Oct 2017
Electricity Distribution
Risk Assessment and Modelling of Smart nEtwork Solutions (RAMSES)
NIA_SSEN_0031
Complete
Oct 2017
Oct 2018
Scottish and Southern Electricity Networks, Scottish Hydro Electric Power Distribution and Southern Electric Power Distribution
SSEN Future Networks Team
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Network Innovation Allowance
ED - Network improvements and system operability
Asset Management
£230,624.00
The project will run for a period of 9 months and is broken down into three work packages. The scope of each work package is shown below with clearly defined deliverables.

Phase One

  1. Consolidated list of non-conventional solutions considered for the risk analysis.
  2. Summarised outputs of expert interviews.
  3. Detailed risk analysis of each non-conventional solution using PESTLE framework and associated insights.
  4. Risk curves for each solution prioritised which will consist of the different risk types relevant to the solution along with a probability function outlining risk of sub-optimal outputs put together evidenced by desk research of relevant projects, lab tests/simulations and expert interviews.

    Phase Two

  5. Set of quality controlled input data to be used for core modelling and sensitivity analysis.
  6. Quantitative outputs from detailed core network modelling indicating materiality of various factors including network types.
  7. Quantitative outputs from sensitivity analysis using network modelling (IC) which will test factors beyond core modelling as identified in the 1st phase.

    Phase Three

  8. Key insights from desk research and interviews in terms of non-conventional risk identification and communication in both within and outside the energy sector.
  9. List of key stakeholders in the process of risk communication and a brief profile of motivations and expectations.
  10. Draft risk communication framework to act as high-level guidance on estimating and communicating risks focusing on glossary of terms, key metrics, methods and presentation styles.
  11. Close down report summarising method, key learnings, recommendations and identified next steps.

Understanding the risks and complexities of new flexible assets are critical to allow network operators to balance costs, network reliability and resilience.
The objective is to:
1. Enable better understanding of the underlying risks that arise from deployment of non-conventional network assets.
2. Develop and configure an existing modelling tool that is able to  test different investment strategies and calculate their associated risks
3. Use model results to develop a new framework and communication strategy that highlights the risks associated with deployment of non-conventional network assets.
 

This project will be a success if:
  1. Understanding of risks associated with deployment of non-conventional network assets is improved compared with current understanding and these learnings are documented coherently. Where understanding is not improved any further, a clear path to improving understanding is documented, as well as the failures/learnings encountered by this project.
  2. A model is developed/configured that is able to test different investment scenarios in order to provide risk outputs, which can help inform investment and strategy decisions. Where a model is created to test different scenarios but is unable to provide usable risk outcomes to inform investment decisions then a clear roadmap on how to improve the model to meet this goal must be provided as well as documenting lessons learned/failures.
  3. A framework/communication strategy is created that utilises the learning from this project to inform DNOs of the different risks associated with non-conventional network assets. Where learnings are inadequate to produce a framework/communication strategy then learnings must be documented with a clear research path necessary to meet this objective.