Planning with multiple transmission and storage investment options under uncertainty: a nested decomposition approach

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Title: Planning with multiple transmission and storage investment options under uncertainty: a nested decomposition approach
Authors: Falugi, P
Konstantelos, I
Strbac, G
Item Type: Journal Article
Abstract: Achieving the ambitious climate change mitigation objectives set by governments worldwide is bound to lead to unprecedented amounts of network investment to accommodate low-carbon sources of energy. Beyond investing in conventional transmission lines, new technologies such as energy storage can improve operational flexibility and assist with the cost-effective integration of renewables. Given the long lifetime of these network assets and their substantial capital cost, it is imperative to decide on their deployment on a long-term cost-benefit basis. However, such an analysis can result in large-scale Mixed Integer Linear Programming (MILP) problems which contain many thousands of continuous and binary variables. Complexity is severely exacerbated by the need to accommodate multiple candidate assets and consider a wide range of exogenous system development scenarios that may occur. In this manuscript we propose a novel, efficient and highly-generalizable framework for solving large-scale planning problems under uncertainty by using a temporal decomposition scheme based on the principles of Nested Benders. The challenges that arise due to the presence of non-sequential investment state equations and sub-problem non-convexity are highlighted and tackled. The substantial computational gains of the proposed method are demonstrated via a case study on the IEEE 118 bus test system that involve planning of multiple transmission and storage assets under long-term uncertainty.
Issue Date: 1-Jul-2018
Date of Acceptance: 11-Nov-2017
URI: http://hdl.handle.net/10044/1/53884
DOI: https://dx.doi.org/10.1109/TPWRS.2017.2774367
ISSN: 0885-8950
Publisher: Institute of Electrical and Electronics Engineers
Start Page: 3559
End Page: 3572
Journal / Book Title: IEEE Transactions on Power Systems
Volume: 33
Issue: 4
Copyright Statement: © 2017 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)
Engineering & Physical Science Research Council (EPSRC)
Engineering & Physical Science Research Council (E
Engineering & Physical Science Research Council (EPSRC)
Funder's Grant Number: EP/E020798/1
EP/K002252/1
EEZ1419554
EP/N030028/1
Keywords: Science & Technology
Technology
Engineering, Electrical & Electronic
Engineering
Energy storage
mixed integer-linear programming
nested Benders decomposition
stochastic programming
transmission planning
STOCHASTIC LINEAR-PROGRAMS
L-SHAPED METHOD
CAPACITY EXPANSION
INTEGER PROGRAMS
GENERATION
ALGORITHM
VALUATION
SYSTEMS
MARKET
0906 Electrical And Electronic Engineering
Energy
Publication Status: Published
Online Publication Date: 2017-11-16
Appears in Collections:Faculty of Engineering
Electrical and Electronic Engineering
Centre for Environmental Policy
Faculty of Natural Sciences



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