Intelligent Automatic Generation Control

Intelligent Automatic Generation Control
Author: Hassan Bevrani
Publisher: CRC Press
Total Pages: 308
Release: 2017-12-19
Genre: Technology & Engineering
ISBN: 1439849544

Automatic generation control (AGC) is one of the most important control problems in the design and operation of interconnected power systems. Its significance continues to grow as a result of several factors: the changing structure and increasing size, complexity, and functionality of power systems, the rapid emergence (and uncertainty) of renewable energy sources, developments in power generation/consumption technologies, and environmental constraints. Delving into the fundamentals of power system AGC, Intelligent Automatic Generation Control explores ways to make the infrastructures of tomorrow smarter and more flexible. These frameworks must be able to handle complex multi-objective regulation optimization problems, and they must be highly diversified in terms of policies, control strategies, and wide distribution in demand and supply sources—all via an intelligent scheme. The core of such intelligent systems should be based on efficient, adaptable algorithms, advanced information technology, and fast communication devices to ensure that the AGC systems can maintain generation-load balance following serious disturbances. This book addresses several new schemes using intelligent control techniques for simultaneous minimization of system frequency deviation and tie-line power changes, which is required for successful operation of interconnected power systems. It also concentrates on physical and engineering aspects and examines several developed control strategies using real-time simulations. This reference will prove useful for engineers and operators in power system planning and operation, as well as academic researchers and students in field of electrical engineering.

Artificial Intelligence in Industrial Decision Making, Control and Automation

Artificial Intelligence in Industrial Decision Making, Control and Automation
Author: S.G. Tzafestas
Publisher: Springer Science & Business Media
Total Pages: 778
Release: 2012-12-06
Genre: Computers
ISBN: 9401103054

This book is concerned with Artificial Intelligence (AI) concepts and techniques as applied to industrial decision making, control and automation problems. The field of AI has been expanded enormously during the last years due to that solid theoretical and application results have accumulated. During the first stage of AI development most workers in the field were content with illustrations showing ideas at work on simple problems. Later, as the field matured, emphasis was turned to demonstrations that showed the capability of AI techniques to handle problems of practical value. Now, we arrived at the stage where researchers and practitioners are actually building AI systems that face real-world and industrial problems. This volume provides a set of twenty four well-selected contributions that deal with the application of AI to such real-life and industrial problems. These contributions are grouped and presented in five parts as follows: Part 1: General Issues Part 2: Intelligent Systems Part 3: Neural Networks in Modelling, Control and Scheduling Part 4: System Diagnostics Part 5: Industrial Robotic, Manufacturing and Organizational Systems Part 1 involves four chapters providing background material and dealing with general issues such as the conceptual integration of qualitative and quantitative models, the treatment of timing problems at system integration, and the investigation of correct reasoning in interactive man-robot systems.

Applications of Computing, Automation and Wireless Systems in Electrical Engineering

Applications of Computing, Automation and Wireless Systems in Electrical Engineering
Author: Sukumar Mishra
Publisher: Springer
Total Pages: 1260
Release: 2019-05-31
Genre: Technology & Engineering
ISBN: 9811367728

This book discusses key concepts, challenges and potential solutions in connection with established and emerging topics in advanced computing, renewable energy and network communications. Gathering edited papers presented at MARC 2018 on July 19, 2018, it will help researchers pursue and promote advanced research in the fields of electrical engineering, communication, computing and manufacturing.

Computational Intelligence in Pattern Recognition

Computational Intelligence in Pattern Recognition
Author: Asit Kumar Das
Publisher: Springer
Total Pages: 1023
Release: 2019-08-17
Genre: Technology & Engineering
ISBN: 9811390428

This book presents practical development experiences in different areas of data analysis and pattern recognition, focusing on soft computing technologies, clustering and classification algorithms, rough set and fuzzy set theory, evolutionary computations, neural science and neural network systems, image processing, combinatorial pattern matching, social network analysis, audio and video data analysis, data mining in dynamic environments, bioinformatics, hybrid computing, big data analytics and deep learning. It also provides innovative solutions to the challenges in these areas and discusses recent developments.

Methods and Applications of Intelligent Control

Methods and Applications of Intelligent Control
Author: S.G. Tzafestas
Publisher: Springer Science & Business Media
Total Pages: 573
Release: 2012-12-06
Genre: Technology & Engineering
ISBN: 9401154988

This book is concerned with Intelligent Control methods and applications. The field of intelligent control has been expanded very much during the recent years and a solid body of theoretical and practical results are now available. These results have been obtained through the synergetic fusion of concepts and techniques from a variety of fields such as automatic control, systems science, computer science, neurophysiology and operational research. Intelligent control systems have to perform anthropomorphic tasks fully autonomously or interactively with the human under known or unknown and uncertain environmental conditions. Therefore the basic components of any intelligent control system include cognition, perception, learning, sensing, planning, numeric and symbolic processing, fault detection/repair, reaction, and control action. These components must be linked in a systematic, synergetic and efficient way. Predecessors of intelligent control are adaptive control, self-organizing control, and learning control which are well documented in the literature. Typical application examples of intelligent controls are intelligent robotic systems, intelligent manufacturing systems, intelligent medical systems, and intelligent space teleoperators. Intelligent controllers must employ both quantitative and qualitative information and must be able to cope with severe temporal and spatial variations, in addition to the fundamental task of achieving the desired transient and steady-state performance. Of course the level of intelligence required in each particular application is a matter of discussion between the designers and users. The current literature on intelligent control is increasing, but the information is still available in a sparse and disorganized way.

Sustainable Developments by Artificial Intelligence and Machine Learning for Renewable Energies

Sustainable Developments by Artificial Intelligence and Machine Learning for Renewable Energies
Author: Krishna Kumar
Publisher: Academic Press
Total Pages: 418
Release: 2022-03-18
Genre: Science
ISBN: 0323914284

Sustainable Developments by Artificial Intelligence and Machine Learning for Renewable Energies analyzes the changes in this energy generation shift, including issues of grid stability with variability in renewable energy vs. traditional baseload energy generation. Providing solutions to current critical environmental, economic and social issues, this book comprises various complex nonlinear interactions among different parameters to drive the integration of renewable energy into the grid. It considers how artificial intelligence and machine learning techniques are being developed to produce more reliable energy generation to optimize system performance and provide sustainable development. As the use of artificial intelligence to revolutionize the energy market and harness the potential of renewable energy is essential, this reference provides practical guidance on the application of renewable energy with AI, along with machine learning techniques and capabilities in design, modeling and for forecasting performance predictions for the optimization of renewable energy systems. It is targeted at researchers, academicians and industry professionals working in the field of renewable energy, AI, machine learning, grid Stability and energy generation. Covers the best-performing methods and approaches for designing renewable energy systems with AI integration in a real-time environment Gives advanced techniques for monitoring current technologies and how to efficiently utilize the energy grid spectrum Addresses the advanced field of renewable generation, from research, impact and idea development of new applications

PowerFactory Applications for Power System Analysis

PowerFactory Applications for Power System Analysis
Author: Francisco M. Gonzalez-Longatt
Publisher: Springer
Total Pages: 496
Release: 2014-12-27
Genre: Computers
ISBN: 3319129589

This book presents a comprehensive set of guidelines and applications of DIgSILENT PowerFactory, an advanced power system simulation software package, for different types of power systems studies. Written by specialists in the field, it combines expertise and years of experience in the use of DIgSILENT PowerFactory with a deep understanding of power systems analysis. These complementary approaches therefore provide a fresh perspective on how to model, simulate and analyse power systems. It presents methodological approaches for modelling of system components, including both classical and non-conventional devices used in generation, transmission and distribution systems, discussing relevant assumptions and implications on performance assessment. This background is complemented with several guidelines for advanced use of DSL and DPL languages as well as for interfacing with other software packages, which is of great value for creating and performing different types of steady-state and dynamic performance simulation analysis. All employed test case studies are provided as supporting material to the reader to ease recreation of all examples presented in the book as well as to facilitate their use in other cases related to planning and operation studies. Providing an invaluable resource for the formal instruction of power system undergraduate/postgraduate students, this book is also a useful reference for engineers working in power system operation and planning.

Emerging Trends in Electrical, Communications, and Information Technologies

Emerging Trends in Electrical, Communications, and Information Technologies
Author: T. Hitendra Sarma
Publisher: Springer Nature
Total Pages: 774
Release: 2019-09-24
Genre: Technology & Engineering
ISBN: 981138942X

This book includes original, peer-reviewed research from the 3rd International Conference on Emerging Trends in Electrical, Communication and Information Technologies (ICECIT 2018), held at Srinivasa Ramanujan Institute of Technology, Ananthapuramu, Andhra Pradesh, India in December 2018. It covers the latest research trends and developments in the areas of Electrical Engineering, Electronic and Communication Engineering, and Computer Science and Information.

Data-Intensive Computing in Smart Microgrids

Data-Intensive Computing in Smart Microgrids
Author: Herodotos Herodotou
Publisher: MDPI
Total Pages: 238
Release: 2021-09-06
Genre: Technology & Engineering
ISBN: 3036516271

Microgrids have recently emerged as the building block of a smart grid, combining distributed renewable energy sources, energy storage devices, and load management in order to improve power system reliability, enhance sustainable development, and reduce carbon emissions. At the same time, rapid advancements in sensor and metering technologies, wireless and network communication, as well as cloud and fog computing are leading to the collection and accumulation of large amounts of data (e.g., device status data, energy generation data, consumption data). The application of big data analysis techniques (e.g., forecasting, classification, clustering) on such data can optimize the power generation and operation in real time by accurately predicting electricity demands, discovering electricity consumption patterns, and developing dynamic pricing mechanisms. An efficient and intelligent analysis of the data will enable smart microgrids to detect and recover from failures quickly, respond to electricity demand swiftly, supply more reliable and economical energy, and enable customers to have more control over their energy use. Overall, data-intensive analytics can provide effective and efficient decision support for all of the producers, operators, customers, and regulators in smart microgrids, in order to achieve holistic smart energy management, including energy generation, transmission, distribution, and demand-side management. This book contains an assortment of relevant novel research contributions that provide real-world applications of data-intensive analytics in smart grids and contribute to the dissemination of new ideas in this area.

Nature Inspired Optimization for Electrical Power System

Nature Inspired Optimization for Electrical Power System
Author: Manjaree Pandit
Publisher: Springer Nature
Total Pages: 129
Release: 2020-04-07
Genre: Technology & Engineering
ISBN: 9811540047

This book presents a wide range of optimization methods and their applications to various electrical power system problems such as economical load dispatch, demand supply management in microgrids, levelized energy pricing, load frequency control and congestion management, and reactive power management in radial distribution systems. Problems related to electrical power systems are often highly complex due to the massive dimensions, nonlinearity, non-convexity and discontinuity associated with objective functions. These systems also have a large number of equality and inequality constraints, which give rise to optimization problems that are difficult to solve using classical numerical methods. In this regard, nature inspired optimization algorithms offer an effective alternative, due to their ease of use, population-based parallel search mechanism, non-dependence on the nature of the problem, and ability to accommodate non-differentiable, non-convex problems. The analytical model of nature inspired techniques mimics the natural behaviors and intelligence of life forms. These techniques are mainly based on evolution, swarm intelligence, ecology, human intelligence and physical science.