微电网多目标随机动态优化调度算法

doi:10.19595/j.cnki.1000-6753.tces.170496

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Abstract To solve the multi-objective stochastic dynamic optimal dispatch problem of microgrid with wind, solar and storage battery, a multi-objective stochastic storage model is established. In this model, the micro-source total operation cost and total network loss are taken as the objective functions, and the sum of the remaining battery energy is taken as the storage level of the system. The AC power flow model is used to accurately describe the security constraints of transmitting power in distribution lines, and the voltage and reactive power characteristics of different distributed generations are also taken into account. Adaptive weighted sum (AWS) algorithm and approximate dynamic programming (ADP) algorithm are combined to solve the model. Firstly, the multi-objective stochastic dynamic optimal model is transformed into a series of single objective stochastic dynamic optimal models by AWS algorithm. Secondly, approximation value function iteration in ADP algorithm is used to solve each single objective stochastic dynamic optimal model with solving the model of each period successively. Finally, through the adjustment of the weight values corresponding to new added Pareto points of each division section in AWS algorithm, a series of evenly distributed Pareto optimal solution sets are obtained. Test results on a real microgrid system demonstrate that the proposed model and algorithm are correct and efficient.

Key words： Microgrid dispatch stochastic optimization multi-objective optimization approximate dynamic programming (ADP) adaptive weighted sum (AWS)

Received: 24 April 2017 Published: 24 May 2018

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	Wang Yaping
	Lin Shunjiang
	Yang Zhibin
	Sun Xinglu
	Liu Mingbo

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Wang Yaping,Lin Shunjiang,Yang Zhibin等. Multi-Objective Stochastic Dynamic Optimal Dispatch Algorithm of Microgrid[J]. Transactions of China Electrotechnical Society, 2018, 33(10): 2196-2207.

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https://dgjsxb.ces-transaction.com/EN/10.19595/j.cnki.1000-6753.tces.170496 OR https://dgjsxb.ces-transaction.com/EN/Y2018/V33/I10/2196

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