Browsing by Author "Chamana, Manohar (TTU)"
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Item An Integrated Testbed for Power System Cyber-Physical Operations Training(2023) Chamana, Manohar (TTU); Bhatta, Rabindra (TTU); Schmitt, Konrad (TTU); Shrestha, Rajendra (TTU); Bayne, Stephen (TTU)The increased adoption of information and communication technology for smart grid applications will require innovative cyber–physical system (CPS) testbeds to support research and education in the field. Groundbreaking CPS testbeds with realistic and scalable platforms have progressively gained interest in recent years, with electric power flowing in the physical layer and information flowing in the network layer. However, CPSs are critical infrastructures and not designed for testing or direct training, as any misbehaving in an actual system operation could cause a catastrophic impact on its operation. Based on that, it is not easy to efficiently train professionals in CPSs. Aiming to support the advancement and encourage the training of industry professionals, this paper proposes and develops a complete testbed using a real-time simulator, protection and automation devices, and a supervisory control and data acquisition (SCADA) system. The testbed replicated the performance of smart grids, and the main potential cyber threats that electric grids may face. Different case scenarios include a distribution system protection study, a denial of service (DoS) attack, a jamming attack, a network packet manipulation attack, a sensor data manipulation attack, a false trip command attack, etc. The system’s performance before and after the cyberattacks are studied using packet-sniffing tools and a network packet analyzer. The impact on the grid is analyzed using metrics such as voltage oscillation, frequency deviation, and loss of active power generation. Moreover, the complex interdependencies between the cyber and physical domains are discussed in detail, providing insightful guidelines for key features and design decisions for future smart grid testbeds.Item Analysis of Grid-Forming Inverter Controls for Grid-Connected and Islanded Microgrid Integration(2024) Ward, Laura; Subburaj, Anitha; Demir, Ayda; Chamana, Manohar (TTU); Bayne, Stephen B.Autonomous grid-forming (GFM) inverter testbeds with scalable platforms have attracted interest recently. In this study, a self-synchronized universal droop controller (SUDC) was adopted, tested, and scaled in a small network and a test feeder using a real-time simulation tool to operate microgrids without synchronous generators. We presented a novel GFM inverter control adoption to better understand the dynamic behavior of the inverters and their scalability, which can impact the distribution system (DS). This paper provides a steady-state and transient analysis of the GFM power inverter controller via simulation to better understand voltage and frequency stabilization and ensure that the critical electric loads are not affected during a prolonged power outage. The controllers of the GFM inverter are simulated in HYPERSIM to examine voltage and frequency fluctuations. This analysis includes assessing the black start capability for photovoltaic microgrids, both grid-connected and islanded, during transient fault conditions. The high photovoltaic PV penetration levels open exciting opportunities and challenges for the DS. The GFM inverter control demonstrated appropriate response times for synchronization, connection, and disconnection to the grid. The DS has become more resilient and independent of fossil fuels by increasing the penetration of inverter-based distributed energy resources (DERs).Item Design and Performance Analysis of a Grid-Connected Distributed Wind Turbine(2023) Murshed, Mahtab (TTU); Chamana, Manohar (TTU); Schmitt, Konrad Erich Kork (TTU); Bhatta, Rabindra (TTU); Adeyanju, Olatunji (TTU); Bayne, Stephen (TTU)The utilization of wind energy has become increasingly popular in the United States and many European countries due to its abundant nature and optimized design. While existing wind turbines are predominantly large-scale and not suitable for standalone or distributed power production, Lubbock County in West Texas offers a diverse range of renewable energy options to meet its energy needs. The region relies heavily on utility-scale wind energy sources to supply power to the Texas Grid, replacing conventional fossil fuel-based systems. Currently, standalone solar PV systems are the preferred choice for renewable energy generation. However, West Texas possesses an ample supply of wind energy that can be harnessed to establish a microgrid and provide standalone power to rural communities. Distributed wind energy offers localized power generation, reducing transmission losses and grid strain, while conventional wind farms require long-distance transmission, leading to efficiency gains. By employing the latest technology and optimizing efficiency, even in low-scale generation, a 6-kilowatt permanent magnet alternator-based distributed wind turbine has been designed. This paper focuses on analyzing the techno-economic aspects of implementing this wind turbine in a real-world scenario, taking into account wind attributes, such as velocity and available power, at the specific location.Item Sizing PV and BESS for Grid-Connected Microgrid Resilience: A Data-Driven Hybrid Optimization Approach(2023) Murshed, Mahtab; Chamana, Manohar (TTU); Schmitt, Konrad Erich Kork; Pol, Suhas (TTU); Adeyanju, Olatunji (TTU); Bayne, StephenThis article presents a comprehensive data-driven approach on enhancing grid-connected microgrid grid resilience through advanced forecasting and optimization techniques in the context of power outages. Power outages pose significant challenges to modern societies, affecting various sectors such as industries, households, and critical infrastructures. The research combines statistical analysis, machine-learning algorithms, and optimization methods to address this issue to develop a holistic approach for predicting and mitigating power outage events. The proposed methodology involves the use of Monte Carlo simulations in MATLAB for future outage prediction, training a Long Short-Term Memory (LSTM) network for forecasting solar irradiance and load profiles with a dataset spanning from 2009 to 2018, and a hybrid LSTM-Particle Swarm Optimization (PSO) model to improve accuracy. Furthermore, the role of battery state of charge (SoC) in enhancing system resilience is explored. The study also assesses the techno-economic advantages of a grid-tied microgrid integrated with solar panels and batteries over conventional grid systems. The proposed methodology and optimization process demonstrate their versatility and applicability to a wide range of microgrid design scenarios comprising solar PV and battery energy storage systems (BESS), making them a valuable resource for enhancing grid resilience and economic efficiency across diverse settings. The results highlight the potential of the proposed approach in strengthening grid resilience by improving autonomy, reducing downtime by 25%, and fostering sustainable energy utilization by 82%.