Key learnings from the first successful city-wide HNES studies

This HNES (Heat Network Efficiency Study) citywide case study summary provides a practical examination of the efficiency and performance of heat networks in urban areas. The study’s findings are not just theoretical; they delve into the real-world complexity of these networks, analysing multiple aspects such as technical practices, standard operating procedures, client interactions, and system efficiency.

By focusing on specific clients within each city, such as conference centres, libraries, civic offices, retail buildings, and hotels, the diversity of the various types of heat networks linked to the district heating network was ensured. The study then identified tangible opportunities for improvement, integration, and optimisation. It is recognised that with critical heat network data, incremental changes for each heat network would significantly impact the total city network.

Why a city-wide HNES study?

So, why did we conduct a citywide HNES study? The answer lies in the complexity and scale of the heat networks in urban areas. These large and complex systems have multiple connections to clients of every type. Our study aimed to understand the general levels of quality and identify improvements to technical practices, standard operating procedures, and interactions between the network operator and clients.

The age of the heat network poses a significant challenge, as many clients are operating systems that are not compatible with modern heat network efficiencies. A common issue is the use of fixed flow controls, initially designed to maintain heat without regard for return temperatures. This is particularly evident in air handling units, fan coil controls, hot water cylinders, and calorifiers. While many systems are making upgrades, it is clear that without technical guidance from heat network operators, these upgrades may not significantly improve efficiency.

Numerous problems are allowed to exist because of a need for more visibility on how systems operate and perform. Heat meter data is available and is used for billing. However, flow rates and return temperatures are not monitored or alarmed. Even though contracts allow for return temperature limits, they have never been enforced due to the complexity and age of the client systems.

HNES Application Methodology

1. Client Site Diversity Analysis
   • Per city, we examined five distinct client sites.  as the diversity can be leveraged to develop comprehensive optimisation measures applicable to all client categories within the city network
   • Identification of system complexity and operational efficiency across different client types
2. Identification of system challenges
   • Identify outdated system practices, mainly using fixed flow controls to prioritise heat maintenance over efficiency
   • Log (historical) client attempts to upgrade systems and the level of technical guidance available
3. Datapoints & metrics to analyse energy wastage points & heat network efficiency overall
   • Install a monitoring tool and/or unlock BMS data to capture critical data for analysis, such as flow rates, return temperatures, differential pressures and network pump control
   • Identifying energy wastage points suggests significant, previously unknown savings beyond network efficiencies
   • Improved visibility on standard data sets is crucial to ensuring that clients and network operators are on the same page
4. Analyse AHU optimisation and network temperature control
   • Analyse heating and cooling practices
   • Log network temperatures and where it is controlled
5. Alarming and other communication
   • Map existing processes and procedures used to control/manage heat network
   • Primary and secondary heat network crossover in alarming
6. Focus on recommendations that impact the whole network first

 Key observations

1. Numerous problems are allowed to exist because of a need for more visibility on how systems operate and perform. Heat meter data is available and is used for billing. However, flow rates and return temperatures are not monitored or alarmed. Even though contracts allow for return temperature limits, they were never enforced due to the complexity and age of the client systems.
2. The most significant hurdle to overcome is the BMS control systems used throughout the network on both client and network operators’ systems. These systems are responsible for the day-to-day operation of systems and for reporting problems and alarms. However, each system is designed and operated in isolation, with a broad spectrum of quality and knowledge. Some BMS systems are unfit for purpose, while a few are hard to find fault with.  Almost all lack efficiency-related data, such as return temperatures or flow rates BMS graphics. This makes it impossible for clients to identify bypass flow within their systems or to track the effect of efforts to optimise the system.
3. With many connections providing heating and cooling, it is known that in many instances, the control of air handling units allows for significant energy waste with heating and cooling simultaneously or oscillating between the two due to poor control. Once identified, such problems can be easily remedied; however, with no visibility, these problems can persist for years.
4. Comprehensive data is priceless when identifying a realistic route to progress upgrades. Together with visibility and KPIs, a planned set of surveys and minor works will impact performance.

Lessons learned from the city-wide HNES case studies

Education and sharing knowledge is essential. Without the buy-in of building owners or facility managers, optimisation changes are unlikely to be implemented. The energy provider has to make a concerted effort to get all the stakeholders involved with improving their heat networks. Moreover, having the collected data visualised in easy-to-understand dashboards showing the inefficiencies/ potential savings were key in facilitating the conversations.