Chinese)．

[4] 陈海焱，陈金富，段献忠．含风电场电力系统经济调度

的模糊建模及优化算法[J]．电力系统自动化，2006，30(2)：22-26．

Chen Haiyan，Chen Jinfu，Duan Xianzhong．Fuzzy modeling and optimization algorithm on dynamic economic dispatch in wind power integrated system

图7 正旋转备用需求关于负备用成本系数函数曲线 Fig. 7 Up spinning reserve demand as a function of

down reserve cost coefficient

负旋转备用需求/MW

kp/($/(MW?h))?

[J]．Automation of Electric Power Systems，2006，30(2)：22-26(in Chinese) ．

[5] Miranda V，Hang P S．Economic dispatch model with

fuzzy wind constraints and attitudes of dispatchers

[J]．IEEE Transactions on Power Systems，2005，20(4)：2143-2145．

[6] Wang L F，Singh C．Tradeoff between risk and cost in

economic dispatch including wind power penetration using particle swarm optimization[C]//International Conference on Power System Technology．Chongqing，China：IEEE，2006：1-7．

[7] 周玮，彭昱，孙辉，等．含风电场的电力系统动态经济

调度[J]．中国电机工程学报，2009，29(25)：13-18． Zhou Wei，Peng Yu，Sun Hui，et al．Dynamic economic

图8 负旋转备用需求关于负备用成本系数函数曲线 Fig. 8 Down spinning reserve demand as a function of

down reserve cost coefficient

5 结论

本文在分析风电功率、负荷等概率特征并建立相应概率模型的基础上，提出了一种计及2种风险备用约束的含风电场电力系统动态经济调度新模

第1期 周玮等：计及风险备用约束的含风电场电力系统动态经济调度 55

[J]．东北电力大学学报，2009，29(1)：1-7

Meng Xiangxing，Wang Hong．Electric system scheduling in the condition of synchronization of large-scale wind power[J]．Journal of Northeast Dianli University，2009，29(1)：1-7(in Chinese)．

[17] Soder L．Reserve margin planning in a wind-hydro-

thermal power system[J]．IEEE Transactions on Power Systems，1993，8(2)：564-571．

[18] Lange M．On the uncertainty of wind power predictions-

analysis of the forecast accuracy and statistical distribution of errors[J]．Solar Energy Engineering，2005，127(2)：177-184．

[19] Matevosyan J，Soder L．Minimization of imbalance cost

trading wind power on the short-term power market [J]．IEEE Transactions on Power Systems，2006，21(3)：1396-1404．

[20] Siahkali H，Vakilian M．Stochastic unit commitment of

wind farms integrated in power system[J]．Electric Power Systems Research，2010，80(9)：1006-1017． [21] Zhao M，Chen Z，Blaabjerg F．Probabilistic capacity of

a grid connected wind farm based on optimization method[J]．Renewable Energy，2006，31(13)：2171–2187． [22] Doherty R，Malley M O．A new approach to quantify

reserve demand in systems with significant installed wind capacity[J]．IEEE Transactions on Power Systems，2005，20(2)：587-595．

[23] Zhou W，Peng Y，Sun H．Probabilistic wind power

penetration of power system using nonlinear predictor- corrector primal-dual interior-point method[C]//IEEE Electric Utility Deregulation and Restructuring and Power Technologies Conference．Nanjing，China：IEEE，2008：2548-2552．

[24] Attaviriyanupap P，Kita H，Tanaka E，et al．A hybrid EP

and SQP for dynamic economic dispatch with nonsmooth fuel cost function[J]．IEEE Transactions on Power Systems，2002，17(2)：411-416．

dispatch in wind power integrated system[J]．Proceedings of the CSEE，2009，29(25)：13-18(in Chinese)． [8] Chen C L．Optimal wind-thermal generating unit

commitment[J]．IEEE Transactions on Energy Conversion，2008，23(1)：273-280．

[9] Chen C L，Lee T Y，Jan R M．Optimal wind-thermal

coordination dispatch in isolated power systems with large integration of wind capacity[J]．Energy Conversion and Management，2006，47(18)：3456- 3472．

[10] Lee T Y．Optimal spinning reserve for a wind-thermal

power system using EIPSO[J]．IEEE Transactions on Power Systems，2007，22(4)：1612-1621．

[11] Hetzer J，Yu D C．An economic dispatch model

incorporating wind power[J]．IEEE Transactions on Energy Conversion，2008，23(2)：603-611．

[12] 任博强，彭鸣鸿，蒋传文，等．计及风电成本的电力系

统短期经济调度建模[J]．电力系统保护与控制，2010，38(14)：67-72．

Ren Boqiang，Peng Minghong，Jiang Chuanwen，et al．Short-term economic dispatch of power system modeling considering the cost of wind power[J]．Power System Protection and Control，2010，38(14)：67-72(in Chinese)．

[13] 江岳文，陈冲，温步瀛．基于随机模拟粒子群算法的含

风电场电力系统经济调度[J]．电工电能新技术，2007，26(3)：37-41．

Jiang Yuewen，Chen Chong，Wen Buying．Economic dispatch based on particle swarm optimization of stochastic simulation in wind power integrated system [J]．Advanced Technology of Electrical Engineering and Energy，2007，26(3)：37-41(in Chinese)．

[14] 孙元章，吴俊，李国杰，等．基于风速预测和随机规划

的含风电场电力系统动态经济调度[J]．中国电机工程学报，2009，29(4)：41-47．

Sun Yuanzhang，Wu Jun，Li Guojie，et al．Dynamic economic dispatch considering wind power penetration based on wind speed forecasting and stochastic programming[J]．Proceedings of the CSEE，2009，29(4)：41-47(in Chinese)．

[15] 戴慧珠，王伟胜，迟永宁．风电场接入电力系统研究的

新进展[J]．电网技术，2007，31(20)：16-23． Dai Huizhu，Wang Weisheng，Chi Yongning．Recent wind power integration study in China[J]．Power System Technology，2007，31(20)：16-23(in Chinese)． [16] 孟祥星，王宏．大规模风电并网条件下的电力系统调度

收稿日期：2011-08-26。 作者简介：

周玮(1981)，女，大连理工大学电气工程学院，博士，讲师，研究方向为含有风电场电力系统调度运行与安全分析，

周玮

zhouwei-ee@163.com。

(责任编辑 刘浩芳)

Extended Summary

正文参见pp.47-55

Dynamic Economic Dispatch of Wind Integrated Power Systems Based on

Risk Reserve Constraints

ZHOU Wei1, SUN Hui1, GU Hong1, MA Qian2, CHEN Xiaodong2

(1. Dalian University of Technology, Dalian 116024, Liaoning Province, China;

2. Liaoning Electric Power Dispatch and Communication Center, Shenyang 110006, Liaoning Province, China)

KEY WORDS: wind power generation; dynamic economic dispatch; spinning reserve; risk reserve constraint; interior point method

Large-scale wind power integration witnesses operational challenges due to the limited predictability and intermittency of wind speed. Especially the dynamic economic dispatch (DED) incorporating with wind power penetration has become complex and difficult. The conventional DED model and method are not suitable for the wind power integrated systems.

In order to deal with the uncertainties induced by generation forced outages, wind speed and load forecast errors, and quantify the effect of random variables on system risk, two risk indexes are introduced to describe the probabilities of shedding load and wasting energy respectively. And then a novel DED model of wind integrated power systems is proposed as follows:

min

h?1n?1

?[?Cn(Pn,h)??Cw,n(Wn,h)?

n?1

HNNw

du

Cp(Rh)?Cr(Rh)]

?N

?Pn,h?Wh?L,h?0?n??1

?Pnmin?Pn,h?Pnmax?

?0?Wh?PrNw???rdnT60?Pn,h?Pn,h?1?runT60s.t.?

u?frisk,u(Rh,Wh,Pn,h)??

?

h,mu

?0?Rh?Rup_sum?d

,Wh)???frisk,d(Rh

?dh,m??0?Rh?Rdown_sum

involved in the objective function of this DED model.

The uncertainties modeled by the probabilistic constraints are converted into deterministic inequality constraints. Simultaneously, the smoothing technology is utilized to transform the optimal problem into a typical nonlinear programming problem, and then predictor- corrector interior point method is adopted to solve the DED model.

The simulation study shows that, besides the optimal allocation of conventional generators, the scheduled power outputs of wind farm, up/down spinning reserve demand in each hour can also be obtained by solving the proposed model, which is given in Tab. 1. Furthermore, analysis indicates that the solution to DED issue using the proposed model is dependent on several factors, such as the system risk threshold, the up and down spinning reserve cost coefficients, etc. For example, the total generation cost decreases when risk threshold ???increases, which can be seen in Fig. 1. This means that the reduction of system security will bring some economic benefits.