Gradyent’s Digital Twin helped IOTOI and Porvoon Energia understand the impact of PIP3 over the entire year thanks to full-year simulations that considered all network hydraulics. The analyses across just 15 network users demonstrated that c. 90% of the total energy consumed by the PIP3 users could be extracted from the return line. This would lead to benefits such as freeing the additional space of 3.5 GWh in the network, reducing fuel costs and CO2 emissions through lower forward and return water temperature, and improving the recovery of waste heat from flue gases. 

District heating networks are rapidly growing, with 350 million connections planned in cities worldwide by 2030. Ensuring that customers can still be connected calls for significant investments from providers who aim to increase their network’s efficiency, reduce forward and return temperatures, and minimise heat losses.  

Many district heating companies turn to energy cascade solutions, which capture low-temperature heat to reuse it (usually from the return line). An example of this is PIP3, an innovative solution developed by IOTOI, a Finnish consultancy company. It allows heating companies to use heat from the return pipe to significantly increase the efficiency of the heating end-user.

Led by the belief that the expansion of current district heating networks will continue to be critical in the future, IOTOI created PIP3 to increase network efficiency by improving user behaviour. The solution allows heating companies to use the heat from the return pipe, which significantly increases the efficiency of the heating end-user and the network. In a Keskuskoulu school, PIP3 has been in operation for over two years, and the simulation is founded on real data from existing PIP3 implementations. 

To maximise the efficiency increase from PIP3 and transfer the benefit from a single user to the full network and production schedule, a utility provider needs to have a full overview of their system and the ability to simulate changing scenarios to understand what implementing a solution like PIP3 would mean in the context of the entire system. This is where Gradyent and IOTOI partnered: 

“Gradyent’s Digital Twin solution matched our requirement for a full, real-time overview of the entire system. We teamed up with Gradyent due to its reputation as a well-established player in the field and as the only company capable of combining live data and thermohydraulic models in an end-to-end solution.” 

Johnny Holmström, CEO at IOTOI 

IOTOI teamed up with Gradyent to simulate PIP3 inside the Porvoon Energia network 

To understand the impact of PIP3 over the entire year, IOTOI needed a solution capable of carrying out full-year simulations that considered all network hydraulics. A simplified or static calculation wouldn't be accurate enough to determine the real financial and sustainability impact of the PIP3 solution. That's why IOTOI chose to use Gradyent’s Digital Twin.  

Porvoon Energia is a Finnish energy company with over 2000 properties as part of its network and around 35,000 customers. The Digital Twin was used to study the impact of multiple PIP3 solutions at different locations in the network. The solution was applied in the Porvoon heating network counting 284 GWh of annual production across 15 different user locations (both commercial and residential users), which represent ~6% of the total heat supply. 

The Digital Twin allowed IOTOI to study the local effect of temperature and hydraulics on specific users as well as the holistic effect on the entire network and power plants. Multiple dynamic simulations were performed covering the entire year and examining the effect at the level of each user, pipe and production unit in the network. This would be extremely challenging to accomplish using a conventional offline parametrised model.  

“The full-year Digital Twin scenarios showed the scale of return temperature reduction in the network close to PIP3 users that Porvoon Energia could achieve by implementing the solution. As a result, the network operator could increase network efficiency or add additional users to the same network area without having to make any further investments.” 

Johnny Holmström, CEO at IOTOI 

Results brought by Gradyent’s Digital Twin 

The Digital Twin simulations revealed that IOTOI's PIP3 solution could highly improve the efficiency of the district heating network. They showed that by incorporating the PIP3 solution in these 15 users, 90% of the heat energy could be delivered by the return line for low-temperature heating applications like space heating, leaving only 10% supply from the forward line, which is mainly used for domestic hot water. This solution was especially beneficial in the winter.  

The combination of a Digital Twin and PIP3 across just 15 users could reduce forward temperature by ~3°C at the main power plant while using the same flow to satisfy the demand and guarantee that all user requirements in terms of temperature, pressure and energy delivered are met. Similar energy savings for an average Finnish district heating network would result in the reduction of ~455 tonnes of CO2. 

Next steps in IOTOI and Gradyent’s collaboration 

Gradyent’s collaboration with IOTOI demonstrated that a Digital Twin can be successfully used to simulate the impact of energy cascade solutions on the efficiency of a heating network. Gradyent will continue to support IOTOI in verifying its technological innovations through simulation aiming to determine their impact on heating network efficiency, helping to increase confidence in such solutions among network operators. 

“Utility providers looking to introduce system changes or new low-carbon energy sources need to be able to simulate such changing scenarios to understand their impact on the network. The project realised with IOTOI and Porvoon Energia demonstrates that a Digital Twin provides such comprehensive understanding of a heating system and its moving parts, which is essential for building a business case for energy cascade solutions like PIP3.” 

Martino Dossi, Solutions Director at Gradyent