摘要
随着绿色能源的大量投入使用,对储能装置的需求也相应增加,要求按比例配套投入,以有效应对电网供需双侧的不确定性,这带来了投资成本过高和回收周期过长的问题。为了应对绿色能源广泛应用带来的储能挑战,提出了一种多微电网储能装置共享模型,旨在显著减少整体储能容量的需求。为实现这一目标,设计了一种双层优化方法,并提出了一种多目标平衡优化器用以求解上层模型,避免结果陷入局部最优。通过数据实验验证,与传统的分布式储能方式相比,多微电网储能装置共享模型使系统所需的储能容量降低了43.30%。同时,算法对比结果表明,所提多目标优化算法具有足够的竞争力。
With the extensive use of green energy,the demand for energy storage devices has correspondingly increased,requiring proportional investments to effectively address the uncertainties on both the supply and demand sides of the power grid.This has led to issues of high investment costs and long payback periods.To tackle the storage challenges brought about by the widespread application of green energy,this paper proposes a shared model for energy storage devices in multiple microgrids,aiming to significantly reduce the overall demand for energy storage capacity.To achieve this goal,a bi-level optimization method is designed,and a multi-objective equilibrium optimizer is proposed to solve the upper-level model,thereby avoiding convergence to local optima.Data experiments validate that,compared to traditional distributed energy storage methods,the shared model for energy storage devices in multiple microgrids reduces the required storage capacity of the system by 43.30%.Additionally,algorithm comparative results indicate that the proposed multi-objective optimization algorithm is sufficiently competitive.
作者
代斌
王红蕾
DAI Bin;WANG Honglei(College of Electrical Engineering,Guizhou University,Guiyang 550025,China)
出处
《软件工程》
2025年第1期8-13,共6页
Software Engineering
基金
国家自然科学基金项目(52067004)
国家重点研发计划项目(2022YFE0205300)。
关键词
双侧不确定性
共享储能模型
多目标优化算法
平衡优化器
储能容量优化
可再生能源消纳率
bilateral uncertainty
shared energy storage model
multi-objective optimization algorithm
equilibrium optimizer
energy storage capacity optimization
renewable energy consumption rate
