Results 21 to 30 of about 9,967,778 (178)

Local solutions of the optimal power flow problem [PDF]

open access: yes, 2013
The existence of locally optimal solutions to the AC optimal power flow problem (OPF) has been a question of interest for decades. This paper presents examples of local optima on a variety of test networks including modified versions of common networks ...
Waqquas A. Bukhsh   +14 more
core   +1 more source

Analytical reformulation of security constrained optimal power flow with probabilistic constraints [PDF]

open access: yes2013 IEEE Grenoble Conference, 2013
ISBN:978-1-4673-5669 ...
Roald, Line   +3 more
openaire   +2 more sources

Fast Calculation of Probabilistic Optimal Power Flow: A Deep Learning Approach [PDF]

open access: yes2019 IEEE Power & Energy Society General Meeting (PESGM), 2019
Probabilistic optimal power flow (POPF) is an important analytical tool to ensure the secure and economic operation of power systems. POPF needs to solve enormous nonlinear and nonconvex optimization problems. The huge computational burden has become the major bottleneck for the practical application.
Yan Yang   +4 more
openaire   +3 more sources

Aspects of wind energy characteristics in transmission related optimisation models : invited panel discussion paper [PDF]

open access: yes, 2011
Presented at the IEEE Power and Energy Society General Meeting, Detroit, USA, 24-29 July 2011This invited panel paper discussion will outline a number of aspects of wind energy characteristics relevant to the optimal wind/transmission model formulation ...
Burke, Daniel J.   +4 more
core   +1 more source

Stochastic variational inference for probabilistic optimal power flows

open access: yesElectric Power Systems Research, 2021
Abstract This paper applies a generative deep learning model, namely a Variational Autoencoder, on probabilistic optimal power flows. The model utilizes Gaussian approximations in order to adequately represent the distributions of the results of a system under uncertainty. These approximations are realized by applying several techniques from Bayesian
openaire   +2 more sources

Probabilistic load flow in systems with high wind power penetration [PDF]

open access: yes, 2008
This paper proposes a method for solving a probabilistic load flows that takes into account the uncertainties of wind generation, but also of load and conventional systems.
Usaola García, Julio, Usaola, Julio
core   +1 more source

Probabilistic analysis for optimal power flow under uncertainty

open access: yesIET Generation, Transmission & Distribution, 2010
This study presents a probabilistic analysis to consider the impact of uncertain system parameters on optimal power flow (OPF). A general OPF under uncertainty is formulated as a chance-constrained programming model and its stochastic features are investigated.
H. Zhang, P. Li
openaire   +1 more source

Optimal Power Flow with Power Flow Routers [PDF]

open access: yes, 2017
Power flow routing is an emerging control paradigm for the dynamic control of electric power flows. In this paper, we propose a generic model of a power flow router (PFR) and incorporate it into the optimal power flow (OPF) problem.
Li, VOK, Leung, KC, Lam, AYS, Lin, J
core   +1 more source

Optimal wind power location on transmission systems - a probabilistic load flow approach [PDF]

open access: yes, 2009
Paper presented at the Tenth International Conference on Probabilistic Methods Applied to Power Systems (PMAPS 2008), Puerto Rico, 25-29 May 2008Renewable electrical energy grid connection is hampered by transmission capacity limitations and public ...
Burke, Daniel J., O'Malley, Mark
core   +1 more source

Probabilistic optimal power flow of AC/DC system with multiport current flow controller

open access: yesCSEE Journal of Power and Energy Systems, 2020
To evaluate the impact of the randomness and correlation of photovoltaic (PV) and load on AC/DC systems with a multiport current flow controller (M-CFC), this paper proposes a probabilistic optimal power flow calculation for AC/DC systems based on a nonparametric kernel density estimation.
Jing Bian   +4 more
openaire   +2 more sources

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