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Estimation, control, and pricing in distribution systems
We focus on the integration of distributed energy resources such as solar and storage in distribution systems.
Bayesian state estimation for unobservable distribution systems via deep learning
IEEE Transactions on Power Systems, to appear in 2020
See an earlier version on arXiv and the conference version at the 2018 IEEE PESGM.
On the dynamics of distributed energy adoption: equilibrium, stability, and limiting capacity
IEEE Transactions on Automatic Control, January, 2020
See an earlier version on arXiv and the conference version
" Killing death spiral softly with a small connection charge" at the 2017 Allerton Conference.
On the efficiency of connection charges---Part I: a stochastic framework
IEEE Transactions on Power Systems, vol 33, no. 4, July 2018.
See earlier versions at arXiv
On the efficiency of connection charges---Part II: integration of distributed energy resources
IEEE Transactions on Power Systems, vol 33, no. 4, July 2018.
See earlier versions at arXiv
Optimal operation and economic value of energy storage at consumer locations
IEEE Transactions on Automatic Control, vol. 62, Issue 2, pp 792-807, 2017
Demand response via large scale charging of electric vehicles
IEEE PES General Meeting, 2016
Renewables and storage in distribution systems: centralized vs. decentralized integration
IEEE Journal on Selected Areas in Communications, vol. 34, no. 3, pp. 665-674, 2016.
See an earlier version on arXiv.
Dynamic pricing and distributed energy management for demand response
IEEE Transactions on Smart Grid,, vol. 7, no. 2, pp. 1128-1136, 2016.
See an earlier version on arXiv.
Modeling and stochastic control for home energy management,
IEEE Trans. Smart Grid, vol. 4, no. 4, December, 2013
Retail pricing for stochastic demand with unknown parameters: an online machine learning approach
2013 Allerton Conference on Communication, Control and Computing, Oct., 2013.
See also a related work Online learning and optimization of jump Markov models.