Energy demands throughout the globe has been increasing and the detrimental effects of carbon emissions on the environment by use of non-renewable resources has impacted life on the planet. The changing climate has caused an increase in natural calamities all over the globe. Many countries in the world have started to produce power using renewable resources like solar, biomass, wind energy, nuclear energy and green fuels. Though there are several technologies for power generation using the above sources, efficient design of these systems still needs lot of research. Mathematical modeling would play a vital role in design of state of the art technologies. Advanced nuclear power plants need special mention since they involve naturally driven safety systems where the complex phenomena of boiling, condensation and thermal stratification take place. These are difficult to model as there is more than one phase coupled with turbulence models, near wall phenomena, coalescence and break up, etc. Scaling up of such systems and their innovative design to reduce stratification requires the help of mathematical modeling. Other opportunities include Computational Fluid Dynamics (CFD) modeling for design of wind turbines for power generation using wind energy. Power generation from biomass involves use of gasifiers which has complex set of reactions and mostly two or three phases which are difficult to model using CFD at industrial scales.

Electricity is the lifeblood of modern society, and for the vast majority of people that electricity is obtained from large, interconnected power grids. However, the grid that was developed in the 20th century, and the incremental improvements made since then, including its underlying analytic foundations, is no longer adequate to completely meet the needs of the 21st century. The next-generation electric grid must be more flexible and resilient. While fossil fuels will have their place for decades to come, the grid of the future will need to accommodate a wider mix of more intermittent generating sources such as wind and distributed solar photovoltaics. Achieving this grid of the future will require effort on several fronts. There is a need for continued shorter-term engineering research and development, building on the existing analytic foundations for the grid. But there is also a need for more fundamental research to expand these analytic foundations. Analytic Research Foundations for the Next-Generation Electric Grid provide guidance on the longer-term critical areas for research in mathematical and computational sciences that is needed for the next-generation grid. It offers recommendations that are designed to help direct future research as the grid evolves and to give the nation's research and development infrastructure the tools it needs to effectively develop, test, and use this research.

This edited monograph offers a summary of future mathematical methods supporting the recent energy sector transformation. It collects current contributions on innovative methods and algorithms. Advances in mathematical techniques and scientific computing methods are presented centering around economic aspects, technical realization and large-scale networks. Over twenty authors focus on the mathematical modeling of such future systems with careful analysis of desired properties and arising scales. Numerical investigations include efficient methods for the simulation of possibly large-scale interconnected energy systems and modern techniques for optimization purposes to guarantee stable and reliable future operations. The target audience comprises research scientists, researchers in the R&D field, and practitioners. Since the book highlights possible future research directions, graduate students in the field of mathematical modeling or electrical engineering may also benefit strongly.

This reference text introduces latest mathematical modeling techniques and analysis for renewable energy systems. It comprehensively covers important topics including study of combustion characteristics of laser ignited gasoline-air mixture, hierarchical demand response controller, mathematical modeling of an EOQ for a multi-item inventory system, and integration and modeling of small-scale pumped storage with micro optimization model (HOMER). Aimed at graduate students and academic researchers in the fields of electrical engineering, environmental engineering, mechanical engineering, and civil engineering, this text: Discusses applied mathematical modeling techniques in renewable energy. Covers effective storage and generation of power through renewable energy generation sources. Provides real life applications and problems based on renewable energy. Covers new ways of applying mathematical techniques for applications in diverse areas of science and engineering.

Proceedings of the NATO Advanced Study Institute, Istanbul, Turkey, June 1979

This book provides the insight of various topology and control algorithms used for power control in distributed energy power conversion systems such as solar, wind, and other power sources. It covers traditional and advanced control algorithms of power filtering including modelling and simulations, and hybrid power generation systems. The adaptive control, model predictive control, fuzzy-based controllers, Artificial Intelligence-based control algorithm, and optimization techniques application for estimating the error regulator gains are discussed. Features of this book include the following: Covers the schemes for power quality enhancement, and voltage and frequency control. Provides complete mathematical modelling and simulation results of the various configurations of the renewable energy-based distribution systems. Includes design, control, and experimental results. Discusses mathematical modelling of classical and adaptive control techniques. Explores recent application of control algorithm and power conversion. This book is aimed at researchers, professionals, and graduate students in power electronics, distributed power generation systems, control engineering, Artificial Intelligent-based control algorithms, optimization techniques, and renewable energy systems.

Mathematical Models and Algorithms for Power System Optimization helps readers build a thorough understanding of new technologies and world-class practices developed by the State Grid Corporation of China, the organization responsible for the world's largest power distribution network. This reference covers three areas: power operation planning, electric grid investment and operational planning and power system control. It introduces economic dispatching, generator maintenance scheduling, power flow, optimal load flow, reactive power planning, load frequency control and transient stability, using mathematic models including optimization, dynamic, differential and difference equations. Provides insights on the development of new mathematical models of power system optimization Analyzes power systems comprehensively to create novel mathematic models and algorithms for issues related to the planning operation of power systems Includes research on the optimization of power systems and related practical research projects carried out since 1981