A Wide Area Hierarchical Voltage Control for Systems with High Wind Penetration and an HVDC Overlay

The modern power grid is undergoing a dramatic revolution. On the generation side, renewable resources are replacing fossil fuel in powering the system. On the transmission side, an AC-DC hybrid network has become increasingly popular to help reduce the transportation cost of electricity. Wind power, as one of the environmental friendly renewable resources, has taken a larger and larger share of the generation market. Due to the remote locations of wind plants, an HVDC overlay turns out to be attractive for transporting wind energy due to its superiority in long distance transmission of electricity. While reducing environmental concern, the increasing utilization of wind energy forces the power system to operate under a tighter operating margin. The limited reactive capability of wind turbines is insufficient to provide adequate voltage support under stressed system conditions. Moreover, the volatility of wind further aggravates the problem as it brings uncertainty to the available reactive resources and can cause undesirable voltage behavior in the system. The power electronics of the HVDC overlay may also destabilize the gird under abnormal voltage conditions. Such limitations of wind generation have undermined system security and made the power grid more vulnerable to disturbances. This dissertation proposes a Hierarchical Voltage Control (HVC) methodology to optimize the reactive reserve of a power system with high levels of wind penetration. The proposed control architecture consists of three layers. A tertiary Optimal Power Flow computes references for pilot bus voltages. Secondary voltage scheduling adjusts primary control variables to achieve the desired set points. The three levels of the proposed HVC scheme coordinate to optimize the voltage profile of the system and enhance system security. The proposed HVC is tested on an equivalent Western Electricity Coordinated Council (WECC) system modified by a multi-terminal HVDC overlay. The effectiveness of the proposed HVC is validated under a wide range of operating conditions. The capability to manage a future AC/DC hybrid network is studied to allow even higher levels of wind

Novel sensorless generator control and grid fault ride-through strategies for variable-speed wind turbines and implementation on a new real-time simulation platform

The usage of MW-size variable-speed wind turbines as sources of energy has increased significantly during the last decade. Advantages over fixed-speed wind turbines include more efficient wind power extraction, reduced grid power fluctuation, and improved grid reactive power support. Two types of typical generation systems for large-size variable-speed wind turbines exist. One is the doubly-fed induction generator (DFIG) with a partial-scale power electronic converter. The other is the permanent-magnet synchronous generator (PMSG) with a full-scale power electronic converter. This research is to develop the model of these two wind turbine systems for real-time simulation, including the complete aerodynamic and mechanical and electrical components. The special focus of this dissertation addresses the mechanical sensorless control of wind generators and grid fault ride-through strategies. In the electrical controller of a DFIG, A mechanical speed sensor is normally required to provide accurate information of the machine speed and rotor position. However, sensorless operation is desirable because the use of a mechanical speed sensor coupled with the machine shaft has several drawbacks in terms of degraded robustness, extra cost and cabling, and difficult maintenance. In this dissertation, design and analysis of a novel sensorless vector controller using a reduced-order state observer is addressed in detail. Results have revealed that the proposed sensorless observer is more robust against parameter variations than other speed estimation schemes. Nowadays, almost all the grid code specifications over the world have included fault ride-through requirements for grid-connected wind turbines. In US, as mandated by the Federal Energy Regulatory Commission (FERC) Order 661-A, wind farms are required to remain online in the presence of severe voltage disturbances as low as 0.0 pu, as measured at the high voltage side of the wind generator step-up transformer, for up to 9 cycles (150 ms). These strict requirements present a significant challenge to the existing wind turbine technologies. In this dissertation, an improved technique combining the traditional crowbar protection circuit and the demagnetizing current injection to ride-through symmetrical grid voltage dips is analyzed and verified for a DFIG-based wind turbine. Also, an improved fault ride-through control strategy without using any extra protection hardware for a PMSG-based wind turbine to mitigate the dc-link overvoltage is developed. In this dissertation, a new real-time simulation platform is developed based on industry standard simulation tools, RTDS and dSPACE. The aforementioned wind turbine models and proposed sensorless controller as well as fault ride-through strategies are all implemented in real-time on this hardware-in-the-loop type of simulation platform. The necessary measures in hardware and software aspects to enable the collaborative simulation of these two industry standard simulators are addressed. Results have shown this integrated real-time simulation platform has broad application prospects in wind turbine controller design and grid interconnection studies

Advanced control schemes for wind power plants and renewable energy-based islanded microgrids

Renewable energy sources are increasingly integrated in power grids, creating significant challenges for control and system operation. Among various renewable energy sources, wind power is one of the dominant forms, mainly generated from large-scale transmission-connected wind power plants (WPPs). The grid-connected WPPs are required to follow grid codes to maintain a predefined power factor range under normal operation and supply required reactive power under faulty conditions. To meet grid code requirements, a WPP control architecture is developed in this thesis. The control system consists of a central WPP controller and a local wind turbine generator (WTG) controller, both operate in the voltage control mode. Therefore, the controller can respond faster and is robust to communication failures. Under normal operating conditions, the proposed controller regulates the WPP’s operation within its steady-state reactive power capability and meets the power factor limits. Under faulty conditions, the controller forces the WPP to its maximum capability to contribute more reactive power support to the grid. Two mathematical models representing the steady-state and maximum reactive power capability of the WPP are developed through regression and analytic approaches, respectively. In the second part of the thesis, a model predictive control (MPC)-based distributed generation (DG) controller is proposed to regulate the voltage and frequency at the point of common coupling (PCC) in an islanded microgrid. A data-driven input-output Box-Jenkins polynomial predictive model for DG control is developed using the Gauss-Newton-based nonlinear least square method with the prediction optimization focus. The model inputs are direct- and quadrature-axis components of the control signal, and the model outputs are deviations of the voltage and frequency from their nominal values at the PCC. The proposed MPC controller operates using the PCC data and does not require the microgrid’s central controllers or DG-to-DG communication networks. It can effectively compensate voltage and frequency deviations at the PCC and ensure proportional reactive power sharing among DGs without a secondary controller and a virtual impedance loop. The integrated Kalman filter in the MPC structure enables a robust controller design when subjected to impedance variations and measurement noises

Wide-area monitoring and control of future smart grids

Application of wide-area monitoring and control for future smart grids with substantial wind penetration and advanced network control options through FACTS and HVDC (both point-to-point and multi-terminal) is the subject matter of this thesis. For wide-area monitoring, a novel technique is proposed to characterize the system dynamic response in near real-time in terms of not only damping and frequency but also mode-shape, the latter being critical for corrective control action. Real-time simulation in Opal-RT is carried out to illustrate the effectiveness and practical feasibility of the proposed approach. Potential problem with wide-area closed-loop continuous control using FACTS devices due to continuously time-varying latency is addressed through the proposed modification of the traditional phasor POD concept introduced by ABB. Adverse impact of limited bandwidth availability due to networked communication is established and a solution using an observer at the PMU location has been demonstrated. Impact of wind penetration on the system dynamic performance has been analyzed along with effectiveness of damping control through proper coordination of wind farms and HVDC links. For multi-terminal HVDC (MTDC) grids the critical issue of autonomous power sharing among the converter stations following a contingency (e.g. converter outage) is addressed. Use of a power-voltage droop in the DC link voltage control loops using remote voltage feedback is shown to yield proper distribution of power mismatch according to the converter ratings while use of local voltages turns out to be unsatisfactory. A novel scheme for adapting the droop coefficients to share the burden according to the available headroom of each converter station is also studied. The effectiveness of the proposed approaches is illustrated through detailed frequency domain analysis and extensive time-domain simulation results on different test systems

Transient stability assessment of hybrid distributed generation using computational intelligence approaches

Includes bibliographical references.Due to increasing integration of new technologies into the grid such as hybrid electric vehicles, distributed generations, power electronic interface circuits, advanced controllers etc., the present power system network is now more complex than in the past. Consequently, the recent rate of blackouts recorded in some parts of the world indicates that the power system is stressed. The real time/online monitoring and prediction of stability limit is needed to prevent future blackouts. In the last decade, Distributed Generators (DGs) among other technologies have received increasing attention. This is because DGs have the capability to meet peak demand, reduce losses, due to proximity to consumers and produce clean energy and thus reduce the production of CO₂. More benefits can be obtained when two or more DGs are combined together to form what is known as Hybrid Distributed Generation (HDG). The challenge with hybrid distributed generation (HDG) powered by intermittent renewable energy sources such as solar PV, wind turbine and small hydro power is that the system is more vulnerable to instabilities compared to single renewable energy source DG. This is because of the intermittent nature of the renewable energy sources and the complex interaction between the DGs and the distribution network. Due to the complexity and the stress level of the present power system network, real time/online monitoring and prediction of stability limits is becoming an essential and important part of present day control centres. Up to now, research on the impact of HDG on the transient stability is very limited. Generally, to perform transient stability assessment, an analytical approach is often used. The analytical approach requires a large volume of data, detailed mathematical equations and the understanding of the dynamics of the system. Due to the unavailability of accurate mathematical equations for most dynamic systems, and given the large volume of data required, the analytical method is inadequate and time consuming. Moreover, it requires long simulation time to assess the stability limits of the system. Therefore, the analytical approach is inadequate to handle real time operation of power system. In order to carry out real time transient stability assessment under an increasing nonlinear and time varying dynamics, fast scalable and dynamic algorithms are required. Transient Stability Assessment Of Hybrid Distributed Generation Using Computational Intelligence Approaches These algorithms must be able to perform advanced monitoring, decision making, forecasting, control and optimization. Computational Intelligence (CI) based algorithm such as neural networks coupled with Wide Area Monitoring System (WAMS) such as Phasor Measurement Unit (PMUs) have been shown to successfully model non-linear dynamics and predict stability limits in real time. To cope with the shortcoming of the analytical approach, a computational intelligence method based on Artificial Neural Networks (ANNs) was developed in this thesis to assess transient stability in real time. Appropriate data related to the hybrid generation (i.e., Solar PV, wind generator, small hydropower) were generated using the analytical approach for the training and testing of the ANN models. In addition, PMUs integrated in Real Time Digital Simulator (RTDS) were used to gather data for the real time training of the ANNs and the prediction of the Critical Clearing Time (CCT)