Houhe Chen

Real-time wide-area loading margin sensitivity (WALMS) in power systems

Loading margin sensitivity (LMS) has been widely used in applications in the realm of voltage stability assessment and control. Typically, LMS is derived based on system equilibrium equations near bifurcation and therefore requires full detailed system model and significant computation effort. Availability of phasor measurement units (PMUs) due to the recent development of wide-area monitoring system (WAMS) provides an alternative computation-friendly approach for calculating LMS. With such motivation, this work proposes measurement-based wide-area loading margin sensitivity (WALMS) in bulk power systems. The proposed sensitivity, with its simplicity, has great potential to be embedded in real-time applications. Moreover, the calculation of the WALMS is not limited to low voltage near bifurcation point. A case study on IEEE 39-bus system verifies the proposed sensitivity. Finally, a voltage control scenario demonstrates the potential application of the WALMS.

Confidence interval estimates for loading margin sensitivity for voltage stability monitoring in the presence of renewable energy

In modern power systems, the integration of variable and random renewable energy brings more challenges to real-time voltage stability monitoring and control. Loading margin sensitivity (LMS) is an index that is widely-used to evaluate voltage stability. The accuracy of LMS relies on the credibility of the data collected by local measurement units, which are used to estimate the system model parameters. Considering the noise signals and the variability of renewable generation, this paper proposes a probabilistic LMS calculation method based on bootstrap technique. Through the bootstrap, the proposed method provides a confidence interval estimate for LMS, which is effective to implement in the presence of renewable generation. Finally, the effectiveness of the proposed method is demonstrated by a TSAT simulation on the 48-machine 140-bus NPCC system.

A two-stage MILP formulation for source-load coordinated dispatch with wind power considering peak-valley regulation and ramping requirements

In this paper, a two-stage mixed integer linear programming (MILP) formulation for source-load coordinated dispatch with wind power considering peak-valley regulation and ramping requirements is proposed. First, the peak-load regulation and ramping requirements of the net load curve are analyzed. Second, the first stage optimization model considering incentive-based demand response (IDR) is formulated to optimize the net load curve, in which the objective function is to minimize the compensation costs of IDR. Several constraints are taken into account to reduce the peak-valley regulation needs and meet the ramping requirements. Then, based on the optimized load curve, the second stage day-ahead dispatch optimization model is proposed to optimize the allocation of generation sources, taking the total costs of power generation minimization as the objective function considering thermal unit reserve costs. The proposed model is applied to a 10-unit system with a wind power farm with 600MW installed capacity. Simulation results demonstrate the effectiveness and feasibility of the proposed model.