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This book examines real-time models and advanced online applications that enhance reliability and resilience of the grid in real-time and near real-time environments. It is written by Peak Reliability engineers who worked on the creation of the West Wide System Model (WSM) and the implementation of advanced real-time operation situational awareness tools for reliability coordination function. The book looks at how a single Reliability Coordinator for the Western Interconnection did its work under normal and emergency conditions, providing a unique perspective on best practices and lessons learned from Peak’s modeling and coordination efforts to create, maintain, and improve state-of-art new technology and algorithms to improve real-time operation situational awareness and Bulk Electric System (BES) grid resilience. Coverage includes practical experience of implementing real-time Energy Management System (EMS) Network Application, real-time voltage stability analysis, online transient stability analysis, synchrophasor technology, Dispatcher Training Simulator and EMS Cybersecurity & Inter-Control Center Communications Protocol (ICCP) implementation experience in a Reliability Coordinator Control Room setting. Explains how to operate a “green” grid and prevent new blackouts against uncertain operation conditions; Written by Peak Reliability engineers who worked on the creation of the West Wide System Model (WWSM); All material verified in practical system operations, or validated by real system measures and system events.
The importance of power system reliability is demonstrated when our electricity supply is disrupted, whether it decreases the comfort of our free time at home or causes the shutdown of our companies and results in huge economic deficits. The objective of Assessment of Power System Reliability is to contribute to the improvement of power system reliability. It consists of six parts divided into twenty chapters. The first part introduces the important background issues that affect power system reliability. The second part presents the reliability methods that are used for analyses of technical systems and processes. The third part discusses power flow analysis methods, because the dynamic aspect of a power system is an important part of related reliability assessments. The fourth part explores various aspects of the reliability assessment of power systems and their parts. The fifth part covers optimization methods. The sixth part looks at the application of reliability and optimization methods. Assessment of Power System Reliability has been written in straightforward language that continues into the mathematical representation of the methods. Power engineers and developers will appreciate the emphasis on practical usage, while researchers and advanced students will benefit from the simple examples that can facilitate their understanding of the theory behind power system reliability and that outline the procedure for application of the presented methods.
The main aims of power electronic converter systems (PECS) are to control, convert, and condition electrical power flow from one form to another through the use of solid state electronics. This book outlines current research into the scientific modeling, experimentation, and remedial measures for advancing the reliability, availability, system robustness, and maintainability of PECS at different levels of complexity.
The advancement of sustainable energy is becoming an important concern for many countries. The traditional electrical grid supports only one-way interaction of power being delivered to the consumers. The emergence of improved sensors, actuators, and automation technologies has consequently improved the control, monitoring and communication techniques within the energy sector, including the Smart Grid system. With the support of the aforementioned modern technologies, the information flows in two-ways between the consumer and supplier. This data communication helps the supplier in overcoming challenges like integration of renewable technologies, management of energy demand, load automation and control. Renewable energy (RE) is intermittent in nature and therefore difficult to predict. The accurate RE forecasting is very essential to improve the power system operations. The forecasting models are based on complex function combinations that include seasonality, fluctuation, and dynamic nonlinearity. The advanced intelligent computing algorithms for forecasting should consider the proper parameter determinations for achieving optimization. For this we need, new generation research areas like Machine learning (ML), and Artificial Intelligence (AI) to enable the efficient integration of distributed and renewable generation at large scale and at all voltage levels. The modern research in the above areas will improve the efficiency, reliability and sustainability in the Smart grid.