Two-stage affine assessment method for flexible ramping capacity: An inverter heat pump virtual power plant case

The increasing penetration of renewable energy generation brings about variability and randomness, which poses challenges to the power systems due to a potential shortage of flexibility resources. Inverter heat pumps (IHPs) can be utilized to address this issue by providing flexible ramping capacity (FRC). However, unlike conventional generation that offers a fixed FRC, the FRC of individual IHPs and their aggregation are influenced by their operational constraints and the indoor temperature thresholds set by buildings. These thresholds, in turn, are affected by uncertainties in ambient temperature and solar irradiation. For the individual IHP, an IHP-FRC assessment model is established. This individual IHP-FRC assessment model is based on the building thermal dynamic model and user comfort model, incorporating uncertainties in ambient temperature and solar irradiation through affine representations. For the IHP aggregation within a virtual power plant (VPP), a two-stage FRC assessment method is proposed to assess the FRC of an IHP-VPP in both the day-ahead and intra-day periods. In the day-ahead period, the VPP-FRC is calculated using the Minkowski sum method to ensure resource adequacy for meeting ramping demands. In the intra-day period, the VPP-FRC is rolling adjusted according to the operating status of each IHP and sent to the dispatch centre of the power system. The max-min fairness (MMF) ramping demand allocation strategy is employed to ensure fairness in allocating ramping demands to individual IHPs within the VPP. The simulation with 10,000 households in a winter heating scenario is conducted. The results indicate that the proposed method provides sufficient ramping capacities during the day-ahead period, with an upward FRC maximum of 6.29 MW/10 min and a downward FRC of −3.65 MW/10 min. The IHP-VPP effectively responds to ramping demands during the intra-day period without affecting the fairness, indoor comfort, and considering uncertainties in solar irradiation and ambient temperature.