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논문검색

RNN NARX Model Based Demand Management for Smart Grid

초록

영어

In the smart grid, it will be possible to communicate with the consumers for the purposes of monitoring and controlling their power consumption without disturbing their business or comfort. This will bring easier administration capabilities for the utilities. On the other hand, consumers will require more advanced home automation tools which can be implemented by using advanced sensor technologies. For instance, consumers may need to adapt their consumption according to the dynamically varying electricity prices which necessitates home automation tools. This paper tries to combine neural network and nonlinear autoregressive with exogenous variable (NARX) class for next week electric load forecasting. The suitability of the proposed approach is illustrated through an application to electric load consumption data. The suggested system provides a useful and suitable tool especially for the load forecasting.

목차

Abstract
 1. Introduction
 2. NARX model class
 3. Multilayer perceptron RNN identification scheme
 4. Results
 5. Conclusion
 References

저자정보

  • Sang-Hyun Lee Dept. of Computer Engineering, Honam University, Korea
  • Park Dae-Won Darwin Company, Korea
  • Kyung-Il Moon Dept. of Computer Engineering, Honam University, Korea

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