Risk Dispatch Strategy Study for Wind-Thermal Power System under Different Reserve Modes

doi:10.3969/j.issn.1000-7229.2016.06.005

Abstract

Abstract:

Due to its feasibility， demand side response and storage device can be used as virtual reserve resources to guarantee the security of power system with intermittent wind power penetration. In order to evaluate the impact of virtual reserve resource on the economy and environmental protection of the system， this paper establishes two different kinds of electricity dispatching models with wind power penetration for traditional thermal reserve and virtual fast reserve respectively. With the consideration of system risk brought by renewable energy generation， electricity market and unit parameters， we combine the interval two-stage stochastic optimization model with CVaR risk theory. The uncertainties of supply side and demand side are integrated with optimization function though interval value and probability， which can reflect the risk preferences of decision makers. The example analysis shows that the proposed hybrid optimization algorithm can effectively optimize the different spinning reserve modes of power system with wind power penetration， and make better trade-off between system cost and risk. The results show that making full use of storage battery and demand response as virtual reserve resources can efficiently reduce the system cost and CO2 emission.

Key words: wind power penetration, demand response, spinning reserve, internal programming, CVaR

CLC Number:

TM 715

JI Ling， XIE Yulei， HUANG Lucheng， NIU Dongxiao. Risk Dispatch Strategy Study for Wind-Thermal Power System under Different Reserve Modes[J]. Electric Power Construction, 2016, 37(6): 31-37.

References

［1］薛必克，张显，郑亚先，等.含风电的电力系统常规火电旋转备用对风电消纳的影响［J］. 华东电力，2014，42（8）：1550-1553.
XUE Bike， ZHANG Xian， ZHENG Yaxian， et al. Influence of thermal unit spinning reserve on wind power accommodation［J］. East China Electric Power， 2014， 42（8）:1550-1553.
［2］王彩霞，乔颖，鲁宗相.考虑风电效益的风火互济系统旋转备用确定方式［J］.电力系统自动化，2012，36（4）：16-21.
WANG Caixia， QIAO Ying， LU Zongxiang. A method for determination of spinning reserve in wind-termal power systems considering wind power benefits［J］. Automation of Electric Power System，2012，36（4）: 16-21.
［3］静铁岩，吕泉，郭琳，等.水电-风电系统日间联合调峰运行策略［J］.电力系统自动化，2011，35（22）：97-104.
JING Tieyan， LU Quan， GUO Lin， et al. An inter-day combined operation strategy of hydro and wind power system for regulating peak load［J］. Automation of Electric Power System，2011，35（22）：97-104.
［4］黄春雷，丁杰，田国良，等.大规模消纳风电的常规水电运行方式［J］.电力系统自动化，2011，35（23）:37-40.
HUANG Chunlei， DING Jie， TIAN Guoliang，et al.Hydropower pperation modes of large-scale wind power grid integration［J］.Automation of Electric Power Systems，2011，35（23）:37-40.
［5］盛四清，谭晓林，李欢，等.含风电场的互联电力系统备用容量优化［J］.电网技术，2013，37（11）：3067-3072.
SHENG Siqing， TAN Xiaolin， LI Huan， et al. Reserve capacity optimization of interconnected power grid containing wind farms［J］. Power System Technology， 2013， 37（11）:3067-3072.
［6］陈守军，辛禾，王涛，等.风电、蓄热式电锅炉联合供暖调度鲁棒优化模型［J］. 电力建设 2016，37（1）:103-109.
CHEN Shoujun， XIN He，WANG Tao， et al. Heating operation scheduling robust optimization model for heat storage electric boiler combined with wind power［J］. Electric Power Construction 2016， 37（1）:103-109.
［7］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（13）：13-17.
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（13）:13-17.
［8］王卿然，谢国辉，张粒子.含风电系统的发用电一体化调度模型［J］.电力系统自动化，2011，35（5）：15-18.
WANG Qingran， XIE Guohui， ZHANG Lizi. An integrated generation-consumption dispatch model with wind power［J］. Automation of Electric Power Systems， 2011， 35（5）:15-18.
［9］王蓓蓓，刘小聪，李杨.面向大容量风电接入考虑用户侧互动的系统日前调度和运行模拟研究［J］. 中国电机工程学报，2013，33（22），35-44.
WANG Beibei， LIU Xiaocong， LI Yang. Day-ahead generation scheduling and operation simulation considering demand side interaction in large-capacity wind power integrated systems［J］. Proceedings of the CSEE， 2013， 33（22）:35-44.
［10］马彦宏，汪宁渤，马明，等.基于神经网络的酒泉风电基地超短期风电功率预测方法［J］. 电力建设 2013，34（9）:1-5.
MA Yanhong， WANG Ningbo，MA Ming，et al. Ultra-short-term wind power prediction method based on neural network for Jiuquan wind power base［J］. Electric Power Construction 2013， 34（9）:1-5.
［11］葛炬，王飞，张粒子.含风电场电力系统旋转备用获取模型［J］. 电力系统自动化，2010，34（6）：32-36
GE Ju， WANG Fei， ZHANG Lizi. Spinning reserve model in the wind power integrated power system［J］. Automation of Electric Power Systems， 2010， 34（6）:32-36.
［12］罗超，杨军，孙元章，等. 考虑备用容量优化分配的含风电电力系统动态经济调度［J］. 中国电机工程学报，2014，34（34）：6109-6118.
LUO Chao， YANG Jun， SUN Yuanzhang， et al. Dynamic economic dispatch of wind integrated power system considering optimal scheduling of reserve capacity［J］. Proceedings of the CSEE， 2014， 34（34）:6109-6118.
［13］赵晋泉，唐洁，罗卫华，等.一种含风电电力系统的日前发电计划和旋转备用决策模型［J］.电力系统自动化设备，2014，34（5）：21-27.
ZHAO Jinquan， TANG Jie， LUO Weihua， et al. Day-ahead generation scheduling and spinning reserve decision-making model for power grid containing wind power［J］. Automation of Electric Power Systems， 2014， 34（5）: 21-27.
［14］苏鹏，刘天琪，李兴源.含风电的系统最优旋转备用的确定［J］.电网技术，2010，34（12）:158-162
SU Peng， LIU Tianqi， LI Xingyuan. Determination of optimal spinning reserve of power grid containing wind［J］. Power System Technology，2010，34（12）:158-162.
［15］余民，杨宸，蒋传文，等.风电并网后电力系统可靠性评估和备用优化研究［J］.电力系统保护与控制，2012，40（12）：100-104.
YU Min， YANG Minchen， JIANG Chuanwen， et al. Study on power system reliability and reserve optimization with wind power integration［J］. Power System Protection and Control， 2012， 40（12）:100-104.
［16］鞠立伟，于超，谭忠富.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［J］.电网技术，2015，39（5）：1287-1293.
JU Liwei， YU Chao， TAN Zhongfu. A two-stage scheduling optimization model and corresponding solving algorithm for power grid containing wind farm and energy storage system considering demand response ［J］. Power System Technology， 2015， 39（5）: 1287-1293.
［17］丁涛，郭庆来，柏瑞，等.考虑风电不确定性的区间经济调度模型及空间分支定界法.中国电机工程学报，2014，34（22）：3707-3914.
DING Tao， GUO Qinglai， BO Rui， et al. Interval economic dispatch model with uncertain wind power injection and spatial branchesand bound method［J］. Proceedings of the CSEE， 2013， 34（22）:3707-3914 .
［18］JI Ling， NIU Dongxiao， HUANG Guohe. An inexact two-stage stochastic robust programming for residential miro-gird management based on random demand［J］. Energy， 2014， 67（4）: 186-199.
［19］JI Ling， ZHANG Xingping， HUANG Guohe， et al. Development of an inexact risk-aversion optimization model for regional carbon constrained electricity system planning under uncertainty ［J］. Energy Conversion & Management， 2015， 94: 353-364.
［20］REDDY SS， BIJWE PR， ABHYANKAR A R. Joint energy and spinning reserve market clearing incorporating wind power and load forecast uncertainties ［J］. IEEE Systems Journal， 2015， 9（1）: 152-164.
［21］王雁凌，许传龙，岳巍澎.时变可靠性约束下含风电系统旋转备用的随机规划模型［J］.电网技术，2013，37（5）：1311-1316.
WANG Yanling， XU Chuanlong， YUE Weipeng. A stochastic programming model for spinning reserve of power grid containing wind farms under constraint of time-varying reliability［J］. Power System Technology， 2013， 37（5）:1311-1316.

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