Medium- and long-term interval optimal scheduling of cascade hydropower-photovoltaic complementary systems considering multiple uncertainties

被引:10
|
作者
Lu, Na [1 ,2 ]
Wang, Guangyan [1 ,2 ]
Su, Chengguo [1 ,2 ]
Ren, Zaimin [3 ]
Peng, Xiaoyue [1 ,2 ]
Sui, Quan [4 ]
机构
[1] Zhengzhou Univ, Yellow River Lab, Zhengzhou 450001, Peoples R China
[2] Zhengzhou Univ, Coll Water Conservancy & Transportat, Zhengzhou 450001, Peoples R China
[3] Power China Huadong Engn Corp Ltd, Hangzhou 311122, Peoples R China
[4] Zhengzhou Univ, Sch Elect & Informat Engn, Zhengzhou 450001, Peoples R China
基金
中国国家自然科学基金;
关键词
Cascade hydro-PV complementary system; Uncertainties of inflow runoff and PV power output; Interval optimization; Mixed integer linear programming; Extreme scenarios; GAP DECISION-THEORY; GENETIC ALGORITHM; OPTIMIZATION; PLANTS; ENERGY; WIND; OPERATION; LOAD; STRATEGY; DESIGN;
D O I
10.1016/j.apenergy.2023.122085
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
An effective way to promote the consumption of renewable energy resource generation is by forming a joint power supply system between photovoltaic (PV) power plants widely distributed along a river basin and largescale cascade hydropower plants, using shared transmission lines to transmit power to the power grid system. However, renewable energy resource generation has significant prediction uncertainty and can flood into the power grid, which is detrimental to its safe and stable operation. To solve the above issues, this paper proposes an improved interval optimization method to model the uncertainties of the inflow runoff of a cascade hydropower plant and the photovoltaic power output. On this basis, a medium- and long-term interval optimization scheduling model is established for a cascade hydro-PV complementary system based on extreme scenarios. This model does not need to obtain an accurate probability density distribution for renewable energy, and can realize the overall optimization of runoff-PV uncertainty scenarios within a certain range, taking into account the economy and robustness of system operation. In order to ensure the solution efficiency, the original model is transformed into a mixed integer linear programming (MILP) model by a variety of deterministic transformation methods and linearization techniques. The case study shows that: 1) Under the premise that the system power output is relatively stable, the power curtailment of the interval optimized scheduling scheme proposed in this paper is reduced by 47.5% compared with the robust scheduling scheme. The ability to cope with extreme scenarios is also significantly improved compared with the deterministic scheduling scheme. 2) There is a game relationship between the robustness and economy of the obtained scheduling scheme. When the fluctuation interval width of random variables increases from 20% to 30% and 40%, the corresponding total power generation decreases by 2.4% and 4.7%, respectively. 3) A large penalty factor is conducive to reducing the amount of abandoned hydropower, but in general, the penalty factor and ecological flow level have no obvious influence on the dispatching results, and the values of both can be reasonably determined according to the actual operation requirements.
引用
收藏
页数:17
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