计入激励政策影响的分布式光伏装机容量预测  

Installed Capacity Forecast of Distributed PVs Incorporating the Influences of Incentive Policies

作　　者：吴璐阳 刘福斌 辛洁晴[1] 邢伟 WU Luyang;LIU Fubin;XIN Jieqing;XING Wei(Department of Electrical Engineering,Shanghai Jiaotong University,Shanghai 201400,China;East China Branch,State Grid Corporation of China,Shanghai 200120,China)

机构地区：[1]上海交通大学电气工程系,上海201400 [2]国网华东分部,上海200120

出　　处：《电力系统及其自动化学报》2020年第10期104-110,共7页Proceedings of the CSU-EPSA

基　　金：国家自然基金重点资助项目(51777121)。

摘　　要：分布式光伏装机容量的准确预测对电网经济规划和安全运行具有重要意义。目前相关研究多忽略或粗略计入激励政策对光伏装机的影响,使得预测结果与实际情况偏差较大。为此,本文提出基于光伏产业利润和成本预测的激励政策预测模型和用户对光伏并网方式的决策模型,在此基础上构建计入激励政策演变的分布式光伏装机容量系统动力学预测模型。对上海市2016—2018年及远景分布式光伏装机容量的预测结果表明,与按固定比例下调激励政策的系统动力学模型相比,所提方法可获得更高的预测精度;而与二阶自适应预测这类趋势预测方法相比,所提方法可对中长期预测获得更好的预测结果。The accurate forecasting of distributed photovoltaic(PV)installed capacity is of great significance for the economic planning and safe operation of power grid.At present,less consideration is given to the influences of incen⁃tive policies on the PV installed capacity,which causes the forecasting results to deviate from the actual data.To this end,two models are proposed in this paper,i.e.,an incentive policy prediction model based on the profit and cost fore⁃cast of the PV industry,and a user’s decision-making model for the PV grid-connected mode.On this basis,a system dynamics model of distributed PV installed capacity forecasting is constructed,which considers the evolution of incen⁃tive policies.The prediction results of Shanghai’s 2016-2018 and long-range distributed PV installed capacity show that the proposed method can achieve a higher prediction accuracy than the system dynamics model that adjusts the in⁃centive policy downwards at a fixed ratio,and it can obtain better medium-and long-term prediction results than the trend extrapolation methods such as second-order adaptive forecast.

关 键 词：系统动力学 分布式光伏 光伏补贴 光伏标杆上网电价 装机容量预测 

分 类 号：TK01[动力工程及工程热物理]