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District heating is expected to play an essential role in the cost-effective decarbonisation strategy of many countries. Resource-optimised management of district heating networks depends on a wide range of factors, including demand forecasting, operational flexibility, and increasingly volatile market conditions. However, traditional operations often still rely on static models and rather simple heuristics, while holistic optimisation requires dynamic cross-domain interoperability to allow the consideration of all these factors. This paper demonstrates a proof-of-concept for a knowledge graph based optimisation problem to minimise total heat generation cost for a district heating provider. The optimisation follows a hierarchical approach based on a merit-order principle and is embedded in a model predictive control framework to allow the system to incorporate most recent information and react to disturbances promptly. A detailed sensitivity study is conducted to identify key model parameters and assess the impact of anticipated changes in regulation and market conditions. Simulation-based optimisation is used to determine the short-term heat generation mix based on data-driven gas consumption models and day-ahead forecasts for the network's energy demand and grid temperatures. Seasonal autoregressive integrated moving average models with exogenous predictor variables are found to be sufficiently accurate and precise. The effectiveness of the approach is demonstrated for a case study of an existing heating network of a midsize town in Germany, where a reduction of approximately 20% and 40% compared to baseline operational data is obtained for operating cost and CO 2 emissions, respectively. [Display omitted] • Developed heat generation optimisation framework for district heating providers. • Identified key cost drivers and market dynamics using a detailed sensitivity analysis. • Developed high accuracy time series forecasting models for key input variables. • Assessed optimisation effectivity using a German municipal utility case study. • Improvement potential for operational cost and CO 2 emissions both exceed 20%. [ABSTRACT FROM AUTHOR]

Abstract: This paper presents a detailed meta-analysis of end and primary energy use for heating, cooling and ventilation of 11 low-energy non-residential buildings and one residential building in Germany that belong to the EnOB research program launched by the German Federal Ministry for Economy. In particular, the analysis emphasizes the substantial impact of auxiliary energy use on the efficiency of heating and cooling performance. The investigated buildings employ environmental energy sources and sinks – such as the ground, ground water, rainwater and the ambient air – in combination with thermo-active building systems. These concepts are promising approaches for slashing the primary energy use of buildings without violating occupant thermal comfort. A limited primary energy use of about 100kWhprim/(m2 neta) as a target for the complete building service technology (HVAC and lighting) was postulated for all buildings presented. With respect to this premise, a comprehensive long-term monitoring in high time resolution was carried out over the course of two to five years, with an accompanying commissioning of the building performance. Measurements include the energy use for heating, cooling, and ventilation, as well as the auxiliary equipment, the performance of the environmental heat source and sink, and local climatic site conditions. [Copyright &y& Elsevier]