Market Behaviour Simulation Tool
Project summary
Traditional planning models often struggle to reflect how developers make commercial and strategic decisions, limiting the ability to understand how market participants may respond to future policy or market design changes.
| Name | Status | Project reference number | Start date | Proposed End date | Expenditure |
|---|---|---|---|---|---|
| Market Behaviour Simulation Tool | Live | NIA2_NESO126 | Mar 2026 | Aug 2027 | £800,000 |
Traditional planning models often struggle to reflect how developers make commercial and strategic decisions, limiting the ability to understand how market participants may respond to future policy or market design changes. This project will address that challenge by creating a proof of concept (POC) Developer Behaviour Simulation Tool that uses advanced modelling techniques to represent realistic investor behaviour across different market conditions. Running from March 2026 to August 2027, the project will deliver a Modelling Definitions Report, a demonstration model, and an Insight Report. The tool will help assess long‑term impacts of market and connection reforms, highlight potential unintended incentives, and provide a stronger evidence base for policy development. Expected benefits include improved forecasting, reduced system risks, and more credible long‑term planning.
Benefits
Much of today’s market design relies on deterministic models with simple behavioural assumptions. In contrast agent based models could:
- Enable NESO to test and refine market and connection reforms using realistic simulations of developer behaviour.
- Provides robust, evidence-based insights for government and regulatory decisions.
- Helps avoid stranded assets, curtailment hotspots, and security gaps by predicting real-world investment responses.
- Supports efficient, timely investment aligned with net zero goals.
- Deliver powerful tools for scenario testing and data-driven decision making.
Incorporating strategic behaviour through agent based modelling addresses this gap by representing individual decisionmakers explicitly. By allowing agents to draw on their own information, rather than converging to a simplified equilibrium, real world market behaviour can be better represented.
| Name | Published |
|---|---|
| NIA Project Registration and PEA Document | 2 Apr 2026 |