Technoeconomic Distribution Network Planning Using Smart Grid Techniques with Evolutionary Self-Healing Network States

The transition to a secure low-carbon system is raising a set of uncertainties when planning the path to a reliable decarbonised supply. The electricity sector is committing large investments in the transmission and distribution sector upon 2050 in order to ensure grid resilience. The cost and limit...

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Main Authors: Jesus Nieto-Martin, Timoleon Kipouros, Mark Savill, Jennifer Woodruff, Jevgenijs Butans
Format: Article
Language:English
Published: Hindawi-Wiley 2018-01-01
Series:Complexity
Online Access:http://dx.doi.org/10.1155/2018/1543179
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spelling doaj-4c7a81d4812841e5a13be50ce9d552b22020-11-25T03:34:48ZengHindawi-WileyComplexity1076-27871099-05262018-01-01201810.1155/2018/15431791543179Technoeconomic Distribution Network Planning Using Smart Grid Techniques with Evolutionary Self-Healing Network StatesJesus Nieto-Martin0Timoleon Kipouros1Mark Savill2Jennifer Woodruff3Jevgenijs Butans4Power and Propulsion Sciences Group, Cranfield University, Cranfield MK43 0AL, UKPower and Propulsion Sciences Group, Cranfield University, Cranfield MK43 0AL, UKPower and Propulsion Sciences Group, Cranfield University, Cranfield MK43 0AL, UKWestern Power Distribution Innovation, Pegasus Business Park, Derby DE74 2TU, UKComplex System Research Centre, Cranfield School of Management, Cranfield MK43 0AL, UKThe transition to a secure low-carbon system is raising a set of uncertainties when planning the path to a reliable decarbonised supply. The electricity sector is committing large investments in the transmission and distribution sector upon 2050 in order to ensure grid resilience. The cost and limited flexibility of traditional approaches to 11 kV network reinforcement threaten to constrain the uptake of low-carbon technologies. This paper investigates the suitability and cost-effectiveness of smart grid techniques along with traditional reinforcements for the 11 kV electricity distribution network, in order to analyse expected investments up to 2050 under different DECC demand scenarios. The evaluation of asset planning is based on an area of study in Milton Keynes (East Midlands, United Kingdom), being composed of six 11 kV primaries. To undertake this, the analysis used a revolutionary new model tool for electricity distribution network planning, called scenario investment model (SIM). Comprehensive comparisons of short- and long-term evolutionary investment planning strategies are presented. The work helps electricity network operators to visualise and design operational planning investments providing bottom-up decision support.http://dx.doi.org/10.1155/2018/1543179
collection DOAJ
language English
format Article
sources DOAJ
author Jesus Nieto-Martin
Timoleon Kipouros
Mark Savill
Jennifer Woodruff
Jevgenijs Butans
spellingShingle Jesus Nieto-Martin
Timoleon Kipouros
Mark Savill
Jennifer Woodruff
Jevgenijs Butans
Technoeconomic Distribution Network Planning Using Smart Grid Techniques with Evolutionary Self-Healing Network States
Complexity
author_facet Jesus Nieto-Martin
Timoleon Kipouros
Mark Savill
Jennifer Woodruff
Jevgenijs Butans
author_sort Jesus Nieto-Martin
title Technoeconomic Distribution Network Planning Using Smart Grid Techniques with Evolutionary Self-Healing Network States
title_short Technoeconomic Distribution Network Planning Using Smart Grid Techniques with Evolutionary Self-Healing Network States
title_full Technoeconomic Distribution Network Planning Using Smart Grid Techniques with Evolutionary Self-Healing Network States
title_fullStr Technoeconomic Distribution Network Planning Using Smart Grid Techniques with Evolutionary Self-Healing Network States
title_full_unstemmed Technoeconomic Distribution Network Planning Using Smart Grid Techniques with Evolutionary Self-Healing Network States
title_sort technoeconomic distribution network planning using smart grid techniques with evolutionary self-healing network states
publisher Hindawi-Wiley
series Complexity
issn 1076-2787
1099-0526
publishDate 2018-01-01
description The transition to a secure low-carbon system is raising a set of uncertainties when planning the path to a reliable decarbonised supply. The electricity sector is committing large investments in the transmission and distribution sector upon 2050 in order to ensure grid resilience. The cost and limited flexibility of traditional approaches to 11 kV network reinforcement threaten to constrain the uptake of low-carbon technologies. This paper investigates the suitability and cost-effectiveness of smart grid techniques along with traditional reinforcements for the 11 kV electricity distribution network, in order to analyse expected investments up to 2050 under different DECC demand scenarios. The evaluation of asset planning is based on an area of study in Milton Keynes (East Midlands, United Kingdom), being composed of six 11 kV primaries. To undertake this, the analysis used a revolutionary new model tool for electricity distribution network planning, called scenario investment model (SIM). Comprehensive comparisons of short- and long-term evolutionary investment planning strategies are presented. The work helps electricity network operators to visualise and design operational planning investments providing bottom-up decision support.
url http://dx.doi.org/10.1155/2018/1543179
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