Bringing probabilistic analysis capability from planning to operation

Chen, Yousu; Etingov, Pavel; Fitzhenry, Erin; Sharma, Puneet; Nguyen, Tony; Makarov, Yuri V.; Rice, Mark; Allwardt, Craig; Widergren, Steve

doi:10.1016/j.conengprac.2017.06.006

Cited by 4 publications

(1 citation statement)

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“…Existing research regarding quantum computing for the power system is still in the very early stage and mostly focuses on how to adapt existing quantum algorithms for power system purposes. Given the limitations on qubit volume and fidelity of present noisy intermediate-scale quantum (NISQ) devices, quantum-classical hybrid algorithms emerge as the most promising applications for the first-generation quantum computers, this includes quantum approximated optimization algorithm (QAOA) for discrete combinatorial optimizations [13,14] , the Harrow-Hassidim-Lloyd (HHL) REVIEW Computing for power system operation and planning: Then, now, and the future algorithm for solving high-order sparse linear equations [15] , quantum annealing for mixed-integer programming [16] , variational quantum algorithms for quantum machine learning [17,18] , etc.…”

Section: Quantum Computingmentioning

confidence: 99%

Computing for power system operation and planning: Then, now, and the future

Chen

Huang

Jin

et al. 2022

iEnergy

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With the global trend of pursuing clean energy and decarbonization, power systems have been evolving in a fast pace that we have never seen in the history of electrification. This evolution makes the power system more dynamic and more distributed, with higher uncertainty. These new power system behaviors bring significant challenges in power system modeling and simulation as more data need to be analyzed for larger systems and more complex models to be solved in a shorter time period. The conventional computing approaches will not be sufficient for future power systems. This paper provides a historical review of computing for power system operation and planning, discusses technology advancements in high performance computing (HPC), and describes the drivers for employing HPC techniques. Some high performance computing application examples with different HPC techniques, including the latest quantum computing, are also presented to show how HPC techniques can help us be well prepared to meet the requirements of power system computing in a clean energy future.

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Section: Quantum Computingmentioning

confidence: 99%