LOAD FORECASTING FOR SMART GRID USING MATLAB
Analysis & Case Studies
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These book provide powerful tools for design, simulation, control, estimation, fault diagnostics and fault tolerant control in modern smart grids (SG) and renewable energy systems(RESs). As one of the key links to make a grid smarter, load forecast plays a significant role, the reliable prediction of load demand contributes to the efficient and economical operations and planning of the power system. The nonlinear nature of the electrical load demand confirms to the ability of the artificial neural network in calculating the nonlinear relationship of inputs and outputs. There are many ways such...
These book provide powerful tools for design, simulation, control, estimation, fault diagnostics and fault tolerant control in modern smart grids (SG) and renewable energy systems(RESs). As one of the key links to make a grid smarter, load forecast plays a significant role, the reliable prediction of load demand contributes to the efficient and economical operations and planning of the power system. The nonlinear nature of the electrical load demand confirms to the ability of the artificial neural network in calculating the nonlinear relationship of inputs and outputs. There are many ways such as Expert Systems, Fuzzy Logic and Artificial Neural Networks and so on are employed into load forecast. A personal computer based expert system using artificial neural network for smart grid forecast is visualized in this book. MATLAB SIMULINK is used as programming language.
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