Abstract
The increasing penetration of distributed generations (DGs) with intermittent and stochastic characteristics into current power distribution networks can lead to increased fault levels and degradation in network protection. As one of the key requirements of active network management (ANM), efficient power supply restoration solution to guarantee network self-healing capability with full consideration of DG uncertainties is demanded. This paper presents a joint power supply restoration through combining the DG local restoration and switcher operation-based restoration to enhance the self-healing capability in active distribution networks considering the availability of distributed generation. The restoration algorithmic solution is designed to be able to carry out power restoration in parallel upon multiple simultaneous faults to maximize the load restoration while additionally minimizing power loss, topology variation and power flow changes due to switcher operations. The performance of the proposed solution is validated based on a 53-bus distribution network with wind power generators through extensive simulation experiments for a range of fault cases and DG scenarios generated based on Heuristic Moment Matching (HMM) method to fully consider the DG randomness. The numerical result in comparison with the existing solutions demonstrates the effectiveness of the proposed power supply restoration solution.
Highlights
The increasing penetration of small-scale renewable distributed generators (DGs), e.g., micro wind turbines, photovoltaic panels, has reshaped the medium/low voltage (MV/LV) electric distribution network from a passive system to an active network which allows coexistence of bidirectional power flows
The minimization of adverse impact of power restoration on made in this paper can be summarized as follows: (1) the restoration algorithmic solution carry failure-free out restoration network jointly based on distributed generations (DGs) localincluded restoration operation-based restoration sectionpower of distribution is explicitly inand theswitcher optimization utility function in power is ableoftothe restore powersolution supply in parallel upon multiple restoration process; thewhich robustness proposed is validated through extensive simultaneous faults; and (2) The minimization of adverse impact of power restoration on failure-free simulation experiments for a range of fault scenarios and DG scenarios
This paper presents an algorithmic solution for power supply restoration for active distribution networks through combining the DG local restoration and topology reconfiguration-based restoration with full consideration of availability and stochastic characteristics of distributed generation
Summary
The increasing penetration of small-scale renewable distributed generators (DGs), e.g., micro wind turbines, photovoltaic panels, has reshaped the medium/low voltage (MV/LV) electric distribution network from a passive system to an active network which allows coexistence of bidirectional power flows. (1) the end, this work presents a parallel joint power supply restoration through combining the DG local solution carry out power restoration jointly based on DG local restoration and switcher operation-based restoration and switcher operation-based restoration to enhance the self-healing capability in active restoration (topology reconfiguration) which isdistributed able to restore power in parallel upon multiple distribution networks considering stochastic generation. The minimization of adverse impact of power restoration on made in this paper can be summarized as follows: (1) the restoration algorithmic solution carry failure-free out restoration network jointly based on DG localincluded restoration operation-based restoration sectionpower of distribution is explicitly inand theswitcher optimization utility function in power is ableoftothe restore powersolution supply in parallel upon multiple restoration process; thewhich robustness proposed is validated through extensive simultaneous faults; and (2) The minimization of adverse impact of power restoration on failure-free simulation experiments for a range of fault scenarios and DG scenarios.
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