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This book comprises five peer-reviewed articles covering original research articles on the modeling and simulation of electricity systems for transport and energy storage. The topics include: 1 - Optimal siting and sizing methodology to design an energy storage system (ESS) for railway lines; 2 - Technical–economic comparison between a 3 kV DC railway and the use of trains with on-board storage systems; 3 - How to improve electrical feeding substations, by changing transformer technology and by installing dedicated high-power-oriented storage systems; 4 - Algorithm applied to a vehicle-to-grid (V2G) technology. 5 - Thermal investigation and optimization of an air-cooled lithium-ion battery pack.

History of engineering & technology --- thermal management system --- optimal configuration --- air-cooling --- lithium-ion battery --- electric vehicles (EVs) --- photovoltaic (PV) systems --- vehicle-to-grid (V2G) --- smart grids (SGs) --- peak shaving --- amorphous transformer --- energy storage --- failure --- feeding substation --- tramway --- optimization --- energy storage system (ESS) --- siting --- sizing --- regenerative braking --- particle swarm optimization (PSO) algorithm --- net present value (NPV) --- railway network --- railway system --- lithium batteries --- supercapacitor --- Simulink --- catenary-free --- thermal management system --- optimal configuration --- air-cooling --- lithium-ion battery --- electric vehicles (EVs) --- photovoltaic (PV) systems --- vehicle-to-grid (V2G) --- smart grids (SGs) --- peak shaving --- amorphous transformer --- energy storage --- failure --- feeding substation --- tramway --- optimization --- energy storage system (ESS) --- siting --- sizing --- regenerative braking --- particle swarm optimization (PSO) algorithm --- net present value (NPV) --- railway network --- railway system --- lithium batteries --- supercapacitor --- Simulink --- catenary-free

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Collectively working robot teams can solve a problem more efficiently than a single robot, while also providing robustness and flexibility to the group. Swarm robotics model is a key component of a cooperative algorithm that controls the behaviors and interactions of all individuals. The robots in the swarm should have some basic functions, such as sensing, communicating, and monitoring, and satisfy the following properties:

n/a --- self-organization --- signal source localization --- multi-robot system --- sensor deployment --- parallel technique --- shape normalization --- genetic algorithm --- multiple robots --- optimization --- improved potential field --- optimal configuration --- autonomous docking --- asymmetrical interaction --- comparison --- behaviors --- patterns --- self-assembly robots --- congestion control --- surface-water environment --- target recognition --- coordinate motion --- UAV swarms --- formation reconfiguration --- swarm robotics --- swarm intelligence --- artificial bee colony algorithm --- obstacle avoidance --- fish swarm optimization --- search algorithm --- robotics --- time-difference-of-arrival (TDOA) --- formation --- mobile robots --- formation control --- meta-heuristic --- event-triggered communication --- search --- virtual structure --- 3D model identification --- surveillance --- event-driven coverage --- scale-invariant feature transform --- system stability --- Swarm intelligence algorithm --- bionic intelligent algorithm --- unmanned aerial vehicle --- underwater environment --- artificial flora (AF) algorithm --- swarm behavior --- weighted implicit shape representation --- Cramer–Rao low bound (CRLB) --- environmental perception --- particle swarm optimization --- modular robots --- cooperative target hunting --- virtual linkage --- multi-AUV --- consensus control --- panoramic view --- nonlinear disturbance observer --- sliding mode controller --- path optimization --- Swarm Chemistry --- multi-agents --- Cramer-Rao low bound (CRLB)