111 research outputs found

    Sparse Wide-Area Control of Power Systems using Data-driven Reinforcement Learning

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    In this paper we present an online wide-area oscillation damping control (WAC) design for uncertain models of power systems using ideas from reinforcement learning. We assume that the exact small-signal model of the power system at the onset of a contingency is not known to the operator and use the nominal model and online measurements of the generator states and control inputs to rapidly converge to a state-feedback controller that minimizes a given quadratic energy cost. However, unlike conventional linear quadratic regulators (LQR), we intend our controller to be sparse, so its implementation reduces the communication costs. We, therefore, employ the gradient support pursuit (GraSP) optimization algorithm to impose sparsity constraints on the control gain matrix during learning. The sparse controller is thereafter implemented using distributed communication. Using the IEEE 39-bus power system model with 1149 unknown parameters, it is demonstrated that the proposed learning method provides reliable LQR performance while the controller matched to the nominal model becomes unstable for severely uncertain systems.Comment: Submitted to IEEE ACC 2019. 8 pages, 4 figure

    Methods for Compression of Feedback in Adaptive Multicarrier 4G Schemes

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    In this paper, several algorithms for compressing the feedback of channel quality information are presented and analyzed. These algorithms are developed for a proposed adaptive modulation scheme for future multi-carrier 4G mobile systems. These strategies compress the feedback data and, used together with opportunistic scheduling, drastically reduce the feedback data rate. Thus the adaptive modulation schemes become more suitable and efficient to be implemented in future mobile systems, increasing data throughput and overall system performance.This work has been partly funded by the Spanish government with projects MACAWI (TEC 2005-07477-c02-02), MAMBO2 (CCG06-UC3M-TIC-0698), and European COST Action 289 and is a result of work done within this European actio
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