This paper investigates the impact of powergrid strength and phase-locked loop (PLL) parameters on small signal stability of grid-connected doubly fed induction generator (DFIG)based wind farm. Modal ...analysis of the grid-connected DFIG wind turbine under different operating conditions and various power grid strengths are investigated at first. Modal analysis results reveal that the DFIG connected to a weak grid may easily lose stability under the heavy-duty operating conditions due to PLL oscillation. The object of this paper is to identify the PLL oscillation mechanism as well as influence factors and propose a damping solution for this oscillation mode. A simplified linear system model of the grid-connected DFIG wind turbine is proposed for analyzing the PLL oscillation. Through the complex torque coefficients method and using this model, the oscillation mechanism and influence factors including the power grid strength and the PLL parameters are identified. To suppress this PLL oscillation, a mixed H 2 /H ∞ robust damping controller is proposed and designed for the DFIG. Electromagnetic transient simulation results of both singleDFIG system and multiply-DFIG system verify the correctness of the analysis results and effectiveness of the proposed damping controller.
Low-frequency oscillation is one of the main barriers limiting power transmission between two connected power systems. Although power system stabilizers (PSSs) have been proved to be effective in ...damping inner-area oscillation, inter-area oscillation still remains a critical challenge in today's power systems. Since the low-frequency oscillation between two connected power systems is active power oscillation, power modulation through energy storage devices (ESDs) can be an efficient and effective way to maintain such power system stability. In this paper, we investigate the integration of a new goal representation heuristic dynamic programming (GrHDP) algorithm to adaptively control ESD to damp inter-area oscillation. A particle swarm optimization (PSO)-based power oscillation damper (POD) has also been proposed for comparison. Various simulation studies with residue-based POD controller design, the proposed PSO optimized controller design, and the GrHDP-based controller design over a four-machine-two-area benchmark power system with energy storage device have been conducted. Simulation results have demonstrated the efficiency and effectiveness of the GrHDP-based approach for inter-area oscillation damping in a wide range of system operating conditions.
This paper proposed a probabilistic load flow method that can address the correlated power sources and loads. The proposed probabilistic load flow method is based on the Nataf transformation and the ...Latin Hypercube Sampling. The main advantage of the proposed method is that high accurate solution can be obtained with less computation. Also, it is almost unconstrained for the probability distributions of the input random variables. Considering the uncertainties of correlated wind power, solar energy and loads, the effectiveness and the accuracy of the proposed probabilistic load flow method are verified by the comparative tests in a modified IEEE 14-bus system and a modified IEEE 118-bus system.
In this paper, we present a new adaptive dynamic programming approach by integrating a reference network that provides an internal goal representation to help the systems learning and optimization. ...Specifically, we build the reference network on top of the critic network to form a dual critic network design that contains the detailed internal goal representation to help approximate the value function. This internal goal signal, working as the reinforcement signal for the critic network in our design, is adaptively generated by the reference network and can also be adjusted automatically. In this way, we provide an alternative choice rather than crafting the reinforcement signal manually from prior knowledge. In this paper, we adopt the online action-dependent heuristic dynamic programming (ADHDP) design and provide the detailed design of the dual critic network structure. Detailed Lyapunov stability analysis for our proposed approach is presented to support the proposed structure from a theoretical point of view. Furthermore, we also develop a virtual reality platform to demonstrate the real-time simulation of our approach under different disturbance situations. The overall adaptive learning performance has been tested on two tracking control benchmarks with a tracking filter. For comparative studies, we also present the tracking performance with the typical ADHDP, and the simulation results justify the improved performance with our approach.
The renewable energy sources (RESs) dominated power grid is an envisaged infrastructure of the future power system, where the commonly used grid following (GFL) control for grid-tied converters ...suffers from lacking grid support capability, low stability, etc. Recently, emerging grid forming (GFM) control methods have been proposed to improve the dynamic performance and stability of grid-tied converters. This paper reviews existing GFM control methods for the grid-tied converters and compares them in terms of control structure, grid support capability, fault current limiting, and stability. Considering the impact of fault current limiting strategies, a comprehensive transient stability analysis is provided. In addition, this paper explores the typical applications of GFM converters, such as AC microgrid and offshore wind farm high-voltage direct current (OWF-HVDC) integration systems. Finally, the challenges to the GFM converters in future applications are discussed.
Wide-area damping controller (WADC) requires communication networks to transmit remote signals. The usage of communication networks will introduce time delays into the control loop of the WADC. ...Ignoring this time delay would deteriorate the damping performance provided by the WADC or even cause the whole system instability. This paper employs networked predictive control (NPC) to design a WADC for the generator exciter to enhance the damping of interarea oscillations in a large-scale power system. The NPC incorporates with a generalized predictive control (GPC) to generate optimal control predictions, and a network delay compensator to detect and compensate both constant and random delays. Moreover, model identification is used to obtain an equivalent reduced-order model of the large-scale power system and deal with the model uncertainties and variation of operating conditions. Case studies are based on the New England 10-machine 39-bus system. Effectiveness of the proposed WADC is verified by simulation studies and compared with a conventional WADC and a GPC-based WADC without delay compensation.
With the increasing penetration of wind power in power systems, it is desirable for wind turbines to have similar characteristics as conventional synchronous generators. Conventional generators ...provide frequency support to the grid through the methods of inertial response and primary and secondary frequency regulation, whereas variable-speed wind turbine generators (WTGs) do not have those desired abilities because they are integrated into the power grid via power electronic converters. Although many different control strategies have already been published to enable WTGs to temporarily support the transient frequency, the published strategies may bring various negative effects to the system. This paper proposes a new control strategy to compensate for inertia of the wind farm. It can improve WTGs' temporary frequency support based on the coordinated control of the WTGs and the energy storage (ES) system. The simulation results show that this strategy could provide better performance of temporary frequency support and overcome problems such as system frequency oscillation and a secondary frequency drop. The proposed control strategy can be realized in all wind speed conditions with a small-scale ES system.
Interarea oscillation is one of the main challenges for the secure and stable operation of a large-scale interconnected power system. To address this problem, this paper presents an adaptive ...supplementary damping controller (SDC) for voltage source converter based high voltage direct current (VSC-HVDC) by using the goal representation heuristic dynamic programming (GrHDP). Compared with conventional heuristic dynamic programming (HDP), GrHDP adds a new goal representation network to generate an adaptive reward signal to achieve better mapping relationship between the system states and the control action. To compensate phase shift between the output and input signals of a large-scale interconnected AC/DC power system, this paper proposes a parallel phase shift channel for the GrHDP. Moreover, the proposed GrHDP-SDC is a model-free control scheme, which does not need the mathematic model of the power system and has quick online learning ability to adapt to the variation of system operating conditions. Case studies are carried out on the 10-machine 39-bus system and 16-machine 68-bus system, respectively. Compared with the conventional lead-lag SDC (LL-SDC) and HDP-SDC, simulation results show that the proposed GrHDP-SDC can always provide satisfactory damping performance over a wide range of system operating conditions and disturbances.
Goal representation heuristic dynamic programming (GrHDP) is proposed in this paper to demonstrate online learning in the Markov decision process. In addition to the (external) reinforcement signal ...in literature, we develop an adaptively internal goal/reward representation for the agent with the proposed goal network. Specifically, we keep the actor-critic design in heuristic dynamic programming (HDP) and include a goal network to represent the internal goal signal, to further help the value function approximation. We evaluate our proposed GrHDP algorithm on two 2-D maze navigation problems, and later on one 3-D maze navigation problem. Compared to the traditional HDP approach, the learning performance of the agent is improved with our proposed GrHDP approach. In addition, we also include the learning performance with two other reinforcement learning algorithms, namely Sarsa(λ) and Q-learning, on the same benchmarks for comparison. Furthermore, in order to demonstrate the theoretical guarantee of our proposed method, we provide the characteristics analysis toward the convergence of weights in neural networks in our GrHDP approach.
Self-blocking modular multilevel converter (SB-MMC) is able to block dc fault current with relatively lower number of power semiconductors and lower valve power loss compared to other dc fault ...tolerant MMC topologies. Operating principle, design, reliability, and redundancy analysis of SB-MMC have been studied while the equivalent modeling and application of SB-MMC at overhead VSC-HVDC have not been fully investigated. Since operating principle of SB-MMC is different from half-bridge MMC, the existing equivalent modeling method of half-bridge MMC cannot be directly applied to modeling of SB-MMC. As dc fault at overhead VSC-HVDC are typically temporary, how to securely and quickly restart a VSC-HVDC after isolating dc fault also needs detailed studies. To solve the above two challenges, an equivalent model (EM) and a fast recovery control of overhead VSC-HVDC based on SB-MMC are proposed. Accuracy of the proposed model is verified by extensive simulations in PSCAD/EMTDC. The proposed fast recovery control further exploits the control capability of SB-MMC and enables fast and secure recovery of overhead VSC-HVDC based on SB-MMC. The proposed model and controllers also provide guidance for the modeling and application of other MMC topologies that are able to block dc fault current.
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