Shoresh Shokoohi
Executive Director of Sanandaj Oil Pipelines and Telecommunication Terminal Facilities
Iranian Oil Pipelines and Telecommunication Company (IOPTC)
Shoresh Shokoohi is an Iranian electrical engineer, researcher, and industry expert whose work spans intelligent control systems, smart microgrids, renewable energy technologies, and condition monitoring of industrial electrical machines. Born in 1987 in Sanandaj, Iran, he earned all his academic degrees—B.Sc. in Electronics Engineering, M.Sc. in Power Engineering, and Ph.D. in Electrical Engineering (Power)—from the University of Kurdistan, completing his doctorate with a strong research record in fault diagnosis of induction motors, intelligent control and power system stability . Dr. Shokoohi has built a distinguished dual-track career across academia and the energy industry. Since 2009, he has served within the National Iranian Oil Company’s subsidiaries, beginning as a senior control and instrumentation engineer in the Lorestan region and later holding key operational and managerial roles in the Kurdistan West Region, including Operations Officer and, ultimately, Head of the Sanandaj Oil Pipeline Facilities—a position that reflects both his technical capability and leadership within critical national energy infrastructure . His performance evaluations in various roles consistently rank at the highest levels, and his contributions have earned him multiple recognitions, including “Top Researcher of the Company” (2017), “Top Energy-Saving Center in the Western Region” (2018), and a provincial appreciation from the General Directorate of Passive Defense of Kurdistan (2021) . Alongside his industrial responsibilities, Dr. Shokoohi has been deeply active in academic research and teaching for more than a decade. He has taught numerous undergraduate and graduate courses at the University of Kurdistan—ranging from Signals and Systems, Logic Circuits, Electrical Measurements, and Industrial Control to specialized MATLAB training for electrical engineering students. He has also served as a laboratory engineer in Control Systems and Instrumentation and as a course instructor at the Technical and Vocational University of Sanandaj . His research contributions cover microgrid stability, artificial-intelligence-based control, inverter-based distributed generation, radio-frequency amplifier design, and fault diagnosis in electric machines. He has published multiple papers in prestigious international journals—including IEEE Transactions on Smart Grid, International Journal of Electrical Power & Energy Systems, Optimization and Engineering, Neural Computing & Applications, and Measurement. His work on intelligent droop control, ANN-based frequency regulation, and model-based fault diagnosis has been cited widely in the field. He also co-authored a book chapter on meta-heuristic optimization applications in engineering (IGI Global, 2012) . Dr. Shokoohi is also an active reviewer for leading international journals. He currently serves as a reviewer for IEEE Transactions on Instrumentation & Measurement, ISA Transactions, Measurement, Engineering Applications of Artificial Intelligence, IEEE Transactions on Transportation Electrification, and others. His earlier reviewing work includes IEEE Transactions on Power Electronics, IEEE Transactions on Power Systems, and IEEE Transactions on Smart Grid between 2015 and 2018 . In addition, he has served as a program committee member and reviewer for several national and international conferences, including the International Iranian Conference on Electrical Engineering and the National Smart Grid Conference. In applied engineering, he has designed and implemented more than 50 solar power systems and numerous smart-home/Building Management Systems (BMS) projects across Tehran and Kurdistan. He also contributed to the smart transformation of laboratory infrastructure at the University of Kurdistan and led condition-monitoring projects for induction motors in the oil industry from 2013 to the present . His skillset includes industrial automation, resilient and intelligent control design, RF amplifier modeling, microgrid operation, renewable integration, and advanced AI-based fault diagnosis. Dr. Shokoohi has taught industrial training courses in smart operation of oil pipelines, solar PV system design and economic evaluation, and intelligent maintenance. He has also served on multiple organizational committees, including the company’s Research Council, Knowledge Management Committee, Energy Committee, and the Kurdistan Province Investment Atlas Technical Committee . Overall, Shoresh Shokoohi stands out as a multidisciplinary engineer and researcher whose contributions bridge academic depth with industrial impact—advancing smarter, safer, and more efficient energy systems in both theory and practice.
Participates in
TECHNICAL PROGRAMME | Energy Fuels and Molecules
The proposed system integrates solar photovoltaic (PV) panels, battery storage, and a diesel generator, coordinated by a smart controller that dynamically prioritizes power sources based on real-time energy availability, load demand, and forecasted solar irradiance. Unlike traditional hybrid systems that use static or rule-based switching logic, the control algorithm uses a predictive model to optimize energy source selection with the goal of minimizing diesel runtime and maximizing renewable energy utilization without compromising system reliability.
At the core of this innovation is a multi-layer control logic that assesses:
Current and predicted PV generation based on irradiance and temperature, Battery state-of-charge and historical discharge patterns, Real-time and forecasted load profiles, and Diesel generator fuel efficiency at varying load levels.
This intelligent coordination ensures that solar energy is always used as the primary source, followed by battery storage when solar is insufficient, and finally diesel generation as a backup. The algorithm also considers operational constraints such as generator startup costs and battery degradation, optimizing both performance and lifespan of the system components.
Simulation results demonstrate significant reductions in diesel fuel consumption (up to 60%) and generator runtime, especially in high solar potential regions. The system is designed for easy integration with SCADA systems and remote monitoring tools commonly used in the oil industry. The paper also discusses scalability, fault-handling features, and potential for machine learning integration for future improvements.
This work provides a practical and intelligent solution for powering remote petroleum infrastructure sustainably, aligning with the global energy transition and carbon reduction goals promoted by the World Petroleum Congress.
Co-author/s:
Somaye Nazari, Researcher, Iranian Oil Pipelines and Telecommunication Company (IOPTC).
