Technoeconomic distribution network planning using smart grid techniques with evolutionary self-healing network states
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Publication Date
2018-01-01Journal Title
Complexity
ISSN
1076-2787
Publisher
Wiley-Blackwell
Volume
2018
Type
Article
Metadata
Show full item recordCitation
Nieto-Martin, J., Kipouros, T., Savill, M., Woodruff, J., & Butans, J. (2018). Technoeconomic distribution network planning using smart grid techniques with evolutionary self-healing network states. Complexity, 2018 https://doi.org/10.1155/2018/1543179
Abstract
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.
Sponsorship
OFGEM and the Low Carbon Network Fund
Identifiers
External DOI: https://doi.org/10.1155/2018/1543179
This record's URL: https://www.repository.cam.ac.uk/handle/1810/285828
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