Modelling Uncertainties in District Heating Supply Modelling

Abstract

District heating (DH) systems are recognized as essential elements in European energy policies aimed at substantially integrating renewable and excess heat sources to meet stringent decarbonization targets. Specific policy objectives include an annual increase of 2.1% in renewable energy and excess heat contributions to DH systems. Despite these clear targets, the pathways to achieve them remain underdefined, emphasizing the need for advanced modeling techniques. Addressing this, understanding and integrating uncertainty becomes pivotal, as it directly influences planning and policy decisions. This research critically examines the application of multistage optimization techniques in DH supply modeling, contrasting these with traditional scenario-based approaches. Traditional methods often operate under a limited number of fixed scenarios and do not fully capture the dynamic uncertainties inherent in the future energy landscape—such as variable DH demand and fluctuating energy prices. Our study begins with an evaluation of existing DH supply models and their methods of incorporating uncertainty, which might arise from factors like new building constructions, demolitions, renovations, and varying climatic conditions. We extend our review to capacity expansion models from other energy sectors, exploring methods that might be adapted to DH systems. Through a comparative analysis of models from Khojaste et al. (2023) on Markov decision processes, Mitjana et al. (2023) on multistage stochastic models for decarbonization, and Hole et al. (2023) on hydroelectric system capacity planning using stochastic dual dynamic programming, we investigate diverse approaches to managing uncertainty across energy systems. The contribution of this paper is twofold: firstly, it provides an in-depth review of uncertainty modeling techniques across energy sectors with a focus on their applicability to DH supply. Secondly, it introduces a multistage stochastic optimization model for DH supply, developed through this cross-disciplinary review, and demonstrates its application in a case study based on a DH system from a central European country. This model aims to enhance DH supply models' strategic relevance and applicability in supporting investment decisions.