LIU Yan-feng1， DONG Hai-ying1,2， WANG Ning-bo3, MA Ming3
（1. School of Automation & Electrical Engineering, Lanzhou Jiaotong University, Lanzhou 730070, China;2. School of New Energy & Power Engineering， Lanzhou Jiaotong University， Lanzhou 730070， China; 3. Wind Power Technology Center of Gansu Electric Power Company, Lanzhou 730070, China）
Abstract： Due to the phenomenon of abandoning wind power and photo voltage (PV) power in the “Three Northern Areas” in China, this paper presents an optimal strategy for coordinating and dispatching “source-load” in power system based on multiple time scales. On the basis of the analysis of the uncertainty of wind power and PV power as well as the characteristics of load side resource dispatching, the optimal model of coordinating and dispatching “source-load” in power system based on multiple time scales is established. It can simultaneously and effectively dispatch conventional generators, wind plant, PV power station, pumped-storage power station and load side resources by optimally using three time scales: day-ahead, intra-day and real-time. According to the latest predicted information of wind power, PV power and load, the original generation schedule can be rolled and amended by using the corresponding time scale. The effectiveness of the model can be verified by a real system. The simulation results show that the proposed model can make full use of “source-load” resources to improve the ability to consume wind power and PV power of the grid-connected system.
Key words： multiple time scales; “source-load” coordination; pumped-storage power station; wind plant; photovoltaic(PV) power station
CLD number： TM734 Document code： A
Article ID： 1674-8042（2018）04-0388-09 doi： 10.3969/j.issn.1674-8042.2018.04.013
References
［1］ Wang W S, Zhang C, He G Q, et al．Overview of research on subsynchronous oscillations in large-scale wind farm integrated system. Power System Technology, 2017, 41(4)： 1050-1060．
［2］ Nie Y H, Feng H R, Yu Y L, et al. Dynamic optimal power-flow of power system with wind power. Electric Power Automation Equipment, 2017, 37(2): 15-21．
［3］ Zhou W, Hu S B, Sun H, et al．Interval nonlinear economic dispatch in large scale wind power integrated system．In: Proceedings of the CSEE, 2017, 37(2): 557-564．
［4］ Li H L, Zhang Z Q, Tang X J, et al．Research on optimal capacity of large wind power considering joint operation with pumped hydro storage. Power System Technology, 2015, 39(10）： 2746-2750．
［5］ Gao C W, Luo H M, Zhu L L, et al. The energy-saving assessment and optimization of energy storage and electricity utilization technology based on the energy efficiency evaluation of power system. Transctions of China Electrotechnical Society, 2016, 31（11）： 140-148．
［6］ Cui Y, Chen Z, Yan G G, et al．Coordinated wind power accommodating dispatch model based on electric boiler and CHP with thermal energy storage．In: Proceedings of the CSEE, 2016, 36(15)： 4072-4080．
［7］ Zhao L, Li J M. Photovoltaic power extraction and the statistical properties of the random component analysis. Automation of Electric Power Systems, 2017, 41（1）： 48-56.
［8］ Chen G P, Li M J, Xu T, et al．Study on technical bottleneck of new energy development．In: Proceedings of the CSEE, 2017, 37(1)： 20-26．
［9］ Zhang X X, Niu H N, Zhao J X. Optimal dispatch method of distribution network with microgrid. Transactions of China Electrotechnical Society, 2017, 32(7): 165-173.
［10］ Luo C J, Li Y W, Xu H P, et al．Influence of demand response uncertainty on day－ahead optimization dispatching． Automation of Electric Power Systems, 2017, 41(5): 22-29．
［11］ Zhao H S, Zhao H Y, Hou J Q, et al. Effect of demand response on supply reliability of distribution network. Electric Power Automation Equipment, 2017, 37(1)： 8-14.
［12］ Li C Y, Chen X, Zhang P, et al. Considering demand response of predicted error of wind power based on multi-time scale optimal dispatching. Power System Technology, 2018, (2): 487-494.
［13］ Li B X, Han X S, Liu G J, et al. Thermal unit commitment with complementary wind power and energy storage system. Electric Power Automation Equipment, 2017, 37（7）： 32-37．
［14］ Chen Z Y, Wang D, Jia H, et al．Research on optimal day-ahead economic dispatching strategy for microgrid considering P2G and multi-source energy storage syste．In: Proceedings of the CSEE, 2017, 37(11)： 3067-3077．
［15］ To T, Rao M V C, Loo C K. A novel approach for unit commitment problem via an effective hybrid particle swarm optimization. IEEE Transactions on Power Systems, 2006, 21(1): 411-418.
［16］ Li D, Liu J Y, Liu Y B, et al．Joint secure & economic dispatch considering wind power, pumped storage and demand response. Electric Power Automation Equipment, 2015, 35(2)： 28-35．
［17］ Sun Y M, Verschuur D J．A self-adjustable input genetic algorithm for the near-surface problem in geophysics. IEEE Transactions on Evolutionary Computation, 2014, 18(3)： 309-325．
一种基于多时间尺度的电力系统“源-荷”协调调度优化策略
刘艳峰1， 董海鹰1,2， 汪宁渤3， 马 明3
（1. 兰州交通大学 自动化与电气工程学院， 甘肃 兰州 730070； 2. 兰州交通大学 新能源与动力工程学院， 甘肃 兰州 730070； 3. 甘肃省电力公司风电技术中心， 甘肃 兰州 730070）
摘 要: 针对三北地区弃风弃光问题， 提出了基于多时间尺度的电力系统“源-荷”协调调度优化策略。 在对风电、 光伏功率的不确定性和负荷侧资源调度特性分析的基础上， 建立了基于多时间尺度的电力系统“源-荷”协调调度优化模型。 该模型针对日前、 日内和实时3种不同时间尺度， 将常规机组、 风电场、 光伏电站、 抽水蓄能电站和负荷侧资源同时进行调度优化。 根据风电、 光伏和负荷等最新预测信息和机组电量实际完成情况， 按照相应的时间周期滚动修正原有发电计划。 以实际系统为例验证了模型的有效性， 仿真结果表明， 上述模型可以充分利用不同时间尺度上的“源-荷”资源， 提高了系统对风电、 光伏的消纳能力和并网后系统运行的经济性。
关键词: 多时间尺度； “源-荷”协调； 抽水蓄能电站； 风电厂； 光伏电站
引用格式： LIU Yan-feng， DONG Hai-ying， WANG Ning-bo, et al. An optimal strategy for coordinating and dispatching “source-load” in power system based on multiple time scales. Journal of Measurement Science and Instrumentation, 2018, 9(4)： 388-403. ［doi：10.3969／j.issn.1674-8042.2018.04.013］
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