District heating networks still rely on fossil-fueled and high-cost peak production units to manage short-duration demand spikes, increasing operational costs and environmental impacts while challenging long-term decarbonization targets. This thesis investigates peak power behavior and building-side strategies within the Ludvika district heating network in Sweden, using real operational data from both the network-side through VB Energi and the building-side through LudvikaHem. The study analyzes the relationship between heat production, building heat demand and outdoor temperature while evaluating the potential of building-side theoretical demand-capping strategy to reduce heat demand and relieve stress within the district heating network.
The results demonstrate a strong dependency between district heating production and outdoor temperature, with regression models producing a coefficient of determination of R2 = 0,84 for average production. The highest observed average production reached 39,64 MW. Median Absolute Deviation-based threshold analysis identified operational threshold values between 22,80 MW and 25,90 MW as representing transitional and abnormal peak conditions. Based on these thresholds, 94,47% of hourly average production values were classified as normal operation, 5,01% as borderline operation and 0,51% as abnormal peak operation. Furthermore, regression analysis showed that abnormal peak conditions began to occur at outdoor temperatures significantly warmer than the approximately -5,00°C operational threshold currently assumed within the network, with the first abnormal crossings occurring around 3,30 °C for hourly average production.
The building-side analysis demonstrated strong seasonal dependency of space heating demand, while domestic hot water demand exhibited more irregular short-term variations associated with occupant behavior. Among the evaluated mitigation strategies, the seasonal average cap on total demand achieved the largest total demand reduction at approximately 16,16%, although this introduced an increased risk of occupant comfort reduction. The regression-based annual cap strategy achieved approximately 10,82% demand reduction, while the seasonal regression-based strategy achieved approximately 8,04%. Statistical peak-shaving strategies based on percentile constraints produced significantly smaller reductions, with the 95th percentile and 99th percentile strategies reducing demand by approximately 1,54% and 0,27%, respectively. Domestic hot water-focused strategies produced reductions of approximately 5,00%.
The study concludes that empirically derived theoretical building-side mitigation strategies can contribute to reducing heat demand and thus decrease peak power occurrences within district heating systems without requiring major infrastructure expansion.