Optimization based approach to assist the transition of large energy users to low temperature networks

Distric Energy System (DES) represents a promising opportunity to improve energy efficiency and boost the decarbonization of the European energy sector. If most of the studies focus on small consumers typically located within urban areas, large energy users like hospitals, university campuses or airports, constitute complex and unique systems with great potential for energy and cost savings. The aim of this work is to propose a robust method to optimize the preliminary design and operation of local DES characterized by complex non-residential buildings. Decision variables include the optimal set of technologies to be installed (type, size, location), their operating schedule, together with temperature and configuration of the thermal network. Focus is given to heat pumping technologies and in particular to the comparison between different degrees of centralization and respectively, decentralization. The mathematical model is based on a Mixed- Integer Linear Programming (MILP) formulation including a set of heat cascade constraints to ensure the feasibility of the heat exchanges. A case study is generated to represent a building-stock constituted by large non-residential buildings, connected to a central plant through an existing network infrastructure. The users differ for power and temperature demand, both estimated as linear function of the ambient temperature. Results show that the optimum degree of decentralization is highly influenced by the distribution of the heat demand among the users at the different temperatures. Therefore, the use of local heat pumps to upgrade the heat produced by a central unit does not always translate in operating cost savings. For the case study presented in this work it is shown that if the lowest temperature user covers 66% or more of the total demand a decentralized configuration is the most cost effective solution.