As industrial, commercial, and residential demands increase and with the rise of privatization and deregulation of the electric energy industry around the world, it is necessary to improve the performance of electric operational management. Intelligent Energy Demand Forecasting offers approaches and methods to calculate optimal electric energy allocation to reach equilibrium of the supply and demand. Evolutionary algorithms and intelligent analytical tools to improve energy demand forecasting accuracy are explored and explained in relation to existing methods. To provide clearer picture of how these hybridized evolutionary algorithms and intelligent analytical tools are processed, Intelligent Energy Demand Forecasting emphasizes on improving the drawbacks of existing algorithms. Written for researchers, postgraduates, and lecturers, Intelligent Energy Demand Forecasting helps to develop the skills and methods to provide more accurate energy demand forecasting by employing novel hybridized evolutionary algorithms and intelligent analytical tools.

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.

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.

This book provides an introduction to forecasting methods for renewable energy sources integrated with existing grid. It consists of two sections; the first one is on the generation side forecasting methods, while the second section deals with the different ways of load forecasting. It broadly includes artificial intelligence, machine learning, hybrid techniques and other state-of-the-art techniques for renewable energy and load predictions. The book reflects the state of the art in distributed generation system and future microgrids and covers theory, algorithms, simulations and case studies. It offers invaluable insights through this valuable resource to students and researchers working in the fields of renewable energy, integration of renewable energy with existing grid and electrical distribution network.

There is no progress without access to energy and no energy use without supporting technology. Only one sixth of the earth's population has an easy access to sufficient energy. The other five sixth will increase their demand for energy in the future. The global environmental problems we face will increasingly affect our daily life. Adjust and fair price for energy is necessary for comparing the pros and cons of energy technology application. The road to an objective analysis of an energy system is called "Integrated Energy Analysis" and covers a cradle-to-grave system approach. This book contains such an analysis of the electricity energy system in Shandong-Province, one of China's 32 Provinces. It also presents a decision support analysis tool. It should allow decision makers in China to choose the right system of electricity supply with minimum environmental impact and/or minimum "true" cost. The book contains a DVD, which contains a more extensive record of the research results obtained. It also contains all the tools, which have been developed. The methodology presented in this book and DVD is easily applicable to other Provinces in China and also other countries and regions. This research presents a pioneering effort in bringing together the three essential partners for any such research program, Industry, Academia and the Stakeholders, i.e. prospective users of the results. An important aspect of this international program with 75 participants was the leadership provided by a dedicated and professional Program Management Team from Industry. Developing a sustainable energy supply in China is an essential part of a global strategy to promote development while mitigating environmental pollution and the effect of greenhouse gas emissions.

This book provides an updated, concise summary of forecasting air travel demand methodology. It looks at air travel demand forecasting research and attempts to outline the whole intellectual landscape of demand forecasting. It helps readers to understand the basic idea of TEI@I methodology used in forecasting air travel demand and how it is used in developing air travel demand forecasting methods. The book also discusses what to do when facing different forecasting problems making it a useful reference for business practitioners in the industry.

With different intensities, depending on the season, every morning and evening of any weekday there are the same peaks in electricity demand. Peaks can bring about significantly negative environmental and economic impacts. Demand Side Response is a relatively recent solution in Europe which has the potential to reduce peak demand and ease impending capacity shortages. Peak Energy Demand and Demand Side Response presents evidence on a set of Demand Side Response activities, ranging from price-based to incentive-based programmes and policies. Examples are drawn from different programmes for both residential and non-residential sectors of electricity demand, including Time of Use tariffs, Critical Peak Pricing Automated Demand Controllers and Ancillary Services. The book also looks at the actual energy saving impacts of smart meters, the activities which constitute peak demand and the potential opportunities associated with European smart grids and Capacity Markets. This is the first book presenting comprehensive analysis of the impacts, cost benefits and risks associated with Demand Side Response programmes and policies. It should be of interest to students, scholars and policy-makers in the areas of energy, environmental economics and applied economics.

Energy consumption and production have major influences on the economy, environment, and society, but in return they are also influenced by how the economy is structured, how the social institutions work, and how the society deals with environmental degradation. The need for integrated assessment of the relationship between energy, economy, environment, and society is clear, and this handbook offers an in-depth review of all four pillars of the energy-economy-environment-society nexus. Bringing together contributions from all over the world, this handbook includes sections devoted to each of the four pillars. Moreover, as the financialization of commodity markets has made risk analysis more complicated and intriguing, the sections also cover energy commodity markets and their links to other financial and non-financial markets. In addition, econometric modeling and the forecasting of energy needs, as well as energy prices and volatilities, are also explored. Each part emphasizes the multidisciplinary nature of the energy economics field and from this perspective, chapters offer a review of models and methods used in the literature. The Routledge Handbook of Energy Economics will be of great interest to all those studying and researching in the area of energy economics. It offers guideline suggestions for policy makers as well as for future research.