自下而上的主动配电网负荷曲线化预测方法
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摘要
为在主动配电网负荷预测工作中计及柔性负荷的影响,提出了一种自下而上的主动配电网负荷的曲线化预测方法。首先,将待预测区域按用地性质、功能边界划分为若干小区,将每个区域的负荷需求细分为刚性负荷和柔性负荷需求两类;然后,建立可转移负荷和可调整负荷两种柔性负荷的曲线化调控模型,进而模拟主动管理策略下柔性负荷对整体负荷需求的调整作用;最后,将待预测区域的地块负荷进行叠加,得到主动配电网管理模式下的负荷需求曲线。通过北京某开发区负荷曲线预测算例,验证了所提预测模型和方法的有效性。
With the consideration of the influence of flexible load on load forecasting,a bottom-to-top load curve forecasting method for active distribution network is put forward in this paper.First,the area to be forecasted is divided into several units according to the land usage property and function boundary,and the load demand of each unit is divided into two types,i.e.,rigid load demand and flexible load demand.Then,the curve regulation models for two flexible loads,i.e.,transferable load and adjustable load,are established,which are further used to simulate the regulation effect of flexible load on the overall load demand under the active management strategy.Finally,the load on each unit of the area to be forecasted is superimposed,thus the load demand curve in the management mode of active distribution network is obtained.The effectiveness of the proposed forecasting model and method is verified by the load curve forecasting result of one development zone in Beijing.
With the consideration of the influence of flexible load on load forecasting,a bottom-to-top load curve forecasting method for active distribution network is put forward in this paper.First,the area to be forecasted is divided into several units according to the land usage property and function boundary,and the load demand of each unit is divided into two types,i.e.,rigid load demand and flexible load demand.Then,the curve regulation models for two flexible loads,i.e.,transferable load and adjustable load,are established,which are further used to simulate the regulation effect of flexible load on the overall load demand under the active management strategy.Finally,the load on each unit of the area to be forecasted is superimposed,thus the load demand curve in the management mode of active distribution network is obtained.The effectiveness of the proposed forecasting model and method is verified by the load curve forecasting result of one development zone in Beijing.
引文
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[2]张琨,葛少云,刘洪,等(Zhang Kun,Ge Shaoyun,Liu Hong,et al).智能配电系统环境下的电动汽车调频竞标模型(A bidding model for electric vehicles to provide regulation services based on intelligent distribution system)[J].电网技术(Power System Technology),2016,40(9):2588-2595.
[3]Yao Enxin,Samadi P,Wong V W S,et al.Residential demand side management under high penetration of rooftop photovoltaic units[J].IEEE Trans on Smart Grid,2016,7(3):1597-1608.
[4]杨旭英,周明,李庚银(Yang Xuying,Zhou Ming,Li Gengyin).智能电网下需求响应机理分析与建模综述(Survey on demand response mechanism and modeling in smart grid)[J].电网技术(Power System Technology),2016,40(1):220-226.
[5]赵兴勇,王帅,吴新华,等(Zhao Xingyong,Wang Shuai,Wu Xinhua,et al).含分布式电源和电动汽车的微电网协调控制策略(Coordinated control strategy research of micro-grid including distributed generations and electric vehicles)[J].电网技术(Power System Technology),2016,42(12):3732-3740.
[6]刘广一,罗凤章,刘友波.主动配电网规划与运行[M].北京:中国电力出版社,2017.
[7]徐青山,杨辰星,颜庆国(Xu Qingshan,Yang Chenxing,Yan Qingguo).计及规模化空调热平衡惯性的电力负荷日前削峰策略(Strategy of day-ahead power peak load shedding considering thermal equilibrium inertia of largescale air conditioning loads)[J].电网技术(Power System Technology),2016,40(1):156-163.
[8]Xie Naiming,Liu Sifeng.Discrete grey forecasting model and its optimization[J].Applied Mathematical Modelling,2009,33(2):1173-1186.
[9]Gilbraith N,Powers S E.Residential demand response reduces air pollutant emissions on peak electricity demand days in New York City[J].Energy Policy,2013,59:459-469.
[10]Huang Kun-Yuan,Huang Yann-Chang.Integrating direct load control with interruptible load management to provide instantaneous reserves for ancillary services[J].IEEETrans on Power Systems,2004,19(3):1626-1634.
[11]Jang Dongsik,Eom Jiyong,Jae Park,et al.Variability of electricity load patterns and its effect on demand response:A critical peak pricing experiment on Korean commercial and industrial customers[J].Energy Policy,2016,88(1):11-26.
[12]Grunewald P,Torriti J.Demand response from the non-domestic sector:Early UK experiences and future opportunities[J].Energy Policy,2013,61(10):423-429.--------