| 基于改进AGA的微电网优化管理研究 |
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| 引用本文： | 韩 宇,马立新,唐继旭,徐文彬.基于改进AGA的微电网优化管理研究[J].教育技术导刊,2019,18(12):151-154. |
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| 作者姓名： | 韩 宇 马立新 唐继旭 徐文彬 |
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| 作者单位： | 上海理工大学 机械工程学院，上海 200093 |
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| 基金项目： | 上海市张江国家自主创新重点项目（201310-PI-B2-008） |
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| 摘 要： | 针对电动汽车无序充放电影响传统微电网稳定性及经济性问题，建立一种根据电动汽车随机负荷种类分时段调度模型，使用蒙特卡洛方法模拟电动汽车的充放电功率。同时，对传统微电网优化收敛速度慢、精度低等问题，提出一种改进自适应遗传优化算法（SAGA）。最优保存策略结合自适应调整交叉变异概率，解决遗传算法多样性问题，从而改善收敛速度与精度。通过建模及仿真计算，证明该方法在含电动汽车的风光柴储微电网优化中，能较快收敛到最优解，提高了微电网稳定性和经济性，具有良好的工程实用性。
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| 关 键 词： | 微电网优化 分布式能源 电动汽车 分类调度 蒙特卡洛模拟 自适应遗传算法 |
| 收稿时间： | 2019-03-01 |
Research on Microgrid with Electric Vehicle Optimization Management Based on Improved AGA |
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| HAN Yu,MA Li-xin,TANG Ji-xu,XU Wen-bin.Research on Microgrid with Electric Vehicle Optimization Management Based on Improved AGA[J].Introduction of Educational Technology,2019,18(12):151-154. |
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| Authors: | HAN Yu MA Li-xin TANG Ji-xu XU Wen-bin |
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| Institution: | School of Mechanical Engineering，University of Shanghai for Science and Technology， Shanghai 200093， China |
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| Abstract: | Aiming at the problem of the stability and economy of the traditional microgrid caused by the disordered charging and discharging of electric vehicles， a time-scheduled scheduling model based on the random load type of electric vehicles was established， and the charging and discharging power of electric vehicles was simulated by Monte Carlo method. At the same time， an improved adaptive genetic optimization algorithm （SAGA） is proposed for the traditional MEMS-containing microgrid with slow convergence and low precision. The optimal preservation strategy combines adaptive adjustment of the cross mutation probability to solve the genetic algorithm diversity problem， thereby improving the convergence speed and accuracy. Through modeling and simulation calculations， it is proved that this method can converge to the optimal solution quickly in the optimization of wind and light storage microgrid with electric vehicle， improve the stability and economical efficiency of microgrid， and has good engineering practicability. |
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| Keywords: | Microgrid optimization distributed energy electric vehicle classification scheduling Monte Carlo simulation adaptive genetic algorithm |
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