摘要
为了缓解用能持续增加对电力系统造成的负担和解决大规模电气设备联合调度时的优化计算问题,提出了考虑需求侧响应的大规模可控用电设备和储能设备的混合分散式优化调度方法。首先,建立可控用电设备负荷和储能设备的数学模型,在此基础上,构建了以系统和各设备运行特性为约束,以系统购电费用、用户不满意度费用和储能设备损耗费用之和最小为目标函数的混合整数非线性集中式优化数学模型。其次,针对此高维、多目标和多约束且难于求解的非线性集中式优化模型,采用拉格朗日松弛法将其分解为两个子问题,即分别对应可控电气设备负荷的优化调度问题和储能设备的优化调度问题。对于前者又可进一步分解为各可控电气设备负荷的优化调度子问题,并通过内点法求解计算;对于后者又可分解为各个储能设备问题的混合整数线性优化调度子问题,并通过Benders分解法并行求解计算。然后,为了验证所提混合分散式优化方法的有效性及其优越性,基于算例,对比分析集中式和分散式优化调度时的目标函数值和电气设备优化调度结果,不同规模电气设备对集中式和分散式优化方法计算效率的影响。根据结果可见,所提优化调度方法与集中式优化方法的目标函数值基本一致,但所提方法对应的电气设备优化调度结果可以很好地响应分时电价策略,储能设备削峰填谷效果好;而且,所提混合分散式优化方法可以降低优化问题的求解复杂度,计算效率高,几乎不受电气设备规模的影响。
In order to alleviate the burden of continuous increasing energy consumption falling on the power system and solve the complex calculation problem in the joint dispatching of large-scale electrical equipment,a hybrid decentralized optimization of dispatching the large-scale controllable appliances and energy storage equipment considering demand side response was proposed in this paper.Firstly,two mathematical models of controllable electrical equipment load and energy storage equipment were established.On this basis,a mixed integer non-linear centralized optimization model was mathematically formulated under the constraints of the operation characteristics of the system and equipment,with the objective of minimizing the sum of electricity purchase cost,users’dissatisfaction cost and energy storage equipment loss cost.Secondly,for tackling the difficult nonlinear centralized optimization problems of high dimensionality,multi objectives and multiple constraints,the Lagrange relaxation method was used to decompose the problem into two sub-problems,namely,optimally scheduling the controllable electrical equipment load and optimizing the dispatch of the energy storage equipment.Then,the former was further decomposed into optimizing dispatch of each controllable electrical equipment and solved by the interior point method,while the latter was decomposed into a set of mixed integer linear optimization sub-problems of scheduling each energy storage equipment and solved in parallel by the Benders decomposition method.Thirdly,a series of numerical simulations together with comparison analysis were performed to verify the effectiveness and superiority of the proposed dispatch optimization method.For example,the optimization objective value and the optimal dispatch solution corresponding to the proposed method were illustrated and compared with those of the centralized method to demonstrate the effectiveness of the hybrid decentralized optimization method.And the influence of different numbers of dispatching equipment on the computation efficiency was investigated on the centralized and decentralized optimization method to show the superiority of the proposed hybrid decentralized optimization method.According to the numerical simulation results,the optimization objective value of the proposed method is basically consistent with that of the centralized.Moreover,the identified dispatch solution enables to efficiently respond to the time-of-use and results in good effect of peak-shaving and valley-filly.Besides,the calculation efficiency of the proposed hybrid decentralized optimization method is of high computation efficiency and not affected by the increasing number of the schedulable electrical equipments.
作者
程杉
尚冬冬
代江
钟仕凌
CHENG Shan;SHANG Dongdong;DAI Jiang;ZHONG Shiling(Hubei Provincial Eng.Center for Intelligent Energy Technol.(CTGU),Yichang 443002,China;Electric Power Dispatching and Control Center of Guizhou Power Grid Co.,Ltd.,Guiyang 550002,China)
出处
《工程科学与技术》
EI
CSCD
北大核心
2021年第6期235-243,共9页
Advanced Engineering Sciences
基金
国家自然科学基金项目(51607105)
三峡大学硕士学位论文培优基金项目(2021SSPY069)。
关键词
需求响应
混合整数非线性规划
分散式优化
拉格朗日松弛法
内点法
Benders分解
demand response
mixed integer nonlinear programming
decentralized optimization
Lagrangian relaxation method
interior point method
Benders decomposition
