Optimization and Model-predictive Control for Overload Mitigation in Resilient Power Systems.

The National Academy of Engineering named the electric power grid the greatest engineering achievement of the 20th century. However, as recent large-scale power grid failures illustrate, the (electro-mechanical) electric grid is being operated closer and closer to its limits. Specifically, the electric grid of the 20th century is aging and congested. Due to the protracted and cost-intensive nature of upgrading energy infrastructures, major research initiatives are now underway to improve the utility of the existing infrastructure. One important topic is contingency management. Accordingly, this dissertation comprises of practical, yet rigorously justified, feedback control algorithms that are suitable for power system contingency management. The main goals of the algorithms are to prevent or mitigate overloads on network elements (e.g. lines and transformers). In this dissertation, a coupling of energy infrastructures is examined as a method for improving system reliability and a simple cascade mitigation approach highlights the role of model-predictive control and energy storage in improving system response to severe disturbances (e.g. line outages). The ideas of balancing economic and safety criteria are developed and implemented with a receding-horizon model-predictive controller (RHMPC) for electric transmission systems with energy storage and renewables. The novel RHMPC scheme employs a lossy "DC" power flow model and is proven to alleviate conductor temperature overloads and returns the system to an economically optimal state. Finally, an incentive-based distributed predictive-control algorithm is developed to prevent overloads in the distribution network caused by overnight charging of plug-in electric vehicles. In addition, Matlab-based simulations are included to illustrate the performance and behavior of all proposed overload mitigation schemes. The automatic schemes presented in this dissertation are, essentially, "closing the loop'' in contingency management, and will help bring the electric power grid into the 21st century.PHDElectrical Engineering: SystemsUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/100049/1/malmassa_1.pd

Synchrophasor-based predictive control considering optimal phasor measurement unit placements methods

A blackout is the total collapse of an electric power grid, due to the inability to balance load demand and power generation. Blackouts generally develop from a series of unattended voltage stability problems, stemming from a combination of human and operational errors, and may have fatal consequences. The report on the blackout incident of August 14 2003, which affected parts of the United States and Canada, particularly emphasised the need for improved wide area monitoring of the grid. In the United Kingdom, the recent blackout of August 9 2019 has reinforced the need for increased grid visibility and data recording. These have led to an ever-increasing interest in a family of measurement devices known as Wide Area Monitoring Systems (WAMS). The most popular device in this family is the Phasor Measurement Unit (PMU), which report voltage and current phasors at rates up to 60 samples/second. PMUs may be used to monitor all or part of the grid to prevent future blackouts with timely control actions. The goal is to ’See it fast: Keep it calm’. Wide-area monitoring enhances the possibility of visualizing the electric grid as a single system. This has led to the extension of the application of WAMS from mainly monitoring to wide-area control in relatively recent research efforts. This work explores how predictive control technique may be used to automate the control of power systems voltages at secondary level using an array of synchrophasors. The intuition is to develop a model-free (or synchrophasor-based) control algorithm, which reduces, as much as possible, the need for human interventions in the mitigation of voltage problems, and is fast enough to be applied online in real-time. Although model-based techniques can be applied online, they may not be fast enough for real-time applications. In addition, this method may depend on components’ parameters, which may not be available in practice. The work is split into two parts. First, novel WAMS deployment algorithms —using multi-variable, multi-objective optimization set-ups, which return optimal placement solutions —are presented. Formulations are described for multi-stage deployments given a limited budget and for application-focused cases. Practical issues which may develop are anticipated and addressed. The formulations were shown to return optimal solutions with qualitative placement specifications. In the second part, methods of realizing models from input-output relationships are developed and described. The first involved a method numerical derivatives based on data that are sampled at PMU rates. This may be seen as a viable alternative to the use of trajectory sensitivity, especially for real-time control design. In the second, subspace algorithm are used to realise models. The process is comprehensively described for secondary voltage regulation in normal and emergency situations. The approach is demonstrated on a number of IEEE test cases and the controller’s performance were found to be satisfactory for non-viable voltage regulations. This research work is particularly relevant in a number of ways. Chief among these is that voltage control problems may be handled in real-time without a knowledge of the model parameters. The model-free approach particularly desired since increasing integration of renewable energy sources means that the electric grid is becoming increasingly complex. Another is that the placement algorithms describe all various practical issues around the measurement-based design, which utilities may found useful, especially when they wish to address budget limitation and device compatibility issues

Dynamic Reactive Power Control of Isolated Power Systems

This dissertation presents dynamic reactive power control of isolated power systems. Isolated systems include MicroGrids in islanded mode, shipboard power systems operating offshore, or any other power system operating in islanded mode intentionally or due to a fault. Isolated power systems experience fast transients due to lack of an infinite bus capable of dictating the voltage and frequency reference. This dissertation only focuses on reactive control of islanded MicroGrids and AC/DC shipboard power systems. The problem is tackled using a Model Predictive Control (MPC) method, which uses a simplified model of the system to predict the voltage behavior of the system in future. The MPC method minimizes the voltage deviation of the predicted bus voltage; therefore, it is inherently robust and stable. In other words, this method can easily predict the behavior of the system and take necessary control actions to avoid instability. Further, this method is capable of reaching a smooth voltage profile and rejecting possible disturbances in the system. The studied MicroGrids in this dissertation integrate intermittent distributed energy resources such as wind and solar generators. These non-dispatchable sources add to the uncertainty of the system and make voltage and reactive control more challenging. The model predictive controller uses the capability of these sources and coordinates them dynamically to achieve the voltage goals of the controller. The MPC controller is implemented online in a closed control loop, which means it is self-correcting with the feedback it receives from the system

Simulation And Control At the Boundaries Between Humans And Assistive Robots

Human-machine interaction has become an important area of research as progress is made in the fields of rehabilitation robotics, powered prostheses, and advanced exercise machines. Adding to the advances in this area, a novel controller for a powered transfemoral prosthesis is introduced that requires limited tuning and explicitly considers energy regeneration. Results from a trial conducted with an individual with an amputation show self-powering operation for the prosthesis while concurrently attaining basic gait fidelity across varied walking speeds. Experience in prosthesis development revealed that, though every effort is made to ensure the safety of the human subject, limited testing of such devices prior to human trials can be completed in the current research environment. Two complementary alternatives are developed to fill that gap. First, the feasibility of implementing impulse-momentum sliding mode control on a robot that can physically replace a human with a transfemoral amputation to emulate weight-bearing for initial prototype walking tests is established. Second, a more general human simulation approach is proposed that can be used in any of the aforementioned human-machine interaction fields. Seeking this general human simulation method, a unique pair of solutions for simulating a Hill muscle-actuated linkage system is formulated. These include using the Lyapunov-based backstepping control method to generate a closed-loop tracking simulation and, motivated by limitations observed in backstepping, an optimal control solver based on differential flatness and sum of squares polynomials in support of receding horizon controlled (e.g. model predictive control) or open-loop simulations. v The backstepping framework provides insight into muscle redundancy resolution. The optimal control framework uses this insight to produce a computationally efficient approach to musculoskeletal system modeling. A simulation of a human arm is evaluated in both structures. Strong tracking performance is achieved in the backstepping case. An exercise optimization application using the optimal control solver showcases the computational benefits of the solver and reveals the feasibility of finding trajectories for human-exercise machine interaction that can isolate a muscle of interest for strengthening

Stability enhancement of HVAC grids using HVDC links.

M. Sc. Eng. University of KwaZulu-Natal, Pietermaritzburg 2016.Eskom is facing challenging times where the national power grid is placed under extreme pressure, therefore, the long existing poorly damped low frequency inter area oscillations affects the stability constraints thus reducing the power transfer capacity. Consequently new power stations are being built in remote locations to reduce the short fall of generation capacity and the HVDC technology has become appealing to transport large amount of power over long distance. This research aims to prove that stability enhancement of parallel AC systems can be achieved with the use of HVDC schemes. The HVDC system has the rapid ability to control the transmitted power during transient disturbances and this power system control has a significant effect on the dynamic performance of the system after a disturbance therefore the dynamic performance is related to the small signal stability, where the rotor oscillations are minimised and the system is brought back to steady state after an event or disturbance.The fundamentals of small signal stability in terms of observability, controllability, residues, network sensitivities and mode shape are explained together with a dominant oscillation path definition for HVDC links location selection. The key importance in controlling the power of the HVDC link to affect stability requires that the oscillation is observable and controllable. Simulation results on a simple four-generator, twoarea test system are presented, with a view to benchmark the results and develop a fundamental understanding of how using HVDC links for power transfer can stabilise the grid. The eigenvalue analysis of the system indicates the frequency of oscillations in the system and the generator’s participation factors, together with the controllability and observability of the inter area mode (mode of interest). There are a number of test simulations results from a LCCHVDC system (First Cigrê benchmark model) integrated into a test network where the influence on the small signal stability is analysed. Various literature has been reviewed which supports the basic principles, promoting the benefits of using HVDC systems to enhance stability of a parallel AC system (Hybrid) and then integrating supplementary control. This research investigates the use of the HVDC system to enhance the small signal stability with supplementary control which is termed predictive control. Power Oscillation Damping (POD) control through LCC HVDC links is studied to ensure secure operation of power systems. The Power oscillating damper is expressed as a transfer function whereas the MPC (Model Predictive Controller) is expressed as cost functions of a feedback signal which is a measured quantity. Two feedback signals are selected and their effectiveness with regard to their contribution to the damping of the system is investigated. The controller feedback signals are real power and voltage difference across the AC tie lines. Bode plots, root locus plots and time domain simulation results show the comparison between the different selected controller inputs and supplementary controls. The voltage angle difference is most effective as it is more sensitive to changes in the system and assists the controller in bringing the system to steady state in a shorter period of time when compared to the controller input that uses real power across the AC tie line. The controllers with the HVDC integrated, do improve the damping of the system and it is related to shorter mode decay time, the MPC however has been investigated to reduce the change of loading levels of the AC tie lines following a change in system operating conditions. Simulation responses from the research show that this method is more promising and does not require prior knowledge of the possible contingencies due to its ability to handle complex multi variable systems with constraints, by using cost function algorithms to perform predictions of future plant behaviour and calculating the suitable corrective control actions needed to take the predicted output as close as possible to the target value which is the steady state. This research however demonstrates the fundamental principle which proves that the HVDC together with supplementary control can enhance stability of a parallel AC system

Model-Predictive Control for Alleviating Transmission Overloads and Voltage Collapse in Large-Scale Electric Power Systems

Emergency control in electric power systems requires rapid identification and implementation of corrective actions. Typically, system operators have performed this service while relying on rules-of-thumb and predetermined control sequences with limited decision support tools. Automatic control schemes offer the potential to improve this process by quickly analyzing large, complex problems to identify the most effective actions. Model-predictive control (MPC) is one such scheme which has a strong record of success in the process industry and has begun receiving attention in power systems applications. Incorporating flexibility into the MPC model using energy storage and temperature-based transmission line limits has shown promising results for relieving transmission overloads on small networks with linear active power models. Separately, MPC has demonstrated its capabilities in correcting transformer-driven voltage collapse behaviors. However, a comprehensive solution combines both aspects into a single controller formulation with knowledge of active and reactive power and voltage magnitude and angle. Additionally, most power system networks are large and result in computationally challenging problem formulations. This work considers these practical limitations and suggests techniques to enable an MPC process capable of operating reliably in the real-world. A new linear controller model is proposed which considers voltage magnitude and angle and both active and reactive power. The new model provides greater accuracy when predicting system behavior and better identifies the actual control needs of the system. The problem size is reduced by limiting the model to only those devices which are significantly affected by the emergency conditions. The new approach is shown to identify controls more rapidly and better suppresses undesirable thermal behavior on overloaded transmission lines while avoiding potential voltage collapse situations.PHDElectrical Engineering: SystemsUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/137120/1/jandrewm_1.pd