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Effective smart grid operation requires rapid decisions in a data-rich, but information-limited, environment. In this context, grid sensor data-streaming cannot provide the system operators with the necessary information to act on in the time frames necessary to minimize the impact of the disturbances. Even if there are fast models that can convert the data into information, the smart grid operator must deal with the challenge of not having a full understanding of the context of the information, and, therefore, the information content cannot be used with any high degree of confidence. To address this issue, data mining has been recognized as the most promising enabling technology for improving decision-making processes, providing the right information at the right moment to the right decision-maker. This Special Issue is focused on emerging methodologies for data mining in smart grids. In this area, it addresses many relevant topics, ranging from methods for uncertainty management, to advanced dispatching. This Special Issue not only focuses on methodological breakthroughs and roadmaps in implementing the methodology, but also presents the much-needed sharing of the best practices. Topics include, but are not limited to, the following:  Fuzziness in smart grids computing  Emerging techniques for renewable energy forecasting  Robust and proactive solution of optimal smart grids operation  Fuzzy-based smart grids monitoring and control frameworks  Granular computing for uncertainty management in smart grids  Self-organizing and decentralized paradigms for information processing

Information technology industries --- voltage regulation --- smart grid --- decentralized control architecture --- multi-agent systems --- t-SNE algorithm --- numerical weather prediction --- data preprocessing --- data visualization --- wind power generation --- partial discharge --- gas insulated switchgear --- case-based reasoning --- data matching --- variational autoencoder --- DSHW --- TBATS --- NN-AR --- time-series clustering --- decentral smart grid control (DSGC) --- interpretable and accurate DSGC-stability prediction --- data mining --- computational intelligence --- fuzzy rule-based classifiers --- multi-objective evolutionary optimization --- power systems resilience --- dynamic Bayesian network --- Markov model --- probabilistic modeling --- resilience models --- voltage regulation --- smart grid --- decentralized control architecture --- multi-agent systems --- t-SNE algorithm --- numerical weather prediction --- data preprocessing --- data visualization --- wind power generation --- partial discharge --- gas insulated switchgear --- case-based reasoning --- data matching --- variational autoencoder --- DSHW --- TBATS --- NN-AR --- time-series clustering --- decentral smart grid control (DSGC) --- interpretable and accurate DSGC-stability prediction --- data mining --- computational intelligence --- fuzzy rule-based classifiers --- multi-objective evolutionary optimization --- power systems resilience --- dynamic Bayesian network --- Markov model --- probabilistic modeling --- resilience models

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The synchronized flashing of fireflies at night. The spiraling patterns of an aggregating slime mold. The anastomosing network of army-ant trails. The coordinated movements of a school of fish. Researchers are finding in such patterns--phenomena that have fascinated naturalists for centuries--a fertile new approach to understanding biological systems: the study of self-organization. This book, a primer on self-organization in biological systems for students and other enthusiasts, introduces readers to the basic concepts and tools for studying self-organization and then examines numerous examples of self-organization in the natural world. Self-organization refers to diverse pattern formation processes in the physical and biological world, from sand grains assembling into rippled dunes to cells combining to create highly structured tissues to individual insects working to create sophisticated societies. What these diverse systems hold in common is the proximate means by which they acquire order and structure. In self-organizing systems, pattern at the global level emerges solely from interactions among lower-level components. Remarkably, even very complex structures result from the iteration of surprisingly simple behaviors performed by individuals relying on only local information. This striking conclusion suggests important lines of inquiry: To what degree is environmental rather than individual complexity responsible for group complexity? To what extent have widely differing organisms adopted similar, convergent strategies of pattern formation? How, specifically, has natural selection determined the rules governing interactions within biological systems? Broad in scope, thorough yet accessible, this book is a self-contained introduction to self-organization and complexity in biology--a field of study at the forefront of life sciences research.

Biological systems. --- Self-organizing systems. --- Adamson, J. --- Attenborough, David. --- Bagnoli, P. --- Buck, E. --- Bénard convection. --- Craig, W. --- Downing, H. A. --- Fick's Law. --- Franks, N. R. --- Grassé, P. P. --- Hanson, F. E. --- Heinrich, B. --- Jeanne, R. L. --- Kauffman, S. A. --- Luciola pupilla (firefly). --- Maruyama, M. --- Myerscough, M. R. --- Oecophylla sp. --- Pardi, L. --- Partridge, B. L. --- Schneirla, T. C., Turillazzi, S. --- decentralized control. --- electric fish electrolocation. --- evolutionary theories. --- inclusive fitness theory.

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This Special Issue collects the latest results on differential/difference equations, the mathematics of networks, and their applications to engineering and physical phenomena. It features nine high-quality papers that were published with original research results. The Special Issue brings together mathematicians with physicists, engineers, as well as other scientists.

History of engineering & technology --- fractional discrete calculus --- discrete chaos --- Tinkerbell map --- bifurcation --- stabilization --- communication networks --- maximum flow --- network policies --- algorithms --- gas flow --- stress-sensitive porous media --- multiple hydraulic fractures --- vertical fractured well --- Output-feedback --- centralized control --- decentralized control --- closed-loop stabilization --- Hardy Cross method --- pipe networks --- piping systems --- hydraulic networks --- gas distribution --- multi-switching combination synchronization --- time-delay --- fractional-order --- stability --- Shehu transformation --- Adomian decomposition --- analytical solution --- Caputo derivatives --- (2+time fractional-order) dimensional physical models --- homotopy perturbation method --- variational iteration method --- Laplace transform method --- acoustic wave equations --- n/a

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This Special Issue collects the latest results on differential/difference equations, the mathematics of networks, and their applications to engineering and physical phenomena. It features nine high-quality papers that were published with original research results. The Special Issue brings together mathematicians with physicists, engineers, as well as other scientists.

History of engineering & technology --- fractional discrete calculus --- discrete chaos --- Tinkerbell map --- bifurcation --- stabilization --- communication networks --- maximum flow --- network policies --- algorithms --- gas flow --- stress-sensitive porous media --- multiple hydraulic fractures --- vertical fractured well --- Output-feedback --- centralized control --- decentralized control --- closed-loop stabilization --- Hardy Cross method --- pipe networks --- piping systems --- hydraulic networks --- gas distribution --- multi-switching combination synchronization --- time-delay --- fractional-order --- stability --- Shehu transformation --- Adomian decomposition --- analytical solution --- Caputo derivatives --- (2+time fractional-order) dimensional physical models --- homotopy perturbation method --- variational iteration method --- Laplace transform method --- acoustic wave equations --- fractional discrete calculus --- discrete chaos --- Tinkerbell map --- bifurcation --- stabilization --- communication networks --- maximum flow --- network policies --- algorithms --- gas flow --- stress-sensitive porous media --- multiple hydraulic fractures --- vertical fractured well --- Output-feedback --- centralized control --- decentralized control --- closed-loop stabilization --- Hardy Cross method --- pipe networks --- piping systems --- hydraulic networks --- gas distribution --- multi-switching combination synchronization --- time-delay --- fractional-order --- stability --- Shehu transformation --- Adomian decomposition --- analytical solution --- Caputo derivatives --- (2+time fractional-order) dimensional physical models --- homotopy perturbation method --- variational iteration method --- Laplace transform method --- acoustic wave equations

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The electric power sector is poised for transformative changes. Improvements in the cost and performance of a range of distributed energy generation (DG) technologies and the potential for breakthroughs in distributed energy storage (DS) are creating new options for onsite power generation and storage, driving increasing adoption and impacting utility distribution system operations. In addition, changing uses and use patterns for electricity—from plug-in electric vehicles (EVs) to demand response (DR)—are altering demands placed on the electric power system. Finally, the infusion of new information and communications technology (ICT) into the electric system and its markets is enabling the collection of immense volumes of data on power sector operations and use; unprecedented control of generation, networks, and loads; and new opportunities for the delivery of energy services. In this Special Issue of Energies, research papers on topics related to the integration of distributed energy resources (DG, DS, EV, and DR) are included. From technologies to software tools to system-wide evaluations, the impacts of all aforementioned distributed resources on both operation and planning are examined.

machine learning --- microgrids --- optimisation methods --- power systems --- reinforcement learning --- high penetration --- renewable energy --- adaptability planning --- source-grid coordination --- renewable electricity distribution for public space --- sustainability assessment model --- integrated assessment for public space --- tripartite altruism --- urban renewable energy --- ecological infrastructures --- Micro-grids --- continuity of supply --- power distribution --- power system planning --- decentralized control --- small hydropower plants --- microgrid --- emergency control --- recloser --- synchronous coupler --- power systems stability --- power system operation --- power system security --- renewable energy integration --- load flow analysis --- congestion management --- distributed generation curtailment --- demand side management --- demand response --- cyber-physical systems --- dynamic pricing --- load forecasting --- attack detection --- photovoltaics --- distributed energy resources (DERs) --- grid impact --- power quality --- low-voltage distribution network --- inverter regulation --- electric vehicles --- uncontrolled charging --- delayed charging --- controlled charging --- V2G --- V2B --- V2H --- peak shaving --- valley filling --- renewable energy sources