Springer eBooks may be purchased by end-customers only and are sold without copy protection (DRM free). Instead, all eBooks include personalized watermarks. This means you can read the Springer eBooks across numerous devices such as Laptops, eReaders, and tablets.
You can pay for Springer eBooks with Visa, Mastercard, American Express or Paypal.
After the purchase you can directly download the eBook file or read it online in our Springer eBook Reader. Furthermore your eBook will be stored in your MySpringer account. So you can always re-download your eBooks.
Approaches the problem of electric power system architecture evolution.
Helps readers develop dedicated systems-engineering based modeling and simulation tools.
Discusses the dynamic and distributed risk management under various uncertainties, such as physical (reliability-related) and financial.
Describes the inherent features of several possible future architectures.
Engineering IT-Enabled Electricity Services: The Tale of Two Low-Cost Green Azores Islands covers sustainable energy services to customers - a balanced choice and coordination of energy generated by traditional and alternative sources. The “Green Islands” project represents a decade of work by over a dozen researchers who have developed a model designed to utilize the potential of distributed clean resources. The key is the proper use of Information Technology (IT). Sited on two islands in the Azores, the project developed the model of careful forecasting of demand and supply, down to the minute, coordinating the output of conventional power plants, wind energy, fly wheels, hydroelectricity, demand reduction, and even plug-in electric vehicles to take full advantage of the clean resources available.
This contributed volume presents methods for predicting variable resources, such as wind power generation, and analyzes the achievable accuracy of these predictions. Throughout this book, contributors show that the cost of serving customers in systems with highly uncertain generation will depend to a very large extent on how well the predictions are done. Therefore, the supporting IT technologies based on predictive models become critical to avoid the need for fast-responding storage. The model the authors have developed could change the way power portfolios are built. A new perspective for optimization of green energy is presented in this book. Data provided with the book represents a repository of real-world electric energy systems and its IT-enabled smarts.