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Model-Free Distributed Optimization

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Distributed Economic Operation in Smart Grid: Model-Based and Model-Free Perspectives

Part of the book series: Studies in Systems, Decision and Control ((SSDC,volume 455))

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Abstract

In this chapter, we move to address the fundamental optimization problems in smart grid from a model-free perspective due to the randomness of the large-scale renewable energies and the flexibility of the load units. That is to say, these fundamental problems cannot be directly modeled as deterministic optimization problems. So we design learning-based approaches to address the uncertainty and randomness.

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Notes

  1. 1.

    Row-stochastic communication matrix means each agent computes a weighted sum of received data with some weighting factors. The column-stochastic requires these factors to be compatible in sense that each column of communication matrix sums to one.

  2. 2.

    Since the energy demand and consumption of loads is affected by many factors, the state transition is rather difficult to obtain. Therefore, we next employ a model-free Q-learning method to solve the dynamic retail pricing problem.

  3. 3.

    Thus the EDP considered in these situations falls under the umbrella of derivative-free blackbox optimization. It is commonly recognized that if the (generalized) gradient information is reliable and obtainable at a reasonable cost, derivative-free blackbox optimization almost never outperform modern gradient-based methods [76].

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Authors and Affiliations

  1. Department of Automation, University of Science and Technology of China, Hefei, Anhui, China

    Jiahu Qin, Yu Kang & Weiming Fu

  2. School of Physics and Electronic-Electrical Engineering, Ningxia University, Yinchuan, Ningxia, China

    Yanni Wan

  3. School of Electrical and Information Engineering, Zhengzhou University, Zhengzhou, Henan, China

    Fangyuan Li

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  1. Jiahu Qin
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Correspondence to Jiahu Qin .

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Qin, J., Wan, Y., Li, F., Kang, Y., Fu, W. (2023). Model-Free Distributed Optimization. In: Distributed Economic Operation in Smart Grid: Model-Based and Model-Free Perspectives. Studies in Systems, Decision and Control, vol 455. Springer, Singapore. https://doi.org/10.1007/978-981-19-8594-2_4

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