Taxonomy of Uncertainty Modeling Techniques in Renewable Energy System Studies

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Title: Taxonomy of Uncertainty Modeling Techniques in Renewable Energy System Studies
Authors: Soroudi, Alireza
Permanent link: http://hdl.handle.net/10197/11238
Date: 28-Jan-2014
Online since: 2019-12-10T10:13:41Z
Abstract: With the introduction of new concepts in operation and planning of power systems, decision making is becoming more critical than ever before. These concepts include restructuring, smart grids, and the importance of environmental concerns. The art of decision making is defined as choosing the best action among available choices considering the constraints and input data of the problem. Decision making is usually a complex task which becomes more sophisticated when the input data of the problem are subject to uncertainty. This chapter presents a critical review of the state-of-the-art uncertainty in handling tools for renewable energy studies. Different uncertainty modeling tools are first introduced and then the appropriate ones for renewable energies are identified. Then, each method is implemented on a simple two-bus case study.
Type of material: Book Chapter
Publisher: Springer
Series/Report no.: Green Energy and Technology book series (GREEN)
Copyright (published version): 2014 Springer
Keywords: UncertaintyMonte Carlo simulationPoint estimate methodScenario based uncertainty modellingScenario based uncertainty decision making
DOI: 10.1007/978-981-4585-30-9_1
Language: en
Status of Item: Peer reviewed
Is part of: Hossain, J., Mahmud, A. (eds.). Large Scale Renewable Power Generation: Advances in Technologies for Generation, Transmission and Storage
ISBN: 978-981-4585-30-9
Appears in Collections:Electrical and Electronic Engineering Research Collection

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