The increasing deployment of Synchrophasor or Pha-sor Measurement Units (PMUs)
across North America helped utilities and system operators enhance monitoring and better
power system observability. PMUs can provide synchronized, high-resolution data on voltage
and current phasors, enabling real-time situational awareness and control of the power system.
This widespread deployment of PMUs has helped system monitoring, offering utilities unprecedented
insight into grid dynamics like system phase changes or bifurcations. One of the critical challenges posed
by this proliferation of PMUs is the vast volume of data generated, necessitating advanced data analytics
techniques for effective decision-making. However, data analytics needs to be done faster and
computationally efficiently to implement the developed algorithm in a utility grid control room.
In this research, the authors proposed a data-driven method to analyze power system bifurcations with
PMU data using statistical metrics known as Early Warning Signals. Generally, bifurcations can lead
to voltage instability, frequency fluctuations, and even blackouts. Hence, timely detection of
bifurcations and types, both pre-event if possible or post-event for detailed forensics with the proposed
data-driven method, helps utilities identify critical patterns and correlations in PMU data,
allowing for proactive grid stability and reliability management.
@inproceedings{10688880,author={Roychowdhury, Rajarshi and Wu, Xuan and Zhang, Hui and Illindala, Mahesh S.},booktitle={2024 IEEE Power & Energy Society General Meeting (PESGM)},title={Power System Bifurcation Detection Using Statistical Early Warning Signals With Synchrophasor Data},year={2024},volume={},number={},pages={1-5},keywords={Data analysis;Voltage fluctuations;Power system dynamics;Bifurcation;Power system stability;Phasor measurement units;Stability analysis;Synchronization;Voltage control;Monitoring;Phasor Measurement Units (PMUs);Data Analytics;Power system monitoring;Early Warning Signals (EWS);Grid dynamics;Phase changes;Bifurcations;Grid stability},doi={10.1109/PESGM51994.2024.10688880}}
IEEE PES
Optimal BESS Sizing for PV Interconnection & Energy Arbitrage with Industrial Customers
Xuan Wu, Rajarshi Roychowdhury, Hui Zhang, and
2 more authors
In 2024 IEEE Power & Energy Society General Meeting (PESGM), 2024
Increasing commercial and industrial (C&I) customers are on board with a
clean-energy future by installing photovoltaic (PV) systems at their facilities to
compensate for the electricity supplied by the utilities. On the other hand, utilities may require no
reverse power flow back to the bulk power system unless the customer is willing to pay potential
network upgrading costs and follow ISO/RTO’s interconnection process. In the meantime, most
equipment and devices of C&I customers are sensitive to voltage fluctuations caused by fault or switching events in the utility’s system. Voltage quality is a challenge to both the customer and
the supplying utility. Therefore, a battery energy storage system (BESS), which can control power
flow and is able to provide a fast response to voltage fluctuations during system events,
is one of the best solutions. In addition to maximizing the PV penetrations, the BESS can be further
utilized to track the locational marginal prices (LMPs) for energy arbitrage. As a result, a
multi-objective optimization problem is needed to size the BESS to maximize the “bang for the buck”.
This paper presents a real-world case study for a manufacturing customer to achieve decarbonization,
arbitrage, and voltage quality improvement using a BESS optimal sizing algorithm and practical
considerations. We believe the proposed approach can be adopted by other utilities or renewable
developers for similar C&I customers.
@inproceedings{10688751,author={Wu, Xuan and Roychowdhury, Rajarshi and Zhang, Hui and Feldman, Barry and Smith, Raiford},booktitle={2024 IEEE Power & Energy Society General Meeting (PESGM)},title={Optimal BESS Sizing for PV Interconnection & Energy Arbitrage with Industrial Customers},year={2024},volume={},number={},pages={1-5},keywords={Renewable energy sources;Voltage fluctuations;Fluctuations;Sensitivity analysis;Switches;Low carbon economy;Power systems;Voltage control;Optimization;Load flow;Decarbonization;energy arbitrage;battery energy storage system;planning;optimization},doi={10.1109/PESGM51994.2024.10688751}}
IEEE PES
Time Series Power Flow and Contingency Analysis with Weather Adjusted Line Ratings: A Synthetic WECC Case Study
Hui Zhang, Natalie Diltz, Rajarshi Roychowdhury, and
1 more author
In 2024 IEEE Power & Energy Society General Meeting (PESGM), 2024
This paper presents a framework to evaluate the impact of weather adjusted line ratings (WALR)
under diverse generation and loading conditions, utilizing a time series model. Hourly power flows and
contingency analysis are conducted on the synthetic 10,000-bus Western Electricity Coordinating Council (WECC)
system over the span of a year identifying overloads and critical contingencies. Hourly WALR are then
calculated using inputs such as ambient temperature, wind speed and direction, and solar radiation.
The sensitivities of these weather inputs on transmission line ratings are also evaluated. Simulation results
showed that weather conditions can significantly impact the rating of a transmission line, and that strategic
use of WALR can effectively alleviate thermal overloads. The proposed methodology provides valuable
insights into the transmission system and enables planning and operations engineers to propose reliable
and cost-effective mitigation solutions. The paper further discusses the practical challenges associated
with the implementation of WALR and provides recommendations for overcoming these obstacles.
@inproceedings{10688870,author={Zhang, Hui and Diltz, Natalie and Roychowdhury, Rajarshi and Wu, Xuan},booktitle={2024 IEEE Power & Energy Society General Meeting (PESGM)},title={Time Series Power Flow and Contingency Analysis with Weather Adjusted Line Ratings: A Synthetic WECC Case Study},year={2024},volume={},number={},pages={1-5},keywords={Power transmission lines;Simulation;Prevention and mitigation;Wind speed;Time series analysis;Contingency management;Real-time systems;Planning;Meteorology;Load flow;Time series power flow;ambient-adjusted rating;dynamic line rating;grid enhancing technologies;power systems},doi={10.1109/PESGM51994.2024.10688870}}
IEEE PES
Deep Learning-Based Failure Prognostic Model for PV Inverter Using Field Measurements
Liming Liu, Yi Luo, Zhaoyu Wang, and
4 more authors
IThis study presents a novel approach for the precise monitoring and prognosis of
photovoltaic (PV) inverter status, which is crucial for the proactive maintenance of PV systems.
It addresses the gaps in traditional model-based methods, which tend to neglect the overall reliability
of inverters, and the limitations of data-driven approaches that largely depend on simulated data.
This research presents a robust solution applicable to real-world scenarios. The proposed data-driven model
for PV inverter failure prognosis employs actual inverter measurements, integrating various operational and
weather-related factors based on domain knowledge. This approach effectively represents inverter stressors
and operational status. Utilizing an Enhanced Siamese Convolutional Neural Network (ESCNN), the model merges
operational data with domain knowledge features, redefining the prognosis challenge as a classification
task. Furthermore, the paper discusses an ESCNN-based real-time inverter failure monitoring method
developed on the well-trained model. The proposed models are rigorously trained and tested with real
inverter data and a novel filtering method is included to address accidental failures in practical
scenarios. The results validate the model’s efficacy, and the directions for future research
are also outlined.
@article{10636809,author={Liu, Liming and Luo, Yi and Wang, Zhaoyu and Qiu, Feng and Zhao, Shijia and Yildirim, Murat and Roychowdhury, Rajarshi},journal={IEEE Transactions on Sustainable Energy},title={Deep Learning-Based Failure Prognostic Model for PV Inverter Using Field Measurements},year={2024},volume={15},number={4},pages={2789-2802},keywords={Inverters;Reliability;Prognostics and health management;Semiconductor device modeling;Data models;Degradation;Insulated gate bipolar transistors;Deep learning;Failure analysis;Photovoltaic systems;Neural networks;Deep learning;domain-knowledge features;failure prognosis;field measurements;PV inverter;siamese neural network},doi={10.1109/TSTE.2024.3443234}}
Elsevier
Optimal allocation of battery energy storage systems for peak shaving and reliability enhancement in distribution systems
Adedoyin Inaolaji, Xuan Wu, Rajarshi Roychowdhury, and
1 more author
Increasing demand for electricity and frequent power outages are common factors that are necessitating power utility companies to refurbish the existing power distribution systems.
To avoid such expensive upgrades, a practical and more viable alternative solution is to use a
battery energy storage system (BESS) that can participate in peak shaving requirements and
function as an additional power source during power outages. In this context, this work develops
an optimization model to optimally determine the size and site of a BESS connected to the distribution
network for the purpose of two critical service options, namely peak shaving and reliability improvement,
under both system normal and outage scenarios. Nonlinearities due to the sizing and siting variables of
the BESS are linearized using the big-M method, and the resulting model becomes a mixed-integer
linear programming (MILP) problem. The decisions made during planning, namely the size and location
of the BESS, directly impact operational decisions regarding how the BESS supports peak shaving
and outage management, if applicable. By considering a utility’s historical load and outage data,
the efficacy of the proposed model is validated on a realistic distribution circuit that
is located at the edge of a service territory with no circuit ties. The optimal BESS allocation
obtained from the model achieves up to 93.5% enhancement in the system’s reliability and also decreases
the feeder’s peak demand by about 17% for a one-year planning horizon. The case studies demonstrate
that the model is computationally scalable and efficient, and electric distribution planners may benefit
from this study and use this as a framework for possible BESS integration to defer expensive peak
capacity-related upgrades while adding an extra source for backup power supply.
@article{INAOLAJI2024112305,title={Optimal allocation of battery energy storage systems for peak shaving and reliability enhancement in distribution systems},journal={Journal of Energy Storage},volume={95},pages={112305},year={2024},issn={2352-152X},doi={https://doi.org/10.1016/j.est.2024.112305},author={Inaolaji, Adedoyin and Wu, Xuan and Roychowdhury, Rajarshi and Smith, Raiford},keywords={Distribution grid reliability, Battery energy storage system, Outages, Peak shaving,
Optimization, Mixed-integer linear program}}
2023
Patent
System and method for circuit testing using remote cooperative devices
Rajarshi Roychowdhury, David Jeffeory Berels, Mahmoud Yousef Ghannam, and
1 more author
A system for testing a plurality of electrical circuits includes a first remote cooperative testing device including a testing component and a first transceiver and a second remote cooperative testing device including a conductive component and a second transceiver. In response to receiving instructions from a remote computing device, the first remote cooperative testing device locates a first electrical circuit and a second electrical circuit and selectively positions the testing component to electrically couple a first portion of the first electrical circuit to a first portion of the second electrical circuit at a first node, and the second remote cooperative testing device selectively positions the conductive component to electrically couple a second portion of the first electrical circuit to a second portion of the second electrical circuit at a second node, thereby forming a testing circuit between the first node and the second node.
@misc{roychowdhury2023system,title={System and method for circuit testing using remote cooperative devices},author={Roychowdhury, Rajarshi and Berels, David Jeffeory and Ghannam, Mahmoud Yousef and Mayberry, Scott},year={2023},month=feb,publisher={Google Patents},note={US Patent 11,592,468},}
Patent
Enhanced management of electrical resources for electric vehicles
Aed M Dudar, Mahmoud Yousef Ghannam, Rajarshi Roychowdhury, and
1 more author
Devices, systems, and methods for management of electrical resources for electric vehicles. A method may include receiving, by a vehicle, sensor data indicative of a first luminosity of a location, and determining that the first luminosity of the location exceeds a luminosity threshold. The method may include determining, based on the first luminosity exceeding the luminosity threshold, a second luminosity to apply to lights of the vehicle while the vehicle is at the location, the second luminosity greater than zero. The method may include applying the second luminosity to the lights while the vehicle is at the location.
@misc{dudar2023enhanced,title={Enhanced management of electrical resources for electric vehicles},author={Dudar, Aed M and Ghannam, Mahmoud Yousef and Roychowdhury, Rajarshi and Eifert, Mark},year={2023},month=mar,publisher={Google Patents},note={US Patent 11,608,016},}
Patent
Dimmable external vehicle lighting and methods of use
Rajarshi Roychowdhury, Mahmoud Yousef Ghannam, Aed M Dudar, and
1 more author
Dimmable external vehicle lighting and methods of use are provided herein. An example method includes determining environmental light intensity around a vehicle, determining a luminance of an external light of the vehicle, determining a difference in magnitude between the environmental light intensity and the luminance of the external light, and selectively adjusting the luminance of the external light based on the difference.
@misc{roychowdhury2023dimmable,title={Dimmable external vehicle lighting and methods of use},author={Roychowdhury, Rajarshi and Ghannam, Mahmoud Yousef and Dudar, Aed M and Eifert, Mark},year={2023},month=jan,publisher={Google Patents},note={US Patent 11,565,624},}
Patent
Dead reckoning correction utilizing patterned light projection
Scott Mayberry, David Berels, Mahmoud Yousef Ghannam, and
1 more author
Dead reckoning correction utilizing patterned light projection is provided herein. An example method can include navigating a drone along a pattern using dead reckoning, the pattern having a plurality of lines, detecting one of the plurality of lines using an optical sensor of the drone, determining when a line of travel of the drone is not aligned with the one of the plurality of lines, and realigning the line of travel of the drone so as to be aligned with the one of the plurality of lines to compensate for drift that occurs during navigation using dead reckoning.
@misc{mayberry2023dead,title={Dead reckoning correction utilizing patterned light projection},author={Mayberry, Scott and Berels, David and Ghannam, Mahmoud Yousef and Roychowdhury, Rajarshi},year={2023},month=may,note={US Patent 11,662,208},}
IEEE PES
Stepping Up to the Future With Power Transformers: Power Transformer Asset Management Strategies: State of the Art and Recommendations for the Future
Rajarshi Roychowdhury, Xuan Wu, Michael Russ, and
2 more authors
Transformers have been used in the power industry for more than a century since the widespread use of ac generation, transmission, and distribution became the standard. Even now, they remain one of the most important substation assets that utilities around the world plan and operate. Figure 1 shows a 200-MVA transformer in service at a utility substation. In the past few decades, with a rapid push toward grid digitalization due to the proliferation of distributed energy resources (DER), the age-old transformer asset management strategy has also evolved for the better.
@article{roychowdhury2023stepping,title={Stepping Up to the Future With Power Transformers: Power Transformer Asset Management Strategies: State of the Art and Recommendations for the Future},author={Roychowdhury, Rajarshi and Wu, Xuan and Russ, Michael and Fleming, Dennis and Spalding, Joshua},journal={IEEE Power and Energy Magazine},volume={21},number={2},pages={40--50},year={2023},publisher={IEEE},}
2022
IEEE IAS
Resiliency-Based Planning for Interconnected Lunar Microgrids using Hybrid-Edge Rewiring
Balaji Guddanti, Rajarshi Roychowdhury, and Mahesh S Illindala
In 2022 IEEE/IAS 58th Industrial and Commercial Power Systems Technical Conference (I&CPS), May 2022
Reliable power system network is necessary to meet the needs of
the ongoing research establishments on the lunar surface. Interconnected microgrids on
the lunar surface will help in load sharing during extreme failure events.
However, detailed system-level planning including network resiliency
is crucial to make the system survive during high-impact low probability events.
A three-stage graph theory-based planning methodology for the interconnected lunar microgrid
network is proposed to maximize the network resiliency and minimize the load shedding.
The methodology utilizes the hybrid-edge rewiring technique to identify the potential
connections between the individual microgrids and secondary lines to enhance the lunar microgrid resiliency.
A directed-weighted graph model approach is used to represent the interconnected lunar microgrid network.
Various graph theory metrics are used to quantify the resiliency of the interconnected microgrid network.
Different case studies are conducted to identify the potential connections for the zonal microgrid of the
interconnected lunar microgrid network.
@inproceedings{guddanti2022resiliency,title={Resiliency-Based Planning for Interconnected Lunar Microgrids using Hybrid-Edge Rewiring},author={Guddanti, Balaji and Roychowdhury, Rajarshi and Illindala, Mahesh S},booktitle={2022 IEEE/IAS 58th Industrial and Commercial Power Systems Technical Conference (I\&CPS)},pages={1--5},year={2022},organization={IEEE},}
Patent
Independent conductive tape dispensing system for manufacturing of electrical distribution circuits in vehicles
David Jeffeory Berels, Mahmoud Yousef Ghannam, Rajarshi Roychowdhury, and
1 more author
An apparatus for applying individual tapes in layers onto a substrate
includes a plurality of reels, applicators, and a guide member.
A first reel holds a first tape and a second reel holds a second tape.
A first applicator includes a first pressure surface that receives the first tape
from the first reel and presses the first tape in a direction toward the substrate
to apply the first tape to the substrate. The second applicator includes a second pressure
surface that receives the second tape from the second reel. The second pressure surface
is aligned to dispense the second tape over a section of the first tape applied to the
substrate and to press the second tape toward the substrate to apply the second tape over the first tape.
The guide member is disposed between the reels and the applicators and aligns the first
and second tapes during application.
@misc{berels2022independent,title={Independent conductive tape dispensing system for manufacturing of electrical distribution circuits in vehicles},author={Berels, David Jeffeory and Ghannam, Mahmoud Yousef and Roychowdhury, Rajarshi and Mayberry, Scott},year={2022},month=mar,publisher={Google Patents},note={US Patent App. 17/035,823},}
Patent
Chionophobia intervention systems and methods
Mahmoud Yousef Ghannam, Rajarshi Roychowdhury, John Robert Van Wiemeersch, and
1 more author
Chionophobia intervention systems and methods are disclosed herein. An example method includes detecting snowfall from a vehicle sensor of a vehicle or a service provider, displaying a prompt on a human machine interface (HMI) to query a user regarding additional assistance in response to the detection of the snowfall, activating a first stage response after detecting the snowfall, determining when the first stage response is insufficient based on feedback received from the user, and activating a second stage response when the feedback received from the user indicates that the first stage response is insufficient.
@misc{ghannam2022chionophobia,title={Chionophobia intervention systems and methods},author={Ghannam, Mahmoud Yousef and Roychowdhury, Rajarshi and Van Wiemeersch, John Robert and Bennie, Brian},year={2022},month=dec,publisher={Google Patents},note={US Patent 11,535,256},}
IEEE IAS
Angular Domain Control Design for Single-Phase Inverter to Enhance Distribution Grid Power Quality
Sergio A Dorado-Rojas, Felipe Galarza-Jiménez, Rajarshi Roychowdhury, and
2 more authors
In 2022 IEEE Industry Applications Society Annual Meeting (IAS), Dec 2022
The United States has seen an enormous influx of single-phase behind-the-meter installations in the last decade. With the latest Federal Energy Regulatory Commission (FERC) order 2222, these behind-the-meter installations can be aggregated and participate in the power markets by providing ancillary services. Hence, controlling smart inverters to maintain power quality in the distribution grid remains challenging. With multiple smaller units forming an aggregation and responding to market signals, nearby standalone single-phase behind-the-meter smart inverters would need better controls to react to frequency excursions. This paper presents an Angular Space Repetitive Control (ASRC)-based Active Power Filter (APF) for a single-phase smart inverter used predominantly in behind-the-meter installations. The proposed control guarantees power quality during large-scale frequency excursions, well above and beyond the stipulated frequency range (59.5-61 Hz) strictly enforced throughout North America. The proposed controller is modeled in Simulink, and the response to input frequency deviations shows a current Total Harmonic Distortion (THD) of less than 3 percent even under extreme frequency excursions.
@inproceedings{dorado2022angular,title={Angular Domain Control Design for Single-Phase Inverter to Enhance Distribution Grid Power Quality},author={Dorado-Rojas, Sergio A and Galarza-Jim{\'e}nez, Felipe and Roychowdhury, Rajarshi and Guddanti, Balaji and Wang, Zongjie},booktitle={2022 IEEE Industry Applications Society Annual Meeting (IAS)},pages={1--8},year={2022},organization={IEEE},}
IEEE IAS
Substation Topology and Line Switching Control Using Deep Reinforcement Learning
Rajarshi Roychowdhury, John B Ocampo, Balaji Guddanti, and
1 more author
In 2022 IEEE/IAS 58th Industrial and Commercial Power Systems Technical Conference (I&CPS), Dec 2022
Electric Power System (EPS) is widely regarded as one of the most complex artificial systems ever created. With the recent penetration of distributed energy resources, controlling the power systems is becoming even more challenging. This paper presents the use of the Dueling DQN (DDQN) Reinforcement Learning algorithm to control line switching and substation topology of the EPS to maintain line flow within limits for all contingency scenarios. The DDQN algorithm is particularly suited in power systems as often, the state of the environment might not be widely affected due to an agent’s actions, particularly during normal operating conditions. This allows the DDQN agent to quickly learn the states that are not important - a definite advantage over traditional vanilla Deep Q Networks. In the case of real-time control of the EPS, not learning all the redundant states has the advantage of fast convergence and reduced training time, both highly desirable in a complex use case like the one studied. The DDQN algorithm was tested on the standard IEEE 14 bus system, and the agent managed to maintain system stability under varied grid operating scenarios.
@inproceedings{roychowdhury2022substation,title={Substation Topology and Line Switching Control Using Deep Reinforcement Learning},author={Roychowdhury, Rajarshi and Ocampo, John B and Guddanti, Balaji and Illindala, Mahesh S},booktitle={2022 IEEE/IAS 58th Industrial and Commercial Power Systems Technical Conference (I\&CPS)},pages={1--6},year={2022},organization={IEEE},}
IEEE IAS
Evaluation of Modified Global Sensitivity Analysis Techniques for Power System Dynamic Studies
Balaji Guddanti, Rajarshi Roychowdhury, and Mahesh S Illindala
In 2022 IEEE Industry Applications Society Annual Meeting (IAS), Dec 2022
When conducting detailed dynamic simulations of a power system network, it is advantageous to know the key parameters of the nonlinear models. The power engineers can Tune the dynamic models’ response to meet the inverter-based resources interconnection requirements and maintain grid reliability. State-of-the-art sensitivity analysis techniques cannot be directly applied to complex nonlinear dynamic models, for example, second-generation renewable energy system models. Thus, this work focuses on proposing modified global sensitivity analysis techniques that are highly applicable for nonlinear dynamic models in the modern power system network. Additionally, the proposed techniques are evaluated based on their computational efforts. The proposed modified techniques are applied on a utility-scale solar photovoltaic power plant dynamic model to determine the sensitive states and identify the key parameters. Detailed dynamic simulation on a 200-bus synthetic grid network is conducted to verify the identified key parameters using PSS®E.
@inproceedings{guddanti2022evaluation,title={Evaluation of Modified Global Sensitivity Analysis Techniques for Power System Dynamic Studies},author={Guddanti, Balaji and Roychowdhury, Rajarshi and Illindala, Mahesh S},booktitle={2022 IEEE Industry Applications Society Annual Meeting (IAS)},pages={1--6},year={2022},organization={IEEE},}
2021
IEEE PES
Sensitivity Analysis Based Identification of Key Parameters in the Dynamic Model of a Utility-Scale Solar PV Plant
Balaji Guddanti, Jorge Ramirez Orrego, Rajarshi Roychowdhury, and
1 more author
Grid modernization and innovations in clean energy are leading to a rapid increase in the penetration of inverter-based resources (IBRs) like wind power and solar photovoltaic (PV) plants in the bulk power system (BPS). To study the implications on BPS dynamics and mitigate potential risks to grid reliability, the second-generation generic renewable energy system model has been developed earlier. However, this model has three modules with 86 user-defined parameters and eight control flags to facilitate the utility-scale solar PV plant operation in different control modes. It presents a major challenge to the transmission system planning engineers. There is a critical need to identify the key parameters of the dynamic model that are highly sensitive to grid events causing large-scale voltage and frequency disturbances. In this work, a sensitivity analysis based on modified Sobol’ method is proposed for identification of the key parameters in the utility-scale solar PV plant model. The total Sobol’ sensitivity index captures even the higher-order effects of the variations in the parameters. Validation of the identified key parameters was carried out on a modified IEEE 9-bus system and 200-bus synthetic grid using PSS®E for plant-level control and local coordinated control operation of the solar PV plant. The reduced set of parameters identified in this work offer help to utility grid planning teams while conducting dynamic studies to meet the interconnection requirements.
@article{guddanti2021sensitivity,title={Sensitivity Analysis Based Identification of Key Parameters in the Dynamic Model of a Utility-Scale Solar PV Plant},author={Guddanti, Balaji and Orrego, Jorge Ramirez and Roychowdhury, Rajarshi and Illindala, Mahesh S},journal={IEEE Transactions on Power Systems},volume={37},number={2},pages={1340--1350},year={2021},publisher={IEEE},}
Analysis of Distributed Energy Aggregations based on Cyber-Physical-Social Systems Modeling
John B Ocampo, Rajarshi Roychowdhury, Balaji Guddanti, and
2 more authors
In 2021 IEEE International Conference on Power, Electrical, Electronic and Industrial Applications (PEEIACON), Dec 2021
@inproceedings{ocampo2021analysis,title={Analysis of Distributed Energy Aggregations based on Cyber-Physical-Social Systems Modeling},author={Ocampo, John B and Roychowdhury, Rajarshi and Guddanti, Balaji and Illindala, Mahesh S and Anirudh, Akundy Vyas},booktitle={2021 IEEE International Conference on Power, Electrical, Electronic and Industrial Applications (PEEIACON)},pages={71--74},year={2021},organization={IEEE}}
IEEE IAS
Effect of endogenous failure events on the survivability of turboelectric distributed propulsion system
Balaji Guddanti, Jongchan Choi, Mahesh S Illindala, and
1 more author
IEEE Transactions on Industry Applications, Dec 2021
Recent advancements in aircraft electrification have led to the introduction of turboelectric distributed propulsion (TeDP). For instance, NASA’s N3X airplane aims to curb jet fuel emissions with the aid of TeDP. However, it is crucial to analyze the survivability of the TeDP system during extreme conditions. The endogenous failure events are of specific interest as they were found to cause a significant number of accidents for commercial aircraft. While the distribution reconfiguration is necessary to meet the critical load demands under extreme failure events, it can also create a transient overload condition in the turboshaft engine. The power system survivability is further deteriorated in the presence of constant power loads. In this article, a mathematical analysis of the survivability of the system is presented to make the aircraft power system highly resilient to endogenous failure events. A power system collapse mitigation strategy is proposed by adding an energy storage system. Moreover, the analytical expressions are formulated to size the energy storage unit to prevent the system collapse. Various failure conditions are modeled using PSCAD/EMTDC to study the minimum energy storage required to prevent system collapse.
@article{guddanti2021effect,title={Effect of endogenous failure events on the survivability of turboelectric distributed propulsion system},author={Guddanti, Balaji and Choi, Jongchan and Illindala, Mahesh S and Roychowdhury, Rajarshi},journal={IEEE Transactions on Industry Applications},volume={58},number={1},pages={224--232},year={2021},publisher={IEEE},}
IEEE IAS
Autonomous voltage regulation by distributed PV inverters with minimal inter-node interference
Sree Subiksha M Reshikeshan, Sarah L Matthiesen, Mahesh S Illindala, and
2 more authors
IEEE Transactions on Industry Applications, Dec 2021
Reactive power capability of distributed photovoltaic (PV) inverters is exploited to mitigate voltage violations under high PV penetration in the distribution grid. Coordinating the reactive power compensations of individual PV inverters to obtain desired voltage regulation performance is a major challenge. In this paper, a decentralized method is proposed to enable PV inverters to autonomously regulate terminal node voltages. The proposed method minimizes the effect of a terminal node’s reactive power compensation on the voltage profile of its respective parent-to-terminal node. This ensures that the interference between the voltage regulation of terminal nodes by individual PV inverters is minimized. The performance of the proposed decentralized scheme is verified by extensive powerflow simulations of the EPRI Circuit 24 test feeder in open-source distribution system simulation platform OpenDSS.
@article{reshikeshan2021autonomous,title={Autonomous voltage regulation by distributed PV inverters with minimal inter-node interference},author={Reshikeshan, Sree Subiksha M and Matthiesen, Sarah L and Illindala, Mahesh S and Renjit, Ajit A and Roychowdhury, Rajarshi},journal={IEEE Transactions on Industry Applications},volume={57},number={3},pages={2058--2066},year={2021},publisher={IEEE},}
2018
Thesis
Solar Photovoltaics: Forecasting & Analysis in Puerto Rico and Effects on the Distribution Grid
@phdthesis{roychowdhury2018solar,title={Solar Photovoltaics: Forecasting \& Analysis in Puerto Rico and Effects on the Distribution Grid},author={Roychowdhury, Rajarshi},year={2018},school={University of Pennsylvania}}