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Author: Kevin Berk
Publisher: Springer Spektrum
ISBN: 9783658086688
Category : Business & Economics
Languages : en
Pages : 0
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Book Description
The master thesis of Kevin Berk develops a stochastic model for the electricity demand of small and medium-sized companies that is flexible enough so that it can be used for various business sectors. The model incorporates the grid load as an exogenous factor and seasonalities on a daily, weekly and yearly basis. It is demonstrated how the model can be used e.g. for estimating the risk of retail contracts. The uncertainty of electricity demand is an important risk factor for customers as well as for utilities and retailers. As a consequence, forecasting electricity load and its risk is now an integral component of the risk management for all market participants.
Author: Kevin Berk
Publisher: Springer Spektrum
ISBN: 9783658086688
Category : Business & Economics
Languages : en
Pages : 0
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Book Description
The master thesis of Kevin Berk develops a stochastic model for the electricity demand of small and medium-sized companies that is flexible enough so that it can be used for various business sectors. The model incorporates the grid load as an exogenous factor and seasonalities on a daily, weekly and yearly basis. It is demonstrated how the model can be used e.g. for estimating the risk of retail contracts. The uncertainty of electricity demand is an important risk factor for customers as well as for utilities and retailers. As a consequence, forecasting electricity load and its risk is now an integral component of the risk management for all market participants.
Author: Rafal Weron
Publisher: John Wiley & Sons
ISBN: 0470059990
Category : Business & Economics
Languages : en
Pages : 192
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Book Description
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.
Author: Kevin Berk
Publisher: Springer
ISBN: 3658086696
Category : Business & Economics
Languages : en
Pages : 123
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Book Description
The master thesis of Kevin Berk develops a stochastic model for the electricity demand of small and medium-sized companies that is flexible enough so that it can be used for various business sectors. The model incorporates the grid load as an exogenous factor and seasonalities on a daily, weekly and yearly basis. It is demonstrated how the model can be used e.g. for estimating the risk of retail contracts. The uncertainty of electricity demand is an important risk factor for customers as well as for utilities and retailers. As a consequence, forecasting electricity load and its risk is now an integral component of the risk management for all market participants.
Author: Maria Jacob
Publisher: Springer Nature
ISBN: 303028669X
Category : Mathematics
Languages : en
Pages : 108
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Book Description
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.
Author: Antonio Gabaldón
Publisher: MDPI
ISBN: 303943442X
Category : Technology & Engineering
Languages : en
Pages : 324
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Book Description
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.
Author: Joe H. Chow
Publisher: Springer Science & Business Media
ISBN: 0387234713
Category : Technology & Engineering
Languages : en
Pages : 345
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Book Description
Applied Mathematics for Restructured Electric Power Systems: Optimization, Control, and Computational Intelligence consists of chapters based on work presented at a National Science Foundation workshop organized in November 2003. The theme of the workshop was the use of applied mathematics to solve challenging power system problems. The areas included control, optimization, and computational intelligence. In addition to the introductory chapter, this book includes 12 chapters written by renowned experts in their respected fields. Each chapter follows a three-part format: (1) a description of an important power system problem or problems, (2) the current practice and/or particular research approaches, and (3) future research directions. Collectively, the technical areas discussed are voltage and oscillatory stability, power system security margins, hierarchical and decentralized control, stability monitoring, embedded optimization, neural network control with adaptive critic architecture, control tuning using genetic algorithms, and load forecasting and component prediction. This volume is intended for power systems researchers and professionals charged with solving electric and power system problems.
Author: Mohamed E. El-Hawary
Publisher: John Wiley & Sons
ISBN: 1118171349
Category : Technology & Engineering
Languages : en
Pages : 341
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Book Description
A comprehensive review of state-of-the-art approaches to power systems forecasting from the most respected names in the field, internationally Advances in Electric Power and Energy Systems is the first book devoted exclusively to a subject of increasing urgency to power systems planning and operations. Written for practicing engineers, researchers, and post-grads concerned with power systems planning and forecasting, this book brings together contributions from many of the world’s foremost names in the field who address a range of critical issues, from forecasting power system load to power system pricing to post-storm service restoration times, river flow forecasting, and more. In a time of ever-increasing energy demands, mounting concerns over the environmental impacts of power generation, and the emergence of new, smart-grid technologies, electricity price forecasting has assumed a prominent role within both the academic and industrial arenas. Short-run forecasting of electricity prices has become necessary for power generation unit schedule, since it is the basis of every maximization strategy. This book fills a gap in the literature on this increasingly important topic. Following an introductory chapter offering background information necessary for a full understanding of the forecasting issues covered, this book: Introduces advanced methods of time series forecasting, as well as neural networks Provides in-depth coverage of state-of-the-art power system load forecasting and electricity price forecasting Addresses river flow forecasting based on autonomous neural network models Deals with price forecasting in a competitive market Includes estimation of post-storm restoration times for electric power distribution systems Features contributions from world-renowned experts sharing their insights and expertise in a series of self-contained chapters Advances in Electric Power and Energy Systems is a valuable resource for practicing engineers, regulators, planners, and consultants working in or concerned with the electric power industry. It is also a must read for senior undergraduates, graduate students, and researchers involved in power system planning and operation.
Author: Monica Greer
Publisher: Academic Press
ISBN: 0080961355
Category : Business & Economics
Languages : en
Pages : 360
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Book Description
A "quick look up guide," Electricity Cost Modeling Calculations places the relevant formulae and calculations at the reader's finger tips. In this book, theories are explained in a nutshell and then the calculation is presented and solved in an illustrated, step-by-step fashion. A valuable guide for new engineers, economists (or forecasters), regulators, and policy makers who want to further develop their knowledge of best practice calculations techniques or experienced practitioners (and even managers) who desire to acquire more useful tips, this book offers expert advice for using such cost models to determine optimally-sized distribution systems and optimally-structured power supplying entities. In other words, this book provides an Everything-that-you-want-to-know-about-cost-modelling-for-electric-utilities (but were afraid to ask) approach to modelling the cost of supplying electricity. In addition, the author covers the concept of multiproduct and multistage cost functions, which are appropriate in modelling the cost of supplying electricity. The author has done all the heavy number-crunching, and provides the reader with real-world, practical examples of how to properly quantify the costs associated with providing electric service, thus increasing the accuracy of the results and support for the policy initiatives required to ensure the competitiveness of the power suppliers in this new world in which we are living. The principles contained herein could be employed to assist in the determination of the cost-minimizing amount of output (i.e., electricity), which could then be used to determine whether a merger between two entities makes sense (i.e., would increase profitability). Other examples abound: public regulatory commissions also need help in determining whether mergers (or divestitures) are welfare-enhancing or not; ratemaking policies depend on costs and properly determining the costs of supplying electric (or gas, water, and local telephone) service. Policy makers, too, can benefit in terms of optimal market structure; after all, the premise of deregulation of the electric industry was predicated on the idea that generation could be deregulated. Unfortunately, the economies of vertical integration between the generation. - A comprehensive guide to the cost issues surrounding the generation, transmission, and distribution of electricity - Real-world examples that are practical, meaningful, and easy to understand - Policy implications and suggestions to aid in the formation of the optimal market structure going forward (thus increasing efficiency of electric power suppliers) - The principles contained herein could be employed to assist in the determination of the cost-minimizing amount of output
Author: Javier Contreras
Publisher: MDPI
ISBN: 3038424153
Category : Technology & Engineering
Languages : en
Pages : 259
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Book Description
This book is a printed edition of the Special Issue "Forecasting Models of Electricity Prices" that was published in Energies
Author: Yi Wang
Publisher: Springer Nature
ISBN: 9811526249
Category : Business & Economics
Languages : en
Pages : 306
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Book Description
This book aims to make the best use of fine-grained smart meter data to process and translate them into actual information and incorporated into consumer behavior modeling and distribution system operations. It begins with an overview of recent developments in smart meter data analytics. Since data management is the basis of further smart meter data analytics and its applications, three issues on data management, i.e., data compression, anomaly detection, and data generation, are subsequently studied. The following works try to model complex consumer behavior. Specific works include load profiling, pattern recognition, personalized price design, socio-demographic information identification, and household behavior coding. On this basis, the book extends consumer behavior in spatial and temporal scale. Works such as consumer aggregation, individual load forecasting, and aggregated load forecasting are introduced. We hope this book can inspire readers to define new problems, apply novel methods, and obtain interesting results with massive smart meter data or even other monitoring data in the power systems.
