基于鸟群算法的分时电价优化研究

Research on Time-of-use Pricing Optimization Based on Bird Swarm Algorithm

分时电价是实施需求侧管理的措施之一,可引导用户的用电时段,削峰填谷,提高电能的利用率。首先,通过模糊隶属度函数对负荷曲线进行时段划分,基于消费者心理学建立用户响应模型,并以峰谷差最小为目标建立分时电价的数学模型;其次,利用测试函数对鸟群算法(BSA)进行验证;最后,利用MATLAB平台,同时用鸟群算法和遗传算法(GA)两种方法对模型求解,对比仿真结果表明本文算法和模型在分时电价定价方面的可行性和有效性。

Time-of-use Pricing is one of the measures to implement demand-side management,which can guide the user's electricity consumption period,cut peaks and fill valleys,and improve the utilization rate of electricity.First-ly,the load curve is divided into periods by fuzzy membership function,a user response model is established based on consumer psychology,and a mathematical model of time-of-use Pricing is established with the minimum peak-val-ley difference as the goal.Secondly,the test function is used to verify the bird swarm algorithm(BSA).Finally,the MATLAB platform was used to solve the model using both the bird swarm algorithm and the genetic algorithm(GA).The comparison of simulation results shows the feasibility and effectiveness of the proposed algorithm and model in time-of-use pricing.