Electric Vehicles (EVs) are gradually replacing conventional vehicles as they are environmentally friendly and cause less pollution problems. Unregulated charging has severe impacts on the distribution grid and may in...
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Electric Vehicles (EVs) are gradually replacing conventional vehicles as they are environmentally friendly and cause less pollution problems. Unregulated charging has severe impacts on the distribution grid and may incur EV owners higher charging costs. Therefore, controlled charging infrastructures to supply the charging needs of large numbers of EVs are of vital importance. In this article, an optimal control scenario is presented to formulate the charge scheduling problem of EVs in a solar charging station (CS). Two different objective functions are considered. The first objective function holds for minimizing the total charging cost of EVs. In this case, the benefits of Vehicle-to-Grid (V2G) are investigated by comparing the charging costs of EVs with and without this capability. The total EV charging costs and grid benefits are also investigated in the second objective function which holds for minimizing the extracted power from the grid. A modified version of dynamicprogramming is used to solve the large state-space model defined for the optimal control problem with extremely shorter computation time and minimal loss of optimality. Extensive simulations are done in two representative summer and winter climates to determine the role of solar energy in the CS performance. The results show that in the cost minimization algorithms, significant savings for EV owners and a smooth load shape for the grid are achieved. For the minimized power from the grid algorithm, a total near Photovoltaic (PV)-curve charging power is obtained to exploit the PV power as much as possible to minimize the impacts on the grid.
With the rapid economic growth in recent years, the power demands in China keep growing and the need for reducing peak loads is becoming more prominent. With the merits of fast startup and shutdown, hydropower is ofte...
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With the rapid economic growth in recent years, the power demands in China keep growing and the need for reducing peak loads is becoming more prominent. With the merits of fast startup and shutdown, hydropower is often used to respond the peak load. In order to meet the practical requirement of peak operation in electrical power system, a novel min-max dynamicprogramming model is formulated for the peak operation of hydropower system. Then, the hybrid dynamicprogramming method is presented to alleviate the dimensionality problem in large-scale hydropower system, where the dynamic programming successive approximation is employed to divide the complex multi-dimensional problem into a series of small subproblems, and then the discrete differential dynamicprogramming is adopted to sequentially solve these subproblems. In addition, inspired by domain knowledge, the initial solution generation method and feasible space identification method are designed to promote the convergence speed of algorithm. The proposed method is used to solve the peak operation problem of a large-scale hydropower system in China. The simulations with different load demands indicate that the hybrid dynamicprogramming can achieve satisfactory performance in reducing peak loads of power system. (C) 2017 Elsevier Ltd. All rights reserved.
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