首页> 外文会议>2015 30th International Power System Conference >Particle swarm optimization with smart inertia factor for combined heat and power economic dispatch
【24h】

Particle swarm optimization with smart inertia factor for combined heat and power economic dispatch

机译:具有智能惯性因子的粒子群算法优化火电联合经济调度

获取原文
获取原文并翻译 | 示例

摘要

In this research, particle swarm optimization with smart inertia factor (PSO-SIF) algorithm is suggested to solve combined heat and power economic dispatch (CHPED) problem. The CHPED problem is one of the most important problems in power systems and a challenging non-convex and non-linear optimization problem. The aim of solving the CHPED problem is to determine optimal heat and power of generating units with the minimized cost of total system and satisfied constraints of the problem. In the proposed algorithm, inertia coefficients are controlled regarding cost function in each population. Thus, each population has unique inertia coefficient and as a result unique velocity in convergent direction for the best group solution. In order to examine the proposed algorithm's capabilities and find optimum solution for CHPED problem, two test systems regarding valve-point effect, system power loss and system constraints are optimized. The obtained results demonstrate the superiority of the proposed method in solving non-convex CHPED problem over compared to the other new and efficient algorithms.
机译:为了解决热电联产经济调度(CHPED)问题,提出了基于智能惯性因子(PSO-SIF)算法的粒子群算法。 CHPED问题是电力系统中最重要的问题之一,也是具有挑战性的非凸和非线性优化问题。解决CHPED问题的目的是确定发电机组的最佳热量和功率,同时降低整个系统的成本并满足问题的约束条件。在提出的算法中,针对每个种群中的成本函数控制惯性系数。因此,每个总体具有唯一的惯性系数,因此对于最佳的组解,其在收敛方向上的唯一速度。为了检查提出的算法的能力并找到CHPED问题的最佳解决方案,针对阀点效应,系统功率损耗和系统约束两个测试系统进行了优化。获得的结果表明,与其他新的高效算法相比,该方法在解决非凸CHPED问题上具有优势。

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