Valuing flexibility: uncertainty, risk and regret

22 Aug 2019
Valuing flexibility - uncertainty, risk and regret

All of Great Britain’s Distribution Network Operators (DNOs) are taking actions to access greater load flexibility on their networks. Together, they have committed to testing the market for flexibility services as a means of managing network constraints[1], and have published six key steps for achieving this[2]. Use of flexibility services could mean increased real-time (or close to real-time) coordination, operation and optimisation of the network, which will require improvements in dispatch capability, forecasting, and management of operational risk.

A robust approach to managing risk will be key for ensuring flexibility requirements can be quantified, procured and managed efficiently, and its value can thus be released. Uncertainty about both the long-term and short-term evolution of the energy system is likely to be a key source of risk for DNOs. There are big questions about, for example, the extent and pace of decarbonisation, which industry is increasingly exploring through the use of plausible energy pathways and scenarios, such as National Grid’s Future Energy Scenarios and equivalents on the distribution network. One of the most salient details about such scenario modelling is that one scenario is not deemed more or less likely than another, the only assumption being that they are all plausible. On the other hand, within a specific scenario, questions like “how much demand will a group of 10 EVs use at a certain time of day” can be answered with associated probabilities (although, this has challenges too, as we described in our February paper[3] on “Small Data”). This is true at all levels of the distribution network, but there might be a different focus for different voltage levels. For example, for flexibility on the EHV network, it is probably most important to consider the statistical correlations between demand and different types of variable generation (wind and solar).

Careful consideration of these different types of uncertainty could help to make flexibility services more efficient. DNOs have a lot of very valuable information about their network, how customers behave, and how this affects and is affected by constraints. DNOs are therefore in a unique position to use this data to help manage risks related to flexibility by, for example, providing as detailed information as possible about specific flexibility service requirements, based on robust modelling and statistical analysis. Quantifying risks and uncertainties where possible, – such as the correlations between extremely high wind output and extremely low demand, and how this varies by season and time of day – will enable better management of risk between the DNO and its flexibility service providers, to ensure economically efficient service costs, to the ultimate benefit of regular customers.

In its August 2019 position paper on distribution system operation, Ofgem notes that flexibility has “optionality value”, “especially when there is a high degree of uncertainty in future system needs for example related to EV uptake”[4]. Where uncertainties can’t be translated into probabilities, approaches from the field of decision making under uncertainty could be used to help quantify this optionality value, thus supporting network planning and investment decisions. TNEI has published a paper which explores this in more detail, and considers how tools from decision theory could be used to help identify the value that flexibility has for DNOs. This is very similar to the approach that NGESO makes when making investment recommendations as part of the Network Options Assessment process - in fact, this is one of the key applications of their Future Energy Scenarios.

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To find out more about our views on flexibility and uncertainty, or to share feedback on our latest paper, please get in touch.