Probabilistic Optimisation of Generation Scheduling Considering Wind Power Output and Stochastic Line Capacity
MetadataShow full item record
Copyright © 2012 IEEE. Personal use of this material is permitted. Permission from IEEEmust be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Optimising the power flow in a system has been a challenge for decades. Due to the complexities that are introduced by new technologies, this problem is evolving. Lately, the effect of integrating wind turbines into the system has been taken into account when solving optimal power flow. However, transmission system constraints are usually modeled as fixed constraints using deterministic methods. Deterministic transmission line ratings have been shown to significantly underestimate the capability of the network. However, probabilistic line ratings are not used in optimization studies. In this paper, stochastic optimisation is used to consider the integration of wind turbines as well as probabilistic real time line capacities. It is shown that optimization considering probabilistic line ratings that lead to dynamic constraints in the OPF problem, represents the operational situation more accurately. This approach further reduces the optimum cost of system operation.
Showing items related by title, author, creator and subject.
Banerjee, Binayak; Jayaweera, Dilan; Islam, Syed (2012)Using wind power forecasts to optimize scheduling of reserves is an active area of research. However, the rating of transmission lines often places a limit on how much wind power can be used and hence reserve scheduling ...
Yin, YanYan; Liu, Y.; Teo, Kok Lay; Wang, Song; Liu, F. (2018)The Franklin Institute In this paper, a new event-trigger based probabilistic controller is designed using a scenario optimization approach for the robust stabilization of uncertain systems subject to nonlinear and unbounded ...
Event-triggered probabilistic robust control of linear systems with input constrains: By scenario optimization approachYin, YanYan; Liu, Y.; Teo, Kok Lay; Wang, S. (2017)This paper addresses the problem of probabilistic robust stabilization for uncertain systems subject to input saturation. A new probabilistic solution framework for robust control analysis and synthesis problems is addressed ...