随着风电渗透率的提高,大功率风电爬坡可造成系统功率不平衡,甚至导致停电事故。提出了基于信息差距决策理论(information gap decision theory,IGDT)鲁棒模型的风电爬坡事件协调调度决策方法。分析了各参与方的调度成本及约束条件,采用常规机组、风电场及需求侧协调调度的方式,降低风电爬坡事件的不利影响,并保证决策方案的经济性;利用IGDT方法处理风电功率的不确定性,构建最恶劣爬坡场景,制定针对预期成本具有鲁棒性的决策方案。算例及实际系统不同情形下调度决策方案的分析和比较,验证了所提调度决策方法的鲁棒性和经济性。
Universal Generating Function(UGF)techniques have been applied to Multi-State System(MSS)reliability analysis,such as long term reserve expansion of power systems with high wind power penetration.However,using simple steady-state distribution models for wind power and large generating units in reliability assessment can yield pessimistic appraisals.To more accurately assess the power system reliability,UGF techniques are extended to dynamic probabilistic simulation analysis on two aspects of modelling improvement.Firstly,a principal component analysis(PCA)combined with a hierarchal clustering algorithm is used to achieve the salient and time-varying patterns of wind power,then a sequential UGF equivalent model of wind power output is established by an apportioning method.Secondly,other than the traditional two-state models,the conventional generator UGF equivalent model is established as a four discrete-state continuous-time Markov model by Lztransform.In the construction process of such a UGF model,the state values are transformed into the integral multiples of one common factor by choosing proper common factors,thus effectively restraining the exponential growth of its state number and alleviating the explosion thereof.The method is suitable for reliability assessment with dynamic probabilistic distributed random variables.In addition,by acquiring the clustering information of wind power,the system reliability indices,such as fuel cost and CO_(2) emissions through different seasons and on different workdays,are calculated.Finally,the effectiveness of the method is verified by a modified IEEE-RTS 79 system integrated with several wind farms of historical hourly wind power data of Zhangbei wind farm in North China.