The project aims to explore the feasibility of a concept designed to reduce the volatility of boundary flows during constrained periods. It proposes using a flexibility service provider (FSP) to modulate supply or demand in response to real-time data, thereby smoothing the flow and potentially reducing the need for costly redispatch or curtailment of generators.
The project will involve worldwide benchmarking research, analysis of boundary flow variability, development of simplified archetypes, exploration of smoothing algorithms, and estimation of consumer and environmental benefits.
Benefits
The project should provide NESO with:
• A clearer understanding of whether an algorithm could be designed to alter the supply and demand of flexible assets, significantly reducing the variability in boundary flows.
• Determine whether a service based on this concept would allow the control room to increase pre-fault boundary flows and generate a significant economic benefit to consumers.
Learnings
Outcomes
The project investigated the feasibility of using assets to smooth short-term volatility in boundary power flows across GB electricity network. The key findings and outcomes are as follows:
1. Reduction in Volatility: Smoothing reduces short-term volatility but does not add network capacity. The monetary benefit depends on Control Room decisions becoming less conservative when volatility is lower.
2. Cost Savings: Indicative gross savings from reduced BOAs are in the low single millions of pounds per year across the analysed boundary set. Annualised savings range from £0.7m to £4.0m, depending on deployment assumptions.
3. Operational Requirements: Over 15 months, the algorithm implies about 711 GWh of cumulative energy throughput, 3.3 GWh of total effective storage capacity, frequent operation during constrained periods, and peak power inputs for assets up to ~2.9 GW at individual boundaries.
4. Provider Opportunity Costs: Derived ceiling prices are low relative to provider opportunity costs.
5. Nested Boundaries: The nested nature of the boundaries often prevents local safety-margin reductions from translating into additional transferable energy, since downstream constraints can block incremental flow.
6. Assumptions and Limitations: The analysis assumes instantaneous asset response, 100% efficiency, and no network losses. These assumptions likely overstate potential savings and operational volumes in some intervals.
7. Technology Suitability: Technologies with fast response and high ramp rates are most suitable. Battery Energy Storage Systems (BESS), long-duration BESS, and flexible data centres meet these criteria.
8. Conclusions: Under current conditions and assumptions, the feasibility case for boundary flow smoothing is weak. Gross BOA savings are modest, benefits are highly assumption-sensitive, nested constraints frequently limit realisable additional flow, and the inferred ceiling prices are low relative to provider opportunity costs.
Lessons Learnt
Establishing a collaborative point of contact in the control room from the outset would have prevented the misunderstanding about whether a safety margin was routinely applied during system operation and would have provided a clearer understanding of the issue.
Engaging with other NESO project leads in the control room, especially the Dispatch Transparency Methodology project (NIA2_NESO092) was valuable, as it enabled us to align methodologies with other internal projects where appropriate.
