基于粒子群算法的变电站工程造价投资估算模型

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。

Optimization for Cost Estimation of Power Grid Projects Basedon Particle Swarm Optimization

There are many factors influencing the cost of power grid projects,which result in difficulty in cost estimation andmanagement. The budgetary estimates of power grid projects often exceed actual costs,which cause the waste of abundant money. Inorder to effectively control cost estimation of power grid projects,it is necessary to investigate the optimization method forestimating costs of power grid projects. Therefore,this paper applied particle swarm optimization（PSO）to the historical data ofAnhui Electric Power Company from 2010 to 2015 to develop a cost estimation model for power grid projects. A typical case studywas also conducted to verify the feasibility of the PSO cost estimation model for power grid projects. The practical suggestions werealso proposed based on current results to control cost estimation of power grid projects in future