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Projects: Projects for Investigator
Reference Number	NIA_SSEN_0031
Title	Risk Assessment and Modelling of Smart nEtwork Solutions (RAMSES)
Status	Completed
Energy Categories	Other Cross-Cutting Technologies or Research(Energy system analysis) 50%; Other Cross-Cutting Technologies or Research(Other Supporting Data) 50%;
Research Types	Applied Research and Development 100%
Science and Technology Fields	SOCIAL SCIENCES (Economics and Econometrics) 20%; SOCIAL SCIENCES (Business and Management Studies) 20%; PHYSICAL SCIENCES AND MATHEMATICS (Applied Mathematics) 20%; PHYSICAL SCIENCES AND MATHEMATICS (Computer Science and Informatics) 20%; ENGINEERING AND TECHNOLOGY (Electrical and Electronic Engineering) 20%;
UKERC Cross Cutting Characterisation	Systems Analysis related to energy R&D (Other Systems Analysis) 100%
Principal Investigator	Project Contact No email address given Scottish and Southern Energy plc
Award Type	Network Innovation Allowance
Funding Source	Ofgem
Start Date	01 October 2017
End Date	01 October 2018
Duration	ENA months
Total Grant Value	£230,624
Industrial Sectors	Power
Region	Scotland
Programme	Network Innovation Allowance
Investigators	Principal Investigator	Project Contact , Scottish and Southern Energy plc (100.000%)
	Industrial Collaborator	Project Contact , Scottish and Southern Energy plc (0.000%)
Web Site	https://smarter.energynetworks.org/projects/NIA_SSEN_0031
Objectives	The project is a technical method which will be delivered over three key phases:Phase One: This phase incudes collecting all input data and putting together risks curves for non-conventional technologies through expert interviewsPhase Two: This phase is focussed on designing model runs, enhancing model capability, running the core model runs, sensitivity analysis and iteration of the model runPhase Three: The final phase will develop risk communication frameworks through analysing best practice examples in energy and other sectors and will also include writing the close down report summarising findings and next stepsCarbon Trust and Imperial College have been selected as project partners as they are able to provide industry expertise and modelling expertise, respectively.Phase OneDevelopment/adaptation of future energy scenarios - While there are several Future Energy Scenarios (FES) developed by a variety of organisations, there are no established scenarios that focus on laying out the various pathways of flexibility solutions. The FES from National Grid has started to provide some detail on the non-conventional solutions in their various pathways and we propose to use this as the starting point. The importance of this step is to mainly draw out key external factors such as policy, regulation, social willingness and development of supply chain and their impact on overall risk landscape and also the relative magnitude of the different categories of risk across different futures.This phase will also include a high-level horizon scanning exercise to draw out experience (successes and failures) from other sectors such as finance and banking in understanding and mitigating evolving risks in complex systems. In addition, relevant projects and initiatives evolving approaches to whole energy systems in the UK such as the Future Power Systems Architecture (FPSA) will be engaged at a high level to complement the horizon scan.Analysis of non-conventional solutions and risk assessment: Using a mixture of desk research, literature reviews and using internal datasets and expert interviews, we will put together data sheets for the key non-conventional solutions. Some of the solutions we will examine include:Demand side response (industrial and commercial)Demand side response (residential)Distributed electricity storage (lithium ion)Backup generatorsThe exact list of attributes and their source data will be finalised once the project is kicked off and will include for example:Typical power ratingDuration of responseRobustness of communications linkPercentage (%) availabilityOnce the key attributes of the solutions are consolidated and validated, the next key step in this phase is developing a detailed risk register for each of the solutions. We propose to use a Political, Economic, Social, Technological and Environmental (PESTLE) framework for guidance to ensure the different categories of risk are considered and outlined where possible. These qualitative risk descriptions will then be converted to quantitative estimates mainly in terms of reduced capacity or reduced availability for specific scenarios using outputs from the 1st phase. As part of the risk assessment, we will also include the assessment of potential combinatorial risks i.e. those that emerge as a result of interactions between different risks. Once the preliminary list of risk categories are identified, an initial prioritisation exercise will be carried out based on desk research further supplemented by expert interviews. The main parameters proposed for driving the prioritisation is likelihood and severity to produce a shortlist set of high risk categories. This phase will also identify those types of risks against relevant flexible network technologies where further work may be necessary to better understand their impact.Phase 2Probabilistic quantitative modelling: The probabilistic model aims to quantify the risk of unserved energy (energy not delivered to customers) and determine the inherent costs of deploying different grid reinforcement strategies. The strategies will include a combination of conventional and non-conventional assets deployed for increasing the grids capacity over the period of analysis. Modelling will also include the effects of mitigation measures on overall risk score. Imperial College has an existing model that is able to model certain network risks. This phase will involve configuring Imperials model to ensure it can be utilised effectively to simulate the risks we are attempting to model.Phase 3Development of a framework to communicate risk: This phase of the work will first carry out a high-level landscape assessment of existing reporting frameworks particularly those used by network operators currently to estimate and report risk to Ofgem such as the common indices methodology.The risk reporting frameworks and standards used in the financial sector will also be examined to see if there are opportunities for transferring best practices. Based on the learnings from the risk reporting frameworks and outputs from the modelling exercise, we will put together a high-level guidance on estimating and communicating risks focussing on glossary of terms, key metrics, methods and presentation styles.This phase will end with a final internal dissemination event with stakeholders to present and discuss the findings. 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 One1. 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 Two5. 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 Three8. 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 risks3.Use model results to develop a new framework and communication strategy that highlights the risks associated with deployment of non-conventional network assets.
Abstract	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 Consolidated list of non-conventional solutions considered for the risk analysis. Summarised outputs of expert interviews. Detailed risk analysis of each non-conventional solution using PESTLE framework and associated insights. 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 Set of quality controlled input data to be used for core modelling and sensitivity analysis. Quantitative outputs from detailed core network modelling indicating materiality of various factors including network types. Quantitative outputs from sensitivity analysis using network modelling (IC) which will test factors beyond core modelling as identified in the 1st phase. Phase Three Key insights from desk research and interviews in terms of non-conventional risk identification and communication in both within and outside the energy sector. List of key stakeholders in the process of risk communication and a brief profile of motivations and expectations. 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. Close down report summarising method, key learnings, recommendations and identified next steps.
Publications	(none)
Final Report	(none)
Added to Database	15/12/22