1.8k citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- University of Colorado BoulderUS112 papers
- Colorado School of MinesUS59 papers
- King's College LondonGB30 papers
- Lawrence Berkeley National LaboratoryUS28 papers
- Fudan UniversityCN17 papers
- Radboud University NijmegenNL15 papers
- Stanford UniversityUS15 papers
- University of MinnesotaUS15 papers
- University of California, BerkeleyUS14 papers
- Colorado State UniversityUS13 papers
- North Carolina State UniversityUS12 papers
- Princeton UniversityUS12 papers
56 papers · 1 filter
Network-Cognizant Time-Coupled Aggregate Flexibility of Distribution Systems Under Uncertainties
Bai Cui, Ahmed Zamzam, Andrey Bernstein
Increasing integration of distributed energy resources (DERs) within distribution feeders provides unprecedented flexibility at the distribution-transmission interconnection. To ex…
Upper Atmosphere Smoke Injection from Large Areal Fires
Stephanie Redfern, Julie K. Lundquist, Owen B. Toon +3
Large fires can inject smoke into the upper troposphere and lower stratosphere. Detailed fire simulations allow for assessment of how local weather interacts with these fires and a…
Disentangling the role of bond lengths and orbital symmetries in controlling in YBaCuO
Francois Jamet, Cedric Weber, Swagata Acharya +2
Optimally doped YBCO (YBaCuO) has a high critical temperature, at 92 K. It is largely believed that Cooper pairs form in YBCO and other cuprates because of spin f…
The effect of price-based demand response on carbon emissions in European electricity markets: The importance of adequate carbon prices
Markus Fleschutz, Markus Bohlayer, Marco Braun +2
Price-based demand response (PBDR) has recently been attributed great economic but also environmental potential. However, the determination of its short-term effects on carbon emis…
Dynamics of spin polarization in tilted polariton rings
S. Mukherjee, V. K. Kozin, A. V. Nalitov +9
We have observed the effect of pseudo magnetic field originating from the polaritonic analog of spin-orbit coupling (TETM splitting) on a polariton condensate in a ring-shaped m…
Voltage Estimation in Low-Voltage Distribution Grids with Distributed Energy Resources
Marija Marković, Amirhossein Sajadi, Anthony Florita +2
The present distribution grids generally have limited sensing capabilities and are therefore characterized by low observability. Improved observability is a prerequisite for increa…
Analytical solution for the cumulative wake of wind turbines in wind farms
Majid Bastankhah, Bridget L. Welch, Luis A. Martínez-Tossas +2
This paper solves an approximate form of conservation of mass and momentum for a turbine in a wind farm array. The solution is a fairly simple explicit relationship that predicts t…
Electronic structure correspondence of singlet-triplet scale separation in strained Sr2RuO4
Swagata Acharya, Dimitar Pashov, Elena Chachkarova +2
At a temperature of roughly 1\,K, \ce{Sr2RuO4} undergoes a transition from a normal Fermi liquid to a superconducting phase. Even while the former is relatively simple and well und…
Switching Device-Cognizant Sequential Distribution System Restoration
Anmar Arif, Bai Cui, Zhaoyu Wang
This paper presents an optimization framework for sequential reconfiguration using an assortment of switching devices and repair process in distribution system restoration. Compare…
Design, characterization and indoor validation of the optical soiling detector "DUSST"
Álvaro Fernández-Solas, Leonardo Micheli, Matthew Muller +2
Nowadays, photovoltaic (PV) technology has reached a high level of maturity in terms of module efficiency and cost competitiveness in comparison with other energy technologies. As…
Ternary Nitride Materials: Fundamentals and Emerging Device Applications
Ann L. Greenaway, Celeste L. Melamed, M. Brooks Tellekamp +4
Interest in inorganic ternary nitride materials has grown rapidly over the past few decades, as their diversity of chemistries and structures make them appealing for a variety of a…
Grid-Interactive Multi-Zone Building Control Using Reinforcement Learning with Global-Local Policy Search
Xiangyu Zhang, Rohit Chintala, Andrey Bernstein +2
In this paper, we develop a grid-interactive multi-zone building controller based on a deep reinforcement learning (RL) approach. The controller is designed to facilitate building…
An overview of block Gram-Schmidt methods and their stability properties
Erin Carson, Kathryn Lund, Miroslav Rozložník +1
Block Gram-Schmidt algorithms serve as essential kernels in many scientific computing applications, but for many commonly used variants, a rigorous treatment of their stability pro…
Economic Dispatch With Distributed Energy Resources: Co-Optimization of Transmission and Distribution Systems
Xinyang Zhou, Chin-Yao Chang, Andrey Bernstein +2
The increasing penetration of distributed energy resources (DERs) in the distribution networks has turned the conventionally passive load buses into active buses that can provide g…
PHASED: Phase-Aware Submodularity-Based Energy Disaggregation
Faisal M. Almutairi, Aritra Konar, Ahmed S. Zamzam +1
Energy disaggregation is the task of discerning the energy consumption of individual appliances from aggregated measurements, which holds promise for understanding and reducing ene…
Accelerating Optimization and Reinforcement Learning with Quasi-Stochastic Approximation
Shuhang Chen, Adithya Devraj, Andrey Bernstein +1
The ODE method has been a workhorse for algorithm design and analysis since the introduction of the stochastic approximation. It is now understood that convergence theory amounts t…
The Area Localized Coupled Model for Analytical Mean Flow Prediction in Arbitrary Wind Farm Geometries
Genevieve M. Starke, Charles Meneveau, Jennifer R. King +1
This work introduces the Area Localized Coupled (ALC) model, which extends earlier approaches to coupling classical wake superposition and atmospheric boundary layer models in orde…
Solar Thermoradiative-Photovoltaic Energy Conversion
Eric J. Tervo, William A. Callahan, Eric S. Toberer +2
We propose a solar thermal energy conversion system consisting of a solar absorber, a thermoradiative cell or negative illumination photodiode, and a photovoltaic cell. Because it…
Computational Framework for Behind-The-Meter DER Techno-Economic Modeling and Optimization -- REopt Lite
Sakshi Mishra, Josiah Pohl, Nick Laws +7
The global energy system is undergoing a major transformation. Renewable energy generation is growing and is projected to accelerate further with the global emphasis on decarboniza…
On analytical construction of observable functions in extended dynamic mode decomposition for nonlinear estimation and prediction
Marcos Netto, Yoshihiko Susuki, Venkat Krishnan +1
We propose an analytical construction of observable functions in the extended dynamic mode decomposition (EDMD) algorithm. EDMD is a numerical method for approximating the spectral…
Probabilistic Resilience of DER systems -- A Simulation Assisted Optimization Approach
Sakshi Mishra, Kate Anderson
Energy systems resilience is becoming increasingly important as the frequency of major grid outages increases. In this work, we present a methodology to optimize a behind-the-meter…
Engineering the reciprocal space for ultrathin GaAs solar cells
Jeronimo Buencuerpo, Jose M. Llorens, Jose M. Ripalda +2
III-V solar cells dominate the high efficiency charts, but with significantly higher cost than other solar cells. Ultrathin III-V solar cells can exhibit lower production costs and…
The ASHRAE Great Energy Predictor III competition: Overview and results
Clayton Miller, Pandarasamy Arjunan, Anjukan Kathirgamanathan +8
In late 2019, ASHRAE hosted the Great Energy Predictor III (GEPIII) machine learning competition on the Kaggle platform. This launch marked the third energy prediction competition…
Learning to Optimize Power Distribution Grids using Sensitivity-Informed Deep Neural Networks
Manish K. Singh, Sarthak Gupta, Vassilis Kekatos +2
Deep learning for distribution grid optimization can be advocated as a promising solution for near-optimal yet timely inverter dispatch. The principle is to train a deep neural net…