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2023 International Conference on Future Energy Solutions, FES 2023

作者： Akbarian, Amirhossein Bahrami, Mahdi Vakilian, Mehdi Lehtonen, Matti Sharif University of Technology Center of Excellence in Power System Management and Control Electrical Engineering Department Tehran Iran Aalto University Department of Electrical Engineering and Automation Espoo Finland

ISBN: (纸本)9798350332308

Electric vehicles (EVs) have experienced an unprecedented increase in their penetration;in well developed countries;due to the advancement of battery technology and the need to make transportation more environmentally friendly. As a result of this trend, EVs have become an integral part of those countries power grid ecosystem, where they may be used as both a source, and a consumer of energy. However, cybersecurity risks associated with large fleets of EVs within the power grids can significantly impact the normal operation of distribution systems. This paper considers the cyber-attack consequences, from attackers' perspective. The cyber attackers under study target the charging price (CP) by increasing the CP in off-peak hours and accordingly subsiding it in on-peak hours. A two-stage optimization framework is proposed to identify the most important ultra-fast charging stations (XFCs) under the cyber-attack, meanwhile, the EV users' response to the compromised CP is considered. Then, the proposed model is implemented on a modified IEEE 123-bus distribution test system, and the effectiveness of the model is proved through some case studies. In particular, they demonstrated that the amount of load shedding is increased by 8.198 MW when the EV user response is taken into account. © 2023 IEEE.

关键词： Crime

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Minimax Regret Robust Co-Planning of Transmission and Energy Storage systems With Mixed Integer Recourse

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IEEE Transactions on Sustainable Energy 2025年第3期16卷 2144-2156页

作者： Barkom, Ehsan Saber, Hossein Moeini-Aghtaie, Moein Ehsan, Mehdi Shahidehpour, Mohammad Sharif University of Technology Center of Excellence in Power System Control and Management Department of Electrical Engineering Tehran11365-11155 Iran Sharif University of Technology Department of Energy Engineering Tehran Iran Illinois Institute of Technology Robert W. Galvin Center for Electricity Innovation ChicagoIL60616 United States King Abdulaziz University Jeddah Saudi Arabia

The growing penetration of renewable energy sources, with intermittent and uncertain nature, brings new challenges to the secure and efficient operation of power systems. Expanding transmission networks and utilizing energy storage (ES) have been introduced as effective solutions to address these challenges. This paper presents a minimax regret robust co-planning model with mixed integer recourse for transmission and ES systems, designed from the perspective of a central planner. The model considers a polyhedral uncertainty set for future peak load growth, while uncertainties in wind farm expansion are addressed through internal scenario analysis. This approach will guarantee the robustness of investment decisions and provide the central planner with a clear picture of the maximum regret among all possible scenarios. Furthermore, the proposed minimax regret framework facilitates strategic planning for ES installation after the resolution of long-term uncertainties. In this paper, we reformulate the model into a standard min-max-min problem, in which the maximization level is only over uncertainties. Subsequently, a five-level solution strategy based on a modified nested column and constraint generation decomposition technique is represented to deal with the intractability and complexity of the problem caused by binary variables of transmission lines and ES blocks. The model is finally evaluated through comprehensive simulation studies to verify its tractability, practicality, and effectiveness. © 2010-2012 IEEE.

关键词： Uncertainty Planning Load modeling power transmission lines Costs Investment Renewable energy sources Optimization Stochastic processes Programming

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A Risk-Aware and Socp-Based Wind Expansion Planning Model Considering Correlated Uncertainties Using Copula Method

SSRN

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SSRN 2023年

作者： Ranjbar, Hossein Saber, Hossein School of Electrical and Mechanical Engineering The University of Adelaide Adelaide Australia Centre of Excellence in Power System Control and Management Department of Electrical Engineering Sharif University of Technology Tehran Iran

Integration of large-scale renewable energy sources (RESs) into existing power grids is challenging for power system operators and planners due to the intermittent and uncertain characteristics of RESs and the limitation of transmission capacity. This paper presents a new risk-based framework to obtain the optimal placement and sizing of wind farms in the bulk power system considering the impact of mutual correlation between wind farms' power productions in different candidate buses. In this regard, a second-order cone programming (SOCP) optimization problem is developed to minimize the total expected social cost including the operation cost of conventional generators, wind curtailment cost, and the investment cost of newly installed wind farms. In the proposed model, the correlated uncertainties of wind power production are incorporated using the copula method. Also, the conditional value-at-risk (CVaR) measure is utilized to manage the risk of the model associated with uncertainties. The proposed planning model is then implemented into the 6-bus Garver and IEEE 118-bus test systems to demonstrate the effectiveness and applicability of the proposed wind power expansion planning model. © 2023, The Authors. All rights reserved.

关键词： Second-order cone programming

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Utilizing Balanced and Unbalanced Partial Techniques in Co-Phase V/v Railway system for Improving Hybrid SVC power Quality Conditioner 7

Utilizing Balanced and Unbalanced Partial Techniques in Co-P...

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7th IEEE International Conference on Recent Advances and Innovations in engineering, ICRAIE 2022

作者： Habibolahzadeh, Mohammad Jalilian, Alireza Iran University of Science and Technology Department of Electrical Engineering Tehran Iran Iran University of Science and Technology Centre of Excellence for Power System Automation and Operation Department of Electrical Engineering Tehran Iran

ISBN: (纸本)9781665489102

This paper proposes a hybrid structure including static VAR compensator (SVC) and conventional hybrid power quality conditioner (HPQC) in co-phase traction railway system powered by V/v transformer. The SVC plays a vital role in compensating the full required load reactive power in addition to filtering the third and fifth harmonics, while the HPQC handles the left harmonics and negative sequence current of the grid side. Moreover, to keep the grid power factor flexibly within acceptable limits, a control strategy employs two partial compensation techniques, one balanced and one unbalanced (BPCT and UPCT, respectively). The proposed arrangement not only drastically improves power quality indices (PQI) but also reduces HPQC capacity by as much as 23%. Since the hybrid structure has a lower capacity and higher performance than the conventional one, it may be a viable option for achieving power quality targets in electric rail networks. © 2022 IEEE.

关键词： Reactive power

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Multi-Objective DER Planning Framework as a TEP Alternative: An Augmented Epsilon-Constraint Approach

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IEEE Transactions on Industry Applications 2025年

作者： Saber, Hossein Ranjbar, Hossein Mazaheri, Hesam Sharif University of Technology Center of Excellence in Power System Control and Management Electrical Engineering Department Tehran11365-11155 Iran University of Adelaide School of Electrical and Mechanical Engineering Adelaide Australia Texas A&M University Department of Electrical and Computer Engineering College StationTX United States

Recently, the construction of new transmission lines has faced extreme challenges due to ever-increasing environmental concerns and construction costs. Investing in distributed energy resources (DERs) offers a viable alternative to reduce reliance on new transmission lines. This study introduces a multi-objective bi-level DER planning model as an alternative to transmission network reinforcement. The upper-level problem aims to minimize the total cost of DERs, mitigate the congestion cost of the transmission network, and improve the system reliability while ensuring the profitability of the DER investment. In the lower-level problem, the wholesale electricity market is cleared to determine the optimal locational marginal prices and the operational status of the bulk power system. A scenario-based approach is employed to account for uncertainties in future loads, renewable generation, and generator bid prices. The bi-level problem is reformulated as a single-level optimization using the strong duality condition, with non-linear terms linearized through the big-M method and complementary slackness conditions. The augmented epsilon-constraint method is then employed to solve the multi-objective optimization problem. Finally, the effectiveness and applicability of the proposed DER planning model are evaluated using the IEEE 24-bus test system, offering insights from both system operators and DER investors. © 1972-2012 IEEE.

关键词： Multiobjective optimization

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Vulnerability of EV Charging Stations to Cyber Attacks Manipulating Prices

Vulnerability of EV Charging Stations to Cyber Attacks Manip...

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Future Energy Solutions (FES), International Conference on

作者： Amirhossein Akbarian Mahdi Bahrami Mehdi Vakilian Matti Lehtonen Electrical Engineering Department Center of Excellence in Power System Management and Control Sharif University of Technology Tehran Iran Department of Electrical Engineering and Automation Aalto University Espoo Finland

Electric vehicles (EVs) have experienced an unprecedented increase in their penetration; in well developed countries; due to the advancement of battery technology and the need to make transportation more environmentally friendly. As a result of this trend, EVs have become an integral part of those countries power grid ecosystem, where they may be used as both a source, and a consumer of energy. However, cybersecurity risks associated with large fleets of EVs within the power grids can significantly impact the normal operation of distribution systems. This paper considers the cyber-attack consequences, from attackers’ perspective. The cyber attackers under study target the charging price (CP) by increasing the CP in off-peak hours and accordingly subsiding it in on-peak hours. A two-stage optimization framework is proposed to identify the most important ultra-fast charging stations (XFCs) under the cyber-attack, meanwhile, the EV users’ response to the compromised CP is considered. Then, the proposed model is implemented on a modified IEEE 123-bus distribution test system, and the effectiveness of the model is proved through some case studies. In particular, they demonstrated that the amount of load shedding is increased by 8.198 MW when the EV user response is taken into account.

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Data-Driven Adequacy and Security Assessment: Machine Learning Trends for Reliable Smart Energy Networks

Data-Driven Adequacy and Security Assessment: Machine Learni...

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Smart Grid Conference (SGC)

作者： Mohammad Mohsen Hayati Hassan Majidi Hossein Shahinzadeh Mehdi Abapour Mahmud Fotuhi-Firuzabad Gevork B. Gharehpetian Faculty of Electrical and Computer Engineering Energy Systems Research Institute (ESRI) University of Tabriz Tabriz Iran Department of Electrical Engineering Amirkabir University of Technology Tehran Iran Center of Excellence in Power System Management and Control (CEPSMC) Sharif University of Technology Tehran Iran

ISBN: (数字)9798331511333

ISBN: (纸本)9798331511340

Smart energy networks (SENs) face numerous challenges related to security, reliability, operational uncertainties, and increasing penetration of renewable energies (REs), necessitating advanced methodologies for adequacy and security assessment. This study delves into the utilization of machine learning-driven approaches (MLDAs) to quantify reliability and gauge the dependability of future sustainable SENs. By autonomously acquiring knowledge from datasets, MLDAs offer swift and reliable evaluations, surpassing traditional methodologies. The integration of artificial intelligence (AI) in enhancing power system reliability is highlighted, emphasizing the importance of extensive datasets and evolving AI algorithms. Data-driven approaches empower energy network operators to proactively identify and mitigate security risks, enhancing the reliability of critical infrastructure systems. The research underscores the significance of constructing reliable databases, addressing challenges in real-time operations, and ensuring the performance and trustworthiness of machine learning (ML) algorithms. Overall, the study showcases the potential of ML techniques in revolutionizing reliability management and risk assessment in smart energy networks, paving the way for sustainable and reliable power systems.

关键词： Uncertainty Machine learning algorithms Databases Machine learning power system reliability Smart grids management Reliability Security Risk management

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Integrated Dual Static Var Compensators to Reduce Railway power Quality Conditioner Volt-ampere Rating in Co-phase V/v Traction system

Integrated Dual Static Var Compensators to Reduce Railway Po...

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power Electronic and Drive systems and Technologies Conference (PEDSTC)

作者： Mohammad Habibolahzadeh Alireza Jalilian Department of Electrical Engineering Iran University of Science and Technology Tehran Iran Department of Electrical Engineering Centre of Excellence for Power System Automation and Operation Iran University of Science and Technology Tehran Iran

This paper proposes a V/v co-phase supply system structure consisting of dual Static Var Compensators (SVCs) connected in parallel with a Railway static power Quality Conditioner (RPC). Dual SVCs play a crucial function in this configuration by compensating load and grid reactive powers, while the role of the RPC is limited to balancing active currents through the two output phases of the V/v transformer. Analysis of the RPC operating region shows that the RPC's compensation currents and dc-link voltage are more modest than those of the conventional design. Also included is a theoretical approach to matching converter output impedances. The comprehensive equations of the PQ instantaneous power theory are given, which are used in either present or traditional schemes. This design eliminates the need for passive filters by providing a control system specifically for suppressing harmonics caused by loads and SVCs. The RPC volt-ampere rating is also affected by load power factors, which may be lowered to as high as 43%. Therefore, the affordable design raises RPC adoption.

关键词： Reactive power Passive filters Impedance matching power quality Harmonic analysis Transformers Rail transportation

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Utilizing Balanced and Unbalanced Partial Techniques in Co-Phase V/v Railway system for Improving Hybrid SVC power Quality Conditioner

Utilizing Balanced and Unbalanced Partial Techniques in Co-P...

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Recent Advances and Innovations in engineering (ICRAIE)

关键词： Reactive power Technological innovation power quality Static VAr compensators Harmonic analysis Transformers Hybrid power systems

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Deep Learning-based Fire Alarmer for Underground power Cable Tunnel with Multiple Information Sources

Deep Learning-based Fire Alarmer for Underground Power Cable...

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International Conference on Intelligent systems Applications to power systems (ISAP)

作者： Jinshuo Jia Zhengwen Huang Yuhang Xia Guoquan Li Yujie Zhang Laurentiu Lipan Ioana Pisica School of Communications and Information Engineering Chongqing University of Posts and Telecommunications Chongqing China Theme of System Optimization BRUNEL-CQUPT Innovation Centre Chongqing China Department of Electronic and Electrical Engineering Brunel University London U.K Engineering Project Management Center Chengdu Power Supply Company of Sichuan Electric Power Company Chengdu China Department of Electric Power Systems University Politehnica of Bucharest Bucharest Romania

ISBN: (数字)9798331531751

ISBN: (纸本)9798331531768

Regarding the issue of risk management and control of tunnel cable fires, a cable fire management and control scheme based on Gene Expression Programming (GEP) has been proposed. This scheme comprises three stages: firstly, a cable skin temperature rise model based on load variations has been established; secondly, a cable fire monitoring model based on YOLOv5 has been trained; and finally, a cable fire management and control scheme that integrates GEP has been proposed. Through the fusion analysis of data from the first two stages, the dynamic adjustment of the weight output of different parts is achieved to achieve automatic recognition of optimal states. Through experiments and analysis, the temperature variation patterns of cables under various loads and environmental conditions have been demonstrated, as well as the recognition performance of the fire monitoring model based on YOLOv5, and a dynamic planning scheme for the GEP model has been provided.

关键词： Adaptation models Analytical models Temperature distribution power cables Computational modeling Predictive models Skin Data models Monitoring Load modeling

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