Decision And Control In Hybrid Wind Farms

This book focuses on two of the most important aspects of wind farm operation: decisions and control. The first part of the book deals with decision-making processes, and explains that hybrid wind farm operation is governed by a set of alternatives that the wind farm operator must choose from in order to achieve optimal delivery of wind power to the utility grid. This decision-making is accompanied by accurate forecasts of wind speed, which must be known beforehand. Errors in wind forecasting can be compensated for by pumping power from a reserve capacity to the grid using a battery energy storage system (BESS). Alternatives based on penalty cost are assessed using certain criteria, and MCDM methods are used to evaluate the best choice. Further, considering the randomness in the dynamic phenomenon in wind farms, a fuzzy MCDM approach is applied during the decision-making process to evaluate the best alternative for hybrid wind farm operation. Case studies from wind farms in the USA are presented, together with numerical solutions to the problem. In turn, the second part deals with the control aspect, and especially with yaw angle control, which facilitates power maximization at wind farms. A novel transfer function-based methodology is presented that controls the wake center of the upstream turbine(s); lidar-based numerical simulation is carried out for wind farm layouts; and an adaptive control strategy is implemented to achieve the desired yaw angle for upstream turbines. The proposed methodology is tested for two wind farm layouts. Wake management is also implemented for hybrid wind farms where BESS life enhancement is studied. The effect of yaw angle on the operational cost of BESS is assessed, and case studies for wind farm datasets from the USA and Denmark are discussed. Overall, the book provides a comprehensive guide to decision and control aspects for hybrid wind farms, which are particularly important from an industrial standpoint.

The reduction of greenhouse gas emissions is a major governmental goal worldwide. The main target, hopefully by 2050, is to move away from fossil fuels in the electricity sector and then switch to clean power to fuel transportation, buildings and industry. This book discusses important issues in the expanding field of wind farm modeling and simulation as well as the optimization of hybrid and micro-grid systems. Section I deals with modeling and simulation of wind farms for efficient, reliable and cost-effective optimal solutions. Section II tackles the optimization of hybrid wind/PV and renewable energy-based smart micro-grid systems.

Supervised Machine Learning in Wind Forecasting and Ramp Event Prediction provides an up-to- date overview on the broad area of wind generation and forecasting, with a focus on the role and need of Machine Learning in this emerging field of knowledge. Various regression models and signal decomposition techniques are presented and analyzed, including least-square, twin support and random forest regression, all with supervised Machine Learning. The specific topics of ramp event prediction and wake interactions are addressed in this book, along with forecasted performance. Wind speed forecasting has become an essential component to ensure power system security, reliability and safe operation, making this reference useful for all researchers and professionals researching renewable energy, wind energy forecasting and generation. Features various supervised machine learning based regression models Offers global case studies for turbine wind farm layouts Includes state-of-the-art models and methodologies in wind forecasting

This book presents the proceedings of the 8th International Workshop on Soft Computing Applications, SOFA 2018, held on 13–15 September 2018 in Arad, Romania. The workshop was organized by Aurel Vlaicu University of Arad, in conjunction with the Institute of Computer Science, Iasi Branch of the Romanian Academy, IEEE Romanian Section, Romanian Society of Control Engineering and Technical Informatics – Arad Section, General Association of Engineers in Romania – Arad Section and BTM Resources Arad. The papers included in these proceedings, published post-conference, cover the research including Knowledge-Based Technologies for Web Applications, Cloud Computing, Security Algorithms and Computer Networks, Business Process Management, Computational Intelligence in Education and Modelling and Applications in Textiles and many other areas related to the Soft Computing. The book is directed to professors, researchers, and graduate students in area of soft computing techniques and applications.

This book presents a comprehensive definition of smart grids and their benefits, and compares smart and traditional grids. It also introduces a design methodology for stand-alone hybrid renewable energy system with and without applying the smart grid concepts for comparison purposes. It discusses using renewable energy power plants to feed loads in remote areas as well as in central power plants connected to electric utilities. Smart grid concepts used in the design of the hybrid renewable power systems can reduce the size of components, which can be translated to a reduction in the cost of generated energy. The proposed hybrid renewable energy system includes wind, photovoltaic, battery, and diesel, and is used initially to feed certain loads, covering the load required completely. The book introduces a novel methodology taking the smart grid concept into account by dividing the loads into high and low priority parts. The high priority part should be supplied at any generated conditions. However, the low priority loads can be shifted to the time when the generated energy from renewable energy sources is greater than the high priority loads requirements. The results show that the use of this smart grid concept reduces the component size and the cost of generated energy compared to that without dividing the loads. The book also describes the use of smart optimization techniques like particle swarm optimization (PSO) and genetic algorithm (GA) to optimally design the hybrid renewable energy system. This book provides an excellent background to renewable energy sources, optimal sizing and locating of hybrid renewable energy sources, the best optimization methodologies for sizing and designing the components of hybrid renewable energy systems, and offers insights into using smart grid concepts in the system’s design and sizing. It also helps readers understand the dispatch methodology and how to connect the system’s different components, their modeling, and the cost analysis of the system.

The subject of energy storage is extremely important for the increased utilization of renewable energies such as solar and wind energy in times when their sources (e.g. the sun and wind) are unavailable. The ability to store energy can also level out the demand curve for electricity and thus lead to a decrease in the peak requirements of energy production. A storage system for ground transportation is also important as a potential replacement for fossil fuel powered transportation. Energy Storage offers a comprehensive look at the possible approaches to energy storage, which are relevant to various situations; from smoothing demand in electrical energy production, applications of energy storage, to transportation. The book covers a variety of approaches to the storage of energy. Beginning with a discussion of the critical importance of energy storage, the book discusses various possible storage options including hydro storage, compressed air energy storage, and electrical and chemical storage in batteries, capacitors and fuel cells. There is also a chapter on the mechanical storage of energy with flywheels using advanced materials. The various applications to power production and transportation are also included. The expertise and active involvement of the authors of the various chapters ensures that the information is reliable, current, and forward looking.

Wind energy systems are central contributors to renewable energy generation, and their technology is continuously improved and updated. Without losing sight of theory, Control of Large Wind Energy Systems demonstrates how to implement concrete control systems for modern wind turbines, explaining the reasons behind choices and decisions. This book provides an extended treatment of different control topics divided into three thematic parts including modelling, control and implementation. Solutions for real-life difficulties such as multi-parameter tuning of several controllers, curve fitting of nonlinear power curves, and filter design for concrete signals are also undertaken. Examples and a case study are included to illustrate the parametrization of models, the control systems design with problems and possible solutions. Advice for the selection of control laws, calculation of specific parameters, which are necessary for the control laws, as the sensitivity functions, is given, as well as an evaluation of control performance based on indices and load calculation. Control of Large Wind Energy Systems covers methodologies which are not usually found in literature on this topic, including fractional order PID and nonlinear PID for pitch control, peak shaving control and extremum seeking control for the generator control, yaw control and shutdown control. This makes it an ideal book for postgraduate students, researchers and industrial engineers in the field of wind turbine control. Advances in Industrial Control reports and encourages the transfer of technology in control engineering. The rapid development of control technology has an impact on all areas of the control discipline. The series offers an opportunity for researchers to present an extended exposition of new work in all aspects of industrial control.