The environment powered unmanned surface vehicle (EPUSV) is capable of achieving large-range and longterm marine operations by harvesting abundant environment energy. However, considering the intermittency of environm...
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The environment powered unmanned surface vehicle (EPUSV) is capable of achieving large-range and longterm marine operations by harvesting abundant environment energy. However, considering the intermittency of environment energy, limitation on battery capacity and varieties of loads, it is necessary to control and coordinate the electric devices of EPUSV to exploit energy efficiently. To address this issue, an optimization based energy management strategy (EMS) is proposed in this paper to achieve optimal management for the devices of EPUSV. The operation constraints and relevant objectives of different types of devices are firstly modeled through mix-integer nonlinear programming (MINLP) method. The uncertainty parameters in the model are addressed by robust optimization method. Then various task modes are defined based on the preference for different objectives. Simulations indicate that the proposed method is able to achieve optimal scheduling for each device while satisfying the underlying operation constraints. Besides, the adaptability for different kinds of tasks and the robustness to the fluctuation of uncertainty parameters of the proposed EMS is analyzed and discussed.
In order to reduce the loss and improve the operating efficiency, it is necessary to optimize the operating schedule for the sources, grids and loads of active distribution network (ADN). Firstly, an operation model i...
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ISBN:
(纸本)9781538660058
In order to reduce the loss and improve the operating efficiency, it is necessary to optimize the operating schedule for the sources, grids and loads of active distribution network (ADN). Firstly, an operation model is established for source-grid-load interactive operation of ADN. In this model, the minimum loss is treated as the objective function, and the distributed generation sources, the tie-line switches of the grid, and the controllable loads serve as the optimized variables. Considering that the established model is about mix-integer nonlinear programming (MINTY) problem, the model is transformed into a bi-level combinatorial optimization problem to simplify the solving process. Finally, numerical tests are performed on the IEEE 33-node distribution network system, and results show that the proposed optimization method for the source-grid-load interactive operation of ADN can reduce the power loss and raise the operational efficiency.
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