PV arrays reconfiguration for partial shading mitigation: Recent advances, challenges and perspectives

B Yang, H Ye, J Wang, J Li, S Wu, Y Li, H Shu… - Energy Conversion and …, 2021 - Elsevier
An intractable but common problem in photovoltaic systems is that the power generated by
photovoltaic will reduce seriously due to partial shading. In order to solve this problem, the …

Wave energy converter array layout optimization: A critical and comprehensive overview

B Yang, S Wu, H Zhang, B Liu, H Shu, J Shan… - … and Sustainable Energy …, 2022 - Elsevier
The production efficiency and optimal control of wave energy converter (WEC) array are
mainly based on array layout, thus it is crucial to establish a reliable mathematical model for …

Optimal PV array reconfiguration under partial shading condition through dynamic leader based collective intelligence

Y Wang, B Yang - Protection and Control of Modern Power …, 2023 - ieeexplore.ieee.org
This paper applies the innovative idea of DLCI to PV array reconfiguration under various
PSCs to capture the maximum output power of a PV generation system. DLCI is a hybrid …

Flexibility clearing in joint energy and flexibility markets considering TSO-DSO coordination

T Jiang, C Wu, R Zhang, X Li… - IEEE transactions on …, 2022 - ieeexplore.ieee.org
Active distribution networks (ADNs) with distributed generators (DGs) can provide flexibility
for the upstream grid by participating in energy and flexibility markets. In this paper, a novel …

Adaptive evolutionary jellyfish search algorithm based optimal photovoltaic array reconfiguration under partial shading condition for maximum power extraction

B Yang, M Zhang, Z Guo, P Cao, J Yang, G He… - Expert Systems with …, 2023 - Elsevier
This paper proposes an adaptive evolutionary jellyfish search algorithm (AEJSA) to
optimally reconfigure photovoltaic (PV) array under partial shading condition (PSC) for real …

Application and progress of artificial intelligence technology in the field of distribution network voltage Control: A review

X Zhang, Z Wu, Q Sun, W Gu, S Zheng… - … and Sustainable Energy …, 2024 - Elsevier
The increasing integration of distributed energy resources has led to heightened complexity
in distribution network models, posing challenges of uncertainty and volatility to the …

Combination of manifold learning and deep learning algorithms for mid-term electrical load forecasting

J Li, S Wei, W Dai - IEEE Transactions on Neural Networks and …, 2021 - ieeexplore.ieee.org
Mid-term load forecasting (MTLF) is of great significance for power system planning,
operation, and power trading. However, the mid-term electrical load is affected by the …

Joint energy disaggregation of behind-the-meter PV and battery storage: A contextually supervised source separation approach

F Wang, X Ge, Z Dong, J Yan, K Li, F Xu… - IEEE transactions on …, 2022 - ieeexplore.ieee.org
An increasing number of residential customers have installed hybrid rooftop solar battery
systems (HRSBSs). Currently, most HRSBSs are installed behind-the-meter (BTM), where …

Deep learning-based linear defects detection system for large-scale photovoltaic plants based on an edge-cloud computing infrastructure

W Tang, Q Yang, X Hu, W Yan - Solar Energy, 2022 - Elsevier
Linear defects detection of photovoltaic (PV) modules plays a key role in the health
assessment in PV plants. However, the conventional defects diagnosis is mainly carried out …

Voltage imbalance mitigation in an active distribution network using decentralized current control

AMM Nour, AA Helal, MM El-Saadawi… - … and Control of …, 2023 - ieeexplore.ieee.org
Voltage imbalance (VI) is caused by the difference in connected single-phase load or
generation in a low voltage distribution network (DN). VI increase in a smart distribution grid …