Energy collaborative optimization strategy for virtual power plants participating in green electricity trading and peak regulation ancillary services

作者：Liming Zhou, Yuyang Wang, Nian Liu, Xin‐Hao Li, Kuan Zhang · 发表于：International Journal of Electrical Power & Energy Systems · 年份：2025 · DOI：10.1016/j.ijepes.2025.111284 · 被引用次数：4 · 研究领域：Smart Grid Energy Management、Integrated Energy Systems Optimization、Smart Grid Security and Resilience

• Fuzzy chance constrained models are established to quantify uncertainty of DERs. • A Minkowski sum-based aggregated adjustable capability evaluation method for VPP is proposed. • An energy joint declaration model is formulated for VPP to participate in multiple electricity services. With the growing proliferation of distributed energy resources (DERs) in power systems, virtual power plants (VPPs) face the challenge of underutilizing their flexible regulatory potential when participating in a single electricity service market. This paper proposes an energy collaborative optimization strategy for VPP to simultaneously engage in green electricity trading and peak regulation ancillary services for improving the utilization efficiency of DERs and increasing economic benefits. Firstly, fuzzy chance constrained models with specified confidence levels are established to quantify the adjustable capacities of various DERs, including distributed photovoltaics (PVs), energy storage, electric vehicle charging stations, and thermostatically controlled loads. Subsequently, since the adjustable capacities of different DERs can be represented as high-dimensional adjustable polytopes, a Minkowski sum-based method is developed to aggregate these polytopes, thereby deriving the time-coupled aggregated adjustable capacity of the VPP. To alleviate the computational burden associated with time-coupling constraints, a maximum inscribed polyhedron approach is further employed to approximate the agg...