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Showing 20 of 41 academic articles

Advances of Commercial and Biological Materials for Electron Transport Layers in Biological Applications

Zhifu Yin, Zhifu Yin, Biao Lu, Yanbo Chen et al. • Frontiers in Bioengineering and Biotechnology (2022)

Electron transport layer (ETL), one of the important layers for high-performing perovskite solar cells (PSCs), also has great potential in bioengineering applications. It could be used for biological sensors, biological imaging, and biomedi...

DOAJ Open Access (DOAJ) DOI: 10.3389/fbioe.2022.900269

A <italic>&#x03BC;</italic>-Synthesis Framework for Multi-Domain Robust Load Frequency Control Under Concurrent Communication Delays and Parametric Uncertainties

Chadi Nohra, Bechara Nehme, Raymond Ghandour, Ossama Dankar et al. • IEEE Access (2026)

The integration of communication networks into modern power systems introduces variable time delays that degrade the performance of traditional Load Frequency Control (LFC), while the shift towards renewable energy sources increases system ...

DOAJ Open Access (DOAJ) DOI: 10.1109/ACCESS.2026.3675126

Optimal dispatching method for integrated energy system based on robust economic model predictive control considering source–load power interval prediction

Yang Yu, Jiali Li, Dongyang Chen • Global Energy Interconnection (2022)

Effective source–load prediction and reasonable dispatching are crucial to realize the economic and reliable operations of integrated energy systems (IESs). They can overcome the challenges introduced by the uncertainties of new energies an...

DOAJ Open Access (DOAJ) DOI: 10.1016/j.gloei.2022.10.010

Spatial Optimization of Wind and Solar Farm Location in Electric Power Systems Considering Power System Flexibility Characteristics

Oleg Sigitov, Iliya Iliev, Hristo Beloev, Ivan Beloev et al. • Energies (2026)

The rapid development of wind and solar energy necessitates a solution to the problem of the optimal spatial placement of wind farms (WFs) and solar farms (SFs) within electric power systems. The non-stationary generation schedules of WFs a...

DOAJ Open Access (DOAJ) DOI: 10.3390/en19122901

Reactive Power Optimization Control for Renewable Energy in Distribution Networks Considering Active Power Uncertainties

Jingzhong ZHANG, Fei MENG, Yang SUN, Huixia YU • Zhongguo dianli (2024)

A dual-layer robust optimization control method based on the droop principle of reactive power and voltage is proposed for renewable energy in distribution networks, considering active power uncertainties. First, in the reference-point opti...

DOAJ Open Access (DOAJ) DOI: 10.11930/j.issn.1004-9649.202310053

The Renewable Energy Sources

• IMPERIAL COLLEGE PRESS eBooks (2010)

Introduction to the report. Introduction and summary. The place of renewable energy as an energy source. Types of renewable energy source. Tidal energy. Wave energy. Wind energy. Small scale hydro- electric energy. Geothermal energy. Ocean ...

OPENALEX DOI: https://doi.org/10.1142/9781848164178_0003

Improving PV Resilience by Dynamic Reconfiguration in Distribution Grids: Problem Complexity and Computation Requirements

Filipe F. C. Silva, Pedro M. S. Carvalho, Luís A. F. M. Ferreira • Energies (2021)

The dissemination of low-carbon technologies, such as urban photovoltaic distributed generation, imposes new challenges to the operation of distribution grids. Distributed generation may introduce significant net-load asymmetries between fe...

DOAJ Open Access (DOAJ) DOI: 10.3390/en14040830

Deep hybrid neural net (DHN-Net) for minute-level day-ahead solar and wind power forecast in a decarbonized power system

Olusola Bamisile, Dongsheng Cai, Humphrey Adun, Chukwuebuka Ejiyi et al. • Energy Reports (2023)

The need to reduce global carbon emissions has led to a significant increase in clean energy globally. While renewable energy penetration into energy grids and power systems is increasing in many countries, the intermittency and stochastic ...

DOAJ Open Access (DOAJ) DOI: 10.1016/j.egyr.2023.05.229

A Review of Cybersecurity in Grid-Connected Power Electronics Converters: Vulnerabilities, Countermeasures, and Testbeds

Ruiyun Fu, Mary E. Lichtenwalner, Thomas J. Johnson • IEEE Access (2023)

With the increasing installations of solar energy, electric vehicles, and other distributed energy resources and the deeper developments of digitalization and standardization, cybersecurity became more and more essential and critical in mod...

DOAJ Open Access (DOAJ) DOI: 10.1109/ACCESS.2023.3324177

Cybersecurity in Distributed Power Systems

Zhiyi Li, Mohammad Shahidehpour, Farrokh Aminifar • Proceedings of the IEEE (2017)

This paper presents the application of cybersecurity to the operation and control of distributed electric power systems. In particular, the paper emphasizes the role of cybersecurity in the operation of microgrids and analyzes the dependenc...

OPENALEX DOI: https://doi.org/10.1109/jproc.2017.2687865

Development of Anticancer Peptides Using Artificial Intelligence and Combinational Therapy for Cancer Therapeutics

Ji Su Hwang, Seok Gi Kim, Tae Hwan Shin, Yong Eun Jang et al. • Pharmaceutics (2022)

Cancer is a group of diseases causing abnormal cell growth, altering the genome, and invading or spreading to other parts of the body. Among therapeutic peptide drugs, anticancer peptides (ACPs) have been considered to target and kill cance...

DOAJ Open Access (DOAJ) DOI: 10.3390/pharmaceutics14050997

A learning‐based energy management strategy for hybrid energy storage systems with compressed air and solid oxide fuel cells

Yundie Guan, Xiangyu Zhang, Zheming Liang, Tao Chen • IET Renewable Power Generation (2025)

Abstract The intermittency and volatility of renewable energy have been major challenges in modern power systems. This paper proposes a self‐adaptive energy management strategy based on deep reinforcement learning (DRL) to integrate renewab...

DOAJ Open Access (DOAJ) DOI: 10.1049/rpg2.13192

Deep learning for power quality

Roger Alves de Oliveira, Math Bollen • Electric Power Systems Research (2022)

This paper aims to introduce deep learning to the power quality community by reviewing the latest applications and discussing the open challenges of this technology. Publications covering deep learning to power quality are stratified in ter...

OPENALEX cc-by DOI: https://doi.org/10.1016/j.epsr.2022.108887

Hybrid Model Based on an SD Selection, CEEMDAN, and Deep Learning for Short-Term Load Forecasting of an Electric Vehicle Fleet

Ahmad Mohsenimanesh, Evgueniy Entchev, Filip Bosnjak • Applied Sciences (2022)

Forecasting the aggregate charging load of a fleet of electric vehicles (EVs) plays an important role in the energy management of the future power system. Therefore, accurate charging load forecasting is necessary for reliable and efficient...

DOAJ Open Access (DOAJ) DOI: 10.3390/app12189288

An Efficient and High-Speed Disturbance Detection Algorithm Design with Emphasis on Operation of Static Transfer Switch

USMAN, A., CHOUDHRY, M. A. • Advances in Electrical and Computer Engineering (2021)

Static Transfer Switch (STS) is required for high-speed transfer of essential load to the alternate power source when the main source fails due to power disturbance (PD). A fast and accurate PD detection method is required to ensure trans...

DOAJ Open Access (DOAJ) DOI: 10.4316/AECE.2021.02010

On the practical aspects of machine learning based active power loss forecasting in transmission networks

Franko Pandžić, Ivan Sudić, Tomislav Capuder, Ivan Pavičić • IET Generation, Transmission & Distribution (2024)

Abstract The cost for covering active power losses makes a significant item in transmission system operators (TSO) annual budgets, and still it received limited attention in the existing literature. The focus of accurate power loss forecast...

DOAJ Open Access (DOAJ) DOI: 10.1049/gtd2.13205

Demand response potential evaluation based on feature fusion with expert knowledge and multi‐image

Jiale Liu, Xinlei Cai, Zijie Meng, Xin Jin et al. • IET Smart Grid (2024)

Abstract Potential evaluation to assist demand response decisions has garnered significant attention with the development of new power systems. However, existing data‐driven methods are challenging to properly exploit multivariate features ...

DOAJ Open Access (DOAJ) DOI: 10.1049/stg2.12182