Probabilistic Flexoffers in residential heat pumps considering uncertain weather forecast

Abstract

The penetration of renewable energies is increasing in energy systems worldwide. Consequently, the intermittency of the energy sources raises technical challenges for sustainable energy supply. Demand-side flexibility is an effective solution to counterbalance renewable power fluctuations. In the residential sector, electrical heat pumps exhibit great flexibility potential. In this paper, a novel approach is proposed to generate FlexOffers for individual heat pumps considering the uncertain nature of weather conditions. To achieve the aim, firstly, the thermal dynamic model of residential buildings is presented mathematically. The model addresses different temperature zones. The constant coefficients of the thermal dynamics are estimated using Continuous-Time Stochastic Model (CTSM) in R software. Afterward, the building model is integrated with a success function to generate FlexOffers. The success function is comprised of two objective functions including minimization and maximization of the energy consumption of heat pumps. The FlexOffers are generated considering the existing gap between the minimum and maximum energy consumption. The patterns of energy consumption are defined based on occupants’ thermal comfort temperature setpoint. The FlexOffers are programmed in UPPAAL-STRATEGO software. Finally, a high-fidelity building model with four rooms is used to examine the proficiency of the suggested approaches. The simulation results confirm that the proposed method generates flexibility potentials for the upstream network in both optimistic and pessimistic states of energy consumption patterns.