Dear Reader,

For the 57th issue of our heatbeat Research Newsletter, we take a look into the latest research in advanced control strategies of district heating networks and waste heat potentials for 5th generation DHC.

The first paper Evaluating Waste Heat Potential for Fifth Generation District Heating and Cooling (5GDHC): Analysis Across 26 Building Types and Recovery Strategies from Chicherin covers different waste heat potentials for the use into 5th generation DHC. The second paper this month evaluates an advanced control strategy in district heating systems by comparing it to rule-based strategies. The title is Operational Control of a Multi-energy District Heating System: Comparison of Model-Predictive Control and Rule-Based Control from Descamps et al.

The study by Stanislav Chicherin presents a comprehensive evaluation of waste heat recovery potential across 26 building types for integration into fifth-generation district heating and cooling (5GDHC) systems. These systems operate at ultra-low temperatures and enable bidirectional energy exchange between prosumers, offering a sustainable alternative to conventional heating and cooling. The research focuses on moderate-temperate regions like Flanders, Belgium, and employs a techno-economic methodology combining performance metrics (e.g., EER, PUE, SCOP) with capital and operational expenditure assessments. Through regression analysis and empirical modeling, the study estimates cooling loads, equipment sizing, and heat recovery efficiency, revealing that average cooling loads reach 58% of peak demand and SCOP values range from 6.1 to 10.3.

Key findings highlight that waste heat recovery potential varies significantly by building type, with conversion rates between 33% and 68%, averaging at 59%. Data centers, supermarkets, and cold storage facilities are identified as high-value prosumers, especially when operating above a 55% capacity factor. For instance, data centers using water-to-water heat pumps can produce up to 10.1 GWh/year in heat pump mode. The study also demonstrates that OpEx and CapEx values converge within 2.5%, indicating balanced system configurations. Seasonal operation modes—heat exchanger in summer, heat pump in winter, and free cooling in colder months—are modeled to optimize energy recovery. The research underscores the importance of building envelope performance, cooling system type, and operational parameters in determining waste heat usability.

Ultimately, the study provides a scalable framework for integrating low-grade waste heat into 5GDHC networks, offering up to 40% energy savings in optimized systems. It emphasizes the need for detailed building-specific data and suggests a simplified input set for planners, including location, building type, equipment specifications, and surface area. By quantifying energy production and recovery feasibility across diverse sectors, the research supports strategic planning for decarbonizing urban energy systems and enhancing the flexibility and efficiency of district heating and cooling infrastructure.

The paper investigates and compares two operational control strategies Rule-Based Control (RBC) and Model Predictive Control (MPC) for a multi-energy District Heating Network (DHN) using a digital twin modeled in Modelica. The DHN includes a gas boiler, a heat pump, a solar thermal field, and a thermal storage tank, with a single aggregated consumer. The study uses the PEGASE co-simulation platform to implement and evaluate both control strategies over a three-month period. While RBC reacts to current system states, MPC optimizes future operations based on forecasts and cost minimization, particularly considering variable electricity prices and solar availability.

The MPC strategy is formulated as a Mixed-Integer Linear Programming (MILP) problem, optimizing the power setpoints of the heat pump and gas boiler while managing the thermal storage. Simulations show that MPC significantly reduces operational costs compared to RBC by 4.6% overall and by over 20% for gas usage by prioritizing the use of the heat pump during low electricity price periods and minimizing gas boiler usage. However, MPC slightly underutilizes solar energy due to prediction errors, which can lead to curtailment when storage reaches capacity. The study also explores different heat plant sizing scenarios, revealing that increasing heat pump capacity or reducing solar field size impacts energy cost and source utilization differently under each control strategy.

In conclusion, MPC outperforms RBC in cost efficiency and flexibility, especially in systems with variable renewable energy sources and storage. The PEGASE platform proves effective for integrating simulation and control, enabling rapid and flexible testing of strategies. Future work includes real-time validation using an experimental DHN and enhancing MPC by integrating solar field constraints and improving forecast accuracy to better leverage renewable energy and storage capabilities.

Further Information

As always, we recommend reading the article in full. In addition to this research newsletter and various blog posts, we have added a monthly feature update to our blog, summarizing important developments and new features in our heatbeat Digital Twin. You can find the latest entry at https://heatbeat.de/en/blog/76/ .

The next issue of our newsletter will be published on August 6th, 2025.