文章摘要
黄伟,葛良军,华亮亮,等.参与双重市场的区域综合能源系统日前优化调度[J].电力系统自动化,2019,43(12):68-75. DOI: 10.7500/AEPS20181102007.
HUANG Wei,GE Liangjun,HUA Liangliang, et al.Day-ahead Optimal Scheduling of Regional Integrated Energy System Participating in Dual Market[J].Automation of Electric Power Systems,2019,43(12):68-75. DOI: 10.7500/AEPS20181102007.
参与双重市场的区域综合能源系统日前优化调度
Day-ahead Optimal Scheduling of Regional Integrated Energy System Participating in Dual Market
DOI:10.7500/AEPS20181102007
关键词: 区域综合能源系统  场景分析技术  日前优化调度  旋转备用市场  调整成本
KeyWords: regional integrated energy system  scenario analysis technology  day-ahead optimal scheduling  spinning reserve market  adjustment cost
上网日期:2019-05-06
基金项目:国家自然科学基金资助项目(E070401)
作者单位E-mail
黄伟 华北电力大学电气与电子工程学院, 北京市 102206  
葛良军 华北电力大学电气与电子工程学院, 北京市 102206 2218173428@qq.com 
华亮亮 蒙东通辽供电公司, 内蒙古自治区通辽市 028000  
陈艳波 华北电力大学电气与电子工程学院, 北京市 102206  
摘要:
      分布式新能源和电负荷等不确定变量是区域综合能源系统(RIES)安全稳定运行面临的巨大挑战之一。根据不确定变量的概率分布,运用场景分析技术生成典型场景拟合次日运行工况及其发生概率。在此基础上考虑不同供能系统间的互补特性,同时参与能量市场和旋转备用市场,建立日前优化调度模型。模型评估RIES各时段备用资源潜力和成本,以调度方案成本和调整成本期望值之和最低为目标函数,制定运行计划和安排备用资源。结合粒子群算法和内点法对模型进行求解。算例表明,该模型通过发挥RIES多能互补优势和合理安排备用资源应对源荷波动,提高了能源供应的经济性和可靠性。
Abstract:
      Uncertain variables such as distributed new energy and electric load are one of the greatest challenges facing regional integrated energy system(RIES)to maintain the safe and stable operation. According to the probability distribution of the variables, scenario analysis technology is applied to generate typical scenarios to fit operation conditions of next day and the occurrence probability. Based on this, a day-ahead optimal scheduling model, which utilizes complementary characteristics of different energy supply systems, is presented while participating in energy market and spinning reserve market. The model proposed evaluates the potential and cost of reserves during each period, and formulates the operation plan including the arrangement of reserves with the object function to minimize the sum of the scheduling plan cost and adjustment cost expectation. A powerful approach combining particle swarm algorithm with interior point algorithm is designed to solve the model. The example verifies that the model can improve the economy and reliability of energy supply by taking full advantage of the multi-energy complementary characteristic of RIES and reasonably arrange the reserves to deal with source-load fluctuations.
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