一种改进马尔科夫链的光伏出力预测方法

An Improved Markov Chain Photovoltaic Output Prediction Method

准确有效的光伏出力预测方法对含光伏配电网的规划和运行具有指导意义,针对光伏随机性,提出一种改进马尔科夫链的光伏出力预测方法。基于云层覆盖水平指标划分云层状态,建立云层状态转移矩阵。引入状态持续时间抽样法,建立具有时序性的改进马尔科夫链模型预测云层状态变化曲线。利用随机抽样法从云层状态时序曲线中抽取各时刻辐照度样本值,依据光伏出力与辐照度的关系间接预测得到光伏出力时序曲线。仿真分析验证了所提方法的有效性。

An accurate and effective photovoltaic output prediction method has guiding significance for the planning and operation of photovoltaic power distribution networks.Aiming at the randomness of photovoltaics,an improved Markov chain photovoltaic output prediction method is proposed.The cloud layer state is divided based on the Cloud Cover Level index,and the cloud layer state transition matrix is established.The state duration sampling method is introduced,and an improved Markov chain model with time sequence is established to predict the cloud state change curve.The random sampling method is used to extract the irradiance sample value at each time from the cloud state time series curve,and the photovoltaic output time series curve is indirectly predicted according to the relationship between photovoltaic output and irradiance.Simulation analysis verifies the effectiveness of the proposed method.