Defense of the dissertation of Djetmekova Saltanat for the degree of Doctor of Philosophy (PhD) in the specialty «6D070200 - Automation and control»
L.N. Gumilyov Eurasian National University, a dissertation defense for the degree of Doctor of Philosophy (PhD) by Djetmekova Saltanat on the topic Development of a control models and algorithms in electric power systems by specialty «6D070200 – Automation and control».
The dissertation was carried out at the «System analysis and management education department» of L.N. Gumilyov Eurasian National University.
The language of defense is russian
Official reviewers:
- Sugurova Laura Alkhaidarovna – PhD, associated professor, Head of the Department of Automation and Telecommunications, Dulaty Taraz University (Taraz, Republic of Kazakhstan).
- Imanbek Baglan Talgatkyzy – PhD, associated professor, Professor-reseacher of the Department of Artificial Intelligence and Big Data, Faculty of Information Technologies and Artificial Intelligence, Al-Farabi Kazakh National University (Almaty, Republic of Kazakhstan).
Temporary members of the Dissertation Council:
- Kurmangaziyeva Lyaylya Taskaliyevna – candidate of technical Sciences, Professor of the Department of software engineering, Kh. Dosmukhamedov Atyrau University, H-index – 7 (Atyrau, Republic of Kazakhstan).
- Kylyshkanov Manarbek Kalymovich – Doctor of physical and mathematical sciences, Professor, Manager of the Department of Science, Rare Metals and Rare Earth Metals, NAC Kazatomprom JSC , H-index – 9 (Astana, Republic of Kazakhstan).
- Xujamatov Xalimjon Ergashevich – PhD, Doctor of Technical Sciences, Professor of the Department of Networks and Data Transmission Systems, Tashkent University of Information Technologies named after Muhammad al-Khwarizmi, H-index – 22 (Tashkent, Republic of Uzbekistan).
Scientific advisors:
Shukirova Aliya Kosanaliyevna – PhD, Associate Professor of the Department of System Analysis and Control, L.N. Gumilyov Eurasian National University (Astana, Republic of Kazakhstan).
Wójcik Waldemar – Doctor of Technical Sciences, Professor of the Department of Electronics and Information Technology, Faculty of Electrical Engineering and Computer Science, Lublin University of Technology (Lublin, Poland).
The defense will take place on April 10, 2026, at 10:00 AM in the Dissertation Council for the training direction «8D071 – Engineering and engineering trades» in the specialty «6D070200 – Automation and control» of L.N. Gumilyov Eurasian National University. The Dissertation Council meeting will be held offline and online.
Link: https://teams.microsoft.com/meet/454363469288?p=yuIOUUX2L2OH67ekpo
Address: 11, Pushkin St., Astana, 010000, No.2 building, aud.222.
Abstract (English):ANNOTATION dissertation work of Jetmekova Saltanat Serikbaevna «Development of a control models and algorithms in electric power systems», submitted for the degree of doctor of Philosophy (PhD) in the specialty: «6D070200 – Automation and сontrol» The purpose of the dissertation research. Development of a model and control algorithm in electric power systems based on multi-agent systems technologies. Research objectives. This research project formulated and consistently developed a set of interrelated objectives, including the following, to ensure comprehensive and methodologically sound achievement of the stated research goal: - to study the current state of Kazakhstan's electric power systems and the challenges of using outdated technologies in the industry; - to analyze existing electric power system management systems and identify their advantages and limitations; - to develop a model and methodology for creating a multi-agent system; - based on the proposed methodology, develop a multi-agent system and implement its integrated architecture; - to develop a method for testing the stability of a multi-agent system based on graph models to identify critical agents; - to test the obtained results at energy facilities. Research Methods. This dissertation utilizes a comprehensive methodological approach integrating modern interdisciplinary methodologies: artificial intelligence tools, conceptual principles for constructing multi-agent systems, mathematical modeling, graph theory algorithms, and specialized methods for managing inter-agent interactions using algebraic network structures. Key points to be defended: 1. Developed methodology for creating a multi-agent system, including: – a method for designing and implementing a multi-agent system; – a computational method for managing agent interactions based on algebraic networks; – algorithms for agent interaction and behavior. 2. Constructed event-driven models of agent-based scenarios using the Joiner network framework, allowing users to independently modify the system's operating algorithm without the involvement of software developers. 3. Developed a numerical method that allows for assessing the stability of a multi-agent system using the mathematical apparatus of graph theory. Description of the main research findings. The study resulted in the development of a comprehensive methodology for creating and implementing multi-agent systems based on an event-driven design approach. A method for constructing a multi-agent system is proposed, including a computational mechanism for managing agent interactions based on algebraic networks, as well as formalized algorithms for agent behavior and coordination. A mechanism for inter-agent interaction using XML files and TCP/IP protocols was implemented, methods for integrating the system with existing software packages were identified, and a unified data storage and processing system was developed to ensure the integrity and consistency of information flows. A significant result of the work was the construction of event-driven models of agent-based scenarios using Joiner networks (JNs). The developed models formalize the system's operating logic and enable modification of its algorithms without the involvement of programmers. This increases the adaptability of the multi-agent system, reduces the time required to implement changes, and allows users to independently adjust operating scenarios based on changes in the subject area. A numerical method for assessing the stability and reliability of a multi-agent system based on the mathematical apparatus of graph theory has also been developed. This method involves forming and analyzing an adjacency matrix of agents, identifying critical elements, quantifying their impact on system operation, determining the need for component redundancy, and predicting possible failure scenarios. The proposed approach allows for the formalization of the reliability assessment process at the design stage and the justification of architectural decisions. Additionally, a multi-agent system architecture was developed and implemented for assessing the state of an electric power system. The architecture incorporates new mechanisms for inter-agent interaction, distributed data processing, and a modular design. Practical testing confirmed the viability of the proposed methods and their applicability for analyzing and monitoring the state of electric power systems, demonstrating the scientific validity and practical significance of the results obtained. Justification of the novelty and importance of the results obtained The results obtained in this dissertation possess both theoretical and applied novelty and are aimed at solving a pressing scientific and technical problem of improving the efficiency, reliability, adaptability, and scalability of multi-agent systems in the electric power industry. The research addresses the growing complexity of modern electric power systems operating under conditions of digital transformation, decentralization of generation, and increasing requirements for operational reliability and cybersecurity. The novelty of this work lies in the development of a holistic methodological approach to the design and implementation of multi-agent systems based on event-driven models, which enables a transition from traditional procedural programming paradigms to an adaptive, event-oriented control architecture. Unlike conventional centralized or rigidly structured distributed systems, the proposed approach ensures dynamic reconfiguration of agent behavior in response to changes in system state and external conditions. This significantly enhances system flexibility and resilience under variable operating modes of electric power networks. The proposed mechanism for agent interaction via XML files and TCP/IP protocols ensures platform independence, interoperability, scalability, and seamless integration with existing information systems without extensive reworking. The use of standardized data exchange formats and open communication protocols reduces integration barriers and ensures compatibility with legacy software and hardware environments. This expands the possibilities for the practical implementation of the developed solutions within the existing infrastructure of electric power enterprises and supports gradual digital modernization without disruptive restructuring. A substantial scientific contribution of the dissertation is the developed method for assessing the reliability of multi-agent systems based on graph theory. Unlike traditional reliability assessment approaches, which primarily focus on physical and technical components, the proposed method introduces a structural-logical analysis of agent interactions. By modeling the system as a graph and using the adjacency matrix to determine connectivity and interdependencies, the method enables identification of structurally critical agents, quantitative evaluation of their influence on overall system stability, and substantiation of redundancy strategies. This approach provides a formalized analytical framework for evaluating fault tolerance in distributed intelligent systems and allows predictive assessment of cascading failures within agent networks. An important methodological innovation is the formalization of agent interaction scenarios through event-driven models using JN, which enables modification of operational algorithms without direct programmer involvement. This represents a fundamentally new step toward increasing the flexibility, transparency, and manageability of complex software systems. The separation of logic description from core program code ensures modularity and simplifies system maintenance. As a result, adaptation time to changing operational conditions in electric power grids is significantly reduced, while dependence on highly specialized IT resources is minimized. The dissertation also introduces a unified data storage and processing concept that supports consistent handling of distributed agent-generated information. This ensures data integrity, traceability of decision-making processes, and reproducibility of analytical results. The proposed architecture facilitates horizontal scaling and distributed deployment, which is especially relevant for geographically dispersed power grid infrastructures. The practical significance of the results is confirmed by the creation and implementation of a multi-agent system architecture for assessing the state of an electric power system (EPS), incorporating new mechanisms for inter-agent interaction, structural reliability assessment, and adaptive scenario management. The developed system improves analytical accuracy, accelerates decision-making processes, enhances fault tolerance, and increases adaptability to changing network parameters, including load fluctuations, topology reconfiguration, and emergency conditions. The obtained results are particularly important in the context of the digital transformation of the energy sector, the integration of renewable energy sources, the transition toward smart grids, and the growing demands placed on the reliability and cybersecurity of critical infrastructure. The proposed solutions contribute to reducing operational risks, improving situational awareness, and strengthening the technological independence of electric power enterprises. Thus, the results of this research contribute to the advancement of the theory and practice of multi-agent system design, expand methodological tools for reliability analysis of distributed intelligent systems, and create a scientifically grounded basis for the large-scale implementation of adaptive, intelligent, and resilient control systems in the electric power industry. Compliance with scientific development directions and state programs. The dissertation work complies strategic state programs «Digital Kazakhstan» and «Kazakhstan-2050», aimed at increasing the sustainability and efficiency of existing energy systems. A description of the applicant's contribution to the preparation of each publication. All scientific publications on the topic of the dissertation research were prepared with the direct and decisive participation of the applicant and reflect the results of independent research in the field of developing models and algorithms for controlling electric power systems based on multi-agent systems technologies. The applicant independently formulated the scientific problem, defined the goal, objectives, object, and subject of the study, and substantiated the relevance of applying multi-agent technologies in the context of the modernization of the electric power system of the Republic of Kazakhstan. The author conducted a systemic analysis of the state of the electric power industry, identified key technological and organizational limitations of existing management methods, and identified areas for improving the reliability and efficiency of the EPS. In publications devoted to the development of algorithms for controlling electric power systems, the applicant: - developed mathematical models for controlling EPS operating modes taking into account distributed computing architecture; - formulated principles for decomposing the electric power system into functional subsystems; - proposed algorithms for inter-agent interaction based on event-driven models; - developed mechanisms for coordinating agents using structured data exchange formats; - The algorithms were implemented and tested on test and simulated power system circuits. In works related to forecasting and analyzing energy consumption time series, the applicant studied the deterministic and stochastic components of time series, performed mathematical modeling of energy consumption processes, developed algorithms for identifying trend and seasonal components, and implemented computational procedures for assessing forecast accuracy. In a publication indexed in the international Scopus database, the author developed a concept for constructing a multi-agent control system for electric power facilities, including: - the architecture of a distributed intelligent system; - a hierarchical structure of agents (executive, control, and coordinating levels); - a methodology for designing agent-based scenarios; - a mechanism for ensuring the stability and reliability of the MAS operation based on graph theory. The candidate developed a mathematical justification for the proposed solutions, modeled the dynamics of inter-agent interactions, and analyzed the effectiveness of the developed system based on technical and economic indicators. Publications presented at international scientific and practical conferences reflect the stages of development of the research concept: from the analysis of existing optimization and control methods to the development of a proprietary methodology for constructing multi-agent intelligent systems. The candidate prepared reports, developed illustrative materials, conducted computational experiments, and interpreted the results. In addition, the author: - developed a method for assessing the stability of a multi-agent system using an adjacency matrix and an analysis of the structural connectivity of agents; - proposed an approach to identifying critical agents and justifying the need for component redundancy; - developed a unified data storage and processing structure for integration with existing software and computing systems; - conducted an analysis of the economic efficiency of implementing multi-agent solutions in the electric power industry. All mathematical calculations, algorithmic developments, software implementation, design and execution of computational experiments, processing of results, their analysis, and formulation of scientific conclusions were performed by the applicant personally. In co-authored publications, the applicant played a key role in formulating the scientific problem, developing the methodological framework, performing calculations, preparing illustrations, and writing the main text of the articles. The published scientific papers are logically interconnected, reflect the consistent development of the scientific idea, and fully correspond to the dissertation topic. The combined results presented in the publications confirm the independent nature of the work performed and the applicant's significant personal contribution to the development of intelligent control methods for electric power systems based on multi-agent technologies.
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