Reducing Generation Uncertainty by Integrating CSP With Wind Power: An Adaptive Robust Optimization-Based Analysis

被引:94
作者
Chen, Runze [1 ]
Sun, Hongbin [1 ]
Guo, Qinglai [1 ]
Li, Zhigang [1 ]
Deng, Tianhu [2 ]
Wu, Wenchuan [1 ]
Zhang, Boming [1 ]
机构
[1] Tsinghua Univ, Dept Elect Engn, Beijing 100084, Peoples R China
[2] Tsinghua Univ, Dept Ind Engn, Beijing 100084, Peoples R China
基金
中国国家自然科学基金; 英国工程与自然科学研究理事会;
关键词
Adaptive robust optimization (RO); concentrating solar power (CSP); thermal energy storage; uncertainty; wind power; CONCENTRATING SOLAR POWER; ENERGY-STORAGE; COORDINATION; PLANTS;
D O I
10.1109/TSTE.2015.2396971
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
The uncertainty of wind power generation brings problems in power system operation, such as requiring more reserves and possible frequency issues. In this paper, we propose an idea of combining concentrating solar power (CSP) plants with wind farms to reduce the overall uncertainty in the joint power output. Taking advantage of the dispatchability of CSP, the uncertainty of joint power generation is expected to decrease. Based on the operational model of CSP plants with thermal storage system, we search for the narrowest but robust bounds of the joint power output with a given uncertainty of the wind power output and solar power availability, and within operational constraints of CSP plants. The problem is formulated as an adaptive robust optimization (RO) problem, containing mixed-integer variables at the second stage. We introduce an algorithm that combines a nested column-and-constraint generation (C-CG) method and an outer approximation (OA) method to solve the problem. The case studies show that robust intervals for the joint power output can be obtained, and the obtained intervals can be significantly narrower than the original intervals of wind power.
引用
收藏
页码:583 / 594
页数:12
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