Data-Driven Analysis of Energy Efficiency and Optimization Potentials in a Local Low-Temperature District Heating and Cooling System

Abstract

This study investigates the potential for energy efficiency improvements and operational optimization in a local low temperature district heating network. A data-driven approach is applied, applying performance analysis to evaluate different configurations and operating strategies and seeks to identify the main factors influencing system performance and to evaluate the impact of varying heat source combinations and configurations on overall energy efficiency. The newly built houses meet high energy-efficiency standards, while the existing buildings achieved around a 25% reduction in heating demand through targeted system and insulation upgrades. While heat pumps show high performance values, the inclusion of auxiliary electricity for brine circulation causes a significant drop, highlighting the need for clear system boundary definitions. Real-world monitoring revealed that cooling is not active when heat pumps are running, usage varies strongly across buildings, and adapted hysteresis control was required during transition periods to prevent frequent switching between heating and cooling and to ensure energy-efficient operation.