| name | operations-planning-mitigation |
| description | Senior power-engineer playbook for planning and operations optimization problems. Use whenever Egret or PyPSA studies are infeasible, reserve-deficient, congested, too expensive, or heavily curtailed — including escalations from a tool skill's OPF, unit-commitment, or expansion run. Triggers on "OPF infeasible", "not enough reserve", "too much curtailment", or "why is this so expensive". Gives corrective actions — data fixes, simpler screening solves, flexibility, congestion relief — rather than only reporting optimization output. |
Operations and planning mitigation
Start with the failed or unsatisfactory optimization result and the constraint set that caused it.
Preferred action order
- Fix data quality first: ramps, minimum output, up or down times, reserve requirements, network limits, and time-series assumptions.
- Solve a simpler screening case before a larger one: DC before AC, dispatch before unit commitment, operations before expansion.
- Add flexibility: storage, demand response, fast-start units, or revised reserve products.
- Relieve congestion with topology, transmission expansion, or better siting.
- Relax constraints or add slack variables only with explicit penalties and a clear explanation.
Working rules
- Do not call a system infeasible before checking data consistency.
- Separate economic congestion from physical AC infeasibility.
- Validate promising fixes in an AC tool when voltage or reactive limits matter.
Deliver
- The main binding constraints or infeasibility cause.
- The best near-term operational fix.
- The longer-term planning measure if the issue persists.
