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| Author | : Rui Xie |
| Publisher | : Springer Nature |
| Total Pages | : 461 |
| Release | : |
| Genre | : |
| ISBN | : 9819725666 |
| Author | : Tinghui Ouyang |
| Publisher | : Frontiers Media SA |
| Total Pages | : 628 |
| Release | : 2022-10-14 |
| Genre | : Technology & Engineering |
| ISBN | : 2832501419 |
| Author | : Aharon Ben-Tal |
| Publisher | : Princeton University Press |
| Total Pages | : 565 |
| Release | : 2009-08-10 |
| Genre | : Mathematics |
| ISBN | : 1400831059 |
Robust optimization is still a relatively new approach to optimization problems affected by uncertainty, but it has already proved so useful in real applications that it is difficult to tackle such problems today without considering this powerful methodology. Written by the principal developers of robust optimization, and describing the main achievements of a decade of research, this is the first book to provide a comprehensive and up-to-date account of the subject. Robust optimization is designed to meet some major challenges associated with uncertainty-affected optimization problems: to operate under lack of full information on the nature of uncertainty; to model the problem in a form that can be solved efficiently; and to provide guarantees about the performance of the solution. The book starts with a relatively simple treatment of uncertain linear programming, proceeding with a deep analysis of the interconnections between the construction of appropriate uncertainty sets and the classical chance constraints (probabilistic) approach. It then develops the robust optimization theory for uncertain conic quadratic and semidefinite optimization problems and dynamic (multistage) problems. The theory is supported by numerous examples and computational illustrations. An essential book for anyone working on optimization and decision making under uncertainty, Robust Optimization also makes an ideal graduate textbook on the subject.
| Author | : Chengbin Zhang |
| Publisher | : Frontiers Media SA |
| Total Pages | : 89 |
| Release | : 2023-03-24 |
| Genre | : Technology & Engineering |
| ISBN | : 2832507484 |
| Author | : Chanan Singh |
| Publisher | : John Wiley & Sons |
| Total Pages | : 352 |
| Release | : 2018-11-13 |
| Genre | : Technology & Engineering |
| ISBN | : 1119486289 |
The groundbreaking book that details the fundamentals of reliability modeling and evaluation and introduces new and future technologies Electric Power Grid Reliability Evaluation deals with the effective evaluation of the electric power grid and explores the role that this process plays in the planning and designing of the expansion of the power grid. The book is a guide to the theoretical approaches and processes that underpin the electric power grid and reviews the most current and emerging technologies designed to ensure reliability. The authors—noted experts in the field—also present the algorithms that have been developed for analyzing the soundness of the power grid. A comprehensive resource, the book covers probability theory, stochastic processes, and a frequency-based approach in order to provide a theoretical foundation for reliability analysis. Throughout the book, the concepts presented are explained with illustrative examples that connect with power systems. The authors cover generation adequacy methods, and multi-node analysis which includes both multi-area as well as composite power system reliable evaluation. This important book: • Provides a guide to the basic methods of reliability modeling and evaluation • Contains a helpful review of the background of power system reliability evaluation • Includes information on new technology sources that have the potential to create a more reliable power grid • Addresses renewable energy sources and shows how they affect power outages and blackouts that pose new challenges to the power grid system Written for engineering students and professionals, Electric Power Grid Reliability Evaluation is an essential book that explores the processes and algorithms for creating a sound and reliable power grid.
| Author | : Bo Yang |
| Publisher | : Elsevier |
| Total Pages | : 252 |
| Release | : 2023-09-20 |
| Genre | : Business & Economics |
| ISBN | : 0443141231 |
Optimal Operation of Integrated Energy Systems Under Uncertainties: Distributionally Robust and Stochastic Models discusses new solutions to the rapidly emerging concerns surrounding energy usage and environmental deterioration. Integrated energy systems (IESs) are acknowledged to be a promising approach to increasing the efficiency of energy utilization by exploiting complementary (alternative) energy sources and storages. IESs show favorable performance for improving the penetration of renewable energy sources (RESs) and accelerating low-carbon transition. However, as more renewables penetrate the energy system, their highly uncertain characteristics challenge the system, with significant impacts on safety and economic issues. To this end, this book provides systematic methods to address the aggravating uncertainties in IESs from two aspects: distributionally robust optimization and online operation. Presents energy scheduling, considering power, gas, and carbon markets concurrently based on distributionally robust optimization methods Helps readers design day-ahead scheduling schemes, considering both decision-dependent uncertainties and decision-independent uncertainties for IES Covers online scheduling and energy auctions by stochastic optimization methods Includes analytic results given to measure the performance gap between real performance and ideal performance
| Author | : Abdulelah Habib |
| Publisher | : |
| Total Pages | : 127 |
| Release | : 2018 |
| Genre | : |
| ISBN | : |
Optimization techniques were applied to solve critical power system problems. We first studied the sizing and scheduling of stand-alone loads and generators for optimal energy utilization. The main application of this work is water treatment or desalination plants which are powered by stand-alone solar farms in off-grid setup. The techniques can also be applied to large loads operating in island modes--such as motors or pumps, steel manufacturing, and data centers. Mixed integer linear programming was used for sizing and scheduling the loads. Historical solar data was also used to optimally schedule the available resources in a selected location. Static and dynamic loads types were simulated. The second portion of this thesis focuses on methods to mitigating macrogrid power outages by utilizing available Distributed Energy Resources (DER) to supply load locally, but across several customers. Real household data was analyzed. The algorithm schedules load and demand to meet certain objective functions such as minimizing power losses or maximizing solar energy utilization and is implemented in the framework of mixed integer linear programming. Reliability metrics increased significantly through power sharing. Finally, optimization methods are applied to size a Battery Energy Storage Systems (BESS) from an economic perspective. As BESS can mitigate effects of intermittent energy production from renewable energy sources they play a critical role in peak shaving and demand charge management. The trade-off between BESS investment costs, lifetime, and revenue from utility bill savings along with microgrid ancillary services are taken into account to determine the optimal size of a BESS. The optimal size of a BESS is solved via a stochastic optimization problem considering wholesale market pricing. A stochastic model is used to schedule arbitrage services for energy storage based on the forecasted energy market pricing while accounting for BESS cost trends, the variability of renewable energy resources, and demand prediction. The approach is illustrated with an application to various realistic case studies based on pricing and demand data from the California Independent System Operator (CAISO). The case study results give insight in optimal BESS sizing from a cost perspective, based on both long-term installation schedules and daily BESS operation.
| Author | : Farkhondeh Jabari |
| Publisher | : Springer Nature |
| Total Pages | : 357 |
| Release | : 2020-07-09 |
| Genre | : Technology & Engineering |
| ISBN | : 3030424200 |
This book presents design principles, performance assessment and robust optimization of different poly-generation systems using renewable energy sources and storage technologies. Uncertainties associated with demands or the intermittent nature of renewables are considered in decision making processes. Economic and environmental benefits of these systems in comparison with traditional fossil fuels based ones are also provided. Case studies, numerical results, discussions, and concluding remarks have been presented for each proposed system/strategy. This book is a useful tool for students, researchers, and engineers trying to design and evaluate different zero-energy and zero-emission stand-alone grids.
| Author | : Yuan Tian |
| Publisher | : Springer Nature |
| Total Pages | : 759 |
| Release | : 2023-05-30 |
| Genre | : Computers |
| ISBN | : 9819933005 |
This book constitutes the refereed proceedings of the 4th International Conference on Big Data and Security, ICBDS 2022, held in Xiamen, China, during December 8–12, 2022. The 51 full papers and 3 short papers included in this book were carefully reviewed and selected from 211 submissions. They were organized in topical sections as follows: answer set programming; big data and new method; intelligence and machine learning security; data technology and network security; sybersecurity and privacy; IoT security.
| Author | : Tamas Terlaky |
| Publisher | : SIAM |
| Total Pages | : 730 |
| Release | : 2017-04-26 |
| Genre | : Mathematics |
| ISBN | : 1611974682 |
Optimization is of critical importance in engineering. Engineers constantly strive for the best possible solutions, the most economical use of limited resources, and the greatest efficiency. As system complexity increases, these goals mandate the use of state-of-the-art optimization techniques. In recent years, the theory and methodology of optimization have seen revolutionary improvements. Moreover, the exponential growth in computational power, along with the availability of multicore computing with virtually unlimited memory and storage capacity, has fundamentally changed what engineers can do to optimize their designs. This is a two-way process: engineers benefit from developments in optimization methodology, and challenging new classes of optimization problems arise from novel engineering applications. Advances and Trends in Optimization with Engineering Applications reviews 10 major areas of optimization and related engineering applications, providing a broad summary of state-of-the-art optimization techniques most important to engineering practice. Each part provides a clear overview of a specific area and discusses a range of real-world problems. The book provides a solid foundation for engineers and mathematical optimizers alike who want to understand the importance of optimization methods to engineering and the capabilities of these methods.
