KEYWORDS: Power grids, Genetic algorithms, Mathematical optimization, Polonium, Power supplies, Design and modelling, Computer simulations, Roads, Optical storage, Analytical research
With the popularity of electric vehicles, the impact of electric vehicle charging on the power grid is also growing. The planning of charging stations not only affects the user experience, but also affects the stable operation of the power grid. By analyzing the impact of charging stations on the power grid and users, as well as the correlation between their construction costs and operating costs, the planning problem of electric vehicle charging stations is modeled as a solution problem under multi-objective and multi constraint conditions, and ADMM algorithm is used to solve the problem. A commercial district is taken as an example for analysis and testing, and the results prove the effectiveness of the proposed algorithm.
In order to alleviate the "power shortage panic" phenomenon caused by the lack of flexibility in the use of fixed charging stations, the introduction of mobile charging vehicles can effectively alleviate the charging problem of electric vehicles and improve the user experience. First, we divide the road network in specific areas, and then forecast the resident traffic volume (OD) data, so as to determine the initial location and distribution of mobile charging vehicles. From the global optimization of the charging time of the mobile charging vehicle at each charging position, ensure that each energy critical sensor is fully charged. At the same time, a mobile charging vehicle path planning algorithm considering the road state is proposed to determine the charging loop of the mobile charging vehicle and the charging time of the corresponding location, so as to minimize the total charging scheduling time on the loop. Finally, the performance of the proposed algorithm is evaluated through simulation experiments. Experimental results show that the proposed algorithm has low energy consumption, strong robustness and excellent performance.
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