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This paper presents a day-ahead optimal energy management strategy for economic operation of industrial microgrids with high-penetration renewables under both isolated and grid-connected operation modes. The approach is based on a regrouping particle swarm optimization (RegPSO) formulated over a day-ahead scheduling horizon with one hour time step, taking into account forecasted renewable energy generations...
Wind generation power output estimation is always associated with some uncertainties as a result of wind speed and other weather parameters intermittency, and accurate short-term predictions are important for their efficient operation. This can greatly help transmission and distribution system operators and schedulers to improve the power network control and management. In this paper, a double stage...
This paper presents an optimal energy management strategy for the operation of multiple energy storage units (batteries) in grid-connected industrial microgrids with high-penetration renewables in a variable grid-price scenario. The approach is based on a regrouping particle swarm optimization (RegPSO) formulated over a day-ahead scheduling horizon with one hour time interval, considering forecasted...
A new mathematics model on multi-facilities location and allocation problem(MLAP) of three-echelon supply chain was built, which mainly took some logistics cost such as inventory cost, carrying cost, transportation cost into consideration. Then, an improved Genetic Algorithm was proposed to solve the MLAP. In this algorithm, the real encoding method was used to encode the solution directly, and meanwhile...
A novel navigation strategy for mobile robot in large unknown environment is put forward here. Globally, the robot's path is planned with genetic algorithm, which is better than A* algorithm and neural networks. Locally, the robot avoids obstacle and moves with some basic behaviors and path memory. With GPS and INS information fusion, the robot can go from one sub target to another sub target with...
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