Decision making in an uncertain world: information-gap modeling in water resources management

Hipel, Keith W.; Ben‐Haim, Yakov

doi:10.1109/5326.798765

Cited by 79 publications

(49 citation statements)

References 16 publications

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“…Examples of the application of IG decision theory in the development of long-term water management strategies can be found in Hipel and Ben-Haim (1999), Woods et al (2011), Korteling et al (2013), Matrosov et al (2013) and in the development of robust climate policies in Hall et al (2012b). IG was found to resolve a lot of the weaknesses in current WRM predictive target headroom approaches by analysing multiple plausible representations of the future and establishing a suitable robustness measure to uncertainty; however it was not clear how the local assessment method itself impacted on the differing solutions produced in regard to alternative methods, nor is it clear as to the impact attributed to the origin of the IG analysis.…”

Section: The Current Approach Within the Uk As Stated In The Environmentioning

confidence: 99%

Comparison of Robust Optimization and Info-Gap Methods for Water Resource Management under Deep Uncertainty

Roach

Kapelan

Ledbetter

et al. 2016

J. Water Resour. Plann. Manage.

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This paper evaluates two established decision making methods and analyses their performance and suitability within a Water Resources Management (WRM) problem. The methods under assessment are Info-Gap decision theory (IG) and Robust Optimisation (RO). The methods have been selected primarily to investigate a contrasting local vs global method of assessing water system robustness to deep uncertainty but also to compare a robustness model approach (IG) with a robustness algorithm approach (RO), whereby the former selects and analyses a set of prespecified strategies and the latter uses optimisation algorithms to automatically generate and evaluate solutions. The study presents a novel area-based method for IG robustness modelling and assesses the applicability of utilising the Future Flows climate change projections in scenario generation for water resource adaptation planning. The methods were applied to a case study 2 resembling the Sussex North Water Resource Zone in England, assessing their applicability at improving a risk-based WRM problem and highlighting the strengths and weaknesses of each method at selecting suitable adaptation strategies under climate change and future demand uncertainties. Pareto sets of robustness to cost are produced for both methods and highlight RO as producing the lower costing strategies for the full range of varying target robustness levels. IG produced the more expensive Pareto strategies due to its more selective and stringent robustness analysis, resulting from the more complex scenario ordering process.

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Section: The Current Approach Within the Uk As Stated In The Environmentioning

confidence: 99%

Comparison of Robust Optimization and Info-Gap Methods for Water Resource Management under Deep Uncertainty

Roach

Kapelan

Ledbetter

et al. 2016

J. Water Resour. Plann. Manage.

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“…Info-Gap decision theory provides an approach to compare the ability of different management options to satisfy system performance criteria over an unbounded range of uncertainty and has been used for decision support in many fields from engineering to conservation science (Ben-Haim 2001;Regan et al 2005;McCarthy and Lindenmayer 2007) with one previous application related to water resources, (Hipel and Ben-Haim 1999) and one to flood risk (Hine and Hall 2010). The prospect of dealing with severe uncertainty forces preference away from what is optimum for a defined set of circumstance (to optimise) towards what is good enough over a wide range of possible circumstance (to satisfice).…”

Section: Uncertainty Characterisation and Quantificationmentioning

confidence: 99%

Using Information-Gap Decision Theory for Water Resources Planning Under Severe Uncertainty

Korteling

Dessai

Kapelan

2012

Water Resour Manage

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Water resource managers are required to develop comprehensive water resources plans based on severely uncertain information of the effects of climate change on local hydrology and future socio-economic changes on localised demand. In England and Wales, current water resources planning methodologies include a headroom estimation process separate from water resource simulation modelling. This process quantifies uncertainty based on only one point of an assumed range of deviations from the expected climate and projected demand 25 years into the future. This paper utilises an integrated method based on Information-Gap decision theory to quantitatively assess the robustness of various supply side and demand side management options over a broad range of plausible futures. Findings show that beyond the uncertainty range explored with the headroom method, a preference reversal can occur, i.e. some management options that underperform at lower uncertainties, outperform at higher levels of uncertainty. This study also shows that when 50 % or more of the population adopts demand side management, efficiency related measures and innovative options such as rainwater collection can perform equally well or better than some supply side options The additional use of Multi-Criteria Decision Analysis shifts the focus away from reservoir expansion options, that perform best in regards to water availability, to combined strategies that include innovative demand side management actions of rainwater collection and greywater reuse as well efficiency measures and additional regional transfers. This paper illustrates how an Information-Gap based approach can offer a comprehensive picture of Water Resour Manage (2013)

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“…In its robustness form, the IGDT technique finds the risk-averse strategy for a conservative decision-maker. The robustness function is the greatest level of uncertainty consistent with no failure while the opportunity function is the least level of uncertainty that entails the possibility of sweeping success [18]. In this paper, the robust form of IGDT theory is used to model the uncertainties of load and line parameters.…”

Section: Undervoltage Load Shedding With Uncertainty Modelingmentioning

confidence: 99%

A robust undervoltage load shedding scheme against voltage instability

Kaffashan¹,

Mortezaee²,

Amraee³

2016

Turk J Elec Eng & Comp Sci

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Abstract:Undervoltage load shedding (UVLS) is an effective measure for restoring voltage stability as a last resort in emergency conditions. In this paper, a UVLS scheme is proposed considering the uncertainties of load and line parameters. The loading margin is considered as the voltage stability index. The proposed scheme determines the optimal load shedding pattern subject to technical constraints. The info-gap decision theory uncertainty modeling technique is utilized to find a robust and cost-effective pattern of load shedding. The proposed scheme is formulated as a nonlinear programming problem, which is solved using the sequential quadratic programming technique. The performance of the proposed scheme is verified for the IEEE-14 bus and IEEE-118 bus test systems.

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Decision making in an uncertain world: information-gap modeling in water resources management

Cited by 79 publications

References 16 publications

Comparison of Robust Optimization and Info-Gap Methods for Water Resource Management under Deep Uncertainty

Comparison of Robust Optimization and Info-Gap Methods for Water Resource Management under Deep Uncertainty

Using Information-Gap Decision Theory for Water Resources Planning Under Severe Uncertainty

A robust undervoltage load shedding scheme against voltage instability

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