A novel GA-ANFIS hybrid model for short-term solar PV power forecasting in Indian electricity market

被引：25
|
作者：
Yadav, Harendra Kumar [1 ]
Pal, Yash [2 ]
Tripathi, Madan Mohan [3 ]
机构：
[1] Natl Inst Technol, Sch Renewable Energy & Efficiency, Kurukshetra 136119, Haryana, India
[2] Natl Inst Technol, Dept Elect Engn, Kurukshetra 136119, Haryana, India
[3] Delhi Technol Univ, Dept Elect Engn, New Delhi 110042, India
来源：
JOURNAL OF INFORMATION & OPTIMIZATION SCIENCES | 2019年 / 40卷 / 02期
关键词：
Restructured market; Genetic algorithm; Fuzzy logic; Network based fuzzy inference system; ANFIS and PV power forecasting; NEURAL-NETWORK; FUZZY;
D O I：
10.1080/02522667.2019.1580880
中图分类号：
G25 [图书馆学、图书馆事业]; G35 [情报学、情报工作];
学科分类号：
1205 ; 120501 ;
摘要：
Solar photovoltaic (PV) power is a most important green energy source of electricity. Accurate solar PV power forecasting is a vital requirement for integration of PV power with electricity grid, stability of grid and its management. This paper proposed, a novel hybrid model, combining genetic algorithm (GA) and adaptive network based fuzzy inference system (ANFIS) for short term solar PV power forecasting in Indian electricity market. The developed hybrid model is applied for study of PV power forecasting in Indian electricity market. Performance of developed model is compared with four different models and proposed model has given more accurate forecasting.
引用
收藏
页码：377 / 395
页数：19
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