基于粒子群算法的变电站工程造价投资估算模型  

Optimization for Cost Estimation of Power Grid Projects Based on Particle Swarm Optimization

作　　者：王道静[1] 朱晓虎[2] 刘士李[2] 刘丽[2] WANG Dao-jing ZHU Xiao-hu LIU Shi-li LIU li(State GridAnhui Electric Power Company, Hefei 230061, China, E-mail： [e-mail] Research Institute of Economy and Technology, State Grid Anhui Electric Power Company, Hefei 230009, China)

机构地区：[1]国网安徽省电力公司,安徽合肥230061 [2]国网安徽省电力公司经济技术研究院,安徽合肥230009

出　　处：《工程管理学报》2017年第3期43-47,共5页Journal of Engineering Management

基　　金：国家电网公司科学技术项目(W2016JSFW0304);安徽省哲学社会科学规划项目(AHSKQ2015D39)

摘　　要：安徽电网变电站工程近年发展迅速,但是由于工程复杂,影响因素多,增加了变电站工程造价管控的难度,使得变电站工程造价节余率过高,降低了电网公司的投资效益。为了有效控制变电站工程概算,有必要创新性展开变电站工程投资估算工具的研究。基于粒子群算法,深度挖掘安徽电网变电站工程2010~2015年的历史造价数据,构建变电站工程投资估算优化模型,分析各种因素对安徽地区变电站工程造价的影响,提出合理控制工程造价的手段。通过典型案例的优化计算,验证了变电站工程投资估算优化模型的可行性,为进一步在安徽电网公司推广奠定了基础。There are many factors influencing the cost of power grid projects, which result in difficulty in cost estimation and management. The budgetary estimates of power grid projects often exceed actual costs, which cause the waste of abundant money. In order to effectively control cost estimation of power grid projects, it is necessary to investigate the optimization method for estimating costs of power grid projects. Therefore, this paper applied particle swarm optimization （PSO） to the historical data of Anhui Electric Power Company from 2010 to 2015 to develop a cost estimation model for power grid projects. A typical case study was also conducted to verify the feasibility of the PSO cost estimation model for power grid projects. The practical suggestions were also proposed based on current results to control cost estimation of power grid projects in future.

关 键 词：变电站工程 工程造价 粒子群算法 投资估算模型 

分 类 号：TU723.3[建筑科学—建筑技术科学]