National Grid ESO (NGESO) is the electricity system operator for Great Britain. It balances the generation and demand for electricity to maintain a secure, reliable and high-quality electricity supply. To achieve this, NGESO’s control room predicts when supply and demand will be imbalanced and dispatches instructions to increase or decrease electricity generation (or consumption) for that time period. The Smith Institute is supporting NGESO as they modernise one of the core software tools in this balancing process, using our expertise in optimisation and algorithm design.

NGESO’s control room instructs electricity generators (or consumers) known as Balancing Mechanism Units (BMUs) to change their power levels or provide other balancing services, such as response, which ensure system security. Response is readiness to provide electricity generation or demand at short notice, enabling NGESO to recover from unexpected events such as the loss of a generator. Control room engineers rely on the dispatch algorithm to aid their decision-making as they make near to real-time balancing decisions. The dispatch algorithm provides economic advice on power levels and response allocation for BMUs.

National Grid ESO ensures that generation of and demand for electricity in Great Britain are always equal. Their control room can take a range of balancing actions including: exporting or importing electricity to other countries via electricity interconnectors, increasing/decreasing the power levels of some generation types, or increasing/decreasing the energy consumption of some demand types (e.g. batteries).

NGESO has embarked on a programme to modernise the dispatch algorithm, to meet the challenges of the rapidly evolving GB electricity network and to ensure a robust software solution for the future. The need for modernisation has largely been driven by NGESO’s commitment to operate a zero carbon electricity network. The legacy algorithm was designed at a time when electricity generation was provided by less than 40 large and mostly non-renewable BMUs. The growth in renewable generation means that the dispatch algorithm will now need to handle the additional volatility introduced by hundreds of smaller and mostly renewable BMUs.

In late 2018 the Smith Institute led a series of knowledge capture workshops on the modelling and software implementation aspects of the legacy dispatch algorithm. We worked closely with NGESO staff, including the control room engineers who are the end users, to identify the strengths and limitations of the legacy algorithm and approach.

As a result of the workshops the Smith Institute recommended an improved mathematical model for the dispatch algorithm and presented further recommendations concerning algorithm design and software implementation choices. In 2019, the Smith Institute created a proof of concept algorithm which demonstrated that the improved model formulation, in combination with the other recommendations, produced equivalent or better dispatch advice than the legacy algorithm.

The Smith Institute continues to support NGESO as they implement a modernised dispatch algorithm based on the proof of concept. We are collaborating with NGESO on integrating a first version of a modernised dispatch algorithm into the control room and in the development of new functionalities which will enable the transition to zero carbon electricity network operation.