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Over the last century, energy storage systems (ESSs) have continued to evolve and adapt to changing energy requirements and technological advances.Energy Storage in Power Systems describes the essential principles needed to understand the role of ESSs in modern electrical power systems, highlighting their application for the grid integration of.

A unique combination of theoretical knowledge and practical analysis experience Derived from Yoshihide Hase's Handbook of Power Systems Engineering, 2nd Edition, this book provides readers with everything they need to know about power system dynamics. Presented in three parts, it covers power system theories, computation theories, and how prevailed engineering platforms can be utilized for various engineering works. It features many illustrations based on ETAP to help explain the knowledge within as much as possible.  Recompiling all the chapters from the previous book, Power System Dynamics with Computer Based Modeling and Analysis offers nineteen new and improved content with updated information and all new topics, including two new chapters on circuit analysis which help engineers with non-electrical engineering backgrounds. Topics covered include: Essentials of Electromagnetism; Complex Number Notation (Symbolic Method) and Laplace-transform; Fault Analysis Based on Symmetrical Components; Synchronous Generators; Induction-motor; Transformer; Breaker; Arrester; Overhead-line; Power cable; Steady-State/Transient/Dynamic Stability; Control governor; AVR; Directional Distance Relay and R-X Diagram; Lightning and Switching Surge Phenomena; Insulation Coordination; Harmonics; Power Electronics Applications (Devices, PE-circuit and Control) and more.  * Combines computer modeling of power systems, including analysis techniques, from an engineering consultant's perspective * Uses practical analytical software to help teach how to obtain the relevant data, formulate 'what-if' cases, and convert data analysis into meaningful information * Includes mathematical details of power system analysis and power system dynamics Power System Dynamics with Computer-Based Modeling and Analysis will appeal to all power system engineers as well as engineering and electrical engineering students.

In smart power systems, information and communication technologies are being broadly installed and two-way communications are being established more effectively and efficiently. However, they are vulnerable to cyber-physical interactive threats and their impact depends on the system infrastructure, degree of interaction, degree of vulnerability, and the intensity and the frequency of the attack. The study addresses this problem and proposes: (i) an innovative Markov-chain based framework of the cyber-intrusion process to implement operating conditions in a smart power system; (ii) an advanced algorithm for power system reliability assessment, incorporating cyber-intrusion process and a detailed model of a heat pump system; and (iii) a new impact assessment framework for different cyber-intrusion detection-time distributions driven by Monte Carlo simulation. The cyber-detection and system recovery process with the presence of cyber-physical interactive operation models suggest that a significant level of impacts could be generated by the interactive operation of the smart power system and a quantitative assessment is needed in order to assess true impacts.

Electricity plays a crucial role in the well-being of humans and is a determining factor of the economic development of a country. Electricity issues have encouraged researchers to focus on improving power availability and quality along with reliability. This pursuit has increasingly raised the intention to integrate renewable energy (RE) into power systems to curb the problem of energy deficiency. However, intermittency in the sources of RE supply coupled with fluctuating changes in demand with respect to time has induced high risk in maintaining system reliability in terms of providing adequate supply to consumers. Whilst an energy storage system (ESS) is not another source of electricity, it is proven to be effective and viable in solving the aforementioned issues. Thus, this paper comprehensively reviews the development of ESS technologies and discusses the benefits and real-life applications of these technologies. The concept of reliability in power systems is also explored to provide an improved understanding of this study. Lastly, notable studies that have addressed the reliability impact of ESSs on power systems are discussed. This review paper therefore is expected to provide a critical analysis of ESS developments, as well as recognize their research gaps in terms of reliability studies in modern RE-integrated power networks.

The exponential rise of electric vehicles (EVs) is transforming the global automobile industry, driving a shift towards greater cleanliness and environmental sustainability. EV charging stations (EVCSs) play a pivotal role in this massive transition towards EVs, where accurate forecasting of EVCS demand is crucial for seamlessly integrating EVs into existing power grids. Most of the existing research mainly concentrates on univariate forecasting, neglecting the multiple factors influencing EVCS demand. Hence, this study offers a comparative analysis of different algorithms for univariate forecasting and multivariate forecasting, where the multivariate scheme incorporates metadata such as charging time, greenhouse gas savings, and gasoline savings. The experimental results indicate the superiority of the multivariate scheme over the univariate forecasting. For multivariate forecasting, the gated recurrent unit (GRU) has outperformed other models such as categorical boosting (Catboost), recurrent neural network (RNN), long short‐term memory (LSTM), extreme gradient boosting (XGBoost), random forest, convolutional neural network (CNN), CNN + LSTM, and LSTM + LSTM. The results of this study emphasize the significance of using the GRU model for multivariate forecasting with metadata during normal and noisy scenarios to yield more reliable and accurate predictions. This approach enhances decision‐making, policy development, and efficient grid integration in the growing EV sector. This work presents a comparative analysis to highlight the superiority of the multivariate scheme over the univariate scheme in forecasting electric vehicle charging station demand. Also, a comparative analysis of several machine learning models is presented to select the optimum method under normal and data abnormality cases.

Research has found an extensive potential for utilizing energy storage within the power system sector to improve reliability. This study aims to provide a critical and systematic review of the reliability impacts of energy storage systems in this sector. The systematic literature review (SLR) is based on peer-reviewed papers published between 1996 and early 2018. Firstly, findings reveal that energy storage utilization in power systems is significant in improving system reliability and minimizing costs of transmission upgrades. Secondly, introduction of policies to shift from the use of fossil fuels to that of renewable energy positively affects energy storage system development. Thirdly, North America is an early pioneer of power system reliability and energy storage system studies. However, Asia has recently taken over the role, with China being the main driver. Research gaps within this field are also identified. This review can serve as basis for scholars in advancing the theoretical understanding of the reliability impacts of energy storage systems and in addressing the gaps within this field.

Ecuador’s power system has experienced a significant decline in reliability due to its strong reliance on hydroelectric generation, which constituted 67.4% of the national energy mix in 2024. The severe drought of 2023–2024 severely diminished generation capacity, exposing critical vulnerabilities in the National Interconnected System. Under actual operating conditions, the system recorded a loss of load expectation (LOLE) of 91 days per year in 2024. Projections indicate that, without urgent corrective actions, energy deficits could exceed 250 days per year by 2029. Addressing these challenges demands a diversification of the energy matrix, integrating flexible generation sources, energy storage systems, and expanded deployment of solar and wind technologies. Achieving international reliability benchmarks (LOLE ≤ 0.1 days/year) will be essential to ensuring a secure and resilient electricity supply. This study underscores that, without strategic intervention, Ecuador may face prolonged energy crises, offering a cautionary outlook for power systems heavily dependent on climate-sensitive resources.

Short‐circuit (SC) current poses a significant threat to power system stability. A fault current limiter (FCL) serves as an effective tool for restricting fault currents. This review article aims to explore the impact of FCLs on power system reliability. To achieve this, it examines existing studies on the influence of FCLs on the reliability of various systems, including substations and distribution networks. It highlights research gaps and challenges within this domain. Based on the identified gaps, it offers recommendations for future research to scholars. This review article provides a solid foundation for researchers engaged in the FCL domain and the reliability of power systems. This article provides a literature review of the effect of FCLs on the reliability of various systems (such as substations and distribution systems) for the first time. It identifies research gaps and challenges in this field. According to identified gaps, it provides suggestions for future works to the researchers.