Power System Stability Analysis using Neural Network

This work focuses on the design of modern power system controllers for automatic voltage regulators (AVR) and the applications of machine learning (ML) algorithms to correctly classify the stability of the IEEE 14 bus system. The LQG controller performs the best time domain characteristics compared to PID and LQG, while the sensor and amplifier gain is changed in a dynamic passion. After that, the IEEE 14 bus system is modeled, and contingency scenarios are simulated in the System Modelica Dymola environment. Application of the Monte Carlo principle with modified Poissons probability distribution principle is reviewed from the literature that reduces the total contingency from 1000k to 20k. The damping ratio of the contingency is then extracted, pre-processed, and fed to ML algorithms, such as logistic regression, support vector machine, decision trees, random forests, Naive Bayes, and k-nearest neighbor. A neural network (NN) of one, two, three, five, seven, and ten hidden layers with 25%, 50%, 75%, and 100% data size is considered to observe and compare the prediction time, accuracy, precision, and recall value. At lower data size, 25%, in the neural network with two-hidden layers and a single hidden layer, the accuracy becomes 95.70% and 97.38%, respectively. Increasing the hidden layer of NN beyond a second does not increase the overall score and takes a much longer prediction time; thus could be discarded for similar analysis. Moreover, when five, seven, and ten hidden layers are used, the F1 score reduces. However, in practical scenarios, where the data set contains more features and a variety of classes, higher data size is required for NN for proper training. This research will provide more insight into the damping ratio-based system stability prediction with traditional ML algorithms and neural networks.Comment: Masters Thesis Dissertatio

Design and Control of Virtual Synchronous Machine Based Energy Systems

Conventionally, the operation and stability of power systems have been governed by the dynamics of large synchronous generators (SGs) which provide the inertial support required to maintain the resilience and stability of the power system. How-ever, the commitment of the UK to drive a zero-carbon economy is accelerating the integration of renewable energy sources (RESs) into the power system. Since the dynamics and operation of RESs differs from SGs, the large-scale integration of RESs will significantly impact the control and stability of the power system.This thesis focuses on the design of grid-friendly control algorithms termed virtual synchronous machines (VSMs), which mimic the desirable characteristics of SGs. Although several VSM topologies have been proposed in literature, most of them require further modifications before they can be integrated into the grid. Hence, a novel VSM algorithm for permanent magnet synchronous generator based wind turbines has been proposed in this thesis.The proposed VSM performs seamlessly in all operating modes and enables maxi-mum power point tracking in grid-connected operation (assuming strong grid), load following power generation in islanded mode and fault ride-through during faults. To ensure optimal performance of the VSM in all operating modes, a comprehensive stability analysis of the VSM was performed in the event of small and large per-turbations. The result of the analysis was used to establish design guidelines and operational limits of the VSM.This thesis further evaluates the impact of VSMs on the power systems low-frequency oscillations (LFOs). A detailed two-machine test-bed was developed to analyze the LFOs which exists when VSMs replace SGs. The characteristics of the LFO modes and the dominant states was comprehensively analyzed. The LFO modes which exists in an all-VSM grid was also analyzed. Further, the role of the power system stabilizers in an all-VSM grid was comprehensively evaluated. An IEEE benchmark two-area four-machine system was employed to validate the results of the small-signal analysis.The analysis and time-domain simulations in this thesis were performed in the MAT-LAB/SIMULINK environment

Robust Design of FACTS Wide-Area Damping Controller Considering Signal Delay for Stability Enhancement of Power System

制度:新 ; 報告番号:甲3426号 ; 学位の種類:博士(工学) ; 授与年月日:2011/9/15 ; 早大学位記番号:新575