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Zhu, Z., Zhang, J. and Ye, Y. (2006) Newsvendor Optimization with Limited Distribution Information. Working Paper, Stanford University, Stanford.

has been cited by the following article:

• TITLE: Wind Power Bidding Strategy Based on the Minimax Regret Criterion with Limited Distribution Information

  AUTHORS: Yashan Mao, Jianfang Tian, Qiaozhu Zhai

  KEYWORDS: Bidding Strategy; Expected Profit; Partial Distribution Information; Minimax Regret Criterion; Imbalance Cost

  JOURNAL NAME: Journal of Power and Energy Engineering, Vol.2 No.4, April 16, 2014

  ABSTRACT: In optimal wind bidding strategy related literatures, it is usually assumed that the full distribution information (for example, the cumulative distribution function or the probability density function) of wind power output is known. In real world applications, however, only very limited distribution information can be obtained. Therefore, the “optimal bidding strategy” obtained based on the hypothetical distribution may be far away from the true optimal one. In this paper, an optimal bidding strategy is obtained based on the minimax regret criterion. The salient feature of the new approach is that it requires only partial information of wind power distribution, for example, the expectation and the support set. Numerical test is then performed and the results suggest that the method established in this paper is effective.