摘要
针对中国西北地区新能源消纳问题,该文聚合风力发电、光伏发电、光热电站、电储能装置组成虚拟电厂(VPP),提出一种基于鲁棒随机优化理论的新能源虚拟电厂多时间尺度优化调度策略。首先对风力发电、光伏发电、光热电站与电储能装置进行数学描述,在此基础上建立VPP多时间尺度优化调度模型。在日前调度层中,以VPP运行效益最大为目标,依据风光日前预测出力建立日前优化调度模型;在时前调度层中,以VPP运行成本最小为目标,根据风光时前预测出力建立时前调度修正模型。同时,为了衡量风电、光伏发电出力不确定性对系统的运行影响,建立VPP随机优化调度模型。仿真结果验证该模型可提高运行效益与新能源消纳能力。
For the consumption problem of new energy in northwest China,the paper integrates the wind power,photovoltaic power,concentrating solar power plant and electric energy storage devices to form a virtual power plant(VPP),and proposes a multi-time scale stochastic optimization scheduling strategy of new energy virtual power plant based on robust stochastic optimization theory. First,mathematical description of the wind power photovoltaic power,concentrating solar power plant and electric energy storage devices is established. Based on that,the VPP multi-time scale optimization scheduling model is established. In the day-ahead scheduling layer,the paper takes the VPP operation benefit maximization as the goal,and establishes the day-ahead optimal scheduling model based on day-ahead forecasting output power of the wind power and photovoltaic power. In the hour-ahead scheduling layer,operation costs minimum is taken as the goal,and the day-ahead scheduling correction model is established by forecasting the current output of the wind power and photovoltaic power. Simultaneously,a VPP random scheduling model is established by application of measuring the impact of output uncertainty of wind power and photovoltaic power on system operation. The results show that the model can improve operating profit and new energy consumption capacity.
作者
张大海
贠韫韵
王小君
和敬涵
Zhang Dahai;Yun Yunyun;Wang Xiaojun;He Jinghan(School of Electrical Engineering,Beijing Jiaotong University,Beijing 100044,China)
出处
《太阳能学报》
EI
CAS
CSCD
北大核心
2022年第11期529-537,共9页
Acta Energiae Solaris Sinica
基金
国家自然科学基金(51977005)。
关键词
新能源
不确定性
虚拟电厂
运行成本
多时间尺度
鲁棒随机优化
new energy
uncertainty
virtual power plant
operating cost
multi-time scale
robust stochastic optimization
