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Author: Wei-Chiang Hong
Publisher: Springer Nature
ISBN: 3030365298
Category : Business & Economics
Languages : en
Pages : 188
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Book Description
This book is written for researchers and postgraduates who are interested in developing high-accurate energy demand forecasting models that outperform traditional models by hybridizing intelligent technologies. It covers meta-heuristic algorithms, chaotic mapping mechanism, quantum computing mechanism, recurrent mechanisms, phase space reconstruction, and recurrence plot theory. The book clearly illustrates how these intelligent technologies could be hybridized with those traditional forecasting models. This book provides many figures to deonstrate how these hybrid intelligent technologies are being applied to exceed the limitations of existing models.
Author: Wei-Chiang Hong
Publisher: Springer Nature
ISBN: 3030365298
Category : Business & Economics
Languages : en
Pages : 188
Get Book Here
Book Description
This book is written for researchers and postgraduates who are interested in developing high-accurate energy demand forecasting models that outperform traditional models by hybridizing intelligent technologies. It covers meta-heuristic algorithms, chaotic mapping mechanism, quantum computing mechanism, recurrent mechanisms, phase space reconstruction, and recurrence plot theory. The book clearly illustrates how these intelligent technologies could be hybridized with those traditional forecasting models. This book provides many figures to deonstrate how these hybrid intelligent technologies are being applied to exceed the limitations of existing models.
Author: Georges Kariniotakis
Publisher: Woodhead Publishing
ISBN: 0081005059
Category : Technology & Engineering
Languages : en
Pages : 388
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Book Description
Renewable Energy Forecasting: From Models to Applications provides an overview of the state-of-the-art of renewable energy forecasting technology and its applications. After an introduction to the principles of meteorology and renewable energy generation, groups of chapters address forecasting models, very short-term forecasting, forecasting of extremes, and longer term forecasting. The final part of the book focuses on important applications of forecasting for power system management and in energy markets. Due to shrinking fossil fuel reserves and concerns about climate change, renewable energy holds an increasing share of the energy mix. Solar, wind, wave, and hydro energy are dependent on highly variable weather conditions, so their increased penetration will lead to strong fluctuations in the power injected into the electricity grid, which needs to be managed. Reliable, high quality forecasts of renewable power generation are therefore essential for the smooth integration of large amounts of solar, wind, wave, and hydropower into the grid as well as for the profitability and effectiveness of such renewable energy projects. - Offers comprehensive coverage of wind, solar, wave, and hydropower forecasting in one convenient volume - Addresses a topic that is growing in importance, given the increasing penetration of renewable energy in many countries - Reviews state-of-the-science techniques for renewable energy forecasting - Contains chapters on operational applications
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: B. Chateau
Publisher: Springer
ISBN: 9783709186411
Category : Business & Economics
Languages : en
Pages : 0
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Book Description
The fIrst oil crisis of 1973-74 and the questions it raised in the economic and social fIelds drew attention to energy issues. Industrial societies, accustomed for two decades or more to energy sufficiently easy to produce and cheap to consume that it was thought to be inexhaustible, began to question their energy future. The studies undertaken at that time, and since, on a national, regional, or world level were over-optimistic. The problem seemed simple enough to solve. On the one hand, a certain number of resources: coal, the abundance of which was discovered, or rather rediscovered oil, source of all the problems ... In fact, the problems seemed to come, if not from oil itself (an easy explanation), then from those who produced it without really owning it, and from those who owned it without really control ling it natural gas, second only to oil and less compromised uranium, all of whose promises had not been kept, but whose resources were not in question solar energy, multiform and really inexhaustible thermonuclear fusion, and geothermal energy, etc. On the other hand, energy consumption, though excessive perhaps, was symbolic of progress, development, and increased well being. The originality of the energy policies set up since 1974 lies in the fact they no longer aimed to produce (or import) more, but to consume less. They sought, and still seek, what might be emphatically called the control of energy consump tion, or rather the control of energy demand.
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: William Holderbaum
Publisher: Springer Nature
ISBN: 3030828484
Category : Technology & Engineering
Languages : en
Pages : 218
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Book Description
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.
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 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: Lorenz M. Hilty
Publisher: Springer
ISBN: 3319092286
Category : Technology & Engineering
Languages : en
Pages : 465
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Book Description
ICT Innovations for Sustainability is an investigation of how information and communication technology can contribute to sustainable development. It presents clear definitions of sustainability, suggesting conceptual frameworks for the positive and negative effects of ICT on sustainable development. It reviews methods of assessing the direct and indirect impact of ICT systems on energy and materials demand, and examines the results of such assessments. In addition, it investigates ICT-based approaches to supporting sustainable patterns of production and consumption, analyzing them at various levels of abstraction – from end-user devices, Internet infrastructure, user behavior, and social practices to macro-economic indicators. Combining approaches from Computer Science, Information Systems, Human-Computer Interaction, Economics, and Environmental Sciences, the book presents a new, holistic perspective on ICT for Sustainability (ICT4S). It is an indispensable resource for anyone working in the area of ICT for Energy Efficiency, Life Cycle Assessment of ICT, Green IT, Green Information Systems, Environmental Informatics, Energy Informatics, Sustainable HCI, or Computational Sustainability.
Author: Wei-Chiang Hong
Publisher: MDPI
ISBN: 3038972924
Category : Technology & Engineering
Languages : en
Pages : 187
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Book Description
This book is a printed edition of the Special Issue "Kernel Methods and Hybrid Evolutionary Algorithms in Energy Forecasting" that was published in Energies
