Multi-objective optimization of district heating network model and assessment of demand side measures using the load deviation index

The future design of small-to-medium scale district heating networks must integrate policy-related targets while being able to provide a certain energy service to its consumers with profitable business models. Policy targets emphasize cross-cutting developments, like the increase of biomass share and the implementation of demand side measures. This implies the need for multi-goal, optimum design of heat production, whose performance is highly dependent on the yearly heat load profile. In this work, a holistic energy service model is proposed for design optimization of energy supply from a biomass-based heating plant for small-to-medium scale applications. Furthermore a new indicator called “load deviation index” is proposed, which is used (a) for characterization of heat load profiles and (b) for the assessment of the impact of different demand side measures onto optimum design. A review of the actual policy framework and the business implications reveal the need for a holistic future district heating network design, where both demand-side and supply-side services are included. A multi-objective optimization is applied for calculating Pareto-optimum solutions of the heating plant design while the demand side is modelled using the load deviation index. The model is applied to a typical case study, whereas its results are not restricted to it. Generic results are obtained through normalization and provide evidence that demand side measures do not always contribute to higher performance of such systems.