Deping Ke

Wind Power Ramp Event Forecasting Using a Stochastic Scenario Generation Method

Wind power ramp events (WPREs) have received increasing attention in recent years as they have the potential to impact the reliability of power grid operations. In this paper, a novel WPRE forecasting method is proposed which is able to estimate the probability distributions of three important properties of the WPREs. To do so, a neural network (NN) is first proposed to model the wind power generation (WPG) as a stochastic process so that a number of scenarios of the future WPG can be generated (or predicted). Each possible scenario of the future WPG generated in this manner contains the ramping information, and the distributions of the designated WPRE properties can be stochastically derived based on the possible scenarios. Actual wind power data from a wind power plant in the Bonneville Power Administration (BPA) were selected for testing the proposed ramp forecasting method. Results showed that the proposed method effectively forecasted the probability of ramp events.

An Eigenstructure-Based Performance Index and Its Application to Control Design for Damping Inter-Area Oscillations in Power Systems

An eigenstructure-based performance index is proposed in this paper to measure the dynamic performance of the system as well as control efforts. Calculation of this index is based on eigenstructure of the closed loop system and the design parameters; it does not rely on control structures. Therefore, this index can be applied for solving structurally constrained control problems. A tuning scheme based on this index is proposed for coordinating power system stabilizers (PSSs) and supplementary damping controllers (SDCs) for flexible AC transmission systems (FACTS) devices to damp inter-area oscillations of systems and to optimize their control efforts under multiple operating conditions. Both PSSs and SDCs utilize control structures as a low order single-input-single-output phase lead-lag compensator. Wide-area signals are employed to upgrade their effectiveness in damping inter-area oscillations. Time delays caused by usage of wide-area signals are also considered in the tuning scheme. Results of simulation on a four-machine two-area system and the New England and New York interconnected system show that the proposed index is effective in measuring dynamic performance of the system and the coordinatedly tuned PSSs and SDCs based on this index can robustly damp inter-area oscillations of systems with optimized control efforts.

A Novel Probabilistic Optimal Power Flow Model With Uncertain Wind Power Generation Described by Customized Gaussian Mixture Model

A novel probabilistic optimal power flow (P-OPF) model with chance constraints that considers the uncertainties of wind power generation (WPG) and load is proposed in this paper. An affine generation dispatch strategy is adopted to balance the system power uncertainty by several conventional generators, and thus the linear approximation of the cost function with respect to the power uncertainty is proposed to compute the quantile (which is also recognized as the value-at-risk) corresponding to a given probability value. The proposed model applies this quantile as the objective function and minimizes it to meet distinct probabilistic cost regulation purposes via properly selecting the given probability. In particular, the hedging effect due to the used affine generation dispatch is also thoroughly investigated. In addition, an analytical method to calculate probabilistic load flow (PLF) is developed with the probability density function of WPG, which is proposed to be approximated by a customized Gaussian mixture model whose parameters are easily obtained. Accordingly, it is successful to analytically compute the chance constraints on the transmission line power and the power outputs of conventional units. Numerical studies of two benchmark systems show the satisfactory accuracy of the PLF method, and the effectiveness of the proposed P-OPF model.

An Optimized Swinging Door Algorithm for Identifying Wind Ramping Events

With the increasing penetration of renewable energy in recent years, wind power ramp events (WPREs) have started affecting the economic and reliable operation of power grids. In this paper, we develop an optimized swinging door algorithm (OpSDA) to improve the state of the art in WPREs detection. The swinging door algorithm (SDA) is utilized to segregate wind power data through a piecewise linear approximation. A dynamic programming algorithm is performed to optimize the segments by: 1)merging adjacent segments with the same ramp changing direction; 2)handling wind power bumps; and 3)postprocessing insignificant-ramps intervals. Measured wind power data from two case studies are utilized to evaluate the performance of the proposed OpSDA. Results show that the OpSDA provides 1)significantly better performance than the SDA and 2)equal-to-better performance compared to the L1-Ramp Detect with Sliding Window (L1-SW) method with significantly less computational time.

An Inter-Area Mode Oriented Pole-Shifting Method With Coordination of Control Efforts for Robust Tuning of Power Oscillation Damping Controllers

An inter-area mode oriented pole-shifting method (named: IAMO-PS) with coordination of control efforts is proposed in this paper to tune power oscillation damping controllers under multiple operating conditions. Firstly, to provide incentives for developing IAMO-PS, a pole-shifting method (named: SCCS-PS), which tunes the controllers by moving all closed loop poles to a sequentially compressed conic section in the complex plane, is proposed to investigate impact of other modes on the control of inter-area modes. Thus, compared to SCCS-PS, a specific pole placement suitable for damping control of inter-area modes is implemented in IAMO-PS. Moreover, since a novel index is proposed to effectively measure control effort of the controller, IAMO-PS is capable of reasonably allocating the control burden among different controllers, which will be attractive for applications in practice. Optimization of both methods is solved by the efficient method of sequential quadratic programming, and a two-stage optimization procedure is proposed for IAMO-PS so that a feasible solution can be easily obtained in practical applications. Both methods are applied for control coordination in the New England and New York interconnected systems. Simulation results verify the effectiveness of IAMO-PS in robustly mitigating inter-area oscillations and coordinating control efforts, and some beneficial conclusions are also confirmed by comparing control results of the two methods.

Advanced Auxiliary Control of an Energy Storage Device for Transient Voltage Support of a Doubly Fed Induction Generator

This paper proposes to employ an energy storage device (ESD) to assist a doubly fed induction generator (DFIG) in providing the required reactive power to the grid during severe grid faults. The energy storage side converter (ESC) that connects the ESD to the rotor circuit is placed in parallel and coordinated with the normally sized rotor-side converter (RSC) to provide the rotor demagnetizing and reactive currents. Moreover, by appropriate distribution of these two rotor current components between the ESC and the RSC, the required current rating of the ESC and the energy capacity of the ESD are optimized. In particular, this paper proposes to utilize the ESD for the above control objective in an auxiliary control manner, where the primary objective of the ESD is also for steady-state active power regulation for the DFIG. This improves the overall performance/cost ratio of the ESD. The proposed use of the ESD for the transient reactive power control of the DFIG is not only a technically advanced but also economically feasible and promising alternative to the existing control methods for enhancing the transient performance of DFIGs. Numerical simulations are performed to validate the proposed control method.

Transient Reconfiguration and Coordinated Control for Power Converters to Enhance the LVRT of a DFIG Wind Turbine With an Energy Storage Device

This paper proposes a novel transient reconfiguration solution and coordinating control strategy for power converters to enhance the fault ride through and transient voltage support capabilities of a doubly-fed induction generator with an energy storage device (DFIG-ESD). During a grid fault, the connection of the grid-side converter is reconfigured such that it is connected to the rotor circuit in parallel with the rotor-side converter to provide an additional route for the rotor current, while the ESD is responsible for dc-link voltage regulation. A coordinated demagnetizing and reactive current control strategy is designed for the reconfigured DFIG during transient conditions. Specifically, the demagnetizing current is used to counteract the dc and negative-sequence stator flux components so that the transient electromotive force will be reduced. Simultaneously, the reactive current is added to meet the reactive power support requirement. The enhanced low-voltage ride through (LVRT) and transient voltage support capabilities obtained from the proposed design are demonstrated on the DFIG-ESD wind conversion system under different severe fault scenarios (asymmetrical and symmetrical fault). Additionally, The enhanced transient voltage support capability of the proposed design is further demonstrated by comparing with different control strategies.

Design of Probabilistically-Robust Wide-Area Power System Stabilizers to Suppress Inter-Area Oscillations of Wind Integrated Power Systems

This paper proposes a systematic approach to coordinately design probabilistically-robust wide-area power system stabilizers (WPSSs) for suppressing inter-area oscillations of power systems incorporating wind power. Specifically, the operating point of the system varies stochastically due to wind power integration and each operating point corresponds to a wind power generation scenario in the steady state. Thus, the WPSSs tuned by solving a delicately formulated optimization problem can maximize the occurrence probability of scenarios where the inter-area modes possess the acceptable damping ratios, and strictly constrain their unfavorable impacts. Multiple contingencies are also directly considered. In addition, several advanced techniques are tactfully employed for accurate and efficient evaluation of occurrence probability (objective function) during the optimization so as to ensure the proposed tuning method can deal with the highly nonlinear relationships between the system eigenvalues and the steady-state power outputs of wind farms; a customized differential evolution algorithm is proposed as well to efficiently solve the formulated optimization problem. Simulations and comparisons conducted on two classic test systems with proper modifications show the effectiveness and efficiency of the proposed control design method.

Wind power ramping product for increasing power system flexibility

With increasing penetrations of wind power, system operators are concerned about a potential lack of system flexibility and ramping capacity in real-time dispatch stages. In this paper, a modified dispatch formulation is proposed considering the wind power ramping product (WPRP). A swinging door algorithm (SDA) and dynamic programming are combined and used to detect WPRPs in the next scheduling periods. The detected WPRPs are included in the unit commitment (UC) formulation considering ramping capacity limits, active power limits, and flexible ramping requirements. The modified formulation is solved by mixed integer linear programming. Numerical simulations on a modified PJM 5-bus System show the effectiveness of the model considering WPRP, which not only reduces the production cost but also does not affect the generation schedules of thermal units.

An optimized swinging door algorithm for wind power ramp event detection

Significant wind power ramp events (WPREs) are those that influence the integration of wind power, and they are a concern to the continued reliable operation of the power grid. As wind power penetration has increased in recent years, so has the importance of wind power ramps. In this paper, an optimized swinging door algorithm (SDA) is developed to improve ramp detection performance. Wind power time series data are segmented by the original SDA, and then all significant ramps are detected and merged through a dynamic programming algorithm. An application of the optimized SDA is provided to ascertain the optimal parameter of the original SDA. Measured wind power data from the Electric Reliability Council of Texas (ERCOT) are used to evaluate the proposed optimized SDA. Results show that the proposed optimized SDA method provided better performance than the L1-Ramp Detect with Sliding Window (L1-SW) method but with significantly less (almost 1,400 seconds less) computational requirements, and it was also used as a baseline to determine the optimal value of the tunable parameter in the original SDA for ramp detection.