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A Peak Load Forecasting Model Case Study
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Book Synopsis A Peak Load Forecasting Model Case Study by : K. Morgan Macrae
Download or read book A Peak Load Forecasting Model Case Study written by K. Morgan Macrae and published by Calgary : Canadian Energy Research Institute. This book was released on 1987 with total page 106 pages. Available in PDF, EPUB and Kindle. Book excerpt: Description of a computer model developed to account for electrical systemfactors, such as demand, time of use, customer profile and planning horizon, and their effects on system peak demand. The model tests the impact ofelectricity price changes on energy consumption and the demand forpower, by sector. Assuming no change in customer class load curves, themodel is thenused to derive a peak load forecast consistent with a long-term forecast ofcustomer class energy sales. The effects of potential load managementprograms and customer-owned electric power generation in specific sectors areassessed by modifying existing customer class load curves and electricitysales predictions.
Book Synopsis Forecasting and Assessing Risk of Individual Electricity Peaks by : Maria Jacob
Download or read book Forecasting and Assessing Risk of Individual Electricity Peaks written by Maria Jacob and published by Springer Nature. This book was released on 2019-09-25 with total page 108 pages. Available in PDF, EPUB and Kindle. Book excerpt: The overarching aim of this open access book is to present self-contained theory and algorithms for investigation and prediction of electric demand peaks. A cross-section of popular demand forecasting algorithms from statistics, machine learning and mathematics is presented, followed by extreme value theory techniques with examples. In order to achieve carbon targets, good forecasts of peaks are essential. For instance, shifting demand or charging battery depends on correct demand predictions in time. Majority of forecasting algorithms historically were focused on average load prediction. In order to model the peaks, methods from extreme value theory are applied. This allows us to study extremes without making any assumption on the central parts of demand distribution and to predict beyond the range of available data. While applied on individual loads, the techniques described in this book can be extended naturally to substations, or to commercial settings. Extreme value theory techniques presented can be also used across other disciplines, for example for predicting heavy rainfalls, wind speed, solar radiation and extreme weather events. The book is intended for students, academics, engineers and professionals that are interested in short term load prediction, energy data analytics, battery control, demand side response and data science in general.
Book Synopsis Electrical Load Forecasting by : S.A. Soliman
Download or read book Electrical Load Forecasting written by S.A. Soliman and published by Elsevier. This book was released on 2010-05-26 with total page 441 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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
Download or read book Energy Research Abstracts written by and published by . This book was released on 1988 with total page 1198 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Statistical Learning Tools for Electricity Load Forecasting by : Anestis Antoniadis
Download or read book Statistical Learning Tools for Electricity Load Forecasting written by Anestis Antoniadis and published by Springer Nature. This book was released on with total page 232 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Forecasting U.S. Electricity Demand by : Adela Maria Bolet
Download or read book Forecasting U.S. Electricity Demand written by Adela Maria Bolet and published by Routledge. This book was released on 2019-08-30 with total page 294 pages. Available in PDF, EPUB and Kindle. Book excerpt: Although the energy headlines of 1985 proclaim the waning of OPEC, the collapse of oil prices, and the demise of the nuclear power industry, few policy analysts are examining the dynamic challenges and opportunities that may confront the electric power industry during the remainder of this century. In this pioneering work, Adela Maria Bolet attempts to do exactly this, namely, to reconcile the differences among forecasters as to the future of electricity demand in the industrial, commercial, and residential sectors.
Book Synopsis Business Models and Reliable Operation of Virtual Power Plants by : Heping Jia
Download or read book Business Models and Reliable Operation of Virtual Power Plants written by Heping Jia and published by Springer Nature. This book was released on 2023-01-02 with total page 167 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book focuses on the business operation of virtual power plants. Both of the business models and reliable operation of virtual power plants have been addressed with engineering practices. This is achieved by providing an in-depth study on several major topics such as load forecasting for distributed energy resources, business model and practice of virtual power plants, the business operation of virtual power plants participating in demand response, and auxiliary service market. The dynamic pricing strategy of virtual power plants and reliable operation of power systems with virtual power plants are provided as well. The comprehensive and systematic treatment in business operation of virtual power plants is one of the major features of the book, which is particularly suited for readers who are interested to learn operation mechanisms of virtual power plants. The book benefits researchers, engineers, and graduate students in the fields of energy internet, electrical engineering, and business administration, etc.
Book Synopsis Core Concepts and Methods in Load Forecasting by : Stephen Haben
Download or read book Core Concepts and Methods in Load Forecasting written by Stephen Haben and published by Springer Nature. This book was released on 2023-06-01 with total page 332 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Modeling and Forecasting Electricity Loads and Prices by : Rafal Weron
Download or read book Modeling and Forecasting Electricity Loads and Prices written by Rafal Weron and published by John Wiley & Sons. This book was released on 2007-01-30 with total page 192 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book offers an in-depth and up-to-date review of different statistical tools that can be used to analyze and forecast the dynamics of two crucial for every energy company processes—electricity prices and loads. It provides coverage of seasonal decomposition, mean reversion, heavy-tailed distributions, exponential smoothing, spike preprocessing, autoregressive time series including models with exogenous variables and heteroskedastic (GARCH) components, regime-switching models, interval forecasts, jump-diffusion models, derivatives pricing and the market price of risk. Modeling and Forecasting Electricity Loads and Prices is packaged with a CD containing both the data and detailed examples of implementation of different techniques in Matlab, with additional examples in SAS. A reader can retrace all the intermediate steps of a practical implementation of a model and test his understanding of the method and correctness of the computer code using the same input data. The book will be of particular interest to the quants employed by the utilities, independent power generators and marketers, energy trading desks of the hedge funds and financial institutions, and the executives attending courses designed to help them to brush up on their technical skills. The text will be also of use to graduate students in electrical engineering, econometrics and finance wanting to get a grip on advanced statistical tools applied in this hot area. In fact, there are sixteen Case Studies in the book making it a self-contained tutorial to electricity load and price modeling and forecasting.
Book Synopsis Practical Data Mining by : Jr., Monte F. Hancock
Download or read book Practical Data Mining written by Jr., Monte F. Hancock and published by CRC Press. This book was released on 2011-12-19 with total page 304 pages. Available in PDF, EPUB and Kindle. Book excerpt: Used by corporations, industry, and government to inform and fuel everything from focused advertising to homeland security, data mining can be a very useful tool across a wide range of applications. Unfortunately, most books on the subject are designed for the computer scientist and statistical illuminati and leave the reader largely adrift in tech
Book Synopsis Spatial Electric Load Forecasting by : H. Lee Willis
Download or read book Spatial Electric Load Forecasting written by H. Lee Willis and published by CRC Press. This book was released on 2002-08-09 with total page 770 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Short-Term Load Forecasting by Artificial Intelligent Technologies by : Wei-Chiang Hong
Download or read book Short-Term Load Forecasting by Artificial Intelligent Technologies written by Wei-Chiang Hong and published by MDPI. This book was released on 2019-01-29 with total page 445 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is a printed edition of the Special Issue "Short-Term Load Forecasting by Artificial Intelligent Technologies" that was published in Energies
Book Synopsis Emerging Trends in Power Systems, Vol. 1 by :
Download or read book Emerging Trends in Power Systems, Vol. 1 written by and published by Allied Publishers. This book was released on with total page 476 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Smart Grids written by A B M Shawkat Ali and published by Springer Science & Business Media. This book was released on 2013-07-16 with total page 233 pages. Available in PDF, EPUB and Kindle. Book excerpt: A Smart Grid delivers renewable energy as a main source of electricity from producers to consumers using two-way monitoring through Smart Meter technology that can remotely control consumer electricity use. This can help to storage excess energy; reduce costs, increase reliability and transparency, and make processes more efficiently. Smart Grids: Opportunities, Developments, and Trends discusses advances in Smart Grid in today’s dynamic and rapid growing global economical and technological environments. Current development in the field are systematically explored with an introduction, detailed discussion and an experimental demonstration. Each chapter also includes the future scope and ongoing research for each topic. Smart Grids: Opportunities, Developments, and Trends provides up to date knowledge, research results, and innovations in Smart Grids spanning design, implementation, analysis and evaluation of Smart Grid solutions to the challenging problems in all areas of power industry. Providing a solid foundation for graduate and postgraduate students, this thorough approach also makes Smart Grids: Opportunities, Developments, and Trends a useful resource and hand book for researchers and practitioners in Smart Grid research. It can also act as a guide to Smart Grids for industry professionals and engineers from different fields working with Smart Grids.
Book Synopsis Energy Forecasting and Control Methods for Energy Storage Systems in Distribution Networks by : William Holderbaum
Download or read book Energy Forecasting and Control Methods for Energy Storage Systems in Distribution Networks written by William Holderbaum and published by Springer Nature. This book was released on 2023-01-07 with total page 218 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book describes the stochastic and predictive control modelling of electrical systems that can meet the challenge of forecasting energy requirements under volatile conditions. The global electrical grid is expected to face significant energy and environmental challenges such as greenhouse emissions and rising energy consumption due to the electrification of heating and transport. Today, the distribution network includes energy sources with volatile demand behaviour, and intermittent renewable generation. This has made it increasingly important to understand low voltage demand behaviour and requirements for optimal energy management systems to increase energy savings, reduce peak loads, and reduce gas emissions. Electrical load forecasting is a key tool for understanding and anticipating the highly stochastic behaviour of electricity demand, and for developing optimal energy management systems. Load forecasts, especially of the probabilistic variety, can support more informed planning and management decisions, which will be essential for future low carbon distribution networks. For storage devices, forecasts can optimise the appropriate state of control for the battery. There are limited books on load forecasts for low voltage distribution networks and even fewer demonstrations of how such forecasts can be integrated into the control of storage. This book presents material in load forecasting, control algorithms, and energy saving and provides practical guidance for practitioners using two real life examples: residential networks and cranes at a port terminal.
Book Synopsis Energy Abstracts for Policy Analysis by :
Download or read book Energy Abstracts for Policy Analysis written by and published by . This book was released on 1989 with total page 486 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis DEMANDA FORECASTING by : Diego Rodrigues
Download or read book DEMANDA FORECASTING written by Diego Rodrigues and published by Diego Rodrigues. This book was released on 2024-11-04 with total page 119 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this transformative book, delve deep into the world of demand forecasting enhanced by artificial intelligence and machine learning, where every decision is based on precise data and strategic insights. This essential resource is crafted for professionals seeking to master cutting-edge techniques, ensuring that your business not only adapts but thrives in a volatile and ever-evolving market. By exploring advanced forecasting methods, you will learn to identify hidden trends, optimize inventories, reduce costs, and avoid bottlenecks that often compromise operational efficiency. With practical and detailed examples, this guide offers a clear and actionable approach designed to elevate your expertise and position your company ahead of the competition. Ensure that every step you take is backed by robust analysis and accurate forecasts, transforming the way you conduct business and driving sustainable growth. This is the ultimate tool for any leader who wants to make informed decisions, mitigate risks, and maximize return on investment in an increasingly dynamic and challenging corporate environment. Keywords: demand forecasting artificial intelligence machine learning profit optimization inventory management cost minimization operational efficiency digital transformation Google AWS Microsoft IBM Oracle SAP Salesforce Tableau Power BI Python R Hadoop Spark IoT Big Data data analysis neural networks deep learning predictive algorithms technological innovation business transformation business competitiveness supply chain management trend analysis process optimization strategic decision making predictive models time series analysis random forests linear regression decision trees Python Java Linux Kali Linux HTML ASP.NET Ada Assembly Language BASIC Borland Delphi C C# C++ CSS Cobol Compilers DHTML Fortran General HTML Java JavaScript LISP PHP Pascal Perl Prolog RPG Ruby SQL Swift UML Elixir Haskell VBScript Visual Basic XHTML XML XSL Django Flask Ruby on Rails Angular React Vue.js Node.js Laravel Spring Hibernate .NET Core Express.js TensorFlow PyTorch Jupyter Notebook Keras Bootstrap Foundation jQuery SASS LESS Scala Groovy MATLAB R Objective-C Rust Go Kotlin TypeScript Elixir Dart SwiftUI Xamarin React Native NumPy Pandas SciPy Matplotlib Seaborn D3.js OpenCV NLTK PySpark BeautifulSoup Scikit-learn XGBoost CatBoost LightGBM FastAPI Celery Tornado Redis RabbitMQ Kubernetes Docker Jenkins Terraform Ansible Vagrant GitHub GitLab CircleCI Travis CI Linear Regression Logistic Regression Decision Trees Random Forests FastAPI AI ML K-Means Clustering Support Vector Tornado Machines Gradient Boosting Neural Networks LSTMs CNNs GANs ANDROID IOS MACOS WINDOWS Nmap Metasploit Framework Wireshark Aircrack-ng John the Ripper Burp Suite SQLmap Maltego Autopsy Volatility IDA Pro OllyDbg YARA Snort ClamAV iOS Netcat Tcpdump Foremost Cuckoo Sandbox Fierce HTTrack Kismet Hydra Nikto OpenVAS Nessus ZAP Radare2 Binwalk GDB OWASP Amass Dnsenum Dirbuster Wpscan Responder Setoolkit Searchsploit Recon-ng BeEF aws google cloud ibm azure databricks nvidia meta x Power BI IoT CI/CD Hadoop Spark Pandas NumPy Dask SQLAlchemy web scraping mysql big data science openai chatgpt Handler RunOnUiThread()Qiskit Q# Cassandra Bigtable VIRUS MALWARE docker kubernetes Kali Linux Nmap Metasploit Wireshark information security pen test cybersecurity Linux distributions ethical hacking vulnerability analysis system exploration wireless attacks web application security malware analysis social engineering Android iOS Social Engineering Toolkit SET computer science IT professionals cybersecurity careers cybersecurity expertise cybersecurity library cybersecurity training Linux operating systems cybersecurity tools ethical hacking tools security testing penetration test cycle security concepts mobile security cybersecurity fundamentals cybersecurity techniques cybersecurity skills cybersecurity industry global cybersecurity trends Kali Linux tools cybersecurity education cybersecurity innovation penetration test tools cybersecurity best practices global cybersecurity companies cybersecurity solutions IBM Google Microsoft AWS Cisco Oracle cybersecurity consulting cybersecurity framework network security cybersecurity courses cybersecurity tutorials Linux security cybersecurity challenges cybersecurity landscape cloud security cybersecurity threats cybersecurity compliance cybersecurity research cybersecurity technology
