| 引用本文: | 韩畅,梁博淼,林振智,文福拴,易仕敏.防灾应急电源优化调度的机会约束规划方法[J].电力自动化设备,2018,(3): |
| HAN Chang,LIANG Bomiao,LIN Zhenzhi,WEN Fushuan,YI Shimin.Chance-constrained programming method for optimal scheduling of emergency power source[J].Electric Power Automation Equipment,2018,(3): |
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| 摘要: |
| 在电力系统防灾应急体系中，需要合理调度防灾应急电源，以最大限度地降低停电损失。在实际停电事故发生时，调度环境非常复杂且具有很多不确定性因素，而现有防灾应急电源优化调度方面的研究大多未计及多重不确定性因素的影响。在此背景下，假定应急电源的行驶时间近似服从正态分布，失电用户的缺电功率近似服从区间均匀分布，在此基础上建立基于机会约束规划的防灾应急电源优化调度模型。该模型以重要失电用户的总停电损失最小为优化目标，采用置信水平处理模型中的不确定参数，并在量子进化算法中嵌入蒙特卡洛仿真来求解。算例分析结果表明所提方法可以处理电力应急过程中的多重不确定性因素，合理分配防灾应急电源，进而降低停电损失。 |
| 关键词: 防灾应急电源 优化调度 机会约束规划 量子进化算法 蒙特卡洛仿真 |
| DOI：10.16081/j.issn.1006-6047.2018.03.020 |
| 分类号:TM73 |
| 基金项目:国家自然科学基金资助项目(51377005)；国家重点研发计划项目(2016YFB0900105)；浙江省自然科学基金资助项目(LY17E070003) |
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| Chance-constrained programming method for optimal scheduling of emergency power source |
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HAN Chang1, LIANG Bomiao1, LIN Zhenzhi1, WEN Fushuan1,2, YI Shimin3
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1.School of Electrical Engineering, Zhejiang University, Hangzhou 310027, China;2.Department of Electrical & Electronic Engineering, Universiti Teknologi Brunei, Bandar Seri Begawan BE1410, Brunei;3.Guangdong Power Grid Co.,Ltd.,Guangzhou 510620, China
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| Abstract: |
| In disaster prevention and emergency support of a power system, the reasonable scheduling of emergency power sources plays an important role in minimizing the outage losses of important customers. The operating condition of a power system is complex and uncertain when power outage occurs. How to properly schedule emergency power sources under multiple uncertain factors has not yet been systematically addressed. Given this background, it is assumed that the traveling time of each emergency power source approximately follows the normal distribution and the outage power of each important customer approximately follows the uniform distribution. An optimal scheduling model of emergency power sources is developed under the well-established chance-constrained programming framework. In the developed optimization model, the objective is formulated as the minimization of the total outage losses of important customers, and the confidence level is adopted to deal with the uncertain parameters. The quantum evolutionary algorithm with the Monte Carlo simulation embedded is employed to solve the optimization model. Case studies show that the proposed scheme can handle multiple uncertain factors in emergency processes, and properly schedule emergency power sources and hence reduce the outage losses. |
| Key words: emergency power sources optimal scheduling chance-constrained programming quantum evolutionary algorithm Monte Carlo simulation |
