Optimal Sizing of Hybrid Wind/PV/Diesel Generation in a Stand-Alone Power System Using Markov-Based Genetic Algorithm
Optimal Sizing of Hybrid Wind/PV/Diesel Generation in a Stand-Alone Power System Using Markov-Based Genetic Algorithm
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DOI：
10.1109/tpwrd.2011.2177102
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发表时间：
2012-01
影响因子：
4.4
通讯作者：
Yingyi Hong;Ruo-Chen Lian
中科院分区：
文献类型：
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作者：
Yingyi Hong;Ruo-Chen Lian
由于《京都议定书》和自然资源的日益枯竭，可再生能源引起了人们的广泛关注。本文考虑25千瓦风力发电机，5千瓦光伏发电机和30千瓦柴油发电机作为独立的电力系统发电规划的单元尺寸。投资成本（安装和单位成本）和燃料成本最小化，同时保持可靠性要求和CO排放限制。首先，模糊C-均值（FCM）聚类的系统负荷，风力发电机（WTG），光伏在8760 h的运行状态。然后，建立了系统负荷、风力发电机和光伏发电的马尔可夫模型。马尔可夫模型嵌入到遗传算法中，以确定WTG，PV和柴油发电机的最佳尺寸。仿真结果表明，与传统的时序数据法相比，该方法在保证最优性的前提下，大大减少了计算时间。
Owing to the Kyoto Protocol and the growing depletion of natural resources, renewable energies have attracted much attention. This paper considers 25-kW wind-turbine generator, 5-kW PV and 30-kW diesel generator as unit sizes for generation planning in a stand-alone power system. The investment cost (installation and unit costs) and fuel cost are minimized while retaining the reliability requirement and CO emission limit. First, the fuzzy-c-means (FCM) is employed to cluster the operation states for system load, wind-turbine generations (WTG), and PV in 8760 h. Then, the Markov models for the system load, WTG, and photovoltaic (PV) are established. The Markov models are embedded into the genetic algorithm to determine the optimal sizes for WTG, PV, and the diesel generator. The simulation results reveal that computation time can be reduced greatly while optimality can be still retained, compared with the traditional method using chronological data.