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Distributed generation is becoming more important in electrical power systems due to the decentralization of energy production. Within this new paradigm, new approaches for the operation and planning of distributed power generation are yet to be explored. This book deals with distributed energy resources, such as renewable-based distributed generators and energy storage units, among others, considering their operation, scheduling, and planning. Moreover, other interesting aspects such as demand response, electric vehicles, aggregators, and microgrid are also analyzed. All these aspects constitute a new paradigm that is explored in this Special Issue.

Technology: general issues --- Benders’ decomposition --- distributed generation planning (DGP) --- two-stage stochastic mixed-integer linear programming (MILP) --- renewable energy sources (RES) --- micro-grid --- energy management system --- IEC 61850 --- 5G --- LoRa --- multi-agent system --- isolated AC/DC hybrid microgrid --- two-layer consensus method --- dynamic economic dispatch --- distributed hierarchical strategy --- MILP optimization --- allocation --- renewable energy sources --- system modeling --- energy storages --- energy curtailment --- mathematical programming --- small scale distributed generation --- distribution networks --- active power management --- battery degradation --- electric vehicles --- electric vehicles aggregator --- electricity markets --- stochastic programming --- combined economic emission dispatch --- environment-based demand response --- emission constraints --- penalty factor --- weighting update artificial bee colony --- distribution network planning --- energy storage system --- multi-objective optimization --- optimal location --- risk assessment --- flexibility --- distributed energy resources --- distribution system operators --- local services --- system services --- arbitrage --- frequency control

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Distributed generation is becoming more important in electrical power systems due to the decentralization of energy production. Within this new paradigm, new approaches for the operation and planning of distributed power generation are yet to be explored. This book deals with distributed energy resources, such as renewable-based distributed generators and energy storage units, among others, considering their operation, scheduling, and planning. Moreover, other interesting aspects such as demand response, electric vehicles, aggregators, and microgrid are also analyzed. All these aspects constitute a new paradigm that is explored in this Special Issue.

Technology: general issues --- Benders’ decomposition --- distributed generation planning (DGP) --- two-stage stochastic mixed-integer linear programming (MILP) --- renewable energy sources (RES) --- micro-grid --- energy management system --- IEC 61850 --- 5G --- LoRa --- multi-agent system --- isolated AC/DC hybrid microgrid --- two-layer consensus method --- dynamic economic dispatch --- distributed hierarchical strategy --- MILP optimization --- allocation --- renewable energy sources --- system modeling --- energy storages --- energy curtailment --- mathematical programming --- small scale distributed generation --- distribution networks --- active power management --- battery degradation --- electric vehicles --- electric vehicles aggregator --- electricity markets --- stochastic programming --- combined economic emission dispatch --- environment-based demand response --- emission constraints --- penalty factor --- weighting update artificial bee colony --- distribution network planning --- energy storage system --- multi-objective optimization --- optimal location --- risk assessment --- flexibility --- distributed energy resources --- distribution system operators --- local services --- system services --- arbitrage --- frequency control

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Research on intelligent agents and multi-agent systems has matured during the past decade, and many effective applications of this technology are currently being deployed. Although computational approaches for multi-agent systems have mainly emerged in the past few decades, scholars have been prolific with regard to the variety of methods proposed to solve this paradigm. Different communities have emerged with multi-agent systems as their main research topic. Multi-agent systems allow the development of distributed and intelligent applications in complex and dynamic environments. Systems of this kind play a crucial role in life, evidenced by the broad range of applied areas involved in their use, including manufacturing, management sciences, e-commerce, and biotechnology. There are many reasons for the interest of researchers in this new discipline. Firstly, computational systems have gradually shifted towards a distributed paradigm where heterogeneous entities with different goals can enter and leave the system dynamically and interact with each other. Secondly, new computational systems should be able to negotiate with one another, typically on the behalf of humans, in order to come to mutually acceptable agreements. As a consequence, autonomy, interaction, mobility, and openness are key concepts studied in the area. The purpose of this book is to document some of the advances made in this paradigm and attempt to show the current state of this technology by analyzing different aspects in addition its possible application in various domains. This review of the current state-of-the-art does not intend to make an exhaustive exploration of all the current existing works but, rather, to try to give an overview of the research in agent technology, showing the high level of activity of this area.

multi-robot --- consensus problem --- formation control --- noise --- time delay --- unmanned surface vehicles --- multi-agent system --- training system --- genetic-based fuzzy rule learning --- intelligent autonomous control --- modeling and simulation --- multi-agent systems --- smart city development --- spatiotemporal modeling --- actor–network theory --- geoparticipation --- social interactions --- simulation model --- photovoltaic energy --- parameter fine-tuning --- self-reported behaviour --- predictive model --- multi-agent planning and scheduling --- potential game --- equilibrium selection --- interoperability --- multiagent systems --- organizational models --- agent-based collective intelligence --- multi-agent complex systems --- scale-free properties --- power law distribution --- biologically inspired approaches and methods --- collective foraging --- physics-based simulation --- methodologies for agent-based systems --- multi-robot simulation --- discrete event simulator --- agent and multi-agent applications --- classification --- prediction --- multi-agent --- wisdom-of-crowds --- Hollywood --- feature-extension --- collective-intelligence --- swarm --- educational games --- game design --- situated psychological agents --- education --- competences --- decision support system --- agent based modeling and simulation --- production scheduling --- green coffee supply chain --- agent-based modeling --- agent-based simulation --- decision support

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At present, the impact of distributed energy resources in the operation of power and energy systems is unquestionable at the distribution level, but also at the whole power system management level. Increased flexibility is required to accommodate intermittent distributed generation and electric vehicle charging. Demand response has already been proven to have a great potential to contribute to an increased system efficiency while bringing additional benefits, especially to the consumers. Distributed storage is also promising, e.g., when jointly used with the currently increasing use of photovoltaic panels. This book addresses the management of distributed energy resources. The focus includes methods and techniques to achieve an optimized operation, to aggregate the resources, namely, by virtual power players, and to remunerate them. The integration of distributed resources in electricity markets is also addressed as a main drive for their efficient use.

autonomous operation --- energy management system --- stochastic programming --- co-generation --- Unit Commitment (UC) --- distributed system --- demand-side energy management --- virtual power plant --- Powell direction acceleration method --- average consensus algorithm (ACA) --- transmission line --- interval optimization --- renewable energy --- microgrids --- scheduling --- business model --- non-cooperative game (NCG) --- domestic energy management system --- time series --- energy trading --- decision-making under uncertainty --- Demand Response Unit Commitment (DRUC) --- real-time simulation --- distributed generation --- discrete wavelet transformer --- microgrid (MG) --- probabilistic programming --- optimal bidding --- ac/dc hybrid microgrid --- building energy flexibility --- storage --- uncertainty --- Cat Swarm Optimization (CSO) --- advance and retreat method --- multiplier method --- microgrid --- Demand Response (DR) --- electricity markets --- aggregators --- fault localization --- aggregator --- consensus algorithm --- black start --- microgrid operation --- local controller --- thermal comfort --- diffusion strategy --- optimal operation --- power system restoration (PSR) --- energy flexibility --- ARIMA --- pricing strategy --- clustering --- adaptive droop control --- multi-agent system (MAS) --- hierarchical game --- energy flexibility potential --- demand response

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This self-contained introduction to the distributed control of robotic networks offers a distinctive blend of computer science and control theory. The book presents a broad set of tools for understanding coordination algorithms, determining their correctness, and assessing their complexity; and it analyzes various cooperative strategies for tasks such as consensus, rendezvous, connectivity maintenance, deployment, and boundary estimation. The unifying theme is a formal model for robotic networks that explicitly incorporates their communication, sensing, control, and processing capabilities--a model that in turn leads to a common formal language to describe and analyze coordination algorithms. Written for first- and second-year graduate students in control and robotics, the book will also be useful to researchers in control theory, robotics, distributed algorithms, and automata theory. The book provides explanations of the basic concepts and main results, as well as numerous examples and exercises. Self-contained exposition of graph-theoretic concepts, distributed algorithms, and complexity measures for processor networks with fixed interconnection topology and for robotic networks with position-dependent interconnection topology Detailed treatment of averaging and consensus algorithms interpreted as linear iterations on synchronous networks Introduction of geometric notions such as partitions, proximity graphs, and multicenter functions Detailed treatment of motion coordination algorithms for deployment, rendezvous, connectivity maintenance, and boundary estimation

Robotics. --- Computer algorithms. --- Robots --- Automation --- Machine theory --- Robot control --- Robotics --- Algorithms --- Control systems. --- Computer algorithms --- Control systems --- 1-center problem. --- Adjacency matrix. --- Aggregate function. --- Algebraic connectivity. --- Algebraic topology (object). --- Algorithm. --- Analysis of algorithms. --- Approximation algorithm. --- Asynchronous system. --- Bellman–Ford algorithm. --- Bifurcation theory. --- Bounded set (topological vector space). --- Calculation. --- Cartesian product. --- Centroid. --- Chebyshev center. --- Circulant matrix. --- Circumscribed circle. --- Cluster analysis. --- Combinatorial optimization. --- Combinatorics. --- Communication complexity. --- Computation. --- Computational complexity theory. --- Computational geometry. --- Computational model. --- Computer simulation. --- Computer vision. --- Connected component (graph theory). --- Connectivity (graph theory). --- Consensus (computer science). --- Control function (econometrics). --- Differentiable function. --- Dijkstra's algorithm. --- Dimensional analysis. --- Directed acyclic graph. --- Directed graph. --- Discrete time and continuous time. --- Disk (mathematics). --- Distributed algorithm. --- Doubly stochastic matrix. --- Dynamical system. --- Eigenvalues and eigenvectors. --- Estimation. --- Euclidean space. --- Function composition. --- Hybrid system. --- Information theory. --- Initial condition. --- Instance (computer science). --- Invariance principle (linguistics). --- Invertible matrix. --- Iteration. --- Iterative method. --- Kinematics. --- Laplacian matrix. --- Leader election. --- Linear dynamical system. --- Linear interpolation. --- Linear programming. --- Lipschitz continuity. --- Lyapunov function. --- Markov chain. --- Mathematical induction. --- Mathematical optimization. --- Mobile robot. --- Motion planning. --- Multi-agent system. --- Network model. --- Network topology. --- Norm (mathematics). --- Numerical integration. --- Optimal control. --- Optimization problem. --- Parameter (computer programming). --- Partition of a set. --- Percolation theory. --- Permutation matrix. --- Polytope. --- Proportionality (mathematics). --- Quantifier (logic). --- Quantization (signal processing). --- Robustness (computer science). --- Scientific notation. --- Sensor. --- Set (mathematics). --- Simply connected space. --- Simulation. --- Simultaneous equations. --- State space. --- State variable. --- Stochastic matrix. --- Stochastic. --- Strongly connected component. --- Synchronous network. --- Theorem. --- Time complexity. --- Topology. --- Variable (mathematics). --- Vector field.