Maximization of Smoothing Effects for Photovoltaic Generation via Game Theoretic Learning Algorithm

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  • HATANAKA Takeshi
    Department of Mechanical and Control Engineering, Tokyo Institute of Technology
  • FUJITA Masayuki
    Department of Mechanical and Control Engineering, Tokyo Institute of Technology

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  • ゲーム理論的学習アルゴリズムに基づく太陽光発電出力のならし効果最大化
  • ゲーム リロンテキ ガクシュウ アルゴリズム ニ モトズク タイヨウコウ ハツデン シュツリョク ノ ナラシ コウカ サイタイカ

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Abstract

In this paper, we focus on smoothing effects for photovoltaic generation and investigate its maximization problem based on game theory. We first confirm the smoothing effects through data analysis of global solar radiation profiles. We next formulate an optimal energy source selection problem and then reduce the problem to so-called resource allocation games. After pointing out that the game is reduced to so-called potential games, we present a real-time implementation method of a payoff-based learning algorithm leading players to the optimal action without prior knowledge on utility functions. Finally, we demonstrate its effectiveness through simulation.

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