Option value of demand-side response schemes under decision-dependent uncertainty

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Title: Option value of demand-side response schemes under decision-dependent uncertainty
Authors: Giannelos, S
Konstantelos, I
Strbac, G
Item Type: Journal Article
Abstract: Uncertainty in power system planning problems can be categorized into two types: exogenous and endogenous (or decision-dependent) uncertainty. In the latter case, uncertainty resolution depends on a choice (the value of some decision variables), as opposed to the former case in which the uncertainty resolves automatically with the passage of time. In this paper, a novel stochastic multistage planning model is proposed that considers endogenous uncertainty around consumer participation in demand-side response (DSR) schemes. This uncertainty can resolve following DSR deployment in two possible ways: locally (at a single bus) and globally (across the entire system). The original formulation is decomposed with the use of Benders decomposition to improve computational performance. Two versions of Benders decomposition are applied: the classic version involving sequential implementation of all operational subproblems and a novel version, specific to problems with endogenous uncertainty, which allows for the parallel execution of only those operational subproblems that are guaranteed to have a unique contribution to the solution. Case studies on 11-bus and 123-bus systems illustrate the process of endogenous uncertainty resolution and underline the strategic importance of deploying DSR ahead of time.
Issue Date: 1-Sep-2018
Date of Acceptance: 17-Jan-2018
URI: http://hdl.handle.net/10044/1/56238
DOI: https://dx.doi.org/10.1109/TPWRS.2018.2796076
ISSN: 0885-8950
Publisher: Institute of Electrical and Electronics Engineers
Start Page: 5103
End Page: 5113
Journal / Book Title: IEEE Transactions on Power Systems
Volume: 33
Issue: 5
Copyright Statement: © 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Sponsor/Funder: Engineering & Physical Science Research Council (EPSRC)
Funder's Grant Number: EP/N030028/1
Keywords: Science & Technology
Technology
Engineering, Electrical & Electronic
Engineering
Benders decomposition
demand side response
endogenous uncertainty
option value
stochastic optimization
STOCHASTIC-PROGRAMMING APPROACH
DISTRIBUTION NETWORKS
POWER
MODEL
0906 Electrical And Electronic Engineering
Energy
Publication Status: Published
Online Publication Date: 2018-01-30
Appears in Collections:Faculty of Engineering
Electrical and Electronic Engineering
Centre for Environmental Policy
Faculty of Natural Sciences



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