Forecasting and Analysis of Solar Power Output from Integrated Solar Energy and IoT System

Adli, Hasyiya Karimah; Husin, Ku Azmie Ku; Hanafiah, Nurul Hasya Mohd; Remli, Muhammad Akmal; Ernawan, Ferda; Wirawan, Panji Wisnu

doi:10.1109/icicos53627.2021.9651831

Cited by 9 publications

(2 citation statements)

References 12 publications

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“…Sometimes, it is worth testing various ARIMA models with different time horizons [55] or exploring potential improvements in accuracy when the input data are normalized [29]. In the case of the ARIMA approach, the model selection is often made on the basis of error assessment [69] or AIC [52,68].…”

Section: Background Literaturementioning

confidence: 99%

ARIMA Models in Solar Radiation Forecasting in Different Geographic Locations

Chodakowska

Nazarko

et al. 2023

Energies

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The increasing demand for clean energy and the global shift towards renewable sources necessitate reliable solar radiation forecasting for the effective integration of solar energy into the energy system. Reliable solar radiation forecasting has become crucial for the design, planning, and operational management of energy systems, especially in the context of ambitious greenhouse gas emission goals. This paper presents a study on the application of auto-regressive integrated moving average (ARIMA) models for the seasonal forecasting of solar radiation in different climatic conditions. The performance and prediction capacity of ARIMA models are evaluated using data from Jordan and Poland. The essence of ARIMA modeling and analysis of the use of ARIMA models both as a reference model for evaluating other approaches and as a basic forecasting model for forecasting renewable energy generation are presented. The current state of renewable energy source utilization in selected countries and the adopted transition strategies to a more sustainable energy system are investigated. ARIMA models of two time series (for monthly and hourly data) are built for two locations and a forecast is developed. The research findings demonstrate that ARIMA models are suitable for solar radiation forecasting and can contribute to the stable long-term integration of solar energy into countries’ systems. However, it is crucial to develop location-specific models due to the variability of solar radiation characteristics. This study provides insights into the use of ARIMA models for solar radiation forecasting and highlights their potential for supporting the planning and operation of energy systems.

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Section: Background Literaturementioning

confidence: 99%

ARIMA Models in Solar Radiation Forecasting in Different Geographic Locations

Chodakowska

Nazarko

et al. 2023

Energies

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“…All these objects are connected via internet protocol (IP) [ 11 , 12 ]. In industrial IoT applications, AI functions as the technology enabler for hundreds of devices and a wide range of applications, including environmental monitoring, agriculture [ 13 , 14 ], smart grids [ 15 ], cities [ 16 ], buildings [ 17 ], homes [ 18 ], transportation [ 19 ], and healthcare [ 20 ].…”

Section: Introductionmentioning

confidence: 99%

Recent Advancements and Challenges of AIoT Application in Smart Agriculture: A Review

Adli

Remli

Wong

et al. 2023

Sensors

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As the most popular technologies of the 21st century, artificial intelligence (AI) and the internet of things (IoT) are the most effective paradigms that have played a vital role in transforming the agricultural industry during the pandemic. The convergence of AI and IoT has sparked a recent wave of interest in artificial intelligence of things (AIoT). An IoT system provides data flow to AI techniques for data integration and interpretation as well as for the performance of automatic image analysis and data prediction. The adoption of AIoT technology significantly transforms the traditional agriculture scenario by addressing numerous challenges, including pest management and post-harvest management issues. Although AIoT is an essential driving force for smart agriculture, there are still some barriers that must be overcome. In this paper, a systematic literature review of AIoT is presented to highlight the current progress, its applications, and its advantages. The AIoT concept, from smart devices in IoT systems to the adoption of AI techniques, is discussed. The increasing trend in article publication regarding to AIoT topics is presented based on a database search process. Lastly, the challenges to the adoption of AIoT technology in modern agriculture are also discussed.

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