Optimal scheduling of district heat pumps conceived for implementation in Energy Management Systems to participate in demand response

Abstract: Nowadays, the exponential growth of Indirect Demand Response (IDR) and Direct Demand Response (DDR) programs is urging researchers to investigate new strategies to enable the provision of flexibility services from any type of energy device. In the case of Heat Pumps (HPs), research efforts revolve around their integration in Energy Management Systems (EMS). To this end, this work proposes a novel formulation of the optimal scheduling problem of district-level HPs, conceived for EMS implementation, and based on a quadratic programming algorithm, with a specific objective function for IDR and DDR. Furthermore, a rigorous methodology is defined to assess HPs’ performance under both IDR and DDR, where IDR price signals pursue a peak-shaving/valley-filling objective, while DDR considers participation in flexibility markets. The proposed optimal scheduling is implemented in a practical case study, based on real data from the Horizon-Europe project REEFLEX. Results under IDR prove the peak shaving and valley filling capabilities, obtaining reductions in consumption peak and peak-to-dip gap of up to 13% and 34% respectively. Possibility of designing IDR price signals to avoid extra costs for the end users is also proven. For DDR, a sensitivity analysis of peak and average consumption against the price of the flexibility offer is conducted. Peak and average consumption are proven to reduce up to 20% and 35% for upwards flexibility, and to increase up to 100% and 80% for downwards flexibility. Besides, the total energy cost increases against the flexibility price offers at rates of up to 3.75% and 11.25%, respectively in upwards and downwards flexibility.