Risk Modeling Analysis And Control Of Multi Energy Systems
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Risk Modeling, Analysis and Control of Multi-energy Systems
This book focuses on the risk modeling, analysis and control of multi-energy systems considering cross-sectorial failure propagation. Both models and methods have been addressed with engineering practice. This is accomplished by doing a thorough investigation into the modeling of system physics and reliabilities in both long- and short-term phases. Different models and methods to evaluate the risk of multi-energy systems considering various disturbances, e.g., component failures, load uncertainties and extreme weather, are studied in detail. Furthermore, several risk control strategies for multi-energy systems, such as long-term capacity planning and integrated demand response, are analyzed in this book, which is especially suited for readers interested in system risk management. The book can benefit researchers, engineers, and graduate students in the fields of electrical and electronic engineering, energy engineering, complex network and control engineering, etc.
Energy Systems Integration for Multi-Energy Systems
Author: Carlos Ocampo-Martinez
language: en
Publisher: Springer Nature
Release Date: 2025-05-24
This book offers a comprehensive approach to energy systems integration (ESI) that optimizes the design and operation of energy systems, maximizing the benefits of all components while minimizing potential negative impacts. By coordinating the production, distribution, and utilization of energy from diverse sources, ESI ensures the most efficient and cost-effective fulfillment of end-users' needs. The true value of ESI lies in its ability to harmonize interconnected systems, enabling the production and supply of energy in its various forms to achieve reliability, environmental sustainability, and economic viability at appropriate scales. Through the analysis and design of integrated energy systems, often referred to as multi-energy systems (MES), decision-makers and industry professionals gain valuable insights into the optimal strategies required to fulfill these objectives while considering contextual conditions and operational constraints. The book explores the design, modeling, supervising, and controlling of energy systems but also examines how these approaches can be seamlessly integrated into future MES through innovative and ESI processes. Through its comprehensive analysis and forward-thinking approach, this book serves as a vital resource for researchers, practitioners, and policymakers seeking to navigate the complexities of energy systems integration and leverage the potential of renewable energy for a sustainable future.
Machine Learning for Energy Systems
This volume deals with recent advances in and applications of computational intelligence and advanced machine learning methods in power systems, heating and cooling systems, and gas transportation systems. The optimal coordinated dispatch of the multi-energy microgrids with renewable generation and storage control using advanced numerical methods is discussed. Forecasting models are designed for electrical insulator faults, the health of the battery, electrical insulator faults, wind speed and power, PV output power and transformer oil test parameters. The loads balance algorithm for an offshore wind farm is proposed. The information security problems in the energy internet are analyzed and attacked using information transmission contemporary models, based on blockchain technology. This book will be of interest, not only to electrical engineers, but also to applied mathematicians who are looking for novel challenging problems to focus on.