Browsing by Author "Jain, Akshay Kumar"

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    Enhancing PV Hosting Capacity of Distribution Feeders using Voltage Profile Design
    Jain, Akshay Kumar (Virginia Tech, 2018-03-06)
    Distribution feeders form the last leg of the bulk power system and have the responsibility of providing reliable power to the customers. These feeders experience voltage drops due to a combination of feeder length, load distribution, and other factors. Traditionally, voltage drop was a major concern. Now, due to an ever-increasing PV penetration, overvoltage has also become a major concern. This limits the amount of solar PV that may be integrated. Few solutions exist to improve the voltage profile, where the most common is the use of voltage control devices like shunt capacitors and voltage regulators. Due to a large number of design parameters to be considered, the determination of the numbers and locations of these devices is a challenging problem. Significant research has been done to address this problem, utilizing a wide array of optimization techniques. However, many utilities still determine these locations and numbers manually. This is because most algorithms have not been adequately validated. The validation of a voltage profile design (VPD) algorithm has been presented here. The validation of this algorithm was carried out on a set of statistically relevant feeders. These feeders were chosen based on the results obtained from a feeder taxonomy study using clustering analysis. The algorithm was found to be effective in enhancing the amount of solar PV a feeder may host, while still maintaining all the voltages within the ANSI standard limits. Furthermore, the methodology adopted here may also be used for the validation of other algorithms.
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    Integrated Optimal Dispatch, Restoration and Control for Microgrids
    Jain, Akshay Kumar (Virginia Tech, 2024-05-22)
    Electric grids across the world are experiencing an ever increasing number of extreme events ranging from extreme weather events to cyberattacks. Such extreme events have the potential to cause widespread power outages and even a blackout. A vast majority of power outages impacting the U.S. electric grid impact the distribution system. There are an estimated five million miles of distribution lines in the US electric grid. A majority of these lines are low-clearance overhead lines making them even more susceptible to damage during extreme events. However, this vital component of the U.S. electric grid remained neglected until recently. In recent decades, the integration of distributed energy resources (DERs) such as solar photovoltaic systems and battery energy storage systems at the grid edge have provided a major opportunity for enhancing the resilience of distribution systems. These DERs can be used to restore power supply when the bulk grid becomes unavailable. However, managing the interactions among different types of DERs has been challenging. Low inertia and significant differences in time constants of operation between conventional generation and inverter based resources (IBRs) are some of these challenges. Widespread deployment of microgrid controller capabilities can be a promising solution to manage these interactions. However, due to interoperability and integration challenges of optimization and dynamics control systems, power conversion systems and communication systems, the adoption of microgrids especially in underserved communities has been slow. The research presented in this dissertation is a significant step forward in this direction by proposing an approach which integrates optimal dispatch, sequential microgrid restoration and control algorithms. Potential cyberattack paths are identified by creating a detailed cyber-physical system model for microgrids. A two-tiered intrusion detection system is developed to detect and mitigate cyberattacks within the cyber layer itself. The developed sequential microgrid restoration algorithm coordinates optimal DER dispatch with the operation of legacy devices with no remote control or communication capabilities and net-metered loads with limited communications. By better utilizing the control capabilities of IBRs, reliance on low-latency centralized control algorithms has also been reduced. The developed approach systematically ensures adequate availability of control during dispatch and restoration to maintain microgrid stability. This research can thus pave the way for faster and more cost-effective deployment of microgrids.