Microgrid Energy Management
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Artificial Intelligence Based Energy Management Systems For Smart Microgrids
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Author : Baseem Khan
language : en
Publisher: CRC Press
Release Date : 2022-06-07
Artificial Intelligence Based Energy Management Systems For Smart Microgrids written by Baseem Khan and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-06-07 with Technology & Engineering categories.
Modeling and optimization of energy management systems for micro- and mini-grids play an important role in the fields of energy generation dispatch, system operation, protection coordination, power quality issues, and peak demand conflict with grid security. This comprehensive reference text provides an in-depth insight into these topics. This text discusses the use of meta-heuristic and artificial intelligence algorithms for developing energy management systems with energy use prediction for mini- and microgrid systems. It covers important concepts including modeling of microgrid and energy management systems, optimal protection coordination-based microgrid energy management, optimal energy dispatch with energy management systems, and peak demand management with energy management systems. Key Features: Presents a comprehensive discussion of mini- and microgrid concepts Discusses AC and DC microgrid modeling in detail Covers optimization of mini- and microgrid systems using AI and meta-heuristic techniques Provides MATLAB®-based simulations on a mini- and microgrid Comprehensively discussing concepts of microgrids with the help of software-based simulations, this text will be useful as a reference text for graduate students and professionals in the fields of electrical engineering, electronics and communication engineering, renewable energy, and clean technology.
Microgrid Energy Management
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Author : Pietro Varilone
language : en
Publisher:
Release Date : 2021
Microgrid Energy Management written by Pietro Varilone and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021 with categories.
In IEEE Standards, a Microgrid is defined as a group of interconnected loads and distributed energy resources with clearly defined electrical boundaries, which acts as a single controllable entity with respect to the grid and can connect and disconnect from the grid to enable it to operate in both grid-connected or island modes. This Special Issue focuses on innovative strategies for the management of the Microgrids and, in response to the call for papers, six high-quality papers were accepted for publication. Consistent with the instructions in the call for papers and with the feedback received from the reviewers, four papers dealt with different types of supervisory energy management systems of Microgrids (i.e., adaptive neuro-fuzzy wavelet-based controls, cost-efficient power-sharing techniques, and two-level hierarchical energy management systems); the proposed energy management systems are of quite general purpose and aim to reduce energy usages and monetary costs. In the last two papers, the authors concentrate their research efforts on the management of specific cases, i.e., Microgrids with electric vehicle charging stations and for all-electric ships.
Fundamentals Of Microgrids
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Author : Stephen A. Roosa
language : en
Publisher: CRC Press
Release Date : 2020-09-03
Fundamentals Of Microgrids written by Stephen A. Roosa and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-09-03 with Technology & Engineering categories.
Microgrids provide opportunities to develop new electrical networks targeted for the needs of communities. The fourth industrial revolution is associated with the global trend toward decentralizing energy grids. Within this context, microgrids are seen as a solution to how renewable electricity can be supplied to local areas. The Fundamentals of Microgrids: Development and Implementation provides an in-depth examination of microgrid energy sources, applications, technologies, and policies. This book considers the fundamental configurations and applications for microgrids and examines their use as a means of meeting international sustainability goals. It focuses on questions and issues associated with microgrid topologies, development, implementation and regulatory issues. Distributed energy resources are defined, stand-a-lone generation systems are described and examples of typical microgrid configurations are provided. The key components of developing a business model for microgrid development are also considered. Features: Describes what microgrids are and details the basics of how they work while considering benefits of microgrids and their disadvantages. Provides answers to the fundamental questions energy managers and other professionals want to know about the basics of microgrids. Details the applications for microgrids and demystifies the types of microgrid architectures that are successful. Includes real-world examples of functioning microgrids which provide models for the development of microgrids in the future. Discusses the key considerations that must be addressed to develop a business case for microgrid development.
Artificial Intelligence Based Energy Management Systems For Smart Micro Grids
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Author : Baseem Khan
language : en
Publisher:
Release Date : 2022
Artificial Intelligence Based Energy Management Systems For Smart Micro Grids written by Baseem Khan and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022 with Microgrids (Smart power grids) categories.
"Modeling and optimization of energy management systems for micro and mini-grids play an important role in the fields of energy generation dispatch, and peak demand confliction with grid security. This comprehensive reference text provides an in-depth insight into these topics. The text discusses the use of metaheuristic and artificial intelligent (AI) algorithms for developing energy management systems with energy usage prediction for mini and microgrid systems. It covers important concepts including modeling of microgrid and energy management systems, blockchain-based microgrid energy management, optimal energy dispatch with energy management systems, and peak demand management with energy management systems. The text will be useful for graduate students and professionals in the fields of electrical engineering, electronics and communication engineering, renewable energy, and clean technologies"--
Urban Dc Microgrid
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Author : Manuela Sechilariu
language : en
Publisher: Butterworth-Heinemann
Release Date : 2016-05-10
Urban Dc Microgrid written by Manuela Sechilariu and has been published by Butterworth-Heinemann this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-05-10 with Technology & Engineering categories.
Urban DC Microgrid: Intelligent Control and Power Flow Optimization focuses on microgrids for urban areas, particularly associated with building-integrated photovoltaic and renewable sources. This book describes the most important problems of DC microgrid application, with grid-connected and off-grid operating modes, aiming to supply DC building distribution networks. The book considers direct current (DC) microgrid to supply DC building distribution networks for positive energy buildings; dynamic interactions with the utility grid based on communication with the smart grid; supervisory control systems; and energy management. The global power system is exposed and the DC microgrid system is presented and analyzed with results and discussion, highlighting both the advantages and limitations of the concept. Coverage at the system level of microgrid control as well as the various technical aspects of the power system components make this a book interesting to academic researchers, industrial energy researchers, electrical power and power system professionals. Provides a strong overview of microgrid modelling Describes the most important problems of DC microgrid application, with grid-connected and off-grid operating modes, aiming to supply DC building distribution networks Offers experimental problem examples and results Includes supervisory control and energy management
Energy Management In Homes And Residential Microgrids
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Author : Reza Hemmati
language : en
Publisher: Elsevier
Release Date : 2023-09-25
Energy Management In Homes And Residential Microgrids written by Reza Hemmati and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-09-25 with Computers categories.
Energy Management in Homes and Residential Microgrids: Short-Term Scheduling and Long-Term Planning provides an in-depth exploration of Home Energy Management Systems (HEMS), with a focus on practical applications for both short- and long-term models. Through this guide, readers will learn how to create efficient systems that facilitate the integration of renewable energy into the grid and simultaneously manage end-users' energy consumption. The short-term operation of Home Energy Management Systems is analyzed through various lenses, including renewable energy integration, energy storage integration, uncertainty in parameters, off-grid operation, outages and events, resilience, electric vehicle integration, and battery swapping strategy. The modelling of these topics is explained with step-by-step instructions, and the parameters and implications are thoroughly discussed. Additionally, the book offers insight into the long-term expansion planning for residential microgrids, providing a detailed examination of dynamic modeling, control, and stability of these small-scale energy systems. Throughout the book, simple and advanced examples are provided, and each example comes with numerical data, detailed formulation, modelling, and simulation. Energy Management in Homes and Residential Microgrids: Short-Term Scheduling and Long-Term Planning is a valuable reference and learning tool for students, researchers, and engineers working on short-term and long-term energy management systems in homes and residential microgrids. Explains how to model all systems as mixed integer linear programming in GAMS software alongside step-by-step instructions Offers numerous examples for each topic discussed, using both simple and advanced concepts Accounts for problems by providing solutions to practical situations and real-world conditions for both short-term and long-term models
Energy Management Of Distributed Generation Systems
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Author : Lucian Mihet-Popa
language : en
Publisher: BoD – Books on Demand
Release Date : 2016-07-13
Energy Management Of Distributed Generation Systems written by Lucian Mihet-Popa and has been published by BoD – Books on Demand this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-07-13 with Technology & Engineering categories.
The book contains 10 chapters, and it is divided into four sections. The first section includes three chapters, providing an overview of Energy Management of Distributed Systems. It outlines typical concepts, such as Demand-Side Management, Demand Response, Distributed, and Hierarchical Control for Smart Micro-Grids. The second section contains three chapters and presents different control algorithms, software architectures, and simulation tools dedicated to Energy Management Systems. In the third section, the importance and the role of energy storage technology in a Distribution System, describing and comparing different types of energy storage systems, is shown. The fourth section shows how to identify and address potential threats for a Home Energy Management System. Finally, the fifth section discusses about Economical Optimization of Operational Cost for Micro-Grids, pointing out the effect of renewable energy sources, active loads, and energy storage systems on economic operation.
Energy Management In Microgrids Algorithms And System
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Author : Wenbo Shi
language : en
Publisher:
Release Date : 2015
Energy Management In Microgrids Algorithms And System written by Wenbo Shi and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015 with categories.
Microgrids, as one of the key components to enable the future smart grid, refer to low-voltage power distribution systems integrated with distributed energy resources (DERs) and controllable loads, which can operate either with or without the grid (i.e., grid-connected or islanded mode). The integration of DERs and controllable loads brings tremendous opportunities to increase power system efficiency, sustainability, and reliability. However, the intermittency and variability of renewable DERs and limited supply especially when the microgrid is operating in islanded mode introduce significant challenges to maintain the fundamental supply-demand balance for system stability. Therefore, the goal of this dissertation is to solve the supply-demand balancing problem in microgrids using optimization-based energy management. Most of the existing energy management algorithms in the literature consider the aggregate supply-demand balance as an abstract mathematical function while omitting the underlying power distribution network and the associated power flow and system operational constraints. Consequently, such approaches may result in control decisions that violate the real-world constraints. Therefore, in the first part of this dissertation, we study the supply-demand balancing problem in microgrids under more realistic conditions and propose algorithms for microgrid energy management that take into account the power flow and system operational constraints on a distribution network. By incorporating the distribution network in the modeling, we present the relationship between the physical structure of a microgrid and the energy management on the network. Another major challenge in microgrid energy management is to design a two-way communication system in order to implement the algorithms. A variety of heterogeneous devices in a microgrid need to be managed by such a system using the energy management algorithms. Unfortunately, most of those devices still use proprietary protocols and cannot interoperate with each other. Furthermore, many devices managed by the system reside on the customer side requiring autonomy and local intelligence. Therefore, in the second part of this dissertation, we focus on the design and implementation of a system architecture that enables interoperability and autonomy for microgrid energy management. We present the design of a unified communication interface that is protocol and technology agnostic for interoperability and a decentralized system architecture for autonomy on the customer side.
Microgrid Technologies
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Author : C. Sharmeela
language : en
Publisher: John Wiley & Sons
Release Date : 2021-04-13
Microgrid Technologies written by C. Sharmeela and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-04-13 with Computers categories.
Microgrid technology is an emerging area, and it has numerous advantages over the conventional power grid. A microgrid is defined as Distributed Energy Resources (DER) and interconnected loads with clearly defined electrical boundaries that act as a single controllable entity concerning the grid. Microgrid technology enables the connection and disconnection of the system from the grid. That is, the microgrid can operate both in grid-connected and islanded modes of operation. Microgrid technologies are an important part of the evolving landscape of energy and power systems. Many aspects of microgrids are discussed in this volume, including, in the early chapters of the book, the various types of energy storage systems, power and energy management for microgrids, power electronics interface for AC & DC microgrids, battery management systems for microgrid applications, power system analysis for microgrids, and many others. The middle section of the book presents the power quality problems in microgrid systems and its mitigations, gives an overview of various power quality problems and its solutions, describes the PSO algorithm based UPQC controller for power quality enhancement, describes the power quality enhancement and grid support through a solar energy conversion system, presents the fuzzy logic-based power quality assessments, and covers various power quality indices. The final chapters in the book present the recent advancements in the microgrids, applications of Internet of Things (IoT) for microgrids, the application of artificial intelligent techniques, modeling of green energy smart meter for microgrids, communication networks for microgrids, and other aspects of microgrid technologies. Valuable as a learning tool for beginners in this area as well as a daily reference for engineers and scientists working in the area of microgrids, this is a must-have for any library.
Microgrid Energy Management System Control Using Reinforcement Learning
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Author : Sam Mottahedi
language : en
Publisher:
Release Date : 2022
Microgrid Energy Management System Control Using Reinforcement Learning written by Sam Mottahedi and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022 with categories.
Microgrids are becoming increasingly popular due to their benefits in terms of energy efficiency, reliability, and resilience. Smart microgrids use advanced control systems to optimize the operation of distributed energy resources (DERs) such as wind turbines, solar PV arrays, and batteries. The goal of smart microgrid controllers is to ensure that the power supplied by DERs matches the load demand as closely as possible while minimizing emissions and operating costs. However, the stochastic nature of DERs may lead to imbalances in supply and demand in the microgrid environment. Energy storage systems, battery control, and operation advances can address these imbalances. In recent years, Reinforcement Learning (RL) algorithms have been widely seen as a competitive approach to solving sequential decision-making problems. Following groundbreaking results in other fields, they are becoming a popular approach in building energy management system research. However, due to the long training time, millions of interactions required during training reinforcement learning agents, and the lack of a standardized simulation environment used in the field, it has been challenging to assess the progress of algorithms applied in the building energy domain. This research is focused on the Energy Management Systems (EMS) application of a deep reinforcement learning algorithm in the presence of stochastic renewable energy sources. To this end, we leveraged existing Building Energy Models (BEM) to design a simulation environment for a small microgrid featuring photovoltaic panels (PV), wind turbines, and short-term storage devices (batteries). Next, We benchmarked popular model-free reinforcement learning algorithms on three tasks to assess their asymptotic performance and sample efficiency. Results show that model-free reinforcement learning algorithms require a tremendous amount of training data to learn successful policies. In addition, during the training procedure and operation, the agent repeatedly takes action that violates safety. To address these issues, the second half of this research study will focus on model-based reinforcement learning algorithms by learning dynamic models of the environment and propose a safe model-based reinforcement learning algorithm based on the constrained Markov Decision Process (CMDP). This dissertation completed four research steps to achieve the research objectives. In the first part of this thesis, we focus on nonintrusive load monitoring techniques where the smart metering data can be disaggregated to individual components for each appliance. The disaggregated data can be integrated into the energy management system to create an efficient microgrid operation without using the high-cost sensor and provide a cost-effective solution. The proposed approach produces a bijective representation with unique polar coordinates, preserving the absolute temporal relationship in the data. Compared to other deep learning architectures used for time-series data, the induced representation can be learned using Convolutional Neural Networks that are parallelizable and scalable. Second, a simulation environment is developed with a detailed Energy Plus (EP) building model that can interact with the Python ecosystem, which enables us to experiment with reinforcement learning-based strategies using sophisticated building models and state-of-the-art deep learning frameworks such as Tensorflow and Pytorch. We implemented a Deep Deterministic Policy Gradient (DDPG) Reinforcement Learning (RL) for the control and operation of a commercial building equipped with battery storage and a photovoltaic (PV) system. We showed that the agent could optimize the objective function based on the provided reward function even with limited and incomplete environmental information. We explored two reward functions for peak reduction and cost minimization. Third, we benchmarked five popular model-free reinforcement learning algorithms on cost minimization, HVAC control, and combined cost minimization and HVAC control. We systematically evaluated the sample efficiency, convergence property, and practical details in training each reinforcement learning algorithm. We found that Proximal Policy Optimization (PPO) showed competitive performance in all tasks, combined with ease of implementation and robustness to changes in model hyperparameters. In the last part of this dissertation, we identified long training time and lack of safety guarantee during the algorithm deployment as significant roadblocks to broader adoption of reinforcement learning in a smart microgrid. To this end, we presented an effective constrained reinforcement learning algorithm formulated under the constrained Markov Decision Process with no additional assumptions on system dynamics. The proposed model-based reinforcement learning algorithm (MPC-CDCEM) induces a differentiable policy that allows an end-to-end learning process while enforcing constraint feasibility. We evaluated the proposed algorithm in the Safety Gym environment, which outperforms other constrained reinforcement algorithms (CPO) and unconstrained reinforcement learning algorithms with the modified objective function. We also evaluated the proposed algorithm in a building energy management environment to minimize energy consumption while ensuring occupants' thermal comfort and preventing excessive cycles. The proposed algorithm saves $12.3\%$ energy compared to the default nighttime setup (NSU) and achieves a comparable result to the MPC-CEM algorithm while showing a considerable reduction in constraints violations. This dissertation demonstrated many potential benefits of using reinforcement learning in energy management systems, but several significant impediments need to be addressed before this technology can be widely adopted. We developed a test-bed to implement and evaluate different reinforcement learning algorithms and identified several issues with current model-free reinforcement learning algorithms. We then proposed a safe reinforcement learning algorithm that addresses these issues. The thesis results indicate the need for developing practical algorithms that are easy to train and can safely operate in critical physical infrastructure. Further development is needed to ensure these algorithms can operate reliably in real-world settings.
