研究方向（1）人工智能与机器人技术.pdfVIP

研究方向(1) ：人工智能与机器人技术 基于人工智能优化的新能源最大功率跟踪 张孝顺 1 基于人工智能优化的新能源最大功率跟踪 1、阴影环境下的光伏最大功率点跟踪 ➢ 在阴影环境下光伏输出功率曲线存在多个 极值，传统跟踪算法难以获得全局最优点。 ➢ 使用性能高效的启发式算法来逼近全局最 优大功率点，提升光伏发电能源转换效率。 [1] Xiaoshun Zhang, Shengnan Li, Tingyi He, et al. Memetic reinforcement learning based maximum power point tracking design of PV systems under partial shading condition. Energy , 2019, 174: 1079- 1090. (IF=5.537，中科院二区) [2] Bo Yang, Tao Yu, Xiaoshun Zhang*, et al. Dynamic leader based collective intelligence for maximum power point tracking of PV systems affected by partial shading condition. Energy Conversion and Management , 2019, 179: 286-303. (IF=7.181, 中科院一区，ESI 高被引) [3] Bo Yang, Tao Yu, Xiaoshun Zhang*, et al. Novel bio-inspired memetic salp swarm algorithm and application to MPPT for PV systems considering partial shading condition. Journal of Cleaner Production , 2019, 215: 1203-1222. (IF=6.395, 中科院一区，ESI 高被引) 2 基于人工智能优化的新能源最大功率跟踪 2、温度非均匀环境下的温差发电最大功率点跟踪 ➢ 在温度非均匀环境下 温差发电输出功率曲 线同样存在多个极值， 传统跟踪算法难以获 得全局最优点。 ➢ 使用性能高效的启发 式算法来逼近全局最 优大功率点，提升温 差发电能源转换效率。 [1] Bo Yang, Junting Wang, Xiaoshun Zhang*, et al. MPPT design of centralized thermoelectric generation system using adaptive compass search under non-uniform temperature distribution condition. Energy Conversion and Management , 2019, 199, 111991. (IF=7.181, 中科院一区) [2] Bo Yang, Junting Wang, Xiaoshun Zhang*, et al. Fast atom search optimization based MPPT design of centralized thermoelectric generation system under heterogeneous temperature difference. Journal of Cleaner Production , 2019, In Press (IF=6.395, 中科院一区) 3