Chinese)．

[4] 陳海焱，陳金富，段獻忠．含風電場電力系統(tǒng)經濟調度

的模糊建模及優(yōu)化算法[J]．電力系統(tǒng)自動化，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

圖7 正旋轉備用需求關于負備用成本系數(shù)函數(shù)曲線 Fig. 7 Up spinning reserve demand as a function of

down reserve cost coefficient

負旋轉備用需求/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] 周瑋，彭昱，孫輝，等．含風電場的電力系統(tǒng)動態(tài)經濟

調度[J]．中國電機工程學報，2009，29(25)：13-18． Zhou Wei，Peng Yu，Sun Hui，et al．Dynamic economic

圖8 負旋轉備用需求關于負備用成本系數(shù)函數(shù)曲線 Fig. 8 Down spinning reserve demand as a function of

down reserve cost coefficient

5 結論

本文在分析風電功率、負荷等概率特征并建立相應概率模型的基礎上，提出了一種計及2種風險備用約束的含風電場電力系統(tǒng)動態(tài)經濟調度新模

第1期 周瑋等：計及風險備用約束的含風電場電力系統(tǒng)動態(tài)經濟調度 55

[J]．東北電力大學學報，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] 任博強，彭鳴鴻，蔣傳文，等．計及風電成本的電力系

統(tǒng)短期經濟調度建模[J]．電力系統(tǒng)保護與控制，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，陳沖，溫步瀛．基于隨機模擬粒子群算法的含

風電場電力系統(tǒng)經濟調度[J]．電工電能新技術，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] 孫元章，吳俊，李國杰，等．基于風速預測和隨機規(guī)劃

的含風電場電力系統(tǒng)動態(tài)經濟調度[J]．中國電機工程學報，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，王偉勝，遲永寧．風電場接入電力系統(tǒng)研究的

新進展[J]．電網技術，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．大規(guī)模風電并網條件下的電力系統(tǒng)調度

收稿日期：2011-08-26。 作者簡介：

周瑋(1981)，女，大連理工大學電氣工程學院，博士，講師，研究方向為含有風電場電力系統(tǒng)調度運行與安全分析，

周瑋

zhouwei-ee@163.com。

(責任編輯 劉浩芳)

Extended Summary

正文參見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.