Coordination of multi-energy prosumers with demand side management

Recently, energy systems have evolved from fully centralized to decentralized systems with prosumers, namely users equipped with energy conversion and storage units. This emerging paradigm, originally intended for the electrical sector, can also bring benefits if extended to district heating networks, as it increases the penetration of local renewable sources and waste heat, thus improving energy efficiency. In addition, prosumers can operate Demand Side Management solutions, e.g. by storing heat in the building heat capacity or taking it back when considered more effective. However, distributed prosumers interact significantly with the energy network, and the optimal operation of an individual sub-system may not align with the most profitable operation of the global system. Hence, the optimal management of a community of multi-energy prosumers constitutes a large-scale problem with considerable computational challenges. This work presents two novel management strategies for communities of multi-energy prosumers who are capable of performing Demand Side Management, based on centralized and distributed optimization, with the goal of reducing operating costs. These strategies are assessed using the case study of a university campus with several prosumers: they are compared with a reference in which every multi-energy system is optimized individually with no regard for community benefits. Both optimization tools give a 42 % to 53 % thermal peak shaving and a 3.8 % to 5.5 % reduction in cost, avoiding the use of high-cost technologies in favor of low-cost ones. Moreover, a scalability analysis demonstrates that distributed optimization is preferred when there is a large number of prosumers or their configuration is complex. • Optimal operation of multi-energy prosumers connected to distribution infrastructure • Inclusion of thermal demand side management to minimize total community cost • Coordination tools based on centralized and distributed optimization • Cost reduction ranging from 3.8 % to 5.5 % with respect to reference • Thermal peak shaving between 42 % and 53 %