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This paper presents the architecture and modeling approach of a Matlab-based toolbox for developing and testing home energy management (HEM) algorithms under a number of typical operation conditions. This toolbox serves as a developer platform that includes a graphical user interface, a model database, a computational engine, and an input-output database. The model database consists of home appliance...
This paper investigates the possibility of providing aggregated regulation services with small loads, such as water heaters or air conditioners. A direct-load control algorithm is presented to aggregate the water heater load for the purpose of regulation. A dual-element electric water heater model is developed, which accounts for both thermal dynamics and users' water consumption. A realistic regulation...
Support vector machine (SVM) is based on the statistical learning theory. It has recently been successfully used to solve nonlinear regression and time series problems and has been applied to predict values. The key problem of SVM is the choice of SVM parameters. Particle swarm optimization (PSO) algorithm has the ability of global optimization. This paper proposed an improved PSO algorithm based...
Support Vector Machine (SVM) is a type of learning machine which has been proved to be available in solving the problems of nonlinear regression. The decision of SVM parameters is essential. In this paper a new SVM model based on particle swarm optimization (PSO) for parameter optimization has been proposed. PSO algorithm has extensive capability of global optimization. Once the PSO finds the optimal...
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