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This comprehensive open access book enables readers to discover the essential techniques for load forecasting in electricity networks, particularly for active distribution networks. From statistical methods to deep learning and probabilistic approaches, the book covers a wide range of techniques and includes real-world applications and a worked examples using actual electricity data (including an example implemented through shared code). Advanced topics for further research are also included, as well as a detailed appendix on where to find data and additional reading. As the smart grid and low carbon economy continue to evolve, the proper development of forecasting methods is vital. This book is a must-read for students, industry professionals, and anyone interested in forecasting for smart control applications, demand-side response, energy markets, and renewable utilization.
Containing 12 new chapters, this second edition offers increased coverage of weather correction and normalization of forecasts, anticipation of redevelopment, determining the validity of announced developments, and minimizing risk from over- or under-planning. It provides specific examples and detailed explanations of key points to consider for both standard and unusual utility forecasting situations, information on new algorithms and concepts in forecasting, a review of forecasting pitfalls and mistakes, case studies depicting challenging forecast environments, and load models illustrating various types of demand.
This book is a printed edition of the Special Issue "Short-Term Load Forecasting by Artificial Intelligent Technologies" that was published in Energies
Succinct and understandable, this book is a step-by-step guide to the mathematics and construction of electrical load forecasting models. Written by one of the world’s foremost experts on the subject, Electrical Load Forecasting provides a brief discussion of algorithms, their advantages and disadvantages and when they are best utilized. The book begins with a good description of the basic theory and models needed to truly understand how the models are prepared so that they are not just blindly plugging and chugging numbers. This is followed by a clear and rigorous exposition of the statistical techniques and algorithms such as regression, neural networks, fuzzy logic, and expert systems. The book is also supported by an online computer program that allows readers to construct, validate, and run short and long term models. Step-by-step guide to model construction Construct, verify, and run short and long term models Accurately evaluate load shape and pricing Creat regional specific electrical load models
Microgrid Protection and Control is the result of numerous research works and publications by R&D engineers and scientists of the Microgrid and Energy Internet Research Centre. Through the authors long-routed experience in the microgrid and energy internet industry, this book looks at the sophisticated protection and control issues connected to the special nature of microgrid. The book explains the different ways of classifying types of microgrids and common misconceptions, looking at industrial and research trends along with the different technical issues and challenges faced with deploying microgrid in various settings. Forecasting short-term demand and renewable generation for optimal operation is covered with techniques for accurate enhancement supported with practical application examples. With chapters on dynamic, transient and tertiary control and experimental and simulation tests this reference is useful for all those working in the research, engineering and application of microgrids and power distribution systems. Contains practical examples to support the research and experimental results on microgrid protection and control Includes detailed theories and referential algorithms Provides innovative solutions to technical issues in protection and control of microgrids
Short-term load forecasting (STLF) plays a key role in the formulation of economic, reliable, and secure operating strategies (planning, scheduling, maintenance, and control processes, among others) for a power system and will be significant in the future. However, there is still much to do in these research areas. The deployment of enabling technologies (e.g., smart meters) has made high-granularity data available for many customer segments and to approach many issues, for instance, to make forecasting tasks feasible at several demand aggregation levels. The first challenge is the improvement of STLF models and their performance at new aggregation levels. Moreover, the mix of renewables in the power system, and the necessity to include more flexibility through demand response initiatives have introduced greater uncertainties, which means new challenges for STLF in a more dynamic power system in the 2030–50 horizon. Many techniques have been proposed and applied for STLF, including traditional statistical models and AI techniques. Besides, distribution planning needs, as well as grid modernization, have initiated the development of hierarchical load forecasting. Analogously, the need to face new sources of uncertainty in the power system is giving more importance to probabilistic load forecasting. This Special Issue deals with both fundamental research and practical application research on STLF methodologies to face the challenges of a more distributed and customer-centered power system.
Accounting Information systems (AIS) have become indispensable in the field, and this book provides clear guidance for students or professionals needing to get up to speed. Designed to suit a one-semester AIS course at the graduate, undergraduate, or community college level, Core Concepts of Accounting Information Systems explores AIS use and processes in the context of modern-day accounting. Coverage includes conceptual overviews of data analytics, accounting, and risk management, as well as detailed discussion of business processes, cybercrime, database design and more to provide a well-rounded introduction to AIS. Case studies reinforce fundamental concepts using real-world scenarios that encourage critical thinking, while AIS-at-Work examples illustrate complex procedures or concepts in everyday workplace situations. Test Yourself questions allow students to gauge their level of understanding, while End of Chapter questions stimulate application of new skills through problems, cases, and discussion questions that facilitate classroom dialogue. Practical, current, relevant, and grounded in everyday application, this book is an invaluable resource for students of managerial accounting, tax accounting, and compliance.
Takes a practical look at how short-term forecasting has actually been undertaken and is being developed in public utility organizations.