All Outputs (17)

Robust MPPT Control of Stand-Alone Photovoltaic Systems via Adaptive Self-Adjusting Fractional Order PID Controller (2023)
Journal Article
Saleem, O., Ali, S., & Iqbal, J. (2023). Robust MPPT Control of Stand-Alone Photovoltaic Systems via Adaptive Self-Adjusting Fractional Order PID Controller. Energies, 16(13), Article 5039. https://doi.org/10.3390/en16135039

The Photovoltaic (PV) system is an eco-friendly renewable energy system that is integrated with a DC-DC buck-boost converter to generate electrical energy as per the variations in solar irradiance and outdoor temperature. This article proposes a nove... Read More about Robust MPPT Control of Stand-Alone Photovoltaic Systems via Adaptive Self-Adjusting Fractional Order PID Controller.

Certainty equivalence-based robust sliding mode control strategy and its application to uncertain PMSG-WECS (2023)
Journal Article
Chand, A., Khan, Q., Alam, W., Khan, L., & Iqbal, J. (2023). Certainty equivalence-based robust sliding mode control strategy and its application to uncertain PMSG-WECS. PLoS ONE, 18(2), Article e0281116. https://doi.org/10.1371/journal.pone.0281116

This work focuses on maximum power extraction via certainty equivalence-based robust sliding mode control protocols for an uncertain Permanent Magnet Synchronous Generator-based Wind Energy Conversion System (PMSG-WECS). The considered system is subj... Read More about Certainty equivalence-based robust sliding mode control strategy and its application to uncertain PMSG-WECS.

Model predictive control of consensus-based energy management system for DC microgrid (2023)
Journal Article
Ali, S. U., Waqar, A., Aamir, M., Qaisar, S. M., & Iqbal, J. (2023). Model predictive control of consensus-based energy management system for DC microgrid. PLoS ONE, 18(1), Article e0278110. https://doi.org/10.1371/journal.pone.0278110

The increasing deployment and exploitation of distributed renewable energy source (DRES) units and battery energy storage systems (BESS) in DC microgrids lead to a promising research field currently. Individual DRES and BESS controllers can operate a... Read More about Model predictive control of consensus-based energy management system for DC microgrid.

Neural network and URED observer based fast terminal integral sliding mode control for energy efficient polymer electrolyte membrane fuel cell used in vehicular technologies (2023)
Journal Article
Javaid, U., Mehmood, A., Iqbal, J., & Uppal, A. A. (2023). Neural network and URED observer based fast terminal integral sliding mode control for energy efficient polymer electrolyte membrane fuel cell used in vehicular technologies. Energy, 269, Article 126717. https://doi.org/10.1016/j.energy.2023.126717

In this research work, a Neural Network (NN) and Uniform Robust Exact Differentiator (URED) observer-based Fast Terminal Integral Sliding Mode Control (FTISMC) has been proposed for Oxygen Excess Ratio (OER) regulation of a Polymer Electrolyte Membra... Read More about Neural network and URED observer based fast terminal integral sliding mode control for energy efficient polymer electrolyte membrane fuel cell used in vehicular technologies.

Electric Vehicle Charging Modes, Technologies and Applications of Smart Charging (2022)
Journal Article
Ahmad, A., Khalid, M., Ullah, Z., Ahmad, N., Aljaidi, M., Malik, F. A., & Manzoor, U. (2022). Electric Vehicle Charging Modes, Technologies and Applications of Smart Charging. Energies, 15(24), Article 9471. https://doi.org/10.3390/en15249471

The rise of the intelligent, local charging facilitation and environmentally friendly aspects of electric vehicles (EVs) has grabbed the attention of many end-users. However, there are still numerous challenges faced by researchers trying to put EVs... Read More about Electric Vehicle Charging Modes, Technologies and Applications of Smart Charging.

The role of ‘living laboratories’ in accelerating the energy system decarbonization (2022)
Journal Article
Fan, Z., Cao, J., Jamal, T., Fogwill, C., Samende, C., Robinson, Z., Polack, F., Ormerod, M., George, S., Peacock, A., & Healey, D. (2022). The role of ‘living laboratories’ in accelerating the energy system decarbonization. Energy Reports, 8, 11858-11864. https://doi.org/10.1016/j.egyr.2022.09.046

To decarbonize the energy system by the year 2050, it is crucial that innovations are trialled in a ‘real world’ setting for the purpose of increasing public adoption and support, and for providing insights to decision-makers to ensure their decision... Read More about The role of ‘living laboratories’ in accelerating the energy system decarbonization.

Automated Question-Answering for Interactive Decision Support in Operations & Maintenance of Wind Turbines (2022)
Journal Article
Chatterjee, J., & Dethlefs, N. (2022). Automated Question-Answering for Interactive Decision Support in Operations & Maintenance of Wind Turbines. IEEE Access, 10, 84710-84737. https://doi.org/10.1109/ACCESS.2022.3197167

Intelligent question-answering (QA) systems have witnessed increased interest in recent years, particularly in their ability to facilitate information access, data interpretation or decision support. The wind energy sector is one of the most promisin... Read More about Automated Question-Answering for Interactive Decision Support in Operations & Maintenance of Wind Turbines.

Synchronous Multi-User Cross-Platform Virtual Reality for School Teachers (2022)
Presentation / Conference Contribution
Kambili-Mzembe, F., & Gordon, N. A. (2022, May). Synchronous Multi-User Cross-Platform Virtual Reality for School Teachers. Presented at 8th International Conference of the Immersive Learning Research Network (iLRN), Vienna, Austria

Motivated by a desire to apply Computer Science and Virtual Reality (VR) technology due to the need for improving secondary school education in Malawi, this paper presents a prototype of a synchronous multi-user cross-platform real-time 3D VR applica... Read More about Synchronous Multi-User Cross-Platform Virtual Reality for School Teachers.

Facilitating a smoother transition to renewable energy with AI (2022)
Journal Article
Chatterjee, J., & Dethlefs, N. (2022). Facilitating a smoother transition to renewable energy with AI. Patterns, 3(6), Article 100528. https://doi.org/10.1016/j.patter.2022.100528

Artificial intelligence (AI) can help facilitate wider adoption of renewable energy globally. We organized a social event for the AI and renewables community to discuss these aspects at the International Conference on Learning Representations (ICLR),... Read More about Facilitating a smoother transition to renewable energy with AI.

Experimental investigation of a novel vertical loop-heat-pipe PV/T heat and power system under different height differences (2022)
Journal Article
Yu, M., Chen, F., Zhou, J., Yuan, Y., Fan, Y., Li, G., Zhao, X., Wang, Z., Li, J., & Zheng, S. (2022). Experimental investigation of a novel vertical loop-heat-pipe PV/T heat and power system under different height differences. Energy, 254, Part A, Article 124193. https://doi.org/10.1016/j.energy.2022.124193

For a novel vertical solar loop-heat-pipe photovoltaic/thermal system, the height difference between evaporator and condenser plays an important role in the heat transport capacity, which has significant impact on the solar thermal efficiency and par... Read More about Experimental investigation of a novel vertical loop-heat-pipe PV/T heat and power system under different height differences.

Maximum Power Extraction from a Standalone Photo Voltaic System via Neuro-Adaptive Arbitrary Order Sliding Mode Control Strategy with High Gain Differentiation (2022)
Journal Article
Anjum, M. B., Khan, Q., Ullah, S., Hafeez, G., Fida, A., Iqbal, J., & R. Albogamy, F. (2022). Maximum Power Extraction from a Standalone Photo Voltaic System via Neuro-Adaptive Arbitrary Order Sliding Mode Control Strategy with High Gain Differentiation. Applied Sciences, 12(6), Article 2773. https://doi.org/10.3390/app12062773

In this work, a photovoltaic (PV) system integrated with a non-inverting DC-DC buck-boost converter to extract maximum power under varying environmental conditions such as irradiance and temperature is considered. In order to extract maximum power (v... Read More about Maximum Power Extraction from a Standalone Photo Voltaic System via Neuro-Adaptive Arbitrary Order Sliding Mode Control Strategy with High Gain Differentiation.

Performance improvement in polymer electrolytic membrane fuel cell based on nonlinear control strategies—A comprehensive study (2022)
Journal Article
Javaid, U., Iqbal, J., Mehmood, A., & Uppal, A. A. (2022). Performance improvement in polymer electrolytic membrane fuel cell based on nonlinear control strategies—A comprehensive study. PLoS ONE, 17(2 February), Article e0264205. https://doi.org/10.1371/journal.pone.0264205

A Polymer Electrolytic Membrane Fuel Cell (PEMFC) is an efficient power device for automobiles, but its efficiency and life span depend upon its air delivery system. To ensure improved performance of PEMFC, the air delivery system must ensure proper... Read More about Performance improvement in polymer electrolytic membrane fuel cell based on nonlinear control strategies—A comprehensive study.

Neural network-based adaptive global sliding mode MPPT controller design for stand-alone photovoltaic systems (2022)
Journal Article
Haq, I. U., Khan, Q., Ullah, S., Ahmed Khan, S., Akmeliawati, R., Khan, M. A., & Iqbal, J. (2022). Neural network-based adaptive global sliding mode MPPT controller design for stand-alone photovoltaic systems. PLoS ONE, 17(1), Article e0260480. https://doi.org/10.1371/journal.pone.0260480

The increasing energy demand and the target to reduce environmental pollution make it essential to use efficient and environment-friendly renewable energy systems. One of these systems is the Photovoltaic (PV) system which generates energy subject to... Read More about Neural network-based adaptive global sliding mode MPPT controller design for stand-alone photovoltaic systems.

Toward Efficient Mobile Electric Vehicle Charging under Heterogeneous Battery Switching Technology (2022)
Journal Article
Ahmad, A., Ullah, Z., Khalid, M., & Ahmad, N. (2022). Toward Efficient Mobile Electric Vehicle Charging under Heterogeneous Battery Switching Technology. Applied Sciences, 12(2), Article 904. https://doi.org/10.3390/app12020904

The fast increase in adoption and development of Electric Vehicles (EVs) has invited a significant challenge to the existing charging management techniques and infrastructure. It is necessary to efficiently manage a large number of mobile EVs. As com... Read More about Toward Efficient Mobile Electric Vehicle Charging under Heterogeneous Battery Switching Technology.

UAVs-UGV Leader Follower Formation Using Adaptive Non-Singular Terminal Super Twisting Sliding Mode Control (2021)
Journal Article
Ullah, N., Mehmood, Y., Aslam, J., Ali, A., & Iqbal, J. (2021). UAVs-UGV Leader Follower Formation Using Adaptive Non-Singular Terminal Super Twisting Sliding Mode Control. IEEE Access, 9, 74385-74405. https://doi.org/10.1109/ACCESS.2021.3081483

Leader follower formation of unmanned aerial vehicles (UAVs) and unmanned ground vehicles (UGVs) has found numerous applications such as surveillance of critical infrastructure, industrial automation and disaster management emergency. For completion... Read More about UAVs-UGV Leader Follower Formation Using Adaptive Non-Singular Terminal Super Twisting Sliding Mode Control.

Scientometric review of artificial intelligence for operations & maintenance of wind turbines: The past, present and future (2021)
Journal Article
Chatterjee, J., & Dethlefs, N. (2021). Scientometric review of artificial intelligence for operations & maintenance of wind turbines: The past, present and future. Renewable & sustainable energy reviews, 144, Article 111051. https://doi.org/10.1016/j.rser.2021.111051

Wind energy has emerged as a highly promising source of renewable energy in recent times. However, wind turbines regularly suffer from operational inconsistencies, leading to significant costs and challenges in operations and maintenance (O&M). Condi... Read More about Scientometric review of artificial intelligence for operations & maintenance of wind turbines: The past, present and future.

Deep reinforcement learning for maintenance planning of offshore vessel transfer (2020)
Presentation / Conference Contribution
Chatterjee, J., & Dethlefs, N. (2020, October). Deep reinforcement learning for maintenance planning of offshore vessel transfer. Presented at 4th International Conference on Renewable Energies Offshore (RENEW 2020), Lisbon, Portugal

Offshore wind farm operators need to make short-term decisions on planning vessel transfers to turbines for preventive or corrective maintenance. These decisions can play a pivotal role in ensuring maintenance actions are carried out in a timely and... Read More about Deep reinforcement learning for maintenance planning of offshore vessel transfer.