Download or read book Exploiting the Structure of Distributed Constraint Optimization Problems with Applications in Smart Grids written by Ferdinando Fioretto and published by . This book was released on 2016 with total page 544 pages. Available in PDF, EPUB and Kindle. Book excerpt: Distributed Constraint Optimization Problems (DCOPs) have emerged as one of the prominent multi-agent architectures to govern the agents’ autonomous behavior in a Multi-Agent System (MAS), where several agents coordinate with each other to optimize a global cost function. They represent a powerful approach to the description and resolution of many practical problems and serve several applications such as distributed scheduling, coordination of unmanned air vehicles, smart grid electric networks, and sensor networks. Typical real world applications are characterized by complex dynamics and interactions among a large number of entities, which translate into hard combinatorial problems, posing significant challenges from a computational point of view. The adoption of DCOPs on large instances of problems faces two main limitations: (1) Modeling limitations, as current resolution methods detach the model from the resolution process, imposing limiting assumptions on the capabilities of an agent (e.g., that it controls a single variable of the problem, and that it operates solely on the resolution of a global problem, ignoring the presence of private objectives); and (2) Solving capabilities, as the inability of current approaches to capitalize on the presence of structural information which may allow incoherent/unnecessary data to reticulate among the agents as well as to exploit latent structure of the agent’s local problems, and/or of the problem of interest. The objective of the proposed dissertation is to address such limitations, studying how to adapt and integrate insights gained from centralized solving techniques, and from Graphic Processing Units (GPUs) parallel architectures, in order to design practical algorithms to efficiently solve large, complex, DCOPs, enabling their use for the resolution of real-world complex problems, such as those arising within the smart electricity grid context. To do so, we hypothesize that one can exploit the structure of DCOPs in both problem modeling and problem resolution phases.

Download or read book Distributed Optimization Game and Learning Algorithms written by Huiwei Wang and published by Springer Nature. This book was released on 2021-01-04 with total page 227 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides the fundamental theory of distributed optimization, game and learning. It includes those working directly in optimization,-and also many other issues like time-varying topology, communication delay, equality or inequality constraints,-and random projections. This book is meant for the researcher and engineer who uses distributed optimization, game and learning theory in fields like dynamic economic dispatch, demand response management and PHEV routing of smart grids.

Download or read book Distributed Optimization Advances in Theories Methods and Applications written by Huaqing Li and published by Springer Nature. This book was released on 2020-08-04 with total page 243 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book offers a valuable reference guide for researchers in distributed optimization and for senior undergraduate and graduate students alike. Focusing on the natures and functions of agents, communication networks and algorithms in the context of distributed optimization for networked control systems, this book introduces readers to the background of distributed optimization; recent developments in distributed algorithms for various types of underlying communication networks; the implementation of computation-efficient and communication-efficient strategies in the execution of distributed algorithms; and the frameworks of convergence analysis and performance evaluation. On this basis, the book then thoroughly studies 1) distributed constrained optimization and the random sleep scheme, from an agent perspective; 2) asynchronous broadcast-based algorithms, event-triggered communication, quantized communication, unbalanced directed networks, and time-varying networks, from a communication network perspective; and 3) accelerated algorithms and stochastic gradient algorithms, from an algorithm perspective. Finally, the applications of distributed optimization in large-scale statistical learning, wireless sensor networks, and for optimal energy management in smart grids are discussed.

Download or read book Distributed Control and Optimization Technologies in Smart Grid Systems written by Fanghong Guo and published by CRC Press. This book was released on 2017-11-09 with total page 192 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book aims to equalize the theoretical involvement with industrial practicality and build a bridge between academia and industry by reducing the mathematical difficulties. It provides an overview of distributed control and distributed optimization theory, followed by specific details on industrial applications to smart grid systems, with a special focus on micro grid systems. Each of the chapters is written and organized with an introductory section tailored to provide the essential background of the theories required. The text includes industrial applications to realistic renewable energy systems problems and illustrates the application of proposed toolsets to control and optimization of smart grid systems.

Download or read book Distributed Linear Programming Models in a Smart Grid written by Prakash Ranganathan and published by Springer. This book was released on 2017-03-31 with total page 231 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book showcases the strengths of Linear Programming models for Cyber Physical Systems (CPS), such as the Smart Grids. Cyber-Physical Systems (CPS) consist of computational components interconnected by computer networks that monitor and control switched physical entities interconnected by physical infrastructures. A fundamental challenge in the design and analysis of CPS is the lack of understanding in formulating constraints for complex networks. We address this challenge by employing collection of Linear programming solvers that models the constraints of sub-systems and micro grids in a distributed fashion. The book can be treated as a useful resource to adaptively schedule resource transfers between nodes in a smart power grid. In addition, the feasibility conditions and constraints outlined in the book will enable in reaching optimal values that can help maintain the stability of both the computer network and the physical systems. It details the collection of optimization methods that are reliable for electric-utilities to use for resource scheduling, and optimizing their existing systems or sub-systems. The authors answer to key questions on ways to optimally allocate resources during outages, and contingency cases (e.g., line failures, and/or circuit breaker failures), how to design de-centralized methods for carrying out tasks using decomposition models; and how to quantify un-certainty and make decisions in the event of grid failures.

Download or read book Exploiting Problem Structure in Distributed Constraint Optimisation with Complex Local Problems written by David A. Burke and published by . This book was released on 2008 with total page 214 pages. Available in PDF, EPUB and Kindle. Book excerpt: In today{u2019}s world, networks are ubiquitous, e.g. supply chain networks, computational grids, telecom networks and social networks. In many situations, the individual entities or {u2018}agents{u2019} that make up these networks need to coordinate their actions in order to make some group decision. Distributed Constraint Optimisation (DisCOP) considers algorithms explicitly designed to handle such problems, searching for globally optimal solutions while balancing communication load with processing time. However, most research on DisCOP algorithms only considers simplified problems where each agent has a single variable, i.e. only one decision to make. This is justified by two problem reformulations, by which any DisCOP with complex local problems (multiple variables per agent) can be transformed to give exactly one variable per agent. The restriction to a single variable has been an impediment to practical applications of DisCOP, since few problems naturally fit into that framework. Furthermore, there has been no research showing whether the standard reformulations are actually effective. In this dissertation, we address this issue. We evaluate the standard reformulation techniques and show that one of them is rarely competitive. We demonstrate that explicitly considering the structure of DisCOPs with complex local problems in the design of algorithms allows problems to be solved more efficiently. In particular, we show the benefits of distinguishing between the public (between agents) and private (within one agent) search spaces. Furthermore, we identify the public variables (those involved in inter-agent constraints) as a critical factor affecting how DisCOPs with complex local problems are solved. From this, we propose a number of novel techniques based on interchangeability, symmetry, relaxation, aggregation and domain reduction. These methods exploit the problem structure and act on the public variables to enable more efficient solving of Dis-COPs with complex local problems, thus greatly extending the range of problems that can be solved using DisCOP algorithms.

Download or read book Distributed Optimization in Networked Systems written by Qingguo Lü and published by Springer Nature. This book was released on 2023-02-08 with total page 282 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book focuses on improving the performance (convergence rate, communication efficiency, computational efficiency, etc.) of algorithms in the context of distributed optimization in networked systems and their successful application to real-world applications (smart grids and online learning). Readers may be particularly interested in the sections on consensus protocols, optimization skills, accelerated mechanisms, event-triggered strategies, variance-reduction communication techniques, etc., in connection with distributed optimization in various networked systems. This book offers a valuable reference guide for researchers in distributed optimization and for senior undergraduate and graduate students alike.

Download or read book Stochastic Optimization for Distributed Energy Resources in Smart Grids written by Yuanxiong Guo and published by Springer. This book was released on 2017-06-21 with total page 84 pages. Available in PDF, EPUB and Kindle. Book excerpt: This brief focuses on stochastic energy optimization for distributed energy resources in smart grids. Along with a review of drivers and recent developments towards distributed energy resources, this brief presents research challenges of integrating millions of distributed energy resources into the grid. The brief then proposes a novel three-level hierarchical architecture for effectively integrating distributed energy resources into smart grids. Under the proposed hierarchical architecture, distributed energy resource management algorithms at the three levels (i.e., smart home, smart neighborhood, and smart microgrid) are developed in this brief based on stochastic optimization that can handle the involved uncertainties in the system.

Download or read book From Smart Grids to Smart Cities written by Massimo La Scala and published by John Wiley & Sons. This book was released on 2021-04-27 with total page 371 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book addresses different algorithms and applications based on the theory of multiobjective goal attainment optimization. In detail the authors show as the optimal asset of the energy hubs network which (i) meets the loads, (ii) minimizes the energy costs and (iii) assures a robust and reliable operation of the multicarrier energy network can be formalized by a nonlinear constrained multiobjective optimization problem. Since these design objectives conflict with each other, the solution of such the optimal energy flow problem hasn’t got a unique solution and a suitable trade off between the objectives should be identified. A further contribution of the book consists in presenting real-world applications and results of the proposed methodologies developed by the authors in three research projects recently completed and characterized by actual implementation under an overall budget of about 23 million €.

Download or read book Proceedings of the 8th International Conference on Foundations of Computer Aided Process Design written by and published by Elsevier. This book was released on 2014-07-14 with total page 835 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume collects together the presentations at the Eighth International Conference on Foundations of Computer-Aided Process Design, FOCAPD-2014, an event that brings together researchers, educators, and practitioners to identify new challenges and opportunities for process and product design. The chemical industry is currently entering a new phase of rapid evolution. The availability of low-cost feedstocks from natural gas is causing renewed investment in basic chemicals in the OECD, while societal pressures for sustainability and energy security continue to be key drivers in technology development and product selection. This dynamic environment creates opportunities to launch new products and processes and to demonstrate new methodologies for innovation, synthesis and design. FOCAPD-2014 fosters constructive interaction among thought leaders from academia, industry, and government and provides a showcase for the latest research in product and process design. - Focuses exclusively on the fundamentals and applications of computer-aided design for the process industries. - Provides a fully archival and indexed record of the FOCAPD14 conference - Aligns the FOCAPD series with the ESCAPE and PSE series

Download or read book Optimal Coordination of Distributed Energy Resources in Smart Grids Enabled by Distributed Optimization and Transactive Energy written by Rabab Haider and published by . This book was released on 2020 with total page 310 pages. Available in PDF, EPUB and Kindle. Book excerpt: Modern active distribution grids are characterized by the increasing penetration of distributed energy resources (DERs). The proper coordination and scheduling of a large numbers of these DERs can only be achieved at the nexus of new technological approaches and policies, primarily distributed computation and transactive energy. Transactive energy is a control mechanism which uses economic incentives, such as time-of-use or real-time electricity prices, to influence the behaviour of independent agents (i.e. DERs in the grid) as needed by the grid operator. This thesis tackles the problem of DER coordination by considering the role of distributed optimization algorithms in solving the optimal power flow (OPF) problem, when a large number of small scale DERs are present. The OPF problem minimizes costs to operate the grid, while subject to network constraints. The distributed implementation makes large-scale problems computationally tractable, while also maintaining privacy of local information. First, we utilize a new convex formulation of the power grid based on current injection (CI) and McCormick Envelopes, to model distribution grids of meshed topology and unbalanced structure. The OPF problem is then solved for such grid structures, using the distributed proximal atomic coordination (PAC) algorithm, which has several advantages over other distributed algorithms. These advantages include reduced network communication requirements, reduced local computational effort, and improved privacy. The DER coordination problem is then extended to consider storage devices. This requires a multi-period OPF formulation, which is also solved using the PAC algorithm. Results from active configurations of the IEEE 123-bus network corroborate the need for a multi-period optimization approach under high penetration of renewable resources. Finally, we propose a retail market mechanism which can be viewed as a transactive energy scheme within the distribution grid. Through the retail market, DERs are optimally scheduled in an energy market, and leveraged in alert system cases in an ancillary services market. The transactions of the energy market are carried out at each primacy feeder through bilateral agreements between the Distribution System Operator (DSO) and agents representing DERs at feeder buses, leveraging the PAC algorithm. These interactions determine the optimal real-time resource schedules and distributed Locational Marginal Price. The PAC algorithm and proposed market are extensively validated on a real distribution grid in Tokyo, a balanced IEEE 123-bus distribution grid, and a three feeder model using the IEEE 13-bus. The energy market is shown to result in an overall increase in revenue for the DSO.

Download or read book A Class of Algorithms for Distributed Constraint Optimization written by Adrian Petcu and published by IOS Press. This book was released on 2009 with total page 304 pages. Available in PDF, EPUB and Kindle. Book excerpt: Addresses three major issues that arise in Distributed Constraint Optimization Problems (DCOP): efficient optimization algorithms, dynamic and open environments, and manipulations from self-interested users. This book introduces a series of DCOP algorithms, which are based on dynamic programming.

Download or read book Distributed Economic Operation in Smart Grid Model Based and Model Free Perspectives written by Jiahu Qin and published by Springer Nature. This book was released on 2023-01-25 with total page 246 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book aims to work out the distributed economic operation in smart grids in a systematic way, which ranges from model-based to model-free perspectives. The main contributions of this book can be summarized into three folds. First, we investigate the fundamental economic operation problems in smart grids from model-based perspective. Specifically, these problems can be modeled as deterministic optimization models, and we propose some distributed optimization algorithms by integrating the multi-agent consensus theory and optimization techniques to achieve the distributed coordination of various generation units and loads. Second, due to the randomness of the large-scale renewable energies and the flexibility of the loads, we further address these economic operation problems from a model-free perspective, and we propose learning-based approaches to address the uncertainty and randomness. At last, we extend the idea of model-based and model-free algorithms to plug-in electric vehicles (PEVs) charging/discharging scheduling problem, the key challenge of which involves multiple objectives simultaneously while the behavior of PEVs and the electricity price are intrinsically random. This book presents several recent theoretical findings on distributed economic operation in smart grids from model-based and model-free perspectives. By systematically integrating novel ideas, fresh insights, and rigorous results, this book provides a base for further theoretical research on distributed economic operation in smart grids. It can be a reference for graduates and researchers to study the operation and management in smart grids. Some prerequisites for reading this book include optimization theory, matrix theory, game theory, reinforcement learning, etc.

Download or read book A Distributed Optimization Method for Optimal Energy Management in Smart Grid written by Dinh Hoa Nguyen and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This chapter presents a distributed optimization method named sequential distributed consensus-based ADMM for solving nonlinear constrained convex optimization problems arising in smart grids in order to derive optimal energy management strategies. To develop such distributed optimization method, multi-agent system and consensus theory are employed. Next, two smart grid problems are investigated and solved by the proposed distributed algorithm. The first problem is called the dynamic social welfare maximization problem where the objective is to simultaneously minimize the generation costs of conventional power plants and maximize the satisfaction of consumers. In this case, there are renewable energy sources connected to the grid, but energy storage systems are not considered. On the other hand, in the second problem, plug-in electric vehicles are served as energy storage systems, and their charging or discharging profiles are optimized to minimize the overall system operation cost. It is then shown that the proposed distributed optimization algorithm gives an efficient way of energy management for both problems above. Simulation results are provided to illustrate the proposed theoretical approach.

Download or read book Distributed Economic Operation in Smart Grid Model Based and Model Free Perspectives written by Jiahu Qin and published by Springer. This book was released on 2024-01-27 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book aims to work out the distributed economic operation in smart grids in a systematic way, which ranges from model-based to model-free perspectives. The main contributions of this book can be summarized into three folds. First, we investigate the fundamental economic operation problems in smart grids from model-based perspective. Specifically, these problems can be modeled as deterministic optimization models, and we propose some distributed optimization algorithms by integrating the multi-agent consensus theory and optimization techniques to achieve the distributed coordination of various generation units and loads. Second, due to the randomness of the large-scale renewable energies and the flexibility of the loads, we further address these economic operation problems from a model-free perspective, and we propose learning-based approaches to address the uncertainty and randomness. At last, we extend the idea of model-based and model-free algorithms to plug-in electric vehicles (PEVs) charging/discharging scheduling problem, the key challenge of which involves multiple objectives simultaneously while the behavior of PEVs and the electricity price are intrinsically random. This book presents several recent theoretical findings on distributed economic operation in smart grids from model-based and model-free perspectives. By systematically integrating novel ideas, fresh insights, and rigorous results, this book provides a base for further theoretical research on distributed economic operation in smart grids. It can be a reference for graduates and researchers to study the operation and management in smart grids. Some prerequisites for reading this book include optimization theory, matrix theory, game theory, reinforcement learning, etc.

Download or read book Distributed Multi agent Optimization and Control with Applications in Smart Grid written by Towfiq Rahman and published by . This book was released on 2020 with total page 109 pages. Available in PDF, EPUB and Kindle. Book excerpt: The algorithm is implemented on a distribution grid with high EV penetration where each agent exchanges relevant information among the neighboring nodes through the communication network, optimizes a combined convex objective of EV welfare and voltage regulation with power equations as constraints. The algorithm falls short when the dynamic equations like EVs state of charge is taken into account. Thus, the algorithm is further developed to incorporate dynamic constraints and the convergence along with control law is developed using Lyapunov direct approach. An alternative approach for convergence using passivity-short properties is also shown. Simulation results are included to demonstrate the effectiveness of proposed schemes.

Download or read book Applications of Distributed Constraint Reasoning Framework for the Control and Management of Customer driven Micro grids written by Saurabh Gupta and published by . This book was released on 2014 with total page 258 pages. Available in PDF, EPUB and Kindle. Book excerpt: The ever-increasing demand of power is posing new challenges and forcing researchers to come up with new ideas. Micro-grid is one such concept, which leverages on the existing power infrastructure, modern telemetry and brilliant advances in computer hardware and software. Micro-grid is an aggregated system of loads and small distributed modular energy sources which are primarily renewables. It promises to make the power system more robust, reliable and environmentally sustainable. Customer-driven micro-grid (CDMG), is a relatively new paradigm in which utility-compatible generation sources, primarily renewable, are installed by the customers in their homes or facilities and the utility plays the role of an enabler for the optimum use of these resources. In a CDMG, customers has the control of their generation resources and loads in their own hands. CDMG presents the computer science researchers a unique opportunity to apply distributed artificial intelligence techniques to a cyber physical system and help in realizing the full potential of such a system. Distributed constraint reasoning is a young but powerful paradigm within distributed artificial intelligence. It has gained a lot of attention in the last 15 years. This dissertation analyzes the use of the distributed constraint optimization problem (DCOP) framework as a potential candidate to solve the control and management problems of the CDMGs in a decentralized manner. This work includes the modeling of a comprehensive CDMG optimization problem into DCOP framework along with a solution using off the shelf distributed constraint optimization algorithms. We also formulated, modeled and solved, a critical CDMG management problem, called islanding or network reconfiguration problem. We also took a step towards improving the existing pseudo tree based DCOP algorithms for solving CDMG problems by taking advantage of the properties of the CDMGs and making a realization that a CDMG is consist of an electrical and a communication network which can be treated separately. While building a pseudo tree in the pre-processing step of solving the problem using DCOP framework, we take into account the communication constraints. We also implemented such a system using Java Agent Development Environment (JADE) along with Distributed Pseudo-tree based optimization (DPOP) algorithm. Solving CDMG problems using DCOP framework in JADE provides a completely distributed and globally optimal solution of the problem.