| The role of firm low-carbon electricity resources in deep decarbonization of power generation NA Sepulveda, JD Jenkins, FJ De Sisternes, RK Lester Joule 2 (11), 2403-2420, 2018 | 484 | 2018 |
| The design space for long-duration energy storage in decarbonized power systems NA Sepulveda, JD Jenkins, A Edington, DS Mallapragada, RK Lester Nature Energy 6 (5), 506-516, 2021 | 335 | 2021 |
| Long-run system value of battery energy storage in future grids with increasing wind and solar generation DS Mallapragada, NA Sepulveda, JD Jenkins Applied Energy 275, 115390, 2020 | 143 | 2020 |
| Converting excess low-price electricity into high-temperature stored heat for industry and high-value electricity production CW Forsberg, DC Stack, D Curtis, G Haratyk, NA Sepulveda The Electricity Journal 30 (6), 42-52, 2017 | 99 | 2017 |
| Enhanced decision support for a changing electricity landscape: the GenX configurable electricity resource capacity expansion model JD Jenkins, NA Sepulveda MIT Energy Initiative, 2017 | 90 | 2017 |
| Enhanced representations of lithium-ion batteries in power systems models and their effect on the valuation of energy arbitrage applications A Sakti, KG Gallagher, N Sepulveda, C Uckun, C Vergara, FJ de Sisternes, ... Journal of Power Sources 342, 279-291, 2017 | 75 | 2017 |
| Long-duration energy storage: A blueprint for research and innovation JD Jenkins, NA Sepulveda Joule 5 (9), 2241-2246, 2021 | 25 | 2021 |
| The role of firm low-carbon electricity resources in deep decarbonization of power generation. Joule 2, 2403–2420 NA Sepulveda, JD Jenkins, FJ de Sisternes, RK Lester | 21 | 2018 |
| The role of firm low-carbon electricity resources in deep decarbonization of power generation. Joule 2018; 2: 2403–20 NA Sepulveda, JD Jenkins, FJ de Sisternes, RK Lester | 16 | |
| Decarbonization of power systems: analyzing different technological pathways NA Sepulveda Massachusetts Institute of Technology, 2016 | 13 | 2016 |
| Total system costs in deep decarbonisation scenarios for a large, interconnected European country: evidence from the GenX model F Sisternes, N Sepulveda Presentation to the OECD-NEA Workshop “Dealing with System Costs in …, 2016 | 7 | 2016 |
| The Role of Firm Low-Carbon Electricity Resources in Deep Decarbonization of Power Generation, Joule. 2 (2018) 2403–2420 NA Sepulveda, JD Jenkins, FJ de Sisternes, RK Lester URL: http://www. sciencedirect. com/science/article/pii S, 0 | 7 | |
| Multilateral Closed-Loop Geothermal Systems as a Zero-Emission Load-Following Resource M Holmes, M Toews, J Jenkins, N Sepulveda 2021 Geothermal Rising Conference: Using the Earth to Save the Earth, GRC …, 2021 | 6 | 2021 |
| The Role of Firm Low-Carbon Electricity Resources in Deep Decarbonization of Power Generation. Joule 2018; 2: 2403–20. doi: 10.1016 NA Sepulveda, JD Jenkins, FJ de Sisternes, RK Lester J. JOULE 6, 2018 | 6 | 2018 |
| Implications of Carbon Constraints on (1) the Electricity Generating Mix for the United States, China, France and the United Kingdom and (1) Future Nuclear System Requirements C Forsberg, K Dawson, N Sepulveda, M Corradini MIT-ANP-TR-184 (March 2019), 2019 | 5 | 2019 |
| Decarbonization of power systems, multi-stage decision-making with policy and technology uncertainty NA Sepulveda Massachusetts Institute of Technology, 2020 | 4 | 2020 |
| Artificial neural networks condensation: A strategy to facilitate adaption of machine learning in medical settings by reducing computational burden D Liu, N Sepulveda, M Zheng arXiv preprint arXiv:1812.09659, 2018 | 4 | 2018 |
| GenX: A Configurable Electricity Resource Capacity Expansion Model N Sepulveda, F de Sisternes, J Jenkins Presentation to the OECD-NEA Workshop “Dealing with system costs in …, 2016 | 4 | 2016 |
| A computationally efficient benders decomposition for energy systems planning problems with detailed operations and time-coupling constraints A Jacobson, F Pecci, N Sepulveda, Q Xu, J Jenkins INFORMS Journal on Optimization 6 (1), 32-45, 2024 | 3 | 2024 |
| Using Artificial Neural Network Condensation to Facilitate Adaptation of Machine Learning in Medical Settings by Reducing Computational Burden: Model Design and Evaluation Study D Liu, M Zheng, NA Sepulveda JMIR Formative Research 5 (12), e20767, 2021 | 3 | 2021 |
Jesse D. JenkinsAssistant professor | Dept of Mechanical & Aerospace Engineering | Princeton UniversityVerified email at princeton.edu
