Abstract: In the context of increasing penetration of renewable energy, to address the rapidly growing demand for flexible ramping in power systems, this paper proposes an optimization operation strategy for a Building-based Virtual Power Plant (BVPP) to participate in energy and flexible ramping markets. First, considering the physical characteristics of various devices within buildings, as well as environmental and human factors, we establish flexible operation models for electric vehicle (EV) clusters and Central Air-conditioning Systems (CACS) to assess the flexible ramping supply capacity of the BVPP. Second, taking into account the uncertainty in load and renewable energy output forecasts, we establish a day-ahead energy and flexible ramp market optimization operation model for BVPP based on Conditional Value-at-Risk (CVaR) theory. Then, considering the impact of BVPP's risk preferences on the revenue distribution among various entities, we introduce a risk effect factor and propose a revenue distribution mechanism within the BVPP based on a risk-modified Shapley method. Finally, through case studies, we verify that the proposed BVPP market optimization operation strategy is both economical and low-carbon, and that the revenue distribution mechanism can reasonably allocate the revenues among the entities within the BVPP.

Key words: flexible resources, central air conditioning system, electric vehicles, conditional value-at-risk, risk-modified Shapley method