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Renewable energy generation will continue to increase in the future. To accommodate high renewable penetrations in power systems, solutions such as demand response, energy storage will be needed. Most of such studies need to combine with the load profile at domestic level, but resources of household load profiles are quite scarce. We propose a rule based domestic load profile generator which allows...
In the smart grid environment, customers are offered to participate more actively in the electricity energy market with the promise of demand side management (DSM) with distributed energy resources and energy storage. By utilizing proper incentive scheme such as dynamic pricing, numerous objectives could be achieved so that it could benefit both the utility companies and consumers. In this paper,...
Aiming at the tracking control for the underactuated surface ship at open sea, an adaptive robust neural network method was proposed. At present, most researches would consider the underactuated characteristics and parameters uncertainties and environmental disturbance. The controller structure was designed by nonlinear algorithm, thus ensuring the tracking loop system robustness. Proposed adaptive...
For ship course control system, this paper proposes a class of sliding mode variable structure control method (SMVSC) based on RBF neural network. The mathematical model of ship steering system possesses parametric perturbation and external disturbances, which combines the advantages of RBF neural network and sliding mode control. The controller is given by the output of RBF neural network and the...
Influenced by global financial crisis and expanding enrolment of higher education, college students face serious employment and re-employment situation. College students must own core competence if they want to get success in employment competition. The professional training model adapting to market needs is to develop comprehensive professionals with advantages in creation, which can be achieved...
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