Universal Smart Grid Agent For Distributed Power Generation Management
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| Author | : Eric MSP Veith |
| Publisher | : Logos Verlag Berlin GmbH |
| Total Pages | : 268 |
| Release | : 2017 |
| Genre | : Computers |
| ISBN | : 3832545123 |
"Somewhere, there is always wind blowing or the sun shining." This maxim could lead the global shift from fossil to renewable energy sources, suggesting that there is enough energy available to be turned into electricity. But the already impressive numbers that are available today, along with the European Union's 20-20-20 goal – to power 20% of the EU energy consumption from renewables until 2020 –, might mislead us over the problem that the go-to renewables readily available rely on a primary energy source mankind cannot control: the weather. At the same time, the notion of the smart grid introduces a vast array of new data coming from sensors in the power grid, at wind farms, power plants, transformers, and consumers. The new wealth of information might seem overwhelming, but can help to manage the different actors in the power grid. This book proposes to view the problem of power generation and distribution in the face of increased volatility as a problem of information distribution and processing. It enhances the power grid by turning its nodes into agents that forecast their local power balance from historical data, using artificial neural networks and the multi-part evolutionary training algorithm described in this book. They pro-actively communicate power demand and supply, adhering to a set of behavioral rules this book defines, and finally solve the 0-1 knapsack problem of choosing offers in such a way that not only solves the disequilibrium, but also minimizes line loss, by elegant modeling in the Boolean domain. The book shows that the Divide-et-Impera approach of a distributed grid control can lead to an efficient, reliable integration of volatile renewable energy sources into the power grid.
| Author | : Eric Msp Veith |
| Publisher | : |
| Total Pages | : 268 |
| Release | : 2017 |
| Genre | : |
| ISBN | : 9783832592233 |
| Author | : Xin Ning |
| Publisher | : Frontiers Media SA |
| Total Pages | : 273 |
| Release | : 2023-11-23 |
| Genre | : Technology & Engineering |
| ISBN | : 2832539564 |
Smart grid (SG) is considered a form of intelligent system that allows the electric grid to perform its functions efficiently. The SG is a network that allows for the flow of electrical energy and data, where the data is used to make intelligent decisions in the operation of the electric grid. Artificial intelligence (AI) techniques, such as expert system (ES), Machine Learning (ML), and deep Learning (DL) have brought an advancing frontier in power electronics and power engineering with their powerful data processing capabilities. The SG relies on the flow of data to make its intelligent control; therefore, AI technology is a perfect fit for the SG. The application of AI technology in the SG has the potential to improve the intelligence of the SG. This research topic is focused on ways of improving the data analysis and control of SG by leveraging technologies. Manuscripts with the progress made in solving a range of miscellaneous and critical problems in SG by leveraging AI methods such as ES, ML, and DL methods are welcome. Reviews and original research that describe the latest developments in this field are considered for publication in this research topic. The scope of this Research Topic will include the following themes, but are not limited to: 1. Data-driven and artificial intelligence approaches to enhancing flexibility and resilience of SG. 2. Expert system, Machine Learning and Deep Learning, reinforcement learning and transfer learning for applications in SG. 3. AI for development in ensuring high reliability and stability of electric power system with high penetration of renewable energy. 4. AI for studies in operation protection, integrated planning, and control of SG systems. 5. AI for development in diagnostics and diagnostics for SG. 6. Health monitoring of a modern wind generation system using an adaptive neuro-fuzzy system. 7. Space vector fault pattern identification of a smart grid subsystem by neural mapping. 8. Control techniques, mathematical programming methods, optimization techniques and metaheuristics applied in SG. 9. AI and optimization techniques for green energy and carbon footprint. 10. Novel applications of AI-based smart grids in smart cities, smart transportation, smart healthcare, and smart manufacturing.
| Author | : Andreas Holzinger |
| Publisher | : Springer Nature |
| Total Pages | : 552 |
| Release | : 2020-08-19 |
| Genre | : Computers |
| ISBN | : 3030573214 |
This book constitutes the refereed proceedings of the 4th IFIP TC 5, TC 12, WG 8.4, WG 8.9, WG 12.9 International Cross-Domain Conference, CD-MAKE 2020, held in Dublin, Ireland, in August 2020. The 30 revised full papers presented were carefully reviewed and selected from 140 submissions. The cross-domain integration and appraisal of different fields provides an atmosphere to foster different perspectives and opinions; it will offer a platform for novel ideas and a fresh look on the methodologies to put these ideas into business for the benefit of humanity. Due to the Corona pandemic CD-MAKE 2020 was held as a virtual event.
| Author | : Jia Hu |
| Publisher | : Springer |
| Total Pages | : 242 |
| Release | : 2016-11-12 |
| Genre | : Computers |
| ISBN | : 3319477293 |
This book constitutes the post-conference proceedings of the First International Conference on Smart Grid Inspired Future Technologies, SmartGIFT 2016, held in May 2016 in Liverpool, UK. Smart grid is the next generation electric grid that enables efficient, intelligent, and economical power generation, transmission, and distribution. The 25 revised full papers presented were reviewed and selected from 36 submissions. The papers cover technical topics such as high-level ideology and methodology, concrete smart grid inspired data sensing, processing, and networking technologies, smart grid system architecture, Quality of Service (QoS), energy efficiency, security in smart grid systems, management of smart grid systems, service engineering and algorithm design, and real-world deployment experiences.
| Author | : Youn-Hee Han |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 864 |
| Release | : 2012-11-28 |
| Genre | : Technology & Engineering |
| ISBN | : 940075857X |
Recent advances in electronic and computer technologies have paved the way for the proliferation of ubiquitous computing and innovative applications that incorporate these technologies. This proceedings book describes these new and innovative technologies, and covers topics like Ubiquitous Communication and Networks, Security Systems, Smart Devices and Applications, Cloud and Grid Systems, Service-oriented and Web Service Computing, Embedded Hardware and Image Processing and Multimedia.
| Author | : Takeshi Hatanaka |
| Publisher | : Springer Nature |
| Total Pages | : 347 |
| Release | : 2020-04-21 |
| Genre | : Business & Economics |
| ISBN | : 9811535760 |
This book gathers contributions from a multidisciplinary research team comprised of control engineering and economics researchers and formed to address a central interdisciplinary social issue, namely economically enabled energy management. The book’s primary focus is on achieving optimal energy management that is viable from both an engineering and economic standpoint. In addition to the theoretical results and techniques presented, several chapters highlight experimental case studies, which will benefit academic researchers and practitioners alike. The first three chapters present comprehensive overviews of respective social contexts, underscore the pressing need for economically efficient energy management systems and academic work on this emerging research topic, and identify fundamental differences between approaches in control engineering and economics. In turn, the next three chapters (Chapters 4–6) provide economics-oriented approaches to the subject. The following five chapters (Chapters 7–11) address optimal energy market design, integrating both physical and economic models. The book’s last three chapters (Chapters 12–14) mainly focus on the engineering aspects of next-generation energy management, though economic factors are also shown to play important roles.
| Author | : OECD |
| Publisher | : OECD Publishing |
| Total Pages | : 133 |
| Release | : 2021-10-27 |
| Genre | : |
| ISBN | : 9264481109 |
As “market referees”, regulators contribute to the delivery of essential public utilities. Their organisational culture, behaviour, actions and governance are important factors in how they, and the sectors they oversee, perform.
| Author | : Przemysław Różewski |
| Publisher | : Springer |
| Total Pages | : 273 |
| Release | : 2015-10-26 |
| Genre | : Technology & Engineering |
| ISBN | : 3319233386 |
This book demonstrates how to apply modern approaches to complex system control in practical applications involving knowledge-based systems. The dimensions of knowledge-based systems are extended by incorporating new perspectives from control theory, multimodal systems and simulation methods. The book is divided into three parts: theory, production system and information system applications. One of its main focuses is on an agent-based approach to complex system analysis. Moreover, specialised forms of knowledge-based systems (like e-learning, social network, and production systems) are introduced with a new formal approach to knowledge system modelling. The book, which offers a valuable resource for researchers engaged in complex system analysis, is the result of a unique cooperation between scientists from applied computer science (mainly from Poland) and leading system control theory researchers from the Russian Academy of Sciences’ Trapeznikov Institute of Control Sciences.
| Author | : Kaile Zhou |
| Publisher | : Springer Nature |
| Total Pages | : 317 |
| Release | : 2022-02-04 |
| Genre | : Business & Economics |
| ISBN | : 9811693609 |
This book provides a relatively whole view of data-driven decision-making methods for energy service innovation and energy system optimization. Through personalized energy services provision and energy efficiency improvement, the book can contribute to the green transformation of energy system and the sustainable development of the society. The book gives a new way to achieve smart energy management, based on various data mining and machine learning methods, including fuzzy clustering, shape-based clustering, ensemble clustering, deep learning, and reinforcement learning. The applications of these data-driven methods in improving energy efficiency and supporting energy service innovation are presented. Moreover, this book also investigates the role of blockchain in supporting peer-to-peer (P2P) electricity trading innovation, thus supporting smart energy management. The general scope of this book mainly includes load clustering, load forecasting, price-based demand response, incentive-based demand response, and energy blockchain-based electricity trading. The intended readership of the book includes researchers and engineers in related areas, graduate and undergraduate students in university, and some other general interested audience. The important features of the book are: (1) it introduces various data-driven methods for achieving different smart energy management tasks; (2) it investigates the role of data-driven methods in supporting various energy service innovation; and (3) it explores energy blockchain in P2P electricity trading, and thus supporting smart energy management.
