Sharma, JatinSoni, SameerPaliwal, PriyankaSaboor, ShaikChaurasiya, Prem K.Sharifpur, MohsenKhalilpoor, NimaAfzal, Asif2023-03-282023-03-282022-08Sharma J, Soni S, Paliwal P, et al. A novel long term solar photovoltaic power forecasting approach using LSTM with Nadam optimizer: a case study of India. Energy Science and Engineering 2022;10:2909‐2929. doi:10.1002/ese3.1178.2050-0505 (online)10.1002/ese3.1178http://hdl.handle.net/2263/90243Solar photovoltaic (PV) power is emerging as one of the most viable renewable energy sources. The recent enhancements in the integration of renewable energy sources into the power grid create a dire need for reliable solar power forecasting techniques. In this paper, a new long-term solar PV power forecasting approach using long short-term memory (LSTM) model with Nadam optimizer is presented. The LSTM model performs better with the time-series data as it persists information of more time steps. The experimental models are realized on a 250.25 kW installed capacity solar PV power system located at MANIT Bhopal, Madhya Pradesh, India. The proposed model is compared with two time-series models and eight neural network models using LSTM with different optimizers. The obtained results using LSTM with Nadam optimizer present a significant improvement in the forecasting accuracy of 30.56% over autoregressive integrated moving average, 47.48% over seasonal autoregressive integrated moving average, and 1.35%, 1.43%, 3.51%, 4.88%, 11.84%, 50.69%, and 58.29% over models using RMSprop, Adam, Adamax, SGD, Adagrad, Adadelta, and Ftrl optimizer, respectively. The experimental results prove that the proposed methodology is more conclusive for solar PV power forecasting and can be employed for enhanced system planning and management.en© 2022 The Authors. Energy Science & Engineering published by the Society of Chemical Industry and John Wiley. This is an open access article under the terms of the Creative Commons Attribution License.Long short‐term memoryNadamPhotovoltaic power forecastingPhotovoltaic power plantTime series forecastingEngineering, built environment and information technology articles SDG-04SDG-04: Quality educationEngineering, built environment and information technology articles SDG-07SDG-07: Affordable and clean energyEngineering, built environment and information technology articles SDG-09SDG-09: Industry, innovation and infrastructureEngineering, built environment and information technology articles SDG-11SDG-11: Sustainable cities and communitiesEngineering, built environment and information technology articles SDG-13SDG-13: Climate actionEngineering, built environment and information technology articles SDG-17SDG-17: Partnerships for the goalsArticle