A novel GA-ANFIS hybrid model for short-term solar PV power forecasting in Indian electricity market. Issue 2 (17th February 2019)

• Record Type: Journal Article
• Authors: Yadav, Harendra Kumar; Pal, Yash; Tripathi, Madan Mohan
• Is Part Of: Journal of information & optimization sciences. Volume 40:Issue 2(2019)
• Page Start: 377
• Page End: 395
• Publication Date: 2019-02-17
• Subjects: Restructured market -- Genetic algorithm -- Fuzzy logic -- Network based fuzzy inference system -- ANFIS and PV power forecasting; Electronic data processing -- Periodicals; Information science -- Periodicals; Mathematical optimization -- Periodicals; 519.6
• DOI: 10.1080/02522667.2019.1580880
• Languages: English
• ISSNs: 0252-2667

Abstract

Abstract: 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.