Energy Demand Forecasting Issues

Energy Demand Forecasting Issues PDF Author: Michael R Jaske
Publisher:
ISBN:
Category : Energy consumption
Languages : en
Pages : 160

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Book Description

Energy Demand Forecasting Issues

Energy Demand Forecasting Issues PDF Author: Michael R Jaske
Publisher:
ISBN:
Category : Energy consumption
Languages : en
Pages : 160

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Book Description


Energy Demand: Facts and Trends

Energy Demand: Facts and Trends PDF 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.

Forecasting and Assessing Risk of Individual Electricity Peaks

Forecasting and Assessing Risk of Individual Electricity Peaks PDF 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.

Energy Economics

Energy Economics PDF Author: Subhes C. Bhattacharyya
Publisher: Springer Nature
ISBN: 1447174682
Category : Business & Economics
Languages : en
Pages : 854

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Book Description
This book provides an updated and expanded overview of basic concepts of energy economics and explains how simple economic tools can be used to analyse contemporary energy issues in the light of recent developments, such as the Paris Agreement, the UN Sustainable Development Goals and new technological developments in the production and use of energy. The new edition is divided into four parts covering concepts, issues, markets, and governance. Although the content has been thoroughly revised and rationalised to reflect the current state of knowledge, it retains the main features of the first edition, namely accessibility, research-informed presentation, and extensive use of charts, tables and worked examples. This easily accessible reference book allows readers to gain the skills required to understand and analyse complex energy issues from an economic perspective. It is a valuable resource for students and researchers in the field of energy economics, as well as interested readers with an interdisciplinary background.

Issues Affecting the Future of Electricity Demand and Demand Forecasting

Issues Affecting the Future of Electricity Demand and Demand Forecasting PDF Author: Stanford University. Energy Modeling Forum
Publisher:
ISBN:
Category :
Languages : en
Pages : 16

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Book Description


Energy Demand Forecasting

Energy Demand Forecasting PDF Author: United States. Congress. House. Committee on Science and Technology. Subcommittee on Investigations and Oversight
Publisher:
ISBN:
Category : Electric power consumption
Languages : en
Pages : 368

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Book Description


Renewable Energy Forecasting

Renewable Energy Forecasting PDF 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

Short-Term Load Forecasting 2019

Short-Term Load Forecasting 2019 PDF 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.

Advanced Optimization Methods and Big Data Applications in Energy Demand Forecast

Advanced Optimization Methods and Big Data Applications in Energy Demand Forecast PDF Author: Federico Divina
Publisher: MDPI
ISBN: 3036508627
Category : Technology & Engineering
Languages : en
Pages : 100

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Book Description
The use of data collectors in energy systems is growing more and more. For example, smart sensors are now widely used in energy production and energy consumption systems. This implies that huge amounts of data are generated and need to be analyzed in order to extract useful insights from them. Such big data give rise to a number of opportunities and challenges for informed decision making. In recent years, researchers have been working very actively in order to come up with effective and powerful techniques in order to deal with the huge amount of data available. Such approaches can be used in the context of energy production and consumption considering the amount of data produced by all samples and measurements, as well as including many additional features. With them, automated machine learning methods for extracting relevant patterns, high-performance computing, or data visualization are being successfully applied to energy demand forecasting.

Artificial Neural Network Modelling

Artificial Neural Network Modelling PDF Author: Subana Shanmuganathan
Publisher: Springer
ISBN: 3319284959
Category : Technology & Engineering
Languages : en
Pages : 468

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Book Description
This book covers theoretical aspects as well as recent innovative applications of Artificial Neural networks (ANNs) in natural, environmental, biological, social, industrial and automated systems. It presents recent results of ANNs in modelling small, large and complex systems under three categories, namely, 1) Networks, Structure Optimisation, Robustness and Stochasticity 2) Advances in Modelling Biological and Environmental Systems and 3) Advances in Modelling Social and Economic Systems. The book aims at serving undergraduates, postgraduates and researchers in ANN computational modelling.