An objective-based scenario selection method for transmission network expansion planning with multivariate stochasticity in load and renewable energy sources

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Title: An objective-based scenario selection method for transmission network expansion planning with multivariate stochasticity in load and renewable energy sources
Authors: Sun, M
Teng, F
Konstantelos, I
Strbac, G
Item Type: Journal Article
Abstract: Transmission Network Expansion Planning (TNEP) in modern electricity systems is carried out on a cost-benefit analysis basis; the planner identifies investments that maximize the social welfare. As the integration of Renewable Energy Sources (RES) increases, there is a real challenge to accurately capture the vast variability that characterizes system operation within a planning problem. Conventional approaches that rely on a large number of scenarios for representing the variability of operating points can quickly lead to computational issues. An alternative approach that is becoming increasingly necessary is to select representative scenarios from the original population via clustering techniques. However, direct clustering of operating points in the input domain may not capture characteristics which are important for investment decision-making. This paper presents a novel objective-based scenario selection framework for TNEP to obtain optimal investment decisions with a significantly reduced number of operating states. Different clustering frameworks, clustering variable s and clustering techniques are compared to determine the most appropriate approach. The superior performance of the proposed framework is demonstrated through a case study on a modified IEEE 118-bus system.
Issue Date: 5-Jan-2018
Date of Acceptance: 30-Dec-2017
URI: http://hdl.handle.net/10044/1/55703
DOI: https://dx.doi.org/10.1016/j.energy.2017.12.154
ISSN: 0360-5442
Publisher: Elsevier
Start Page: 871
End Page: 885
Journal / Book Title: Energy
Volume: 145
Copyright Statement: © 2018, Elsevier. Licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International http://creativecommons.org/licenses/by-nc-nd/4.0/
Sponsor/Funder: Engineering & Physical Science Research Council (EPSRC)
Engineering & Physical Science Research Council (EPSRC)
Engineering and Physical Sciences Research Council
Funder's Grant Number: EP/K002252/1
EP/N005996/1
EP/N005996/1
Keywords: Science & Technology
Physical Sciences
Technology
Thermodynamics
Energy & Fuels
Clustering
Transmission network expansion planning
Resource variability
Wind power
MODEL
POWER
GENERATION
SYSTEMS
CLASSIFICATION
UNCERTAINTY
MANAGEMENT
ALGORITHM
DEMAND
CHINA
0913 Mechanical Engineering
0915 Interdisciplinary Engineering
Energy
Publication Status: Published
Appears in Collections:Faculty of Engineering
Electrical and Electronic Engineering
Centre for Environmental Policy
Faculty of Natural Sciences



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