Short-term photovoltaics power forecasting using Jordan recurrent neural network in Surabaya
Aji Akbar Firdaus,Riky Tri Yunardi,Eva Inaiyah Agustin,Tesa Eranti Putri,Dimas Okky Anggriawan +4 more
Reads0
Chats0
TLDR
In this article, the Jordan recurrent neural network (JRNN) was used to predict short-term PV power based on temperature and solar radiation in the tropical island of Java, Indonesia.Abstract:
Photovoltaic (PV) is a renewable electric energy generator that utilizes solar energy. PV is very suitable to be developed in Surabaya, Indonesia. Because Indonesia is located around the equator which has 2 seasons, namely the rainy season and the dry season. The dry season in Indonesia occurs in April to September. The power generated by PV is highly dependent on temperature and solar radiation. Therefore, accurate forecasting of short-term PV power is important for system reliability and large-scale PV development to overcome the power generated by intermittent PV. This paper proposes the Jordan recurrent neural network (JRNN) to predict short-term PV power based on temperature and solar radiation. JRNN is the development of artificial neural networks (ANN) that have feedback at each output of each layer. The samples of temperature and solar radiation were obtained from April until September in Surabaya. From the results of the training simulation, the mean square error (MSE) and mean absolute percentage error (MAPE) values were obtained at 1.3311 and 34.8820, respectively. The results of testing simulation, MSE and MAPE values were obtained at 0.9858 and 1.3311, with a time of 4.591204. The forecasting has minimized significant errors and short processing times.read more
Citations
More filters
Journal ArticleDOI
Determination of the parameters of the firefly method for PID parameters in solar panel applications
Machrus Ali,Hadi Suyono,M. Aziz Muslim,Muhammad Ruswandi Djalal,Yanuar Mahfudz Safarudin,Aji Akbar Firdaus +5 more
TL;DR: This Dual Axis photovoltaic tracking study uses the beta value determination, changing the Bêta value from 0.1 to 0.9, to optimize the PID constant values from the results of 10 models.
Book ChapterDOI
Estimation of Solar Radiation at Farasan Island with Two-Step ANN Concepts
TL;DR: In this paper, a two-step artificial neural network (ANN) is proposed to estimate both the daily average and hourly solar radiation at Farasan Island, KSA (Kingdom of Saudi Arabia).
Proceedings ArticleDOI
Optimization of Water Level Control Systems Using ANFIS and Fuzzy-PID Model
TL;DR: Comparisons of designed methods related to water level without control, standard PID method, Fuzzy Logic method, fuzzy-PID method, and Adaptive Neuro-Fuzzy Inference System (ANFIS) method found that the four control models have different performance.
Journal ArticleDOI
Optimization of controller frequency in wind-turbine based on hybrid PSO-ANFIS
TL;DR: PID-PSO-ANFIS model is the best model in this study and can be proposed to be applied to higher systems.
Journal ArticleDOI
Application of PV systems in the process of drying fish for traditional fisherman
TL;DR: In this article , a fish drying machine was made using a PV system, which can meet 169.95% of the need for 240 Wh/day of electrical energy from fish dryers.