A5037310822- Optimal Power Flow Distribution
- Smart Grid Energy Management
- Microgrid Control and Optimization
- Smart Grid Security and Resilience
- Power System Reliability and Maintenance
- Power System Optimization and Stability
- Electric Power System Optimization
- Infrastructure Resilience and Vulnerability Analysis
- Electric Vehicles and Infrastructure
- Amyotrophic Lateral Sclerosis Research
- Energy Load and Power Forecasting
- Neurogenetic and Muscular Disorders Research
- Power Systems and Renewable Energy
- Islanding Detection in Power Systems
- Frequency Control in Power Systems
- Electric and Hybrid Vehicle Technologies
- Vehicle emissions and performance
- Power Systems Fault Detection
- Advanced Battery Technologies Research
- Alzheimer's disease research and treatments
- Electricity Theft Detection Techniques
- Cholinesterase and Neurodegenerative Diseases
- Fault Detection and Control Systems
- Power Systems and Technologies
- Blockchain Technology Applications and Security
Pacific Northwest National Laboratory
2024-2025
Idaho National Laboratory
2023-2024
McMaster University
2024
University of Calgary
2024
University of Nottingham
2024
Polytechnic University of Turin
2024
Teachers Development Group
2024
S&C Electric Company (United States)
2024
DuPont (United States)
2024
Colorado School of Mines
2023
Abstract Mitochondrial defects result in dysregulation of metabolomics and energy homeostasis that are detected upper motor neurons (UMNs) with TDP-43 pathology, a pathology is predominantly present both familial sporadic cases amyotrophic lateral sclerosis (ALS). While same mitochondrial problems the UMNs ALS patients mouse models, since pathologies shared at cellular level, regardless species, we first analyzed metabolite profile healthy diseased cortex to investigate whether metabolomic...
Mitochondrial defects are one of the common underlying causes neuronal vulnerability in neurodegenerative diseases, such as amyotrophic lateral sclerosis (ALS), and TDP-43 pathology is most commonly observed proteinopathy. Disrupted inner mitochondrial membrane (IMM) reported upper motor neurons (UMNs) ALS patients with recapitulated UMNs well-characterized hTDP-43 mouse model ALS. The construct validity, shared cellular mice human, offers a unique opportunity to test treatment strategies...
Abstract Background Upper motor neurons (UMNs) are a key component of neuron circuitry. Their degeneration is hallmark for diseases, such as hereditary spastic paraplegia (HSP), primary lateral sclerosis (PLS), and amyotrophic (ALS). Currently there no preclinical assays investigating cellular responses UMNs to compound treatment, even diseases the UMNs. The basis UMN vulnerability not fully understood, has yet been identified improve health diseased UMNs: two major roadblocks building...
Several wired and wireless advanced communication technologies have been used for coordinated voltage regulation schemes in distribution systems. These employed to both receive measurements from field sensors transmit control settings regulating devices (VRDs). Communication networks can be susceptible data falsification attacks, which lead instability. In this context, an attacker alter multiple a manner disturb algorithms. This paper proposes machine learning-based two-stage approach...
The frequency of disruptive and newly emerging threats (e.g. man-made attacks-cyber physical attacks; extreme natural events-hurricanes, earthquakes, floods) has escalated in the last decade. Impacts these events are very severe ranging from long power outage duration, major system equipment generation plants, transmission distribution lines, substation) destruction, complete blackout. Accurate modeling is vital as they serve mathematical tools for assessment evaluation various operations...
Distribution network reconfiguration (DNR) has proved to be an economical and effective way improve the reliability of distribution systems. As optimal configuration depends on system operating states (e.g., loads at each node), existing analytical population-based approaches need repeat entire analysis computation find with a change in states. Contrary this, if properly trained, deep reinforcement learning (DRL)-based DNR can determine or nearoptimal quickly even changes In this paper, Deep...
This article investigates the intricate dynamics between Distributed Energy Resources (DERs) and Microgrid Operator (MGO) within a microgrid interconnected with main grid. Employing an evolutionary game framework, study scrutinizes strategic evolution of DERs’ decision-making processes in their interactions MGO. Modeled as game, these encapsulate strategies adopted by DERs, resulting stable equilibrium over time. Motivated direct benefits linked to increased active power production, DERs...
With the rise of renewable energy penetration in grid, photovoltaic (PV) panels are connected to grid via inverters supply solar energy. Transformer-less grid-tied PV gaining popularity because their improved efficiency, reduced size, and lower costs. However, they can induce a path for leakage currents between due absence galvanic isolation. This leads serious electromagnetic interference, loss safety concerns. The current is primarily influenced by nature common mode voltage (CMV), which...
In concept, a smart charging management system (SCMS) optimizes the of plug-in vehicles (PEVs) and provides various grid services including voltage control, frequency regulation, peak shaving, renewable energy integration support, spinning reserve, emergency demand response. These functionalities largely depend upon data collected from entities such as PEVs, electric vehicle supply equipment (EVSE), service providers, utilities. SCMS can be susceptible to both cyber physical threats (e.g....
The ever-increasing penetration of intermittent renewable resources in low-voltage power grids necessitates efficient operational strategies for voltage regulation as well scheduling the available resources. In this paper, a risk-aware Volt/VAR support framework followed by real-time reinforcement learning controller is presented three-phase distribution systems. stochastic stage, legacy regulating assets along with inverter-based photovoltaics (PVs) and energy storage system (ESS) are...
Abstract Even though amyotrophic lateral sclerosis (ALS) is a disease of the upper and lower motor neurons, to date none compounds in clinical trials have been tested for improving health diseased neurons (UMNs). There an urgent need develop preclinical assays that include UMN as readout. Since ALS complex disease, combinatorial treatment strategies will be required address mechanisms perturbed patients. Here, we describe novel vitro platform takes advantage reporter line which UMNs are...
In recent years, deep reinforcement learning (DRL) has garnered substantial attention in the context of enhancing resilience power and energy systems. Resilience, characterized by ability to withstand, absorb, quickly recover from natural disasters human-induced disruptions, become paramount ensuring stability dependability critical infrastructure. This comprehensive review delves into latest advancements applications DRL systems, highlighting significant contributions key insights. The...
This paper presents a spanning tree-based genetic algorithm (GA) for the reconfiguration of electrical distribution systems with objective minimizing active power losses. Due to low voltage levels at systems, losses are very high and sensitive system configuration. Therefore, optimal is an important factor in operation minimize Smart automated electric should be able reconfigure as response changes load The proposed method searches trees potential configurations finds tree using two steps....
The integration of distributed energy resources (DERs) into the power grid has made it important for distribution systems to participate in frequency regulation. Regulatory authorities (e.g., Federal Electricity Commission United States) are recommending that DERs and reserve markets, a mechanism is needed facilitate this at level. Though single system may not have sufficient reserves tertiary regulation, stacked from multiple can be utilized This paper proposes coalitional game theory-based...
This paper presents a Resilient Integrated Resource Planning (IRP) framework for transmission systems, specifically focusing on the analysis of High Impact Low Probability (HILP) events. The addresses need to assess and enhance resilience networks in face extreme Conventional reliability-based planning methods typically average impact various outage durations, whereas resilience-oriented studies prioritize events with significant consequences. Therefore, this work adopts metric based...
Modern distribution grids are undergoing new challenges due to the stochastic nature of distributed energy resources (DERs). High penetration DERs has a significant impact on Volt-VAR profile and system power losses. This work proposes deep reinforcement learning (DRL)-based optimization approach for improving voltage reducing loss under high resources, such as battery storage solar photovoltaic units in grids. The twin delayed deterministic policy gradient (TD3) method-based DRL agent is...