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IGDT based robust decision making tool for DNOs in load procurement under severe uncertainty

Soroudi, A ; Sharif University of Technology | 2013

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  1. Type of Document: Article
  2. DOI: 10.1109/TSG.2012.2214071
  3. Publisher: 2013
  4. Abstract:
  5. This paper presents the application of information gap decision theory (IGDT) to help the distribution network operators (DNOs) in choosing the supplying resources for meeting the demand of their customers. The three main energy resources are pool market, distributed generations (DGs), and the bilateral contracts. In deregulated environment, the DNO is faced with many uncertainties associated to the mentioned resources which may not have enough information about their nature and behaviors. In such cases, the classical methods like probabilistic methods or fuzzy methods are not applicable for uncertainty modeling because they need some information about the uncertainty behaviors like probability distribution function (PDF) or their membership functions. In this paper, a decision making framework is proposed based on IGDT model to solve this problem. The uncertain parameters considered here, are as follows: price of electricity in pool market and demand of each bus. The robust strategy of DNO is determined to hedge him against the risk of increasing the total cost beyond what it is willing to pay. The effectiveness of the proposed tool is assessed and demonstrated by applying it on a large distribution network
  6. Keywords:
  7. Distributed generation ; Information gap decision theory ; Risk ; Bilateral contracts ; Decision-making frameworks ; Deregulated environments ; Distributed generations (DGs) ; Distribution network operators ; Information gap ; Probabilistic methods ; Uncertainty ; Commerce ; Distributed power generation ; Distribution functions ; Energy resources ; Probability distributions ; Risks ; Uncertainty analysis ; Decision making
  8. Source: IEEE Transactions on Smart Grid ; Volume 4, Issue 2 , 2013 , Pages 886-895 ; 19493053 (ISSN)
  9. URL: http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6338333