Deep learning based data-driven model for detecting time-delay water quality indicators of wastewater treatment plant influent

Y Zhang, C Li, H Duan, K Yan, J Wang… - Chemical Engineering …, 2023 - Elsevier
Rapid and accurate detection of time-delayed water quality indicators (WQIs) is the key to
achieving fast feedback regulation of wastewater treatment plants (WWTPs) that enables its …

Multi-scale carbon emission characterization and prediction based on land use and interpretable machine learning model: A case study of the Yangtze River Delta …

H Luo, C Wang, C Li, X Meng, X Yang, Q Tan - Applied Energy, 2024 - Elsevier
Carbon emissions are a significant factor contributing to global climate change, and their
characterization and prediction are of great significance for regional sustainable …

[HTML][HTML] Voltage optimization in PV-rich distribution networks—a review

M Dubravac, K Fekete, D Topić, M Barukčić - Applied Sciences, 2022 - mdpi.com
There is a rising trend to integrate different types of distributed generation (DG), especially
photovoltaic (PV) systems, on the roofs of existing consumers, who then become prosumers …

[PDF][PDF] 可解释人工智能在电力系统中的应用综述与展望

王小君, 窦嘉铭, 刘曌, 刘畅宇, 蒲天骄… - 电力系统 …, 2024 - epjournal.csee.org.cn
可解释人工智能(XAI) 作为新型人工智能(AI) 技术, 具有呈现AI 过程逻辑, 揭示AI 黑箱知识,
提高AI 结果可信程度的能力. XAI 与电力系统的深度耦合将加速AI 技术在电力系统的落地应用 …

Artificial emotional deep Q learning for real-time smart voltage control of cyber-physical social power systems

L Yin, X He - Energy, 2023 - Elsevier
The volatility of renewable energy leads to numerous voltage changes in a short period, thus
affecting the quality of the power supply. A real-time smart voltage control framework of …

[HTML][HTML] A multi-hierarchical interpretable method for DRL-based dispatching control in power systems

K Zhang, J Zhang, P Xu, T Gao, W Gao - International Journal of Electrical …, 2023 - Elsevier
Timely, effective, and robust artificial intelligence (AI) technology is urgently needed to
improve decision-making efficiency in the presence of renewable energy with high …

A multi-objective techno-economic operation of distribution network considering reactive power support from renewable energy and battery storage system

G Gangil, SK Goyal, A Saraswat - Journal of Energy Storage, 2024 - Elsevier
In the modern power system, the integration of distributed energy resources are increases
day-by-day and the energy sector becomes more flexible and efficient in terms of optimal …

Advancements and Future Directions in the Application of Machine Learning to AC Optimal Power Flow: A Critical Review

B Jiang, Q Wang, S Wu, Y Wang, G Lu - Energies, 2024 - mdpi.com
Optimal power flow (OPF) is a crucial tool in the operation and planning of modern power
systems. However, as power system optimization shifts towards larger-scale frameworks …

Explainable artificial intelligence of tree-based algorithms for fault detection and diagnosis in grid-connected photovoltaic systems

HN Noura, Z Allal, O Salman, K Chahine - Engineering Applications of …, 2025 - Elsevier
A grid-connected photovoltaic system integrates solar panels with the utility grid through a
power inverter unit, allowing them to operate in parallel with the grid. Commonly known as …

[HTML][HTML] Unlocking predictive insights and interpretability in deep reinforcement learning for Building-Integrated Photovoltaic and Battery (BIPVB) systems

Y Gao, Z Hu, S Yamate, J Otomo, WA Chen, M Liu… - Applied Energy, 2025 - Elsevier
The deployment of renewable energy and the implementation of intelligent energy
management strategies are crucial for decarbonizing Building Energy Systems (BES) …