| 引用本文: | 杜娟,安世华,魏明磊,等.基于直流微网的电力分组传输调度[J].电力系统保护与控制,2020,48(10):106-112.[点击复制] |
| DU Juan,AN Shihua,WEI Minglei,et al.Power packet transmission scheduling based on a DC microgrid[J].Power System Protection and Control,2020,48(10):106-112[点击复制] |
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| 摘要: |
| 可再生能源的大范围渗透使得直流微网逐步受到重视。针对新能源供电，直流微网可以减少交直流变换时的损耗以及不稳定性。因此，在直流微网环境下，构建销售商为领导者和用户为跟随者的多主从博弈模型，对销售商价格与用户需求量进行博弈，并根据分布式选择算法得到多个销售商-用户匹配对。基于两个通道传输损耗不同的路由器，通过遗传算法实现了多个匹配对的最优电力分组调度。仿真结果验证了上述两种算法的可行性以及优越性。 |
| 关键词: 可再生能源 直流微网 主从博弈 分布式选择算法 遗传算法 |
| DOI：10.19783/j.cnki.pspc.190775 |
| 投稿时间：2019-07-04修订日期：2019-12-05 |
| 基金项目:国家自然科学基金项目资助(61501185);国网河北省电力有限公司科技项目资助(SGHEHS00FCJS1800274) |
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| Power packet transmission scheduling based on a DC microgrid |
| DU Juan,AN Shihua,WEI Minglei,GAO Bing,ZHAO Zhichen,WANG Mengyuan,LI Baogang |
| (State Grid Hengshui Power Supply Company, Hengshui 053000, China;School of Electrical & Electronic Engineering, North China Electric Power University, Baoding 071003, China) |
| Abstract: |
| The large-scale penetration of renewable energy has promoted great attention on the DC microgrid. For the supply of new energy, the DC microgrid can reduce loss and instability of AC/DC conversion. Therefore, in the DC microgrid environment, a multi-master-slave game model which regards the sellers as the leaders and the users as the followers is constructed. Then a game analysis for the seller’s price and user’s demand is carried out and finally multiple seller-user pairs can be obtained according to the distributed selection algorithm. Based on two routes with different transmission losses of channels, the optimal power packet scheduling of multiple matched pairs is realized by genetic algorithm. Simulation results demonstrate the feasibility and superiority of the two proposed algorithms. This work is supported by National Natural Science Foundation of China (No. 61501185) and Science and Technology Project of State Grid Hebei Electric Power Co., Ltd. (No. SGHEHS00FCJS1800274). |
| Key words: renewable energy DC microgrid master-slave game distributed selection algorithm genetic algorithm |
