A novel sky image-based solar irradiance nowcasting model with convolutional block attention mechanism DOI Creative Commons
Shaojian Song, Zijun Yang, Hui Hwang Goh

et al.

Energy Reports, Journal Year: 2022, Volume and Issue: 8, P. 125 - 132

Published: Feb. 25, 2022

Global horizontal irradiance (GHI) is a crucial factor impacting photovoltaic (PV) production, and required for accurate real-time power forecasting. And it new effective solution to obtain the GHI by sky images because mainly affected cloud cover motion. Therefore, research proposes unique artificial intelligence approach forecasting ('nowcasting') based on images, which can significantly enhance accuracy cloudy days. First, nowcasting model with convolutional block attention module (CBAM) proposed, Visual Geometry Group (VGG) networks. Then, taking local (LCC) as numerical feature, we coupled feature in image improve performance of model. Finally, verify effectiveness advantages proposed method, when compared state-of-the-art methods, such Sun's model, Jiang's others, method outperforms them demonstrated 11.67% nRMSE, 7.97% nMAE, 27.69% MAPE, 0.91 CORR results ASI-16 dataset.

Language: Английский

Explainable Artificial Intelligence (XAI) techniques for energy and power systems: Review, challenges and opportunities DOI Creative Commons
Ram Machlev,

Leena Heistrene,

M. Perl

et al.

Energy and AI, Journal Year: 2022, Volume and Issue: 9, P. 100169 - 100169

Published: May 25, 2022

Despite widespread adoption and outstanding performance, machine learning models are considered as "black boxes", since it is very difficult to understand how such operate in practice. Therefore, the power systems field, which requires a high level of accountability, hard for experts trust justify decisions recommendations made by these models. Meanwhile, last couple years, Explainable Artificial Intelligence (XAI) techniques have been developed improve explainability models, that their output can be better understood. In this light, purpose paper highlight potential using XAI system applications. We first present common challenges applications then review analyze recent works on topic, on-going trends research community. hope will trigger fruitful discussions encourage further important emerging topic.

Language: Английский

Citations

218
Interpretable machine learning for building energy management: A state-of-the-art review DOI Creative Commons
Zhe Chen, Fu Xiao, Fangzhou Guo

et al.

Advances in Applied Energy, Journal Year: 2023, Volume and Issue: 9, P. 100123 - 100123

Published: Jan. 13, 2023

Machine learning has been widely adopted for improving building energy efficiency and flexibility in the past decade owing to ever-increasing availability of massive operational data. However, it is challenging end-users understand trust machine models because their black-box nature. To this end, interpretability attracted increasing attention recent studies helps users decisions made by these models. This article reviews previous that interpretable techniques management analyze how model improved. First, are categorized according application stages techniques: ante-hoc post-hoc approaches. Then, analyzed detail specific with critical comparisons. Through review, we find broad faces following significant challenges: (1) different terminologies used describe which could cause confusion, (2) performance ML tasks difficult compare, (3) current prevalent such as SHAP LIME can only provide limited interpretability. Finally, discuss future R&D needs be accelerate management.

Language: Английский

Citations

164
How solar radiation forecasting impacts the utilization of solar energy: A critical review DOI

Naveen M. Krishnan,

K. Ravi Kumar,

Chandrapal Singh Inda

et al.

Journal of Cleaner Production, Journal Year: 2023, Volume and Issue: 388, P. 135860 - 135860

Published: Jan. 12, 2023

Language: Английский

Citations

78
Potential of Explainable Artificial Intelligence in Advancing Renewable Energy: Challenges and Prospects DOI
Van Nhanh Nguyen, W. Tarełko, Prabhakar Sharma

et al.

Energy & Fuels, Journal Year: 2024, Volume and Issue: 38(3), P. 1692 - 1712

Published: Jan. 19, 2024

Modern machine learning (ML) techniques are making inroads in every aspect of renewable energy for optimization and model prediction. The effective utilization ML the development scaling up systems needs a high degree accountability. However, most approaches currently use termed black box since their work is difficult to comprehend. Explainable artificial intelligence (XAI) an attractive option solve issue poor interoperability black-box methods. This review investigates relationship between (RE) XAI. It emphasizes potential advantages XAI improving performance efficacy RE systems. realized that although integration with has enormous alter how produced consumed, possible hazards barriers remain be overcome, particularly concerning transparency, accountability, fairness. Thus, extensive research required address societal ethical implications using create standardized data sets evaluation metrics. In summary, this paper shows potential, perspectives, opportunities, challenges application system management operation aiming target efficient energy-use goals more sustainable trustworthy future.

Language: Английский

Citations

46
PV power forecasting based on data-driven models: a review DOI Open Access
Priya Gupta, Rhythm Singh

International Journal of Sustainable Engineering, Journal Year: 2021, Volume and Issue: 14(6), P. 1733 - 1755

Published: Oct. 6, 2021

Accurate PV power forecasting techniques are a prerequisite for the optimal management of grid and its stability. This paper presents review recent developments in field forecasting, mainly focusing on literature which uses ML techniques. The (sub-branch artificial intelligence) extensively used due to their ability solve nonlinear complex data structures. can either be direct, or indirect, involves solar irradiance forecast model, plane array estimation performance model. both these pathways based proposed methodology, horizons considered input parameters. In case unavailability historical new plant failure real-time acquisition, indirect viable alternative. Although ranking various models is complicated no model universal, studies suggest that methodologies like deep neural networks ensemble hybrid outperform conventional methods short-term forecasting. Recent articles also present intelligent optimisation data-preparation improve accuracy.

Language: Английский

Citations

95
Mitigating the effects of partial shading on PV system’s performance through PV array reconfiguration: A review DOI
Khaled Osmani, Ahmad Haddad, Hadi Jaber

et al.

Thermal Science and Engineering Progress, Journal Year: 2022, Volume and Issue: 31, P. 101280 - 101280

Published: March 19, 2022

Language: Английский

Citations

52
A theory-guided deep-learning method for predicting power generation of multi-region photovoltaic plants DOI

Jian Du,

Jianqin Zheng, Yongtu Liang

et al.

Engineering Applications of Artificial Intelligence, Journal Year: 2022, Volume and Issue: 118, P. 105647 - 105647

Published: Nov. 28, 2022

Language: Английский

Citations

39
A multi-step ahead global solar radiation prediction method using an attention-based transformer model with an interpretable mechanism DOI
Yong Zhou, Yizhuo Li, Dengjia Wang

et al.

International Journal of Hydrogen Energy, Journal Year: 2023, Volume and Issue: 48(40), P. 15317 - 15330

Published: Jan. 21, 2023

Language: Английский

Citations

26
A Review on the Evaluation of Feature Selection Using Machine Learning for Cyber-Attack Detection in Smart Grid DOI Creative Commons

Saad Hammood Mohammed,

Abdulmajeed Al-Jumaily, Mandeep Singh Jit Singh

et al.

IEEE Access, Journal Year: 2024, Volume and Issue: 12, P. 44023 - 44042

Published: Jan. 1, 2024

The Smart Grid is a modern power grid that relies on advanced technologies to provide reliable and sustainable electricity. However, its integration with various communication IoT devices makes it vulnerable cyber-attacks. Such attacks can lead significant damage, economic losses, public safety hazards. To ensure the security of smart grid, increasingly strong solutions are needed. This paper provides comprehensive analysis vulnerabilities different approaches for detecting It examines including system cyber-attacks, discusses all elements. also investigates rule-based, signature-based, anomaly detection, ma-chine learning-based methods, focus their effectiveness related research. Finally, prospective cybersecurity such as AI blockchain, discussed along challenges future prospects cyberattacks grid. paper's findings help policymakers stakeholders make informed decisions about develop effective strategies protect from

Language: Английский

Citations

9
Optimal design of solar/wind/energy storage system-powered RO desalination unit: Single and multi-objective optimization DOI

Kamyar Ghanbari,

Akbar Maleki,

Dariush Rezaei Ochbelagh

et al.

Energy Conversion and Management, Journal Year: 2024, Volume and Issue: 315, P. 118768 - 118768

Published: July 5, 2024

Language: Английский

Citations

9