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IGDT Based Robust Decision Making Tool for DNOs in Load Procurement Under Severe Uncertainty
Author(s)
Date Issued
2013-06
Date Available
2014-11-17T15:18:54Z
Abstract
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, demand of each bus and the decisions of DG investors. The robust strategy of DNO is determined to hedge him against the risk of increasing the total cost beyond what he is willing to pay. The effectiveness of the
proposed tool is assessed and demonstrated by applying it on a test distribution network.
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, demand of each bus and the decisions of DG investors. The robust strategy of DNO is determined to hedge him against the risk of increasing the total cost beyond what he is willing to pay. The effectiveness of the
proposed tool is assessed and demonstrated by applying it on a test distribution network.
Type of Material
Journal Article
Publisher
Institute of Electrical and Electronics Engineers
Journal
IEEE Transactions on Smart Grid
Volume
4
Issue
2
Start Page
886
End Page
895
Copyright (Published Version)
2012 Institute of Electrical and Electronics Engineers
Language
English
Status of Item
Peer reviewed
This item is made available under a Creative Commons License
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