Search results for: model-predictive-control-for-microgrids

Model Predictive Control for Microgrids

Author : Jiefeng Hu
File Size : 31.28 MB
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Model predictive control (MPC) is a method for controlling a process while satisfying a set of constraints. The use of MPC for controlling power systems has been gaining traction in recent years. This work presents the use of MPC for distributed renewable power generation in microgrids.

Model Predictive Control of Microgrids

Author : Carlos Bordons
File Size : 35.39 MB
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The book shows how the operation of renewable-energy microgrids can be facilitated by the use of model predictive control (MPC). It gives readers a wide overview of control methods for microgrid operation at all levels, ranging from quality of service, to integration in the electricity market. MPC-based solutions are provided for the main control issues related to energy management and optimal operation of microgrids. The authors present MPC techniques for case studies that include different renewable sources – mainly photovoltaic and wind – as well as hybrid storage using batteries, hydrogen and supercapacitors. Experimental results for a pilot-scale microgrid are also presented, as well as simulations of scheduling in the electricity market and integration of electric and hybrid vehicles into the microgrid. in order to replicate the examples provided in the book and to develop and validate control algorithms on existing or projected microgrids. Model Predictive Control of Microgrids will interest researchers and practitioners, enabling them to keep abreast of a rapidly developing field. The text will also help to guide graduate students through processes from the conception and initial design of a microgrid through its implementation to the optimization of microgrid management. 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.

Model Predictive Control of DC Microgrids

Author : Asal Zabetian Hosseini
File Size : 80.89 MB
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New Directions on Model Predictive Control

Author : Jinfeng Liu
File Size : 35.12 MB
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This book is a printed edition of the Special Issue "New Directions on Model Predictive Control" that was published in Mathematics

Solving Urban Infrastructure Problems Using Smart City Technologies

Author : John R. Vacca
File Size : 59.70 MB
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Solving Urban Infrastructure Problems Using Smart City Technologies is the most complete guide for integrating next generation smart city technologies into the very foundation of urban areas worldwide, showing how to make urban areas more efficient, more sustainable, and safer. Smart cities are complex systems of systems that encompass all aspects of modern urban life. A key component of their success is creating an ecosystem of smart infrastructures that can work together to enable dynamic, real-time interactions between urban subsystems such as transportation, energy, healthcare, housing, food, entertainment, work, social interactions, and governance. Solving Urban Infrastructure Problems Using Smart City Technologies is a complete reference for building a holistic, system-level perspective on smart and sustainable cities, leveraging big data analytics and strategies for planning, zoning, and public policy. It offers in-depth coverage and practical solutions for how smart cities can utilize resident’s intellectual and social capital, press environmental sustainability, increase personalization, mobility, and higher quality of life. Brings together experts from academia, government and industry to offer state-of- the-art solutions for urban system problems, showing how smart technologies can be used to improve the lives of the billions of people living in cities across the globe Demonstrates practical implementation solutions through real-life case studies Enhances reader comprehension with learning aid such as hands-on exercises, questions and answers, checklists, chapter summaries, chapter review questions, exercise problems, and more

Model Predictive Control Strategies for Polygeneration Systems and Microgrids

Author : Ramanunni Parakkal Menon
File Size : 33.69 MB
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Mots-clés de l'auteur: Polygeneration ; Demand Response ; Model Predictive Control ; Distributed Generation ; Microgrid.

Model Predictive Based Approach for Microgrid Control

Author : Ilja Novickij
File Size : 21.30 MB
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"The main aim of this thesis is to utilize established model predictive control strategies so that it can be used to improve microgrid efficiency and cost optimization. Current model predictive control based energy management systems can be computationally intensive and can become too slow for online optimization. An improved model predictive control based energy management system was developed to reduce the computational time and improve the scalability of the current model predictive control based control schemes. This was done by decoupling the unit commitment and economic dispatch problems, and then solving them separately. Additionally a distributed approach was explored. To properly evaluate and validate this algorithm, a hardware-in-the-loop testing platform was developed. A basic controller was first validated to ensure the hardware-in-the-loop is working and matches up with co-simulation simulation results. Next, an improved model predictive control based energy management system was proposed and then compared against one commonly found in the literature. The proposed approaches were found to perform better in terms of computational time and scalability. However, a trade-off was identified in terms of cost optimality and computational time. An additional improvement was suggested and applied to mitigate this trade-off. Finally, model predictive control was extended to include combined heat and power generation. This extended control strategy was shown to successfully control a simulated combined heat and power based microgrid when compared against a benchmark and a standard algorithm used to control combined heat and power based microgrids"--

Virtual Inertia Synthesis and Control

Author : Thongchart Kerdphol
File Size : 51.62 MB
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This book provides a thorough understanding of the basic principles, synthesis, analysis, and control of virtual inertia systems. It uses the latest technical tools to mitigate power system stability and control problems under the presence of high distributed generators (DGs) and renewable energy sources (RESs) penetration. This book uses a simple virtual inertia control structure based on the frequency response model, complemented with various control methods and algorithms to achieve an adaptive virtual inertia control respect to the frequency stability and control issues. The chapters capture the important aspects in virtual inertia synthesis and control with the objective of solving the stability and control problems regarding the changes of system inertia caused by the integration of DGs/RESs. Different topics on the synthesis and application of virtual inertia are thoroughly covered with the description and analysis of numerous conventional and modern control methods for enhancing the full spectrum of power system stability and control. Filled with illustrative examples, this book gives the necessary fundamentals and insight into practical aspects. This book stimulates further research and offers practical solutions to real-world power system stability and control problems with respect to the system inertia variation triggered by the integration of RESs/DGs. It will be of use to engineers, academic researchers, and university students interested in power systems dynamics, analysis, stability and control.

Research Anthology on Smart Grid and Microgrid Development

Author : Management Association, Information Resources
File Size : 33.49 MB
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Smart grid and microgrid technology are growing exponentially as they are adopted throughout the world. These new technologies have revolutionized the way electricity is produced, delivered, and consumed, and offer a plethora of benefits as well as the potential for further growth. It is critical to examine the current stage of smart grid and microgrid development as well as the direction they are headed as they continue to expand in order to ensure that cost-effective, reliable, and efficient systems are put in place. The Research Anthology on Smart Grid and Microgrid Development is an all-encompassing reference source of the latest innovations and trends within smart grid and microgrid development. Detailing benefits, challenges, and opportunities, it is a crucial resource to fully understand the current opportunities that smart grids and microgrids present around the world. Covering a wide range of topics such as traditional grids, future smart grids, electrical distribution systems, and microgrid integration, it is ideal for engineers, policymakers, systems developers, technologists, researchers, government officials, academicians, environmental groups, regulators, utilities specialists, industry professionals, and students.

Distributed Model Predictive Control of Power Converters in Microgrids Under Different Modes of Operation

Author : Riyadh Toman Thahab Toman
File Size : 87.18 MB
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Microgrids consist of many distributed energy sources (DERs) and the overall system is viewed as a number of subsystems. In this work, a finite control set model predictive control is proposed to control power converters in both grid and island modes of operation of the microgrid. Each subsystem is assigned a local controller that relies on measurements of common coupling point (PCC) and/or terminal quantities to provide accurate regulation of current or voltage components. This meets the local objective of each subsystem and contributes to the global objective of the microgrid. In the first part of the work, a microgrid system is considered with linear loading conditions: balanced and unbalanced portions. The control is based on decomposing voltage and current quantities into positive and negative sequence components by using synchrouns reference frames. Components to be controlled are then extracted by Notch filters. These components are mathematically modeled so that future predictions can be facilitated. In grid mode of operation, current is controlled based on the per component approach. In island mode of operation, a subsystem is singled out to be controlled by a per component voltage strategy. In the second part of this study, model predictive controllers are designed for the various converters for both linear and non-linear loading. For this purpose, multi-synchrouns reference frames are used to decompose converter and point of common coupling voltage and current quantities according to the needs of the control strategy. The cost function for each local controller extends to all components with an aim of regulating each component considered in the controls toward a set-out reference. In the third part of this work, current components extractions under a non-ideal grid mode operation are investigated. Current components obtained from the multi-synchrouns reference frames are compared with those obtained by the current physical components theory. Several loading conditions at the point of common coupling are considered under the effect of a grid voltage that is contaminated with negative sequence fundamental and positive/negative sequence harmonic voltage components. Results obtained throughout this study prove the feasibility of the individual component approach in providing regulation. In addition, with the obtained components, power quality improvements, in terms of negative sequence voltage content, can be easily implemented.