摘要
为解决大规模新能源接入导致传统电网中常规机组调节压力不断增大的问题,提出了一种考虑储能和多种工业负荷参与的多时间尺度优化调度策略。该策略通过协调荷侧电解铝、水泥、钢铁、非生产性负荷与储能以及源侧常规机组调用计划,有效缓解电网调节压力。首先,分析储能和多种工业负荷的调节特性,建立风-光-荷-储的滚动调节框架。然后,针对源荷不确定性,采用多场景随机规划与模糊机会约束目标规划相结合的方法,建立日前和日内阶段以系统经济性最优为目标、实时调度阶段兼顾安全性和经济性的多时间尺度调度模型。最后,通过新能源充足与不足典型日算例可知,本文所提调度策略能够充分发挥可调控资源的调节能力,在两种典型日的总成本较日前最优调度分别降低了17.08%、44.13%,弃新能源量降低39%、失负荷量降低23%,有效提高了电网运行经济性和安全性。
In order to solve the problem of increasing regulation pressure of conventional units in traditional power grid caused by large-scale new energy access,a multi-time scale optimal dispatching strategy considering energy storage and multi-industrial load participation was proposed.This strategy can effectively relieve the pressure of power grid regulation by coordinating electrolytic aluminum,cement,steel,unproductive load and energy storage on the load side and conventional unit calling plan on the source side.Firstly,the regulation characteristics of energy storage and various industrial loads were analyzed,and a rolling regulation framework of wind-light-load-storage was established.Secondly,aiming at the source load uncertainty,the multi-scenario stochastic programming combined with fuzzy chance constrained goal programming was adopted to establish a multi-time scale scheduling model,which aimed at the optimal system economy in the day-ahead and day-ahead stages,and took into account both security and economy in the real-time scheduling stage.Finally,through the typical days of sufficient and insufficient new energy,it can be seen that the scheduling strategy can give full play to the adjustment ability of controllable resources.The total cost on the two typical days was reduced by 17.08%and 44.13%respectively compared with the previous optimal scheduling,the amount of abandoned new energy was reduced by 39%,and the amount of lost load by 23%,which effectively improved the safety and economy of power grid operation.
作者
王小庆
王海云
范添圆
闫斯哲
郑红娟
WANG Xiao-qing;WANG Hai-yun;FAN Tian-yuan;YAN Si-zhe;ZHENG Hong-juan(Engineering Research Center of Education Ministry for Renewable Energy Power Generation and Grid Connection,Xinjiang University,Urumqi 830047,China;College of Electrical Engineering,Zhejiang University,Hangzhou 310027,China;Nari Technology Co.,Ltd.,Nanjing 211106,China)
出处
《科学技术与工程》
北大核心
2024年第15期6290-6299,共10页
Science Technology and Engineering
基金
新疆维吾尔自治区重点研发计划(2022B01020-3)。
关键词
工业负荷
储能
多时间尺度
多场景随机规划
模糊机会约束目标规划
industrial loads
energy storage
multiple time scales
multi-scenario stochastic programming
fuzzy chance-constrained goal programming