Decentralized Stochastic Control of Power Systems using Genetic Algorithms for Interaction Estimation
| Authors: | Dehghani Maryam, Amirkabir University of Technology, Iran (Islamic Republic of)
Afshar Ahmad, Amirkabir University of Technology, Iran (Islamic Republic of)
Nikravesh Seyyed Kamaleddin, Amirkabir University of Technology, Iran (Islamic Republic of) |
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| Topic: | 5.4 Large Scale Complex Systems |
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| Session: | Large Scale Complex Systems |
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| Keywords: | large-scale systems, decentralized control, stochastic control, Kalman filter,genetic algorithms, power systems. |
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Abstract
A decentralized feedback control scheme is proposed for optimization of largescalesystems. First, local controllers are used to optimize each subsystem, ignoring theinterconnections. Next, an additional compensating controller was applied to minimizethe effect of interactions and improve the performance of the overall system. At the costof the suboptimal performance, this optimization strategy ensures stability of the system.To account for the modeling uncertainties, both a local Kalman filter and a novelapproach by the usage of genetic algorithm is used to estimate all local states andinteractions for each subsystem. A sample three-bus system is given to illustrate theproposed methodologies.
