An Efficient Stochastic Reconfiguration Model for Distribution Systems With Uncertain Loads
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Data
2022-01-01
Autores
Mahdavi, Meisam [UNESP]
Alhelou, Hassan Haes
Hesamzadeh, Mohammad Reza
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Resumo
Active power losses of distribution systems are higher than transmission ones, in which these losses affect the distribution operational costs directly. One of the efficient and effective methods for power losses reduction is distribution system reconfiguration (DSR). In this way, the network configuration is changed based on a specific power demand that has been already predicted by load forecasting techniques. The ohmic loss level in distribution system is affected by energy demand level, this is while an error in load forecasting can influence losses. Accordingly, including load uncertainty in DSR formulation is essential but this issue should not lead to change of the reconfiguration results significantly (i.e. the model should be robust). This paper presents a robust and efficient model for considering load uncertainty in network reconfiguration that is simple enough to implement in available commercial software packages and it is precise enough to find accurate solutions with low computational time. The analysis of results shows high efficiency and robustness of the proposed model for reconfiguration of distribution systems under demand uncertainty.
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Computational modeling, Distribution networks, Load flow analysis, Load modeling, Mathematical models, Probability density function, Uncertainty
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IEEE Access, v. 10, p. 10640-10652.