Hybrid Advanced Techniques For Forecasting In Energy Sector
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Author | : Wei-Chiang Hong |
Publisher | : MDPI |
Total Pages | : 251 |
Release | : 2018-10-19 |
Genre | : Technology & Engineering |
ISBN | : 3038972908 |
This book is a printed edition of the Special Issue "Hybrid Advanced Techniques for Forecasting in Energy Sector" that was published in Energies
Author | : Georges Kariniotakis |
Publisher | : Woodhead Publishing |
Total Pages | : 388 |
Release | : 2017-09-29 |
Genre | : Technology & Engineering |
ISBN | : 0081005059 |
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 | : Javier Contreras |
Publisher | : MDPI |
Total Pages | : 259 |
Release | : 2018-04-06 |
Genre | : Technology & Engineering |
ISBN | : 3038424153 |
This book is a printed edition of the Special Issue "Forecasting Models of Electricity Prices" that was published in Energies
Author | : Ravinesh Deo |
Publisher | : Elsevier |
Total Pages | : 553 |
Release | : 2020-09-30 |
Genre | : Technology & Engineering |
ISBN | : 012817773X |
Predictive Modeling for Energy Management and Power Systems Engineering introduces readers to the cutting-edge use of big data and large computational infrastructures in energy demand estimation and power management systems. The book supports engineers and scientists who seek to become familiar with advanced optimization techniques for power systems designs, optimization techniques and algorithms for consumer power management, and potential applications of machine learning and artificial intelligence in this field. The book provides modeling theory in an easy-to-read format, verified with on-site models and case studies for specific geographic regions and complex consumer markets. - Presents advanced optimization techniques to improve existing energy demand system - Provides data-analytic models and their practical relevance in proven case studies - Explores novel developments in machine-learning and artificial intelligence applied in energy management - Provides modeling theory in an easy-to-read format
Author | : Information Resources Management Association |
Publisher | : Engineering Science Reference |
Total Pages | : 2250 |
Release | : 2021-06-25 |
Genre | : |
ISBN | : 9781799891529 |
Energy usage and consumption continue to rise globally each year, with the most efficient and cost-effective energy sources causing huge impacts to the environment. In an effort to mitigate harmful effects to the environment, implementing clean energy resources and utilizing green energy management strategies have become worldwide initiatives, with many countries from all regions quickly becoming leaders in renewable energy usage. Still, not every energy resource is without flaws. Researchers must develop effective and low-cost strategies for clean energy in order to find the balance between production and consumption. The Research Anthology on Clean Energy Management and Solutions provides in-depth research that explores strategies and techniques used in the energy production field to optimize energy efficiency in order to maintain clean and safe use while delivering ample energy coverage. The anthology also seeks solutions to energy that have not yet been optimized or are still produced in a way that is harmful to the environment. Covering topics such as hydrogen fuel cells, renewable energy, solar power, solar systems, cost savings, and climate protection, this text is essential for electrical engineers, nuclear engineers, environmentalists, managers, policymakers, government officials, professionals in the energy industry, researchers, academicians, and students looking for the latest research on clean energy management.
Author | : Wei-Chiang Hong |
Publisher | : MDPI |
Total Pages | : 251 |
Release | : 2018-10-19 |
Genre | : Technology & Engineering |
ISBN | : 303897286X |
This book is a printed edition of the Special Issue "Hybrid Advanced Optimization Methods with Evolutionary Computation Techniques in Energy Forecasting" that was published in Energies
Author | : Wei-Chiang Hong |
Publisher | : |
Total Pages | : |
Release | : 2018 |
Genre | : |
ISBN | : 9783038972914 |
Accurate forecasting performance in the energy sector is a primary factor in the modern restructured power market, accomplished by any novel advanced hybrid techniques. Particularly in the Big Data era, forecasting models are always based on a complex function combination, and energy data are always complicated by factors such as seasonality, cyclicity, fluctuation, dynamic nonlinearity, and so on. To comprehensively address this issue, it is insufficient to concentrate only on simply hybridizing evolutionary algorithms with each other, or on hybridizing evolutionary algorithms with chaotic mapping, quantum computing, recurrent and seasonal mechanisms, and fuzzy inference theory in order to determine suitable parameters for an existing model. It is necessary to also consider hybridizing or combining two or more existing models (e.g., neuro-fuzzy model, BPNN-fuzzy model, seasonal support vector regression-chaotic quantum particle swarm optimization (SSVR-CQPSO), et cetera). These advanced novel hybrid techniques can provide more satisfactory energy forecasting performances. This book aimed to attract researchers with an interest in the research areas described above. Specifically, we were interested in contributions towards recent developments, id est, hybridizing or combining any advanced techniques in energy forecasting, with the superior capabilities over the traditional forecasting approaches, with the ability to overcome some embedded drawbacks, and with the very superiority to achieve significant improved forecasting accuracy.
Author | : S.A. Soliman |
Publisher | : Elsevier |
Total Pages | : 441 |
Release | : 2010-05-26 |
Genre | : Business & Economics |
ISBN | : 0123815444 |
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
Author | : Jane O. Ebinger |
Publisher | : World Bank Publications |
Total Pages | : 224 |
Release | : 2011 |
Genre | : Business & Economics |
ISBN | : 0821386980 |
"While the energy sector is a primary target of efforts to arrest and reverse the growth of greenhouse gas emissions and lower the carbon footprint of development, it is also expected to be increasingly affected by unavoidable climate consequences from the damage already induced in the biosphere. Energy services and resources, as well as seasonal demand, will be increasingly affected by changing trends, increasing variability, greater extremes and large inter-annual variations in climate parameters in some regions. All evidence suggests that adaptation is not an optional add-on but an essential reckoning on par with other business risks. Existing energy infrastructure, new infrastructure and future planning need to consider emerging climate conditions and impacts on design, construction, operation, and maintenance. Integrated risk-based planning processes will be critical to address the climate change impacts and harmonize actions within and across sectors. Also, awareness, knowledge, and capacity impede mainstreaming of climate adaptation into the energy sector. However, the formal knowledge base is still nascent?information needs are complex and to a certain extent regionally and sector specific. This report provides an up-to-date compendium of what is known about weather variability and projected climate trends and their impacts on energy service provision and demand. It discusses emerging practices and tools for managing these impacts and integrating climate considerations into planning processes and operational practices in an environment of uncertainty. It focuses on energy sector adaptation, rather than mitigation which is not discussed in this report. This report draws largely on available scientific and peer-reviewed literature in the public domain and takes the perspective of the developing world to the extent possible."
Author | : Fouzi Harrou |
Publisher | : BoD – Books on Demand |
Total Pages | : 212 |
Release | : 2020-04-01 |
Genre | : Technology & Engineering |
ISBN | : 1838800913 |
Fault detection, control, and forecasting have a vital role in renewable energy systems (Photovoltaics (PV) and wind turbines (WTs)) to improve their productivity, ef?ciency, and safety, and to avoid expensive maintenance. For instance, the main crucial and challenging issue in solar and wind energy production is the volatility of intermittent power generation due mainly to weather conditions. This fact usually limits the integration of PV systems and WTs into the power grid. Hence, accurately forecasting power generation in PV and WTs is of great importance for daily/hourly efficient management of power grid production, delivery, and storage, as well as for decision-making on the energy market. Also, accurate and prompt fault detection and diagnosis strategies are required to improve efficiencies of renewable energy systems, avoid the high cost of maintenance, and reduce risks of fire hazards, which could affect both personnel and installed equipment. This book intends to provide the reader with advanced statistical modeling, forecasting, and fault detection techniques in renewable energy systems.