"A significant barrier to the widespread adoption of many forms of renewable energy, including wind, solar, and marine and hydrokinetic power, is that these sources are intermittent. Electric grid managers address this intermittency by adjusting the delivery of other sources of power based on expected changes in renewable power output. These expected changes are called power production forecasts. Such forecasts must take into account changing weather conditions in conjunction with the land's topography near a renewable energy device, along with the device's expected technical performance ... Several recent reports have determined that improving the accuracy and frequency of these forecasts can have a major impact on the economic viability of renewable energy resources" ... This hearing provides "testimony on the roles that various Federal agencies as well as the private sector play in providing forecasting data and services relevant to expanding the availability of reliable, renewable power, and the extent to which these efforts are coordinated. The hearing will also explore any research, development, demonstration, and monitoring needs that are not currently being adequately addressed."--P. 3-4.

Mathematical Modelling of Contemporary Electricity Markets reviews major methodologies and tools to accurately analyze and forecast contemporary electricity markets in a ways that is ideal for practitioner and academic audiences. Approaches include optimization, neural networks, genetic algorithms, co-optimization, econometrics, E3 models and energy system models. The work examines how new challenges affect power market modeling, including discussions of stochastic renewables, price volatility, dynamic participation of demand, integration of storage and electric vehicles, interdependence with other commodity markets and the evolution of policy developments (market coupling processes, security of supply). Coverage addresses all major forms of electricity markets: day-ahead, forward, intraday, balancing, and capacity. - Provides a diverse body of established techniques suitable for modeling any major aspect of electricity markets - Familiarizes energy experts with the quantitative skills needed in competitive electricity markets - Reviews market risk for energy investment decisions by stressing the multi-dimensionality of electricity markets

This book constitutes the thoroughly refereed conference proceedings of the 6th International Workshop on Business Intelligence for the Real-Time Enterprise, BIRTE 2012, held in Istanbul, Turkey, in August 2012, in conjunction with VLDB 2012, the International Conference on Very Large Data Bases. The BIRTE workshop series provides a forum to discuss and advance the science and engineering enabling real-time business intelligence and the novel applications that build on these foundational techniques. This volume contains ten research papers, which were carefully reviewed and selected from 13 submissions.

Smart grid (SG) is considered a form of intelligent system that allows the electric grid to perform its functions efficiently. The SG is a network that allows for the flow of electrical energy and data, where the data is used to make intelligent decisions in the operation of the electric grid. Artificial intelligence (AI) techniques, such as expert system (ES), Machine Learning (ML), and deep Learning (DL) have brought an advancing frontier in power electronics and power engineering with their powerful data processing capabilities. The SG relies on the flow of data to make its intelligent control; therefore, AI technology is a perfect fit for the SG. The application of AI technology in the SG has the potential to improve the intelligence of the SG. This research topic is focused on ways of improving the data analysis and control of SG by leveraging technologies. Manuscripts with the progress made in solving a range of miscellaneous and critical problems in SG by leveraging AI methods such as ES, ML, and DL methods are welcome. Reviews and original research that describe the latest developments in this field are considered for publication in this research topic. The scope of this Research Topic will include the following themes, but are not limited to: 1. Data-driven and artificial intelligence approaches to enhancing flexibility and resilience of SG. 2. Expert system, Machine Learning and Deep Learning, reinforcement learning and transfer learning for applications in SG. 3. AI for development in ensuring high reliability and stability of electric power system with high penetration of renewable energy. 4. AI for studies in operation protection, integrated planning, and control of SG systems. 5. AI for development in diagnostics and diagnostics for SG. 6. Health monitoring of a modern wind generation system using an adaptive neuro-fuzzy system. 7. Space vector fault pattern identification of a smart grid subsystem by neural mapping. 8. Control techniques, mathematical programming methods, optimization techniques and metaheuristics applied in SG. 9. AI and optimization techniques for green energy and carbon footprint. 10. Novel applications of AI-based smart grids in smart cities, smart transportation, smart healthcare, and smart manufacturing.

Published as an Open Access book available on Science Direct, IEA Wind Recommended Practices for the Implementation of Renewable Energy Forecasting Solutions translates decades of academic knowledge and standard requirements into applicable procedures and decision support tools for the energy industry. Designed specifically for practitioners in the energy industry, readers will find the tools to maximize the value of renewable energy forecast information in operational decision-making applications and significantly reduce the costs of integrating large amounts of wind and solar generation assets into grid systems through more efficient management of the renewable generation variability. Authored by a group of international experts as part of the IEA Wind Task 36 (Wind Energy Forecasting), the book addresses the issue that many current operational forecast solutions are not properly optimized for their intended applications. It provides detailed guidelines and recommended practices on forecast solution selection processes, designing and executing forecasting benchmarks and trials, forecast solution evaluation, verification, and validation, and meteorological and power data requirements for real-time forecasting applications. In addition, the guidelines integrate probabilistic forecasting, integrate wind and solar forecasting, offer improved IT data exchange and data format standards, and have a dedicated section to dealing with the requirements for SCADA and meteorological measurements. A unique and comprehensive reference, IEA Wind Recommended Practices for the Implementation of Renewable Energy Forecasting Solutions is an essential guide for all practitioners involved in wind and solar energy generation forecasting from forecast vendors to end-users of renewable forecasting solutions. - Brings together the decades-long expertise of authors from a range of backgrounds, including universities and government laboratories, commercial forecasters, and operational forecast end-users into a single comprehensive set of practices - Addresses all areas of wind power forecasting, including forecasting methods, measurement selection, setup and data quality control, and the evaluation of forecasting processes related to renewable energy forecasting - Provides purpose-built decision-support tools, process diagrams, and code examples to help readers visualize and navigate the book and support decision-making

Lars Dannecker developed a novel online forecasting process that significantly improves how forecasts are calculated. It increases forecasting efficiency and accuracy, as well as allowing the process to adapt to different situations and applications. Improving the forecasting efficiency is a key pre-requisite for ensuring stable electricity grids in the face of an increasing amount of renewable energy sources. It is also important to facilitate the move from static day ahead electricity trading towards more dynamic real-time marketplaces. The online forecasting process is realized by a number of approaches on the logical as well as on the physical layer that we introduce in the course of this book. Nominated for the Georg-Helm-Preis 2015 awarded by the Technische Universität Dresden.

This book contains selected papers presented during the World Renewable Energy Congress (WREC) 2020 at the Instituto Superior Técnico in Lisbon. The WREC is dedicated to promoting renewable energy global development, and features top international experts, policy makers, scientists, engineers, technology developers, and business practitioners addressing the most current research and technological breakthroughs in sustainable energy development and innovation. The contributions address policy and renewable energy technologies and applications in all sectors—for heating and cooling, agricultural applications, water, desalination, industrial applications, and for the transport sectors. Presents cutting-edge research in green building and renewable energy from all over the world; Covers the most up-to-date research developments, government policies, business models, best practices, and innovations; Contains case studies and examples to enhance practical application of the technologies.