Forecasting of photovoltaic power using probabilistic approach

被引:3
|
作者
Sreenivasulu, J. [1 ]
Dukkipati, Sudha [2 ]
Marthanda, A. V. G. A. [3 ]
Pandian, A. [2 ]
机构
[1] JNTUA Coll Engn, Dept EEE, Anantapur, Andhra Pradesh, India
[2] Koneru Lakshmaiah Educ Fdn, Dept EEE, Guntur, Andhra Pradesh, India
[3] Lakireddy Balireddy Coll Engn, Dept EEE, Mylavaram, India
关键词
Monte Carlo Simulation (MCS); Probability Distribution; Root Mean Square Error (RMSE);
D O I
10.1016/j.matpr.2020.12.910
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
With the developing establishment in the power network of photovoltaic sources and the increasing demand, the requirement of Photovoltaic plants is essential. But the major drawback in PV system is forecasting of power generation because of intermittent behavior of solar energy. Power produced by PV majorly depends on environmental conditions like temperature, irradiance, and humidity which are highly uncertain in nature. Using probabilistic distribution functions, the probability of solar irradiance and temperature is predicted in three seasons i.e., summer, rainy and winter season. The predicted values of temperature and irradiance are used to forecast PV output power for three seasons i.e., summer, winter and rainy seasons. The forecasted PV output power is useful to meet the load demand with reliability and can be used for extending the capacity of PV plant to meet future load demand. (c) 2020 Elsevier Ltd. All rights reserved. Selection and peer-review under responsibility of the scientific committee of the International Conference on Mechanical, Electronics and Computer Engineering 2020: Materials Science.
引用
收藏
页码:6800 / 6803
页数:4
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