Day-ahead interval optimization for CCHP system considering uncertainty of wind power and PV

被引：46

作者：

Zeng, Linjun ^{[1
]}

Xu, Jiazhu ^{[1
]}

Wu, Min ^{[1
]}

Tang, Jiachang ^{[2
]}

Wu, Qiuwei ^{[3
]}

Wang, Qike ^{[1
]}

Fan, Guoqi ^{[4
]}

机构：

[1] Hunan Univ, Coll Elect & Informat Engn, Changsha, Hunan, Peoples R China

[2] Hunan Univ Technol, Dept Mech Engn, Changsha, Hunan, Peoples R China

[3] Tech Univ Denmark, Dept Elect Engn, Copenhagen, Denmark

[4] State Grid Jinhua Power Supply Co, Jinhua, Zhejiang, Peoples R China

来源：

INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS | 2022年 / 138卷

关键词：

CCHP; Day-ahead optimization; Interval optimization; MILP; Uncertainty; OPERATION; GAS; ELECTRICITY;

D O I：

10.1016/j.ijepes.2021.107895

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

To address the uncertainty of renewable energy and different load demands under different seasons in combined cooling, heating, and power (CCHP) system, a day-ahead interval scheduling optimization method is proposed for the CCHP system taking into account the uncertainty of wind power and photovoltaic (PV). Based on the interval theory, the uncertainty of wind power and PV are expressed by intervals. The total operating cost of carbon oxide emissions treatment cost and energy purchase cost is minimized as an objective function. A day- ahead interval optimization model of the CCHP system including wind power, PV, and energy storage is established considering different load demands in four seasons. The established nonlinear integer programming model is converted into the mixed-integer linear programming (MILP) model. The model is solved by interval linear programming. The CCHP system of a park is studied and compared with robust optimization. The simu-lation results verify the effectiveness of the method in this paper to achieve effective cooperative operation of the economy and environmental protection

引用

页数：9

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