Catálogo de publicaciones

Future of Utilities - Utilities of the Future: How technological innovations in distributed generation will reshape the electric power sector relates the latest information on the electric power sector its rapid transformation, particularly on the distribution network and customer side. Trends like the rapid rise of self-generation and distributed generation, microgrids, demand response, the dissemination of electric vehicles and zero-net energy buildings that promise to turn many consumers into prosumers are discussed.

The book brings together authors from industry and academic backgrounds to present their original, cutting-edge and thought-provoking ideas on the challenges currently faced by electric utilities around the globe, the opportunities they present, and what the future might hold for both traditional players and new entrants to the sector.

The book's first part lays out the present scenario, with concepts such as an integrated grid, microgrids, self-generation, customer-centric service, and pricing, while the second part focuses on how innovation, policy, regulation, and pricing models may come together to form a new electrical sector, exploring the reconfiguring of the current institutions, new rates design in light of changes to retail electricity markets and energy efficiency, and the cost and benefits of integration of distributed or intermittent generation, including coupling local renewable energy generation with electric vehicle fleets.

The final section projects the future function and role of existing electrical utilities and newcomers to this sector, looking at new pathways for business and pricing models, consumer relations, technology, and innovation.

• Contains discussions that help readers understand the underlying causes and drivers of change in the electrical sector, and what these changes mean in financial, operational, and regulatory terms
• Provides thought-provoking ideas on the challenges currently faced by electric utilities around the globe, the opportunities they present, and what the future might hold for both traditional players and new entrants to the sector
• Helps readers anticipate what developments are likely to define the function and role of the utility of the future

Fuzzy Modeling and Genetic Algorithms for Data Mining and Exploration is a handbook for analysts, engineers, and managers involved in developing data mining models in business and government. As you’ll discover, fuzzy systems are extraordinarily valuable tools for representing and manipulating all kinds of data, and genetic algorithms and evolutionary programming techniques drawn from biology provide the most effective means for designing and tuning these systems.

You don’t need a background in fuzzy modeling or genetic algorithms to benefit, for this book provides it, along with detailed instruction in methods that you can immediately put to work in your own projects. The author provides many diverse examples and also an extended example in which evolutionary strategies are used to create a complex scheduling system.

* Written to provide analysts, engineers, and managers with the background and specific instruction needed to develop and implement more effective data mining systems.
* Helps you to understand the trade-offs implicit in various models and model architectures.
* Provides extensive coverage of fuzzy SQL querying, fuzzy clustering, and fuzzy rule induction.
* Lays out a roadmap for exploring data, selecting model system measures, organizing adaptive feedback loops, selecting a model configuration, implementing a working model, and validating the final model.
* In an extended example, applies evolutionary programming techniques to solve a complicated scheduling problem.
* Presents examples in C, C++, Java, and easy-to-understand pseudo-code.
* Extensive online component, including sample code and a complete data mining workbench.

AN INDISPENSABLE RESOURCE FOR ALL THOSE WHO DESIGN AND IMPLEMENT TYPE-1 AND TYPE-2 FUZZY NEURAL NETWORKS IN REAL TIME SYSTEMS

Delve into the type-2 fuzzy logic systems and become engrossed in the parameter update algorithms for type-1 and type-2 fuzzy neural networks and their stability analysis with this book!

Not only does this book stand apart from others in its focus but also in its application-based presentation style. Prepared in a way that can be easily understood by those who are experienced and inexperienced in this field. Readers can benefit from the computer source codes for both identification and control purposes which are given at the end of the book.

A clear and an in-depth examination has been made of all the necessary mathematical foundations, type-1 and type-2 fuzzy neural network structures and their learning algorithms as well as their stability analysis.

You will find that each chapter is devoted to a different learning algorithm for the tuning of type-1 and type-2 fuzzy neural networks; some of which are:

• Gradient descent

• Levenberg-Marquardt

• Extended Kalman filter

In addition to the aforementioned conventional learning methods above, number of novel sliding mode control theory-based learning algorithms, which are simpler and have closed forms, and their stability analysis have been proposed. Furthermore, hybrid methods consisting of particle swarm optimization and sliding mode control theory-based algorithms have also been introduced.

The potential readers of this book are expected to be the undergraduate and graduate students, engineers, mathematicians and computer scientists. Not only can this book be used as a reference source for a scientist who is interested in fuzzy neural networks and their real-time implementations but also as a course book of fuzzy neural networks or artificial intelligence in master or doctorate university studies. We hope that this book will serve its main purpose successfully.

• Parameter update algorithms for type-1 and type-2 fuzzy neural networks and their stability analysis
• Contains algorithms that are applicable to real time systems
• Introduces fast and simple adaptation rules for type-1 and type-2 fuzzy neural networks
• Number of case studies both in identification and control
• Provides MATLAB^® codes for some algorithms in the book

Reinforced concrete is one of the most widely used modern materials of construction. It is comparatively cheap, readily available, and suitable for a variety of building and construction applications.

This reference provides a detailed resource covering all aspects of this important material. Both servicability and durability aspects are well covered, with all the information needed maximise the life of buildings constructed from it.

Containing an up-to-date and comprehensive collection of technical information and data from world renound authors, it will be a valuable source of reference for academics, researchers, students and professionals alike.

*Provides information vital to prolong the life of buildings constructed from this versatile material

* Brings together a disparate body of knowledge from many parts of the world into a concise and authoritative text

*Containing an up-to-date and comprehensive collection of technical information