基于需求响应的新能源置信容量提升方法、设备及介质
By constructing an optimized scheduling model with reliability indicators as the target, and combining the temporal characteristics and constraints of demand response resources, the problems of large computational load and large error in traditional methods are solved. This achieves efficient and accurate improvement of new energy confidence capacity, and the generated scheduling strategy conforms to actual physical laws and has practical engineering value.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- CHINA DATANG TECH & ECONOMY RES INST CO LTD
- Filing Date
- 2025-12-10
- Publication Date
- 2026-07-17
AI Technical Summary
Existing technologies struggle to effectively incorporate demand response resources into the assessment of new energy confidence capacity. Traditional methods involve large computational loads, significant errors, and cannot guarantee optimal scheduling strategies, thus failing to effectively improve the confidence capacity of new energy sources.
An optimal scheduling model with reliability index as the objective function is constructed. The probability table of outage capacity of conventional units is fitted by an exponential function. Combining the time-series characteristics and constraints of demand response resources, a nonlinear programming solver is used to solve the optimal scheduling strategy. The maximum confidence capacity is obtained through a two-stage optimization evaluation framework.
It achieves efficient and accurate optimization of demand response strategies, ensures maximum confidence capacity, improves the system reliability and computational efficiency of new energy, and the generated scheduling strategy conforms to actual physical laws and has practical engineering value.
Smart Images
Figure CN121689054B_ABST