Supply-Demand Balance Optimization Considering Ancillary Services with Energy Storage

High penetration of renewable energy increases the flexibility requirements of modern power systems, posing significant challenges to system operation and security. In particular, sufficient ancillary services, including peak regulation, ramping capability, and frequency regulation, are required to maintain system stability. Therefore, this paper proposes a modeling and estimation framework for ancillary service requirements in power systems with energy storage. Specifically, this paper first investigates the modeling of peak regulation, ramping, and frequency regulation demands, and a Kernel Density Estimation (KDE)-based method is introduced to estimate these requirements using historical operational data. Based on the estimated requirements, a supply-demand balance optimization model incorporating thermal units, renewable generation, and energy storage is formulated. Case studies demonstrate that the proposed model effectively ensures system operational feasibility while improving system flexibility and reducing the cost of ancillary service provision.