplied to the district heating system. Many of the methods used and the obtained results could also be used in a study on the demand side.
The demo case has investigated different approaches to analysis of smart meter data in a way to identify different consumption patterns. The demo case used data from Syd Energi, which had data from about 270.000 smart meters, with 15 minutes to 1-hour resolution and recorded for approximately one year. The idea was that the classification and characterization of electricity consumption should have to give a more detailed picture of consumption patterns to use for estimation and dimensioning of the energy grid.
Smart Energy Systems: Flexible Cooling of Data Centers
Energy demand for cooling of data centres has been increasing steadily in Denmark and the world. On the other hand, the aim of the energy transition is to make the system more efficient, including end-user energy efficiency. In order to continue the energy transition, as well as to integrate a rising number of data centres across Denmark, this demo project will look into possibilities for flexible and intelligent cooling of data centres.
Smart water management to improve water-energy nexus for water supply systems
In the demo case the CITIES project wants to allow water utilities to holistically manage their processes in a flexible way by operational management recommendations focused on: decrease the non-revenue water, improve the pressure management, detect leakages, save energy and water (water-energy nexus), and above all, improve the integrated water resources management in terms of water resources and revenues supporting financial, social and environmental sustainability, while maintaining quality and level of service.
By collecting data from Greenhouse consumers and weather observations the demo case has derived an offline model structure for load forecasting in greenhouses and established an online setup for load forecasting in greenhouses. In the online setup, the model parameters have been adapted to the actual dynamics.
Dynamic CO2-based control of summerhouse swimming pool heating
In this demo case CITIES has shown that CO2 emissions can be reduced by at least 10 per cent by heating the water in the indoor swimming pools when the electricity is generated by wind turbines and stopping it when the electricity comes from sources with a higher carbon footprint. This will also make itself felt on the electricity bill, which can usually be cut by EUR 1,400-2,000 (DKK 10-15,000).
Regulating Power Market: Modelling and Forecasting
The demo case has formulated stochastic models for the regulating power market in the Nordic area, however with a special focus on the prices in DK1 and DK2. Ultimately the purpose was to obtain better methodologies for predicting the probabilities for up-or down-regulation, and the related prices and/or volume. Such forecasts have also been used in some other demo projects in CITIES.
The demo case has used research from a parallel demo case on load forecasting in greenhouses, and another demo project on dynamic prices for DH systems to develop methods for optimal control of district heating supply temperature to greenhouses. on load forecasting in greenhouses, and another demo project on dynamic prices for DH systems.