电力系统自动化2017，Vol.41Issue(15)：58-65,8.DOI:10.7500/AEPS20170101001
考虑需求响应虚拟机组和碳交易的含风电电力系统优化调度
Optimal Dispatch of Power System Integrated with Wind Power Considering Virtual Generator Units of Demand Response and Carbon Trading
摘要
Abstract
With carbon trading and virtual generator units based demand response considered,a power system optimal dispatch model integrated with wind power is proposed against the background of smart grid and low-carbon electricity.Firstly,demand-side resources are divided into resources that are to be dispatched and those that are not.Virtual generator units of price-based demand response and incentive-based demand response are established and their operation characteristics are analyzed.Secondly,the carbon trading is introduced into the optimal dispatch model.The concept of CO2 emission mitigation target is presented and its restriction on carbon emission is analyzed.On this basis,a model considering cost of carbon trading,power generation cost of thermal power units and operating cost of virtual generator units is presented to formulate a novel low-carbon economical dispatch that takes into account constraints on power balance,units output and climbing rate,operation constraints of virtual generator units,and so on.Finally,the bacterial colony chemotaxis (BCC) algorithm is applied to solving this model.Wind power accommodating and the comprehensive operation costs of the system in different scenarios are analyzed through simulation examples.The feasibility and effectiveness of the proposed model and algorithm are verified by the results of numerical examples.关键词
智能电网/低碳电力/需求响应/虚拟机组/碳交易/细菌群体趋药性算法Key words
smart grid/low-carbon electricity/demand response/virtual generator unit/carbon trading/bacterial colony chemotaxis (BCC) algorithm引用本文复制引用
卢志刚,郭凯,闫桂红,何良策..考虑需求响应虚拟机组和碳交易的含风电电力系统优化调度[J].电力系统自动化,2017,41(15):58-65,8.基金项目
国家自然科学基金资助项目(61374098) （61374098）
高等学校博士学科点专项科研基金资助项目(20131333110017).This work is supported by National Natural Science Foundation of China (No.61374098) and Specialized Research Fund for the Doctoral Program of Higher Education (SPFDP) of China (No.20131333110017). （20131333110017）
