• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Journal of Hydroinformatics >Optimal hydropower operation of multi-reservoir systems: hybrid cellular automata-simulated annealing approach
【24h】

Optimal hydropower operation of multi-reservoir systems: hybrid cellular automata-simulated annealing approach

机译：多储层系统的最优水电运行：混合蜂窝自动机模拟退火方法

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Hydropower operation of multi-reservoir systems is very difficult to solve mostly due to their nonlinear, nonconvex and large-scale nature. While conventional methods are long known to be incapable of solving these types of problems, evolutionary algorithms are shown to successfully handle the complexity of these problems at the expense of very large computational cost, particularly when population-based methods are used. A novel hybrid cellular automata-simulated annealing (CA-SA) method is proposed in this study which avoids the shortcomings of the existing conventional and evolutionary methods for the optimal hydropower operation of multi-reservoir systems. The start and the end instances of time at each operation period is considered as the CA cells with the reservoir storages at these instances are taken as the cell state which leads to a cell neighborhood defined by the two adjacent periods. The local updating rule of the proposed CA is derived by projecting the objective function and the constraints of the original problem on the cell neighborhoods represented by an optimization sub-problem with the number of decision variables equal to the number of reservoirs in the system. These sub-problems are subsequently solved by a modified simulated annealing approach to finding the updated values of the cell states. Once all the cells are covered, the cell states are updated and the process is iterated until the convergence is achieved. The proposed method is first used for hydropower operation of two well-known benchmark problems, namely the well-known four- and ten-reservoir problems. The results are compared with the existing results obtained from cellular automata. Genetic algorithm and particle swarm optimization indicating that the proposed method is much more efficient than existing algorithms. The proposed method is then applied for long-term hydropower operation of a real-world three-reservoir system in the USA, and the results are presented and compared with the existing results.
机译：多水库系统的水电操作很难大多因其非线性，非凸显和大型性质而解决。虽然常规方法很长，但是可以不能解决这些类型的问题，但是示出了进化算法以以非常大的计算成本为代价成功地处理这些问题的复杂性，特别是当使用基于种群的方法时。本研究提出了一种新型杂交蜂窝自动机模拟的退火（CA-SA）方法，避免了用于多储层系统的最佳水力发电操作的现有常规和进化方法的缺点。每个操作周期的时段的开始和结束实例被认为是具有这些实例的储存器存储器的CA单元被视为电池状态，该单元状态导致由两个相邻时段定义的小区邻域。通过投影目标函数和由优化子问题所示的小区邻域的原始问题的约束来导出所提出的CA的本地更新规则，该决策变量的数量等于系统中的储存器的数量。随后通过修改的模拟退火方法解决了这些子问题，以找到单元格状态的更新值。覆盖所有单元后，更新单元格状态，并将过程迭代，直到实现收敛。所提出的方法首先用于两个众所周知的基准问题的水电运行，即众所周知的四个水库问题。将结果与从细胞自动机获得的现有结果进行比较。遗传算法和粒子群优化，表明所提出的方法比现有算法更有效。然后将所提出的方法应用于美国现实世界三层储存系统的长期水电操作，并与现有结果呈现并比较结果。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号