Markus Miller | Electrical Engineering Award | Best Researcher Award

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Mr Markus Miller | Electrical Engineering Award | Best Researcher Award

Mr Markus Miller, Institute of Automation Technology, University of Bremen ,Germany

👨‍🎓 Markus Miller is an accomplished electrical engineer and Ph.D. researcher at the University of Bremen’s Institute of Automation Technology under Prof. Dr. Johanna Myrzik. His work focuses on integrating renewable energy into power grids, developing methodologies for hybrid AC-DC systems. Markus excels in probability and stochastic processes, aiding power grid planning as a tutor for “Stochastic Systems.” Noteworthy achievements include winning the 2016 Bremen Big Data Challenge. His research emphasizes cost-effective, flexible, and resilient grid expansion using AI and optimization techniques. Currently, he explores Smart Power Cells (SPCs) under the DFG SPP 1984 program, addressing challenges in decentralized power systems and Distributed Energy Resources (DERs).

Publication Profile

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Education

🎓 Markus Miller pursued his academic journey at the University of Bremen, where he earned a Bachelor of Science in Electrical Engineering and Information Technology from 2015 to 2019. Building upon this foundation, he continued to excel, completing his Master of Science in the same field from 2019 to 2021. His education equipped him with profound knowledge in electrical engineering, preparing him for his current role as a Ph.D. researcher specializing in renewable energy integration at the Institute of Automation Technology. Markus’s academic path underscores his dedication to advancing sustainable energy solutions and enhancing power grid efficiency through innovative methodologies and advanced technologies.

Experience

🔋 Markus Miller is currently immersed in pioneering research at the University of Bremen, focusing on integrating renewable energy into power grids. His work centers on developing comprehensive methodologies for planning interconnected hybrid and multimodal AC-DC power systems. As part of the DFG SPP 1984 program’s second phase, Markus explores the pivotal role of Smart Power Cells (SPCs) in decentralized power networks. Leveraging AI and mathematical programming solvers, he optimizes SPC operations and planning, tackling challenges such as Distributed Energy Resources (DERs), power generation uncertainties, and storage system operations. Additionally, Markus imparts his expertise as a tutor for “Stochastic Systems,” enhancing students’ grasp and application of probability and stochastic processes in power grid planning.

 

Research Focus

Markus Miller’s current research focuses on optimizing the allocation of renewable energy systems within weak distribution networks. This work, highlighted in the journal article “Optimal allocation of renewable energy systems in a weak distribution network” published in Electric Power Systems Research, aims to enhance the integration of renewable energy sources into power grids. Collaborating with JosĂ© Luis Paternina Durán, Sergio F. Contreras, Camilo A. Cortes, and Johanna M.A. Myrzik, Markus addresses critical challenges such as grid stability and efficiency. By employing advanced methodologies and leveraging interdisciplinary insights, his research contributes to sustainable energy solutions that are crucial for meeting future energy demands while minimizing environmental impact.

Publication Top Note

Optimal allocation of renewable energy systems in a weak distribution network

Dr Fahad Allahaim | Technology Award | Best Researcher Award

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Dr Fahad Allahaim | Technology Award | Best Researcher Award

Dr Fahad Allahaim , King Saud University , Saudi Arabia

Dr. Fahad Saud Allahaim is an Assistant Professor at King Saud University’s College of Architecture and Planning in Riyadh, Saudi Arabia. With a Ph.D. in Architectural & Engineering Economics from the University of Sydney, his expertise spans architecture, building technology, urban economics, and AI in the built environment. Dr. Allahaim also serves as Vice Dean for Academic Affairs and Head of Business Development at his university. He holds multiple leadership roles in national committees shaping Saudi building codes and urban standards. Passionate about sustainable design, he is a certified Architectural Consultant and Quality Ambassador. 🏢🌍

Publication Profile

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Education

Dr. Fahad Saud Allahaim holds a Ph.D. in Architectural & Engineering Economics from the University of Sydney, specializing in understanding and mitigating cost overruns in infrastructure projects. His research includes developing risk-based cost estimation models and typologies for cost overrun causes, particularly focused on Saudi Arabia. With master’s degrees in Building Services/Technology and Facilities Management from the University of Sydney, he advocates for adaptable building design frameworks. Dr. Allahaim completed his Bachelor of Science in Architecture & Building Science at King Saud University, contributing to projects addressing urban challenges in Riyadh. He is also a certified Consultant, Accredited Trainee, and Quality Ambassador in related fields.

Research Focus

Dr. Fahad Saud Allahaim’s research focuses on understanding and mitigating cost overruns in infrastructure projects, employing innovative methodologies such as cluster analysis and risk-based cost contingency models. His work, notably presented at international conferences like ICMA 2019 and AACE International Annual Meeting 2016, contributes significantly to improving cost forecasting accuracy and enhancing project management strategies. As an Assistant Professor at King Saud University, he integrates these insights into teaching and consultancy, emphasizing sustainable and efficient building practices. Dr. Allahaim’s commitment to advancing architectural and engineering economics is marked by his roles as a consultant and quality ambassador, driving forward industry standards. 🏗️

Publication Top Notes

An empirical typology of cost overrun in infrastructure projects by using cluster analysis to understand Saudi Building code

Risk-Based Cost Contingency Estimation Model for Infrastructure Projects

Improving the cost forecasting accuracy through classification of main causes of cost overrun in infrastructure project – illustration using Saudi Arabia survey data