文章摘要
张利,杨建,菅学辉,等.考虑次小时尺度运行灵活性的含储能机组组合[J].电力系统自动化,2018,42(16):48-56. DOI: 10.7500/AEPS20170930007.
ZHANG Li,YANG Jian,JIAN Xuehui, et al.Unit Commitment with Energy Storage Considering Operation Flexibility at Sub-hourly Time-scales[J].Automation of Electric Power Systems,2018,42(16):48-56. DOI: 10.7500/AEPS20170930007.
考虑次小时尺度运行灵活性的含储能机组组合
Unit Commitment with Energy Storage Considering Operation Flexibility at Sub-hourly Time-scales
DOI:10.7500/AEPS20170930007
关键词: 机组组合  储能  运行灵活性  次小时尺度
KeyWords: unit commitment(UC)  energy storage  operational flexibility  sub-hourly time-scale
上网日期:2018-06-01
基金项目:国家自然科学基金资助项目(51477091)
作者单位E-mail
张利 电网智能化调度与控制教育部重点实验室(山东大学), 山东省济南市 250061 yzhangli@sdu.edu.cn 
杨建 国网青岛供电公司, 山东省青岛市 266002  
菅学辉 电网智能化调度与控制教育部重点实验室(山东大学), 山东省济南市 250061  
张峰 电网智能化调度与控制教育部重点实验室(山东大学), 山东省济南市 250061  
韩学山 电网智能化调度与控制教育部重点实验室(山东大学), 山东省济南市 250061  
摘要:
      大规模可再生能源并网加重了电网的调频负担,对电力系统快速响应功率变化的能力,即次小时尺度的运行灵活性提出了更高要求。对此,文中提出一种考虑次小时尺度运行灵活性的含储能机组组合模型。在对系统净负荷区间变化规律进行分析的基础上,确立净负荷波动的关键场景并依此设置运行灵活性约束,明确了机组组合中小时尺度调度决策与次小时尺度运行灵活性需求间的牵制关系;同时,基于对储能在充电、放电、非充非放等各运行状态下提供运行灵活性的原理与制约因素的分析建立相关数学表达,并将其加入系统能量、功率平衡方程与运行灵活性约束,由此构建储能统筹利用与机组组合一体的数学模型。通过线性化处理,整个模型形成混合整数线性规划问题以实现求解。仿真分析表明,所提方法可优化利用储能,有效实现系统次小时尺度运行灵活性的提升。
Abstract:
      The integration of large-scale renewable energy aggravates the burden of frequency regulation for power grid, so the power system is required to be more capable of following power changes timely, that means higher demand for operational flexibility at sub-hourly time-scales. Thus this paper proposes a unit commitment(UC)model with energy storage considering operational flexibility at sub-hourly time-scales. Based on the analysis of range characteristics of the net load, the operational flexibility constraints are set according to the key scenarios of net load fluctuation. Therefore day-ahead dispatch in hourly time-scale is tied with sub-hourly operational flexibility requirements in UC. Meanwhile, the principles and restrictive factors of energy storage in different running states of charging, discharging and non-charging-and-non-discharging are discussed. Then the flexibility provided by energy storage is modeled and added to the system energy and power balance equation and operational flexibility constraints, respectively. Therefore the model of UC integrated with optimal deployment of energy storage is developed. By linearized processing, the model is reformed as a mixed integer linear programming(MILP)problem for solving. Simulations show that the proposed method can significantly improve the operational flexibility of power system at sub-hourly time-scales by using energy storage optimally.
查看全文(Free!)   查看附录   查看/发表评论  下载PDF阅读器