Xiaojie Qiu | Smart Grid | Best Researcher Award

Best Researcher Award

Xiaojie Qiu
The State Key Laboratory of Industrial Control Technology

                            Xiaojie Qiu
Affiliation The State Key Laboratory of Industrial Control Technology
Country China
Scopus ID 57211005876
Documents 10
Citations 289
h-index 5
Subject Area Smart Grid
Event Technology Scientists Awards
ORCID 0000-0003-0024-7794

Xiaojie Qiu is a researcher associated with The State Key Laboratory of Industrial Control Technology, China, whose scholarly work focuses on smart grid systems, distributed control strategies, cyber-secure power networks, and data-driven control methodologies. Through contributions to resilient microgrid control and distributed intelligent systems, the researcher has established a measurable academic presence supported by publications, citations, and collaborative research activities within modern energy and automation domains.[1]

Abstract

Xiaojie Qiu’s research activities are centered on smart grid technologies, distributed control systems, resilient microgrids, and secure energy management frameworks. The research emphasizes data-driven control strategies, event-triggered communication mechanisms, and cyberattack-resilient operation of interconnected power systems. Published studies contribute to voltage restoration, current sharing optimization, and distributed coordination in microgrids and multi-agent networks. These contributions support the advancement of reliable, intelligent, and secure energy infrastructures while addressing practical challenges associated with distributed energy resources, communication constraints, and modern smart grid deployment requirements.[2]

Keywords

Smart Grid, DC Microgrid, Distributed Control, Data-Driven Systems, Multi-Agent Systems, Event-Triggered Control, Cybersecurity, Voltage Restoration, Current Sharing, Industrial Control Technology.

Introduction

Modern smart grids require secure, resilient, and distributed control architectures capable of maintaining stability under communication limitations and cyber threats. Xiaojie Qiu’s research addresses these challenges through innovative control methodologies for microgrids and multi-agent systems, supporting reliable energy distribution, operational security, and efficient coordination across increasingly complex power infrastructures.[2]

Research Profile

The research profile of Xiaojie Qiu demonstrates sustained engagement in smart grid control, distributed automation, and intelligent energy systems. With scholarly outputs indexed in Scopus and measurable citation impact, the researcher contributes to advancing secure control frameworks, data-driven optimization methods, and resilient operation strategies for contemporary electrical power networks.[1]

Research Contributions

Key contributions include distributed resilient control techniques for DC microgrids under deception attacks, secure voltage restoration mechanisms, adjustable current-sharing approaches, and fully distributed event-triggered control algorithms. These studies improve robustness, communication efficiency, and system stability while addressing practical implementation challenges in distributed energy and automation environments.[2][3]

Publications

  • Edge-Event-Based Distributed Resilient Control of DC Microgrid Against Multipattern Deception Attacks. This study proposes resilient distributed control mechanisms that enhance microgrid security and operational stability under coordinated cyberattacks while reducing communication burden through edge-event-triggered strategies.[2]
  • Distributed Data-Driven Control for Adjustable Current Sharing and Secure Voltage Restoration in DC Microgrids. The publication develops data-driven methodologies for voltage regulation and current sharing, improving distributed coordination and operational reliability in microgrid applications.[3]
  • Data-driven-based Fully Distributed Event-Triggered Control for Nonlinear Multi-Agent Systems. The research introduces event-triggered distributed control approaches that reduce communication requirements while maintaining system performance and coordination across nonlinear networked agents.[4]

Research Impact

The research has contributed to the broader understanding of secure distributed energy management and intelligent control systems. Citation performance and scholarly visibility indicate relevance within smart grid and automation communities. The developed methodologies provide practical value for enhancing resilience, scalability, and operational efficiency in modern power infrastructures.[1]

Award Suitability

Xiaojie Qiu demonstrates strong alignment with the objectives of the Technology Scientists Awards through contributions to smart grid innovation, resilient microgrid control, and distributed intelligent systems. The combination of academic publications, measurable citation metrics, and practical technological relevance supports recognition within research excellence and technology advancement categories.[2]

Conclusion

The body of work associated with Xiaojie Qiu reflects a focused commitment to advancing secure, distributed, and data-driven control methodologies for smart grids and multi-agent systems. Through research addressing cybersecurity, resilience, and operational efficiency, the researcher contributes valuable knowledge supporting the development of next-generation intelligent energy networks.[1]

References

  1. Elsevier. (n.d.). Scopus author details: Xiaojie Qiu, Author ID 57211005876. Scopus.
    https://www.scopus.com/authid/detail.uri?authorId=57211005876
  2. Qiu, X., et al. (2025). Edge-Event-Based Distributed Resilient Control of DC Microgrid Against Multipattern Deception Attacks. IEEE Transactions.
    https://ieeexplore.ieee.org/document/11300711/
  3. Qiu, X., et al. (2025). Distributed Data-Driven Control for Adjustable Current Sharing and Secure Voltage Restoration in DC Microgrids. IEEE Transactions.
    https://ieeexplore.ieee.org/document/11220903/
  4. Qiu, X., et al. (2025). Data-driven-based Fully Distributed Event-Triggered Control for Nonlinear Multi-Agent Systems. Nonlinear Analysis: Hybrid Systems.
    https://linkinghub.elsevier.com/retrieve/pii/S0096300325000347

Jack Mathebula | Planning and Operations | Best Researcher Award

Mr. Jack Mathebula | Planning and Operations | Best Researcher Award

Research Manager, Eskom, South Africa

Jack Mathebula is a veteran energy systems strategist with over two decades of experience in power system planning, operations, and renewable energy integration. Currently serving as Acting Research Manager at Eskom RT&D, Jack leads strategic grid innovation efforts aligned with global sustainability goals. His journey began with technical roles in HVDC plant operations and evolved into thought leadership in transmission planning, capital budgeting, and smart grid transformation. Jack has authored multiple Award papers and peer-reviewed articles focusing on HVDC planning and MCDA methodologies. A recipient of several international Award honors, he has also chaired global forums and mentored young engineers across Africa. He is a registered Professional Technologist (Pr Tech Eng) and a Senior Member of SAIEE, with a growing academic profile. Jack’s work directly supports energy transition efforts in South Africa and beyond, combining academic insight with real-world applications to meet the energy challenges of tomorrow.

📘Author Profile

🎓 Education

Jack Mathebula is currently pursuing a PhD in Electrical Engineering at the University of South Africa (UNISA), building on a Cum Laude MSc from the University of Pretoria (2015). His master’s thesis focused on optimizing HVDC scheme planning. He also holds a BSc Honours in Applied Sciences–Electrical from the University of Pretoria (2004), a B-Tech in Power Engineering from Technikon Pretoria (2001), and a National Diploma in Electrical Engineering from Technikon Witwatersrand (1998). His academic training blends strong theoretical knowledge with practical energy systems expertise. Jack further expanded his leadership acumen through specialized programs, including a Project Management Programme from UNISA’s School of Business Leadership and the Middle Managers Programme (MMP) via Henley Business School in collaboration with Eskom. His education reflects a lifelong dedication to combining engineering excellence with strategic project management in the energy sector.

🛠️ Experience

Jack’s career spans over 25 years at Eskom, where he has held progressively senior roles in grid planning, transmission strategy, and renewable integration. Since April 2024, he serves as Acting Research Manager (Distribution) in Eskom’s RT&D division, leading strategic energy projects and guiding national/international technical initiatives. Between 2008 and 2024, Jack was Middle Manager for Grid Planning and Operation, overseeing research portfolios and contract/resource management. Previously, he contributed to capital planning (2006–2008), network investment (2005–2006), and master planning (2000–2005). His career began in 1999 at the Apollo HVDC Converter Station, where he optimized plant performance. Jack’s career reflects deep technical competency coupled with leadership in digital transformation, grid simulation (RTDS), and policy-relevant research on EV infrastructure and hosting capacity assessments. He continues to mentor emerging engineers and drive forward-thinking energy planning initiatives.

🔬 Research Focus 

Jack Mathebula’s research concentrates on power system planning, HVDC optimization, renewable integration, and electric mobility infrastructure. He is particularly known for applying multi-criteria decision analysis (MCDA) and TOPSIS models in selecting optimal grid expansion strategies. His ongoing PhD explores advanced planning tools for dynamic energy systems under uncertainty, contributing to resilient grid development. His technical projects include hosting capacity assessments, RTDS-based simulation, and distribution-level renewable integration via DSTATCOMs. Jack is also involved in shaping EV-ready grid infrastructure and tariff structures, through cross-border collaborations with institutions like the Danish Technical University. His commitment to applied systems thinking is evident in his work linking technical feasibility, policy formulation, and national energy planning. His research is impactful not only in scholarly terms but also in operationalizing energy transition strategies for utilities and regulators.

📚 Publication Top Notes

Application of TOPSIS in Power Systems: A Review

Authors: J. Mathebula, N. Mbuli
Conference: 2024 International Conference on Electrical, Computer and Energy Engineering
Citations: 2
Summary:
This comprehensive review explores the use of the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) in addressing multi-criteria challenges in power systems. The paper synthesizes over a decade of applications, detailing how TOPSIS has been utilized for substation site selection, transmission route optimization, and renewable energy prioritization. It emphasizes the method’s effectiveness in quantifying trade-offs between conflicting objectives like cost, reliability, and environmental impact. The authors also discuss emerging trends such as hybrid TOPSIS models and their role in decision support systems for utilities.

Potential Factors for Multi-Criteria Evaluation of HVDC Compared to HVAC in Power Transmission

Authors: J. Mathebula, N. Mbuli
Conference: 2024 International Conference on Green Energy, Computing and Sustainable Technologies
Citations: 2
Summary:
This paper provides a structured framework for evaluating High Voltage Direct Current (HVDC) and High Voltage Alternating Current (HVAC) systems using multi-criteria analysis. Technical aspects like voltage stability, power losses, and system compatibility are considered alongside economic (CAPEX/OPEX) and environmental parameters. The study offers guidance for policymakers and transmission planners by identifying the most influential factors when choosing transmission technology for large-scale power corridors, particularly in developing countries with expanding renewable capacity.

Approach for Screening and Ranking Potential Receiving End Points in Planning New HVDC Schemes

Authors: J. Mathebula, M.N. Gitau, N. Mbuli, J.H.C. Pretorious
Conference: 2018 IEEE PES/IAS PowerAfrica
Citations: 1
Summary:
This research introduces a structured screening and ranking method to determine optimal receiving terminals for HVDC links. Using a case study in the South African grid, the authors apply decision matrix techniques based on projected load growth, geographic accessibility, system redundancy, and cost. The proposed framework supports utilities in identifying HVDC endpoints that align with long-term energy planning and enhances strategic transmission deployment in emerging economies.

Simplified Negative Load-Based Approach Versus Full HVDC Modeling in Assessing Options for the Cape Network

Authors: J. Mathebula, M.N. Gitau, N. Mbuli
Conference: 2013 13th International Conference on Environment and Electrical Engineering
Citations: 1
Summary:
This study contrasts two methodologies for evaluating HVDC implementation in the Cape region of South Africa: a simplified negative load approach and a full HVDC model. By comparing simulation results and cost-efficiency, the paper discusses the limitations and applicability of each method. The simplified model offers quicker decision support, while the full model yields greater accuracy. The work provides guidance on the trade-offs between modeling complexity and planning effectiveness in early-stage transmission projects.

Application of TOPSIS for MCDA in Power Systems: A Systematic Literature Review

Authors: J. Mathebula, N. Mbuli
Journal: Energies (2025)
Summary:
This peer-reviewed article presents a rigorous literature review of the integration of TOPSIS with multi-criteria decision analysis (MCDA) in power system engineering. Covering applications from renewable site selection to grid reinforcement prioritization, it categorizes studies by criteria sets, modeling tools, and decision contexts. The authors propose a future research agenda emphasizing the integration of real-time data, stakeholder weighting schemes, and AI-enhanced decision-making in power systems. The review positions TOPSIS as a valuable, yet underutilized, tool for navigating the complexity of modern grids.

Potential Factors for HVDC Evaluation in Selection of the Suitable Location Within HVAC System

Authors: J. Mathebula, N. Mbuli
Conference: 2024 ICECCME
Summary:
The paper investigates the suitability of integrating HVDC terminals within existing HVAC networks. Key criteria include system stability impact, proximity to generation/load centers, infrastructure compatibility, and future scalability. The study proposes a location scoring model tailored for hybrid AC-DC systems in grid modernization scenarios. Case illustrations from the South African transmission system reinforce the practical relevance of the proposed methodology, particularly for utilities preparing for high renewable penetration.

Design Options for Thermal Uprate of a Transmission Line: A Case Study in the South African Power System

Authors: J. Mathebula, N. Mbuli, S. Mushabe
Conference: 2024 International Conference on Electrical, Communication and Computer Engineering (ECCCE)
Summary:
This case study explores cost-effective design modifications to increase the thermal capacity of aging transmission lines. Options include conductor replacement, dynamic line rating, and advanced monitoring systems. Using a real-world line segment in South Africa, the paper evaluates each method based on cost, downtime, and long-term benefits. The findings aid transmission operators in choosing appropriate uprate techniques to meet increasing demand without incurring full infrastructure replacement costs.

Conclusion

Jack Mathebula is a highly suitable and deserving candidate for the Best Researcher Award, particularly in the domain of power systems, HVDC planning, and renewable energy integration. His blend of technical depth, leadership, applied research, and mentorship exemplifies the qualities of an impactful researcher driving innovation in the energy sector.