• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Electric power systems research >Transmission expansion planning using multivariate interpolation
【24h】

Transmission expansion planning using multivariate interpolation

机译：使用多元插值的传输扩展计划

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

The total cost of the transmission expansion planning (TEP) problem consists of investment and operation costs. The former is the required capital investment cost for new circuits throughout the network, and the latter is the cost of optimal generation dispatch to meet the demand at each hour. Traditionally, due to computational limits and long-term planning, the operation cost is not computed for hourly demand in the TEP problem. It is typically computed for the peak demand occurring during each year. In addition, the price of fuel used in the operation problem is considered fixed rather than variable overtime. In this paper, we use a multivariate interpolation method to compute the operation cost for the TEP problem in which the demand changes from hour to hour and the fuel price from day to day. A binary particle swarm optimization (BPSO) is proposed to solve the TEP problem. We apply our method to the Garver's 6-bus system and the IEEE 24-bus system for a planning horizon of ten years. By using the multivariate interpolation, the computational time of the solving algorithm is reduced. We compare our method with traditional methods based on the total cost of the obtained expansion plans. Experimental results show that the proposed method is an enhancement to solving the multi-year security-constrained TEP problem. (C) 2015 Elsevier B.V. All rights reserved.
机译：传输扩展计划（TEP）问题的总成本包括投资和运营成本。前者是整个网络中新电路所需的资本投资成本，而后者是满足每小时需求的最佳发电调度成本。传统上，由于计算限制和长期计划，TEP问题中的每小时需求不会计算运营成本。通常针对每年发生的高峰需求进行计算。另外，在操作问题中使用的燃料价格被认为是固定的，而不是可变的加班费。在本文中，我们使用多元插值方法来计算TEP问题的运行成本，在该过程中需求随时间变化，燃料价格随时间变化。提出了一种二进制粒子群算法（BPSO）来解决TEP问题。我们将我们的方法应用于Garver的6总线系统和IEEE 24-bus系统，规划期为十年。通过使用多元插值，减少了求解算法的计算时间。根据获得的扩展计划的总成本，我们将我们的方法与传统方法进行比较。实验结果表明，该方法是对多年安全受限的TEP问题的一种改进。 （C）2015 Elsevier B.V.保留所有权利。

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