Renewable Energy Forecasting And Risk Management

Gathering selected, revised and extended contributions from the conference ‘Forecasting and Risk Management for Renewable Energy FOREWER’, which took place in Paris in June 2017, this book focuses on the applications of statistics to the risk management and forecasting problems arising in the renewable energy industry. The different contributions explore all aspects of the energy production chain: forecasting and probabilistic modelling of renewable resources, including probabilistic forecasting approaches; modelling and forecasting of wind and solar power production; prediction of electricity demand; optimal operation of microgrids involving renewable production; and finally the effect of renewable production on electricity market prices. Written by experts in statistics, probability, risk management, economics and electrical engineering, this multidisciplinary volume will serve as a reference on renewable energy risk management and at the same time as a source of inspiration for statisticians and probabilists aiming to work on energy-related problems.

It is the purpose of this book to provide the meteorological knowledge and tools to improve the risk management of energy industry decisions, ranging from the long term finance and engineering planning assessments to the short term operational measures for scheduling and maintenance. Most of the chapters in this book are based on presentations given at the inaugural International Conference Energy & Meteorology (ICEM), held in the Gold Coast, Australia, 8-11 November 2011. The main aim of the conference was to strengthen the link between Energy and Meteorology, so as to make meteorological information more relevant to the planning and operations of the energy sector. The ultimate goal would be to make the best use of weather and climate data in order to achieve a more efficient use of energy sources. This book seeks to realise the same objective.

Meteorological and climate data are indeed essential both in day-to-day energy management and for the definition of production and distribution infrastructures. For instance, the supply of electricity to users can be disturbed by extreme meteorological events such as thunderstorms with unusually strong winds, severe icing, severe cold spells, sea level elevation associated with storm surges, floods ... To be protected against such events, it is not sufficient to act after they have taken place. It is necessary to identify their potential impacts precisely and assess the probability of their occurrence. This book shows that this can only be done through an enhanced dialogue between the energy community and the climate and meteorology community. This implies an in-depth dialogue between actors to define precisely what kind of data is needed and how it should be used. Météo-France has been in long-term cooperation with the energy sector, including the fields of electricity production and distribution. Drawing on this experience, it should be noted in this respect the importance of lo- term partnership between actors as exemplified here by the message of EDF.

Appropriate risk management tools can help remove some of the barriers to financing Renewable Energy Technology (RET) projects, particularly in developing countries where risk and risk perceptions are highest. That is why UNEP is working on a comprehensive overview of currently available and potential financial risk management instruments for Renewable Energy Technology (RET) projects. This study will pave the way for an upcoming GEF project that will promote the use of financial risk management instruments that favor the development of RETs.

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

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.

An overview of today's energy markets from a multi-commodity perspective As global warming takes center stage in the public and private sectors, new debates on the future of energy markets and electricity generation have emerged around the world. The Second Edition of Managing Energy Risk has been updated to reflect the latest products, approaches, and energy market evolution. A full 30% of the content accounts for changes that have occurred since the publication of the first edition. Practitioners will appreciate this contemporary approach to energy and the comprehensive information on recent market influences. A new chapter is devoted to the growing importance of renewable energy sources, related subsidy schemes and their impact on energy markets. Carbon emissions certificates, post-Fukushima market shifts, and improvements in renewable energy generation are all included. Further, due to the unprecedented growth in shale gas production in recent years, a significant amount of material on gas markets has been added in this edition. Managing Energy Risk is now a complete guide to both gas and electricity markets, and gas-specific models like gas storage and swing contracts are given their due. The unique, practical approach to energy trading includes a comprehensive explanation of the interactions and relations between all energy commodities. Thoroughly revised to reflect recent changes in renewable energy, impacts of the financial crisis, and market fluctuations in the wake of Fukushima Emphasizes both electricity and gas, with all-new gas valuation models and a thorough description of the gas market Written by a team of authors with theoretical and practical expertise, blending mathematical finance and technical optimization Covers developments in the European Union Emissions Trading Scheme, as well as coal, oil, natural gas, and renewables The latest developments in gas and power markets have demonstrated the growing importance of energy risk management for utility companies and energy intensive industry. By combining energy economics models and financial engineering, Managing Energy Risk delivers a balanced perspective that captures the nuances in the exciting world of energy.

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.