Electric vehicles (EVs) are promising to provide frequency regulation services due to their fast regulating characteristics. However, when EVs participate in supplementary frequency regulation, it is challenging to simultaneously achieve the dispatch of the control center and the expected state of charge (SOC) levels of EV batteries. To solve this problem, in this paper we propose a vehicle-to-grid (V2G) control strategy, in which an uncertain dispatch is implemented in the control center without detailed EV charging/discharging information. The regulation from the control center is achieved by allocating the regulation task within the frequency regulation capacity of EVs. The expected SOC levels of EV batteries are guaranteed by a real-time correction of their scheduled V2G power in EV charging stations. Simulations on an interconnected two-area power system validate the effectiveness of the proposed V2G control in achieving both the frequency regulation and the expected SOC levels of EVs.

Frequency dynamics during primary frequency control is closely related to pre-disturbance operating conditions, the disturbance, and equipment characteristics. How to rigorously express such a relation in a frequency stability constrained optimal dispatch problem is still an open question. This paper presents an optimal power flow (OPF) model for generation redispatch that considers dynamic frequency response constraints to ensure frequency stability during primary frequency regulation. The distinct feature of the model is that the dynamic frequency response is formulated as a set of differential algebraic equations (DAEs), which allows considering the transient behavior of frequency and mechanical/electromagnetic power for each generator during primary frequency control period. Based on the solution of the optimization problem, a definition of the primary reserve for each unit is proposed according to the maximum of incremental mechanical power. This definition helps meet the adequacy requirement of primary frequency response and achieve partial frequency restoration. Simulation results on WSCC 3-machine 9-bus system, New England 10-machine 39-bus system and the modified IEEE 54-machine 118-bus system validate the effectiveness of the proposed model and reveal the strong coupling between frequency dynamics and the predisturbance generation.

The occasional oscillation in large interconnected power system can cause the small‐signal stability problem. As a complement to the damping controllers, the small‐signal stability constrained‐optimal power flow (SSSC‐OPF) model has been used to obtain the required stability margin. Applying the approximate technique to SSSC‐OPF may not only increase the value of the objective function, but also suffer the oscillation of the iterations during the solving process. In this study, an eigenvalue‐optimisation‐based non‐linear semi‐definite programming (NLSDP) model and algorithm is proposed for the small‐signal stability constraints. It is a significant challenge to model the SSSC‐OPF directly because of the implicit and non‐Lipschitz property for the spectral abscissa of the system state matrix. Based on the Lyapunov theorem, the positive definite constraints can express the small‐signal stability accurately and equivalently, so that SSSC‐OPF can be modelled as NLSDP. Afterward, the NLSDP model is transformed into a non‐linear programming problem by formulating the positive definite constraints into non‐linear ones, which can be solved by the interior point method finally. Numerical simulations for two systems confirm the validity of the model and the robustness of the algorithm.

This letter formulates network connectivity as Miller-Tucker-Zemlin (MTZ) constraints and incorporates them into the mixed-integer linear programming (MILP) model for the optimal transmission switching (OTS) problem. The connectivity constraints are linear and for a power network with n buses, m branches, and d loads in pre-contingency or each post-contingency state there are approximately O (n+5m+d) constraints, and O (n) continuous and O (2 m) binary variables, which is much smaller than those in the existing formulations. The MILP OTS model with the proposed connectivity constraints can be readily solved by well-developed MILP solvers. Case studies on the PJM 5-bus system, IEEE 300-bus system, and French 1888-bus system validate the effectiveness of the proposed model.