A framework for agile optimization of district energy systems

This paper presents an approach to tackle output uncertainty in District Energy Systems' performance for variable time horizons and progressive changes in urbanization processes and energy policy, which we define as agile optimization of District Energy Systems (DES). Multi-objective optimization of DES provides non-dominated tradeoff solutions among conflicting objectives in the form of a Pareto-front. A single solution needs to be chosen from the Pareto-front to proceed further in the urban design process. To facilitate this, an uncertainty analysis is performed on the parameters corresponding to equipment lifetime and operational costs of DES. The method is tested on an existing neighborhood with 24 buildings in the city of Zug. The energy systems configuration of the neighborhood was optimized and uncertainty analysis was performed on the Pareto-front to identify the most reliable system configuration. The final solution chosen, has the highest frequency (30.8%) of being the most stable solution. It also has the highest probability (96%) of being below the Cutoff point of Total Annualized Costs.