Plenary Speakers



Prof. Michael Negnevitsky | University of Tasmania, Australia

Chair in Power Engineering and Computational Intelligence&Director of the Centre for Renewable Energy and Power Systems;
Fellow of Engineers Australia; Member of the National ITEE College Board;Chair of the IEEE PES Working Group


Biography-Professor Michael Negnevitsky is Chair in Power Engineering and Computational Intelligence and Director of the Centre for Renewable Energy and Power Systems, University of Tasmania, Australia. The primary focus of his research is smart grids, power system security, demand response, and isolated and remote area power systems with high renewable energy penetration. Professor Negnevitsky authorised more than 400 research publications including 102 journal papers, more than 300 conference papers, 12 chapters in books, 2 books, 9 edited conference proceedings and received 4 patents for inventions. He is Fellow of Engineers Australia, and Member of the National ITEE College Board. Professor Negnevitsky is Chair of the IEEE PES Working Group on High Renewable Energy Penetration in Remote and Isolated Power Systems, Vice Chair of the IEEE PES Working Group on Asian and Australasian Infrastructure – Smart Grids with Large Penetration of Renewable Energy, Member of CIGRE AP C4 (System Technical Performance) and CIGRE AP C6 (Distribution Systems and Dispersed Generation), Australian Technical Committee, Member of CIGRE Working Group JWG C1/C2/C6.18 (Coping with Limits for Very High Penetrations of Renewable Energy), International Technical Committee, and Member of CIGRE Working Group C6.30 (The Impact of Battery Energy Storage Systems on Distribution Networks), International Technical Committee.


Speech Title "High Renewable Energy Penetration and Power System Security: New Challenges and Opportunities"


Abstract-The word “security” in the context of a power system implies its security against a complete collapse, or a blackout. Secure operation involves practices aimed to keep the system operating normally when contingencies occur. An increasing penetration of intermittent renewable energy generation introduces additional uncertainties in power systems. However, the impact of variable generation on the system security is often exaggerated. On average, no significant mitigation measures are required until the wind and solar penetration reaches 20 per cent. The main challenge facing a power system with high penetration of renewables is the displacement of conventional synchronous generation by non-synchronous generation. Kinetic energy stored in the rotating masses of synchronous generators provides the system rotational inertia. Wind power generators are mostly doubly-fed induction or full-converter machines. Because these machines are either partially or completely decoupled from the grid by electronic converters, they do not provide inertia to the system. This reduces the total system inertia, and as a result, the system becomes more vulnerable to contingencies. Traditionally security assessment is performed based on deterministic criteria. The N-1 security criterion requires a power system to withstand an outage of any single system component without violating any system operating limits. This is based on the worst-case scenario criterion and provides a simple rule in the system design and operation. It has satisfied the needs of the power industry for decades. However, the deterministic approach to security is not adequate in modern power systems with market driven dispatch and high penetration of renewable energy and distributed generation. In this paper, security is defined as the risk in the system’s ability to withstand random contingencies without interruption to customer service. The higher the risk the lower the security, and vice-versa.  System operational risk is defined as the sum of products of the probabilities of random contingencies that may occur in a particular system state and the expected cost of load interruptions caused by these contingencies. In calculating the operational risk, we take into account not just the likelihood of contingencies, but also uncertainties in load variability and renewable energy generation. In risk-based security assessment, we generate contingencies at random, based on their probabilities.  Then, we assess the consequences of these contingencies in order to determine whether loads are disconnected following voltage violations, overloads and significant imbalance between load and generation.




Prof. Dr. Hamidah Ibrahim | Universiti Putra Malaysia

Member of IEEE, Member of IEEE Computer Society, Member of Association Computing Machinery (ACM)


Biography-HAMIDAH IBRAHIM is currently a professor in the Department of Computer Science at Universiti Putra Malaysia (UPM), Malaysia. She received her Ph.D. in Computer Science in 1998 from Cardiff University, UK, with a dissertation entitled Semantic Integrity Constraints Enforcement for a Distributed Database, guided by Prof. Alex Gray. She is a member of IEEE, IEEE Computer Society, and Association Computing Machinery (ACM). Her current research interests include databases (distributed, parallel, mobile, biomedical, XML) focusing on issues related to integrity maintenance/checking, ontology/schema/data integration, ontology/schema/data mapping, cache management, data security, transaction processing, query optimization, query reformulation, preference evaluation – context-aware, information extraction, concurrency control; and data management in mobile, grid, and cloud. She has received several research grants; among others are the Fundamental Research Grant Scheme (Ministry of Higher Education Malaysia), Science Fund (Ministry of Science, Technology, and Innovation), and Research University Grant Putra.  She has authored more than 300 scientific publications and book chapters. She serves as the editorial board member of several outstanding journals like International Arab Journal of Information Technology (IAJIT), International Journal of Electrical and Computer Engineering (IJECE), International Journal of Networks and Communications, International Journal of Mobile Network Communications & Telematics (IJMNCT), Asian Research Journal of Mathematics as well as reviewer of several scholarly journals like IEEE Access, Information Sciences, Journal of Supercomputing, etc.


Speech Title "Energy-Efficient Skyline Query Computation for Sensing Data"


Abstract-Query processing, a technique for retrieving objects from a database in a reliable and efficient way; has achieved tremendous success at both research and industry levels. It operates by retrieving only those data points that strictly satisfy the conditions specified in the query or returning an empty result if otherwise. Recent developments in query processing attempt to relax these stringent requirements, by retrieving the best, most preferred data points from a database. These queries known as skyline queries rely on the notion of Pareto dominance, have achieved significant success, as they are widely used in applications related to multi-criteria decision making; wherein several conflicting criteria need to be evaluated in the process of making decision. It is more challenging when there are too many criteria to be considered while the data points to be analysed are those generated and transmitted from sensing devices also known as sensing data. This group of sensors which constitutes a sensor network monitors data points at different sites and transmits these data points to a central site for further analysis. Inevitably, the network lifetime is reduced due to energy consumption for transmitting these sensing data. Furthermore, with the growth of network sizes, the sensing data become massive. Intuitively, it is crucial to reduce the transmission energy consumption for energy-efficient of skyline query computation by filtering the unwarranted data points in the sensor networks. In this abstract, we surveyed the recent works that have been conducted in improving energy efficiency of skyline query computation of sensors networks in terms of the total energy consumption, the maximum energy consumption, and the network lifetime. Hence, the following questions will be the main focus of the abstract: What are the challenges in computing skylines of sensing data particularly in sensor networks? How to reduce the transmission energy consumption of sensor networks for energy-efficient of skyline query computation? What are the limitations of existing energy-efficient models and the potential extension works that can be conducted in future?


2022 12th International Conference on Future Environment and Energy