A day-ahead unit commitment optimization method for ramping demand in uncertain scenarios
Through a day-ahead unit combination optimization method for uncertain scenarios, combined with thermal power unit and energy storage scheduling models, Latin hypercube sampling is used to generate renewable energy output error prediction curves. Taking into account the power support of inter-provincial interconnection lines, the output of flexible resources within the power system is optimized, solving the problem of insufficient peak-shaving capacity of the power system, achieving cost reduction and stable system operation.
Patent Information
- Application Number
- CN202411947435.7
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- Filing Date
- 2024-12-27
- Publication Date
- 2025-09-23
- Estimated Expiration
- 2044-12-27
AI Technical Summary
Existing technologies, when dealing with the uncertainty of renewable energy output, result in insufficient peak-shaving capacity of the power system, and existing methods have problems of poor economic efficiency or conservative results.
A day-ahead unit commitment optimization method for uncertain scenarios is adopted. Through the thermal power unit scheduling model, energy storage scheduling model and renewable energy output scenario set, combined with Latin hypercube sampling, a renewable energy output error prediction curve is generated. Taking into account the power support of inter-provincial interconnection lines, the output of flexible resources within the system is optimized.
While ensuring the stable operation of the system, it reduces power supply costs, optimizes the output of thermal power units and energy storage resources within the system, and solves the problem of insufficient peak-shaving capacity of the power system.