摘要
对电力产品预售期最后时间段内收益进行单独分析,得到一个分段收益函数。利用积分性质和函数性质得到旺季、淡季和一般需求情况下的最佳预留量。然后构建了需求旺季情况下最佳预留量动态定价模型。对模型进行数值仿真实验,利用粒子群算法对模型进行求解。对该模型与一般动态定价模型进行对比,结果表明,在需求旺季时,最佳预留量模型预售期最优价格相对于一般动态定价模型价格波动更灵活,具有更好的适应性,获得的总收益要大于一般动态定价模型,证明了模型对于收益提升的有效性。
A subsection revenue function is obtained by analyzing the revenue in the last period of the reserved amount of electric power products.The optimal reserve quantity in peak season,low season and general demand is obtained by using integral and functional properties.Then the dynamic pricing model of optimal reserve volume in peak demand season is constructed.Numerical simulation experiments are carried out on the model,and particle swarm optimization algorithm is used to solve the model.Compared with general dynamic pricing model on the model,the results show that the peak in demand,optimal reserve volume model,the optimal price relative to the target date for price fluctuation general dynamic pricing model is more flexible and has better adaptability,the total revenue is greater than the general dynamic pricing model,prove the validity of the model for income increase.
作者
郝维一
王波
张媛
张国栋
HAO Wei-yi;WANG Bo;ZHANG Yuan;ZHANG Guo-dong(Management School,University of Shanghai for Science and Technology,Shanghai 200093,China)
出处
《经济研究导刊》
2020年第6期22-25,27,共5页
Economic Research Guide
关键词
最佳预留量
预售期
动态定价
粒子群算法
the best reserved quantity
reserved amount
dynamic pricing
particle swarm optimization algorithm
