基于RWCS搜索算法的电网多项目组合投资优化决策研究

电网企业的投资项目数量多、金额大,其投资决策是一项较为复杂的工作,需要权衡很多的影响因素和目标函数,考虑如何进行合理的资金分配。通过引入投资组合优化的概念,以经济效益、安全性和社会性为目标函数,考虑电力需求、可靠性、企业投资能力等约束条件,构建了电网企业多项目组合投资优化决策模型。结合布谷鸟搜索算法(Cuckoo search algorithm,CS)在优化问题中较高的求解性能,利用随机权重(Random Weight,RW)动态优化布谷鸟算法。运用实际的算例,验证该模型方法应用于电网建设项目投资组合决策的可操作性和有效性。

Optimal Decision-Making of Multi-Project Portfolio Investment for Power Grid Based on Cuckoo Search Algorithm Optimized by Stochastic Weight

Because of the large number and amount of investment projects in power grid enterprises, investment decision-making is a relatively complex task, which needs to weigh many factors and objective functions and consider how to allocate the limited funds to different construction projects. By introducing the concept of portfolio optimization, this paper takes the maximization of economy, security and sociality as the objective function, considers the constraints of power demand, reliability, enterprise investment capacity and other resources, and constructs optimal decision-making of multi-project portfolio investment for power grid enterprises. Cuckoo search algorithm (CS), as a new heuristic algorithm, has high performance in solving optimization problems. In this paper, stochastic weights are introduced to dynamically optimize cuckoo algorithm, which can further improve the optimization performance of the algorithm. Combining with practical examples and using MATLAB tools, the operability and practicability of the model in multi-project portfolio optimization of power grid are verified.