考虑平滑效应的多源优化调度模型研究
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摘要
充分利用风光出力的平滑效应,可以降低可再生能源的总体波动性,有助于缓解风光并网对系统的冲击,提升系统运行经济性。针对基于平滑效应的电力系统多源调度问题,文章首先研究了基于风光出力波动的自适应天气辨识方法,实现了不同天气的自适应辨识;之后,以标准差及电源额定功率对平滑效应进行量化,以平滑效应最优、发电成本最低为双层目标函数,建立了不同天气类型下多源互补双层优化调度模型。通过仿真算例表明,优化调度模型不仅降低了可再生能源的波动性,且减少系统备用成本和发电成本,可以实现系统经济效益的提升。
Making full use of the smooth effect of renewable energy output can reduce the volatility of renewable energy.It reduces the impact of renewable energy access to the grid and improves the economic efficiency of the system.For the multi-source scheduling problem of power system based on the smoothing effect,this paper first studies the adaptive weather identification method based on the fluctuation of wind and power output,and realizes the adaptive identification of different weather.After that,the smoothing effect is quantified by the standard deviation and the power nominal power.With the smoothest effect and the lowest cost of power generation as the double-layer objective function,a multi-source complementary bi-level optimal scheduling model for different weather types is established.The simulation example shows that the optimized scheduling model proposed in this paper not only reduces the volatility of renewable energy,but also reduces the system standby cost and power generation cost,and improves the system economic efficiency.
Making full use of the smooth effect of renewable energy output can reduce the volatility of renewable energy.It reduces the impact of renewable energy access to the grid and improves the economic efficiency of the system.For the multi-source scheduling problem of power system based on the smoothing effect,this paper first studies the adaptive weather identification method based on the fluctuation of wind and power output,and realizes the adaptive identification of different weather.After that,the smoothing effect is quantified by the standard deviation and the power nominal power.With the smoothest effect and the lowest cost of power generation as the double-layer objective function,a multi-source complementary bi-level optimal scheduling model for different weather types is established.The simulation example shows that the optimized scheduling model proposed in this paper not only reduces the volatility of renewable energy,but also reduces the system standby cost and power generation cost,and improves the system economic efficiency.
引文
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[2]SOLOMON A A,FAIMAN D,MERON G.Grid matching of large-scale wind energy conversion systems alone and in tandem with large-scale photovoltaic systems:an Israeli case study[J].Energy Policy,2010(38):7070-7081.
[3]刘燕华,田茹,张东英,等.风电出力平滑效应的分析与应用[J].电网技术,2013,37(4):987-991.LIU Yanhua,TIAN Ru,ZHANG Dongying,et al.Analysis and application of wind farm output smoothing effect[J].Power System Technology,2013,37(4):987-991.
[4]申颖,赵千川,李明扬.多时空尺度下风电平滑效应的分析[J].电网技术,2015,39(2):400-405.SHEN Ying,ZHAO Qianchuan,LI Mingyang.Analysis on wind power smoothing effect in multiple temporal and spatial scales[J],Power System Technology,2015,39(2):400-405.
[5]马骏毅,陈蕾,许象明,等.基于模糊控制的风光储发电系统输出功率平滑控制[J].广东电力,2014(12):35-41.MA Junyi,CHEN Lei,XU Xiangming.Smoothing control on output power of wind/solar hybrid generation system based on fuzzy control[J],Guangdong Electric Power,2014(12):35-41.
[6]李湃,管晓宏,吴江,等.基于天气分类的风电场群总体出力特性分析[J].电网技术,2015,39(7):1866-1872.LI Pai,GUAN Xiaohong,WU Jiang,et al.Analyzing characteristics of aggregated wind power generation based on weather regime classification[J].Power System Technology,2015,39(7):1866-1872.
[7]STEPHANE G M.A theory for multi-resolution signal decomposition:the wavelet representation[J].IEEETransactions on Pattern Analysis and Machine ntelligence,1989,11(7):674-693.
[8]National renewable energy laboratory.Wind power data of west coast[EB/OL].[2008-8-15].http://wind.nrel.gov/Web_nrel/.
[9]UO Solar Radiation Monitoring Laboratory.Solar data of university of oregon[EB/OL].[2013-8-9].http://solardat.uoregon.edu/Select Monthly Average.html.
[10]CARRION M,ARROYO J M.A computationally efficient mixed-integer linear formulation for the thermal unit commitment problem[J].IEEE Transactions on Power Systems,2006,21(3):1371-1378.
[11]LOFBERG J.YALMIP:a toolbox for modeling and optimization in Matlab[C]//Computer Aided Control Systems Design,2004 IEEE International Symposium on New Orleans:IEEE,2004:284-289.