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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2018-01-01
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Series: | Complexity |
Online Access: | http://dx.doi.org/10.1155/2018/1543179 |
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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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