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考虑次小时尺度运行灵活性的含储能机组组合 被引量:13

Unit Commitment with Energy Storage Considering Operation Flexibility at Sub-hourly Time-scales
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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。 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 timescale 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.
作者 张利 杨建 菅学辉 张峰 韩学山 ZHANG Li;YANG Jian;JIAN Xuehui;ZHANG Feng;HAN Xueshan(Key Laboratory of Power System Intelligent Dispatch and Control of Ministry of Education (Shandong University), Jinan 250061, China;State Grid Qingdao Electric Power Company, Qingdao 266002, China)
出处 《电力系统自动化》 EI CSCD 北大核心 2018年第16期48-56,共9页 Automation of Electric Power Systems
基金 国家自然科学基金资助项目(51477091)~~
关键词 机组组合 储能 运行灵活性 次小时尺度 unit commitment (UC) energy storage operational flexibility sub-hourly time scale
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