基于风光联合概率分布的微电网概率潮流预测

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Abstract Wind and photovoltaic generations are important units of a microgrid. Considering that the effects of wind and irradiance on the microgrid are of certain correlation, forecasting the joint probability distribution of power flow can reduce the impact of varied wind speed and irradiance on the operation of the microgrid and provides the theory base for the energy management in a microgrid. The deterministic power flow is forecasted firstly based on the forecasting of wind and photovoltaic generations, and then Markov chain and Latin hypercube sampling are combined to forecast the conditional and unconditional joint probability distribution of power flow in the microgrid. The results show that the confidence interval calculated by the former is more valuable, which provides a theoretical basis for further analyzing and optimizing system operation.

Key words： Microgrid probabilistic power flow Markov process joint probability distribution confidence interval

Received: 08 December 2013 Published: 18 June 2014

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TM732

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	Mao Meiqin
	Zhou Songlin
	Su Jianhui

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Mao Meiqin,Zhou Songlin,Su Jianhui. Probabilistic Power Flow Forecasting of Microgrid Based on Joint Probability Distribution about Wind and Irradiance[J]. Transactions of China Electrotechnical Society, 2014, 29(2): 55-63.

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http://dgjsxb.ces-transaction.com/EN/ OR http://dgjsxb.ces-transaction.com/EN/Y2014/V29/I2/55

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