Vatajankoski optimizes Kankaanpää district heating system with Gradyent's real-time Digital Twin
The Finnish new energy company Vatajankoski has partnered with Gradyent since 2022 to optimize its heating system, reducing heat losses, energy costs, and CO2 emissions. The Digital Twin Platform provides operators with a full understanding of the network behavior in real-time to allow issue identification and optimization of supply temperatures and production portfolio operation. The company also uses Gradyent's user module to improve user performance and simulate various scenarios to derisk CAPEX investments.
Challenge
Vatajankoski is a Finnish new energy company that delivers heat to around 8,000 customers across the cities of Kankaanpää and Niinisalo, supplying approximately 80 GWh of thermal energy annually.
Vatajankoski’s energy production portfolio includes a CHP (Combined Heat and Power) unit running on a biomass-based fuel mix, several heat pumps, an electric boiler, oil and gas-fired peak load and reserve boilers, and accumulators to increase the system flexibility. Moreover, the company recovers waste heat from several data centers and a plasterboard factory, and launches a new e-boiler this spring.
Vatajankoski has an ambitious plan to cut all CO2 emissions from Kankaanpää and Niinisalo district heating network. To reduce heat losses, energy costs, and CO2 emissions all at once, the company needed a solution that would enable a real-time network overview and operational excellence far beyond what traditional software tools allow.
Solution
Vatajankoski decided to partner with Gradyent and use its Digital Twin Platform to launch a project focusing on minimizing heat losses via supply temperature optimization and efficient production portfolio operation with source dispatch optimization.
The solution focused on several areas:
Insights that enable real-time network optimization
Gradyent's Digital Twin helps the company's operators to fully understand their network's behavior in real-time and thus quickly identify issues with differential pressures and temperatures at different locations in the network.
In addition to delivering real-time insights, the Digital Twin optimizes the network operation by providing the operators with a 24-hour schedule of supply temperatures and flow setpoints.
The operating schedule is updated every 15 minutes to ensure that the optimization accounts for changes to the forecasted heat demand, fuel cost, and electricity price – all the while ensuring that every customer receives their contracted temperatures, and all source limitations are respected.
System performance monitoring and improvement
Vatajankoski recognizes that true system optimization requires visibility across the entire network, from heat production to end users. With Gradyent’s user module, Vatajankoski can identify user-side devices that are operating sub-optimally, understand their impact on overall system performance, and prioritize targeted improvements.
We chose Gradyent as our partner for multiple reasons. We believe that they have the expertise to utilise AI not only to optimise the heating network but also to efficiently integrate many different heat production sources and storages with each other at any given time. With the Digital Twin, we can also identify optimal locations for our future production plant and energy storage facilities. In addition, we found the Digital Twin user interface very user-friendly and easy to understand and use.
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Efficient design studies and analyses
The above features are all relevant to improving the current network. But what about simulating other scenarios, such as new user connections, network expansion, new heat sources, the addition of pumping stations, or any other change to the system?
Vatajankoski leveraged the Digital Twin to do just that. Among the many scenarios investigated were a new pipeline serving additional users, adding electric boilers to their existing source portfolio, and utilizing waste heat from a planned data center. By exploring various scenarios using the Digital Twin, Vatajankoski gained valuable insights into how the proposed modifications would affect network behavior, economics, and operation.
Understanding the impact of network expansion
One of the scenarios involved a 6-kilometre expansion of the network connecting new users located north of Kankaanpää. Gradyent helped Vatajankoski understand the system impact of the expansion, as well as correctly dimensioning the new 6-kilometre pipeline.
One of the main concerns from Vatajankoski was understanding if the expansion would result in any bottlenecks. By simulating the pressures, flows, and temperatures in the whole network, the Digital Twin was able to show that the expansion would not result in any bottlenecks.
Utilizing waste heat and introducing E-boilers
Additionally, Vatajankoski was looking to study the economical and operational effects of exploiting waste heat from a data center and introducing E-boilers. Gradyent's Digital Twin was able to quickly analyse the economic impact of different dispatch strategies, showing that the new sources could reduce operating costs by 43%.
The key to unlocking these savings is to only operate the electric boilers when the electricity prices are low and favoring production from the existing CHP when electricity prices are high.
Results
Vatajankoski's partnership with Gradyent and the use of its Digital Twin Platform yielded significant advancements in the optimization and operation of their heating network.
Following a successful two-year-long collaboration, Vatajankoski signed a 6-year contract with Gradyent to continue optimizing and future-proofing its heating networks.
By implementing Gradyent’s Digital Twin, Vatajankoski achieved an end-to-end visibility on the network, with coverage spanning heat production sources to the final consumers.
The Digital Twin optimization modules aim to reduce heat losses in the network, minimize the global operational costs of the heat production sources, and lower the CO2 emissions of the entire system.
Real-time network optimization
The Digital Twin provides Vatajankoski's operators with real-time insights into network behavior, enabling them to identify and resolve issues related to differential pressures and temperatures at various network locations.
To minimize the operational costs, ensure security of supply, and predict the operation in the next hours and days, the operation of this system implies a full understanding of the network, including its coupling with the electricity system.
System performance monitoring
Gradyent's user module enabled Vatajankoski to identify user-side devices that are operating sub-optimally, understand their impact on overall system performance, and prioritize targeted improvements.
Efficient design studies
Vatajankoski leveraged the Digital Twin to simulate various scenarios, such as network expansion, new user connections, and the integration of new heat sources. This capability provided insights into the potential effects on network behavior, economics, and operations.
Among the design studies carried out, Vatajankoski explored the opportunity to introduce electric boilers in its energy production mix. The company’s E-boilers are now operational and ready to increase the electrification ratio of the energy production mix at Vatajankoski.
These results highlight the successful application of Gradyent's Digital Twin in optimizing Vatajankoski's heating network, enabling real-time adjustments, strategic prioritization, and efficient scenario analysis for future network developments. The next steps in the project will center around the full integration of the Digital Twin in Vatajankoski’s operations via co-pilot mode.