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电网技术  2015 

计及需求响应的风电储能两阶段调度优化模型及求解算法

DOI: 10.13335/j.1000-3673.pst.2015.05.018, PP. 1287-1293

Keywords: 需求响应,储能系统,风电,2阶段调度,混沌搜索,二进制粒子群算法

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Abstract:

为解决风电功率不确定性对系统稳定运行带来的影响,在含风电的系统优化调度问题中引入需求响应和储能系统。首先利用区间法模拟风电场景并构建了基于Kantorovich距离的场景削减策略,然后分别在需求侧和发电侧引入需求响应和储能系统,结合2阶段优化理论,以风电日前预测功率和超短期预测功率作为随机变量及其实现,构建了计及需求响应的风电储能2阶段调度优化模型。为求解该模型,在传统二进制粒子群算法中引入混沌搜索,构建了混沌二进制粒子群算法。最后,以IEEE36节点10机系统进行算例仿真。结果表明,混沌二进制粒子群算法能够得到全局最优解,适用于风电储能系统2阶段模型求解;利用需求响应和储能系统的协作效应,可以抑制风电功率的不确定性,提高系统风电利用效率,降低系统发电煤耗水平,因此综合效益显著。

References

[1]  徐玮,杨玉林,李政光,等.甘肃酒泉大规模风电参与电力市场模式及其消纳方案[J].电网技术,2010,34(6):71-77.Xu Wei,Yang Yulin,Li Zhengguang,et al.Participation mode of large-scale Jiuquan wind power farm in Gansu province to electricity market and its utilization scheme[J].Power System Technology,2010,34(6):71-77(in Chinese).
[2]  别朝红,胡国伟,谢海鹏.考虑需求响应的含风电电力系统的优化调度[J].电力系统自动化,2014,38(13):115-119.Bie Zhaohong,Hu Guowei,Xie Haipeng.Optimal dispatch for wind power integrated system considering demand response[J].Automation of Electric Power Systems,2014,38(13):115-119(in Chinese).
[3]  师洪涛,杨静玲,丁茂生,等.基于小波-BP神经网络的短期风电功率预测方法[J].电力系统自动化,2011,35(16):44-48.Shi Hongtao,Yang Jingling,Ding Maosheng,et al.A short-term wind power prediction method based on wavelet decomposition and BP neural network[J].Automation of Electric Power Systems,2011,35(12):44-48(in Chinese).
[4]  陆宁,周建中,何耀耀.粒子群优化的神经网络模型在短期负荷预测中的应用[J].电力系统保护与控制,2010,38(12):65-68.Lu Ning,Zhou Jianzhong,He Yaoyao.Particle swarm optimization-5 based neural network model for short-term load forecasting[J].Power System Protection and Control,2010,38(12):65-68(in Chinese).
[5]  张笑,何光宇,刘铠诚,等.基于半绝对离差风险的联合经济调度[J].电力系统自动化,2012,36(10):53-59.Zhang Xiao,He Guangyu,Liu Kaicheng,et al.A coordinated economic dispatch based on lower semi-absolute deviation risk[J].Automation of Electric Power Systems,2012,36(10):53-59(in Chinese).
[6]  Abreu L V L,Khodayar M E,Shahidehpour M,et al.Risk-constrained coordination of cascaded hydro units with variable wind power generation[J].IEEE Transactions on Sustainable Energy,2012,3(3):359-368.
[7]  熊虎,向铁元,陈红坤,等.含大规模间歇式电源的模糊机会约束机组组合研究[J].中国电机工程学报,2013,33(13):36-44.Xiong Hu,Xiang Tieyuan,Chen Hongkun,et al.Research of fuzzy chance constrained unit commitment containing large-scale intermittent power[J].Proceedings of the CSEE,2013,33(13):36-448 (in Chinese).
[8]  艾欣,刘晓.基于可信性理论的含风电场电力系统动态经济调度[J].中国电机工程学报,2011,31(S1):12-18.Ai Xin,Liu Xiao.Dynamic economic dispatch for wind farms integrated power system based on credibility theory[J].Proceedings of the CSEE,2011,31(S1):12-18 (in Chinese).
[9]  张钦,王锡凡,王建学.电力市场下需求响应研究综述[J].电力系统自动化,2008,32(3):97-106Zhang Qin ,Wang Xifan ,Wang Jianxue.Survey of demand response research in deregulated electricity markets[J].Automation of Electric Power Systems,2008,32(3):97-106(in Chinese).
[10]  王蓓蓓,李扬.面向智能电网的电力需求侧管理规划及实施机制[J].电力自动化设备,2010,30(12):19-24.Wang Beibei,Li Yang.Demand side management planning and implementation mechanism for smart grid[J].Electric Power Automation Equipment,2010,30(12):19-24(in Chinese).
[11]  Aalami H A,Moghaddam P M,Yousefi G R.Demand response modeling considering interruptible/curtailable loads and capacity market programs[J].Applied Energy,2010,(87):243-250.
[12]  吴雄,王秀丽,李骏,等.风电储能混合系统的联合调度模型及求解[J].中国电机工程学报,2013,33(33):10-17.Wu Xiong,Wang Xiuli,Li Jun,et al.A joint operation model and solution for hybrid wind energy storage systems[J].Proceedings of the CSEE,2013,33(33):10-17(in Chinese).
[13]  杨媛媛,杨京燕,夏天,等.基于改进差分进化算法的风电并网系统多目标动态经济调度[J].电力系统保护与控制,2012,40(23):24-29,35.Yang Yuanyuan,Yang Jingyan,Xia Tian,et al.Multi-objective dynamic economic dispatch in wind power integrated system based on an improved differential evolution algorithm[J].Power System Protection and Control,2012,40(23):24-29,35(in Chinese).
[14]  娄素华,余欣梅,熊信艮,等.电力系统机组启停优化问题的改进DPSO算法[J].中国电机工程学报,2005,25(8):30-35.Lou Suhua,Yu Xinmei,Xiong Xinyin,et al.Unit commitment using improved discrete particle swarm optimization algorithm[J].Proceedings of the CSEE,2005,25(8):30-35(in Chinese).
[15]  吴小珊,张步涵,袁小明,等.求解含风电场的电力系统机组组合问题的改进量子离散粒子群优化方法[J].中国电机工程学报,2013,33(4):45-52.Wu Xiaoshan,Zhang Buhan,Yuan Xiaoming,et al.Solutions to unit commitment problems in power systems with wind farms using advanced quantum-inspired binary PSO[J].Proceedings of the CSEE,2013,33(4):45-52(in Chinese).
[16]  Ding Huajie,Hu Zechun,Song Yonghua.Stochastic optimization of the daily operation of wind farm and pumped-hydro-storage plant[J].Renewable Energy,2012(48):571-578.
[17]  Growe-Kuska N,Heitsch H,Romisch W.Scenario reduction and scenario tree construction for power management problems[C]// Proceeding of IEEE Power Tech Conference.Bologna,Italy:IEEE,2003:1-7.
[18]  宋艺航,谭忠富,李欢欢,等.促进风电消纳的发电侧、储能及需求侧联合优化模型[J].电网技术,2014,38(3):610-615.Song Yihang,Tan Zhongfu,Li Huanhuan,et al.An optimization model combining generation side and energy storage system with demand side to promote accommodation of wind power[J].Power System Technology,2014,38(3):610-615(in Chinese).
[19]  谭忠富,鞠立伟,陈致宏,等.基于粗糙集理论与CLSDE算法的环境经济调度优化模型[J].电网技术,2014,38(5):1339-1345.Tan Zhongfu,Ju Liwei,Chen Zhihong,et al.An environmental economic dispatch optimization model based on rough set theory and chaotic local search strategy differential evolution algorithm[J].Power System Technology,2014,38(5):1339-1345(in Chinese).
[20]  钱玉良,张浩,彭道刚,等.基于新的广义粒子群方法的发电机组轴心轨迹提纯[J].中国电机工程学报,2012,32(2):130-137.Qian Yuliang,Zhang Hao,Peng Daogang,et al.Orbit purification of generator unit based on a new generalized particle swarm optimization method[J].Proceedings of the CSEE,2012,32(2):130-137(in Chinese).
[21]  李鹏,李涛,张双乐,等.基于混沌二进制粒子群算法的独立微网系统的微电源组合优化[J].电力自动化设备,2013,33(12):33-38.Li Peng,Li Tao,Zhang Shuangle,et al.Combinatorial optimization of micro-sources in standalone microgrid based on chaotic binary particle swarm optimization algorithm[J].Electric Power Automation Equipment,2013,33(12):33-38(in Chinese).
[22]  宗瑾.含风电和抽水蓄能的电力系统二阶段发电调度模型及算法研究[D].北京:华北电力大学,2012.
[23]  鞠立伟,李欢欢,陈致宏,等.基于两步制自适应求解算法的风电-电动汽车多种并网模式效益对比分析模型[J].电网技术,2014,38(6):1492-1498.24 Ju Liwei,Li Huanhuan,Chen Zhihong,et al.A benefit contrastive analysis model of multi grid-connected modes for wind power and plug-in hybrid electric vehicles based on two-step adaptive solving algorithm[J].Power System Technology,2014,38(6):1492-1498(in Chinese).
[24]  Kuk-Hyun H,Jong-Hwan K.Genetic quantum algorithm and its application to combinatorial optimization problem[C]//Proceedings of IEEE International Conference on Evolutionary Computation.California,USA:IEEE,2000:1354-1360.

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