Feb 2016
Electricity Transmission
Managing uncertainty in future load-related investment
NIA_SPT_1504
Live
Feb 2016
Feb 2019
SP Energy Networks and SP Transmission
James Yu (Future Networks Manager)
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Network Innovation Allowance
None
Electricity Transmission Networks
£300,000.00
To model the uncertainties underlying changing demands on the network and therefore the need for load-related investment.

  • To make use of statistical relationships between weather/time of day/season and the demand/output of individual and aggregated LCTs and underlying demand.
  • To provide the capability to model the uptake of LCTs with respect to customer type etc.
  • To identify and model a suitable exemplar network for test purposes.
  • To construct and demonstrate a framework to sample uncertain factors influencing use of a network and simulate network performance under each of a large number of instances of those variations to  produce a database of input-linked outcomes
  • To develop methods of interrogating and analysing the database to identify intervention priorities and the underlying network, demand and LCT conditions which trigger them
  • To apply the models, framework and methodology to the selected exemplar network to identify ‘weak points’ and ‘points of pressure’, assess overall intervention need and urgency, identify suitable interventions.
  • Compare results with existing Business as Usual (BAU) planning methods.

The development of a ‘production quality’ software tool is not an objective of this project. In order that investment risk is reduced, the development of such a tool will be considered under a subsequent/parallel project once the learning derived from this project is sufficiently developed.

  • Establishment of external influences on the need for network development – generation and demand including installation of solar PV – can be modelled probabilistically in an efficient manner providing useful information to network development planners and network designers on network performance under different conditions.

  • Evidence to support a decision on whether or not to engage with a professional software provider to develop a production grade, supported software tool enabling probabilistic network planning.

  • Specification for suitable professional simulation and analysis tools to exploit models of external influences on network adequacy and for a tool to interrogate and analyse its outputs.