Voltage Regulation in Private Environment: Opportunity or Threat

“…Both networks are connected to the upstream grid by the point of common connection (PCC). Used load profile and MGs consumers demand are taken from [25].…”

Section: Resultsmentioning

confidence: 99%

Optimal reliable and resilient construction of dynamic self‐adequate multi‐microgrids under large‐scale events

Khalili

Hagh

Zadeh

et al. 2019

IET Renewable Power Generation

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Existence of distributed generators (DGs) makes it possible to split distribution systems into multi-microgrids (MGs) in emergency conditions. In this study, after optimal allocation of distributed generation sources with a multi-objective function, the test system is optimally subdivided into some self-adequate MGs with the least not supplied active and reactive power during large-scale events. By using the proposed method, the network will be more resilient against large-scale events such as critical lines outages or big generation outage under natural events with the optimal voltage regulation for each MG. The multi-objective problem is solved by the fuzzy satisfying approach and Pareto optimality methods. The proposed method in this study is based on the exchange market algorithm and tested on two systems, IEEE 33-and 69-bus distribution systems. Also, under normal network conditions, operation of distribution networks is evaluated using different objective functions like micro-virtual networks with minimum power exchange and loss minimisation, to determine which function causes the network to have the best status in terms of reliability and resiliency. Obtained results confirm the efficiency of this method for partitioning distribution systems to increase network robustness before a fault occurrence and also improve reliability and resiliency after a fault occurrence. Nomenclature a, b weight coefficients related to the importance of each function c z q , c i q , c p q coefficients of the ZIP model of the reactive power c z p , c i p , c p p coefficients of the ZIP model of the active power L, Z number of the last line/zone i z , i z′ busses in each zone l z existing line in each zone L′ set of connection lines of two zones NL number of lines in the zth zone N ob j number of the objective functions NZ number of busses in a zone COF combination of two objective functions OF s max , OF s min maximum/minimum of the sth objective function among the obtained answers OF s n optimality of the nth answer of the sth objective function OF s 1 , OF s 2 two answers to the sth objective function OF 1 , OF 2 two main objective functions P d, z, t DG , Q d, z, t DG generated active and reactive power of the dth DG at the zth zone at the tth hour 0 voltage at the ith bus and tth hour after/before optimisation w 1 , w 2 weighted coefficients WL set of all lines of the distribution system

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“…The reduction in the supply voltage of the power system by CVR results in a reduction of power consumption. References 16–19 showed that the total load in the system could be reduced by reducing the voltage in the supplying feeder of the power system. Moreover, Reference 20 showed that the CVR could be applied to effectively minimize the energy losses in a reconfiguration of a distribution system.…”

Section: Introductionmentioning

confidence: 99%

Development of service restoration algorithm under cold load pickup condition using conservation voltage reduction and particle swarm optimization

Widiputra

Jufri

Jung

2020

Int Trans Electr Energ Syst

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The presence of cold load pickup (CLPU) creates a challenge in service restoration owing to an increased load in power systems. To mitigate the effects of CLPU, the system is divided into sections to restore them sequentially. Another approach to solving the CLPU problem is by reducing the total power consumption, with conservation voltage reduction (CVR) as the popular approach to achieve this. This article develops a new restoration algorithm with discrete particle swarm optimization (DPSO) using CVR with CLPU in a power system. DPSO is a global search algorithm that is able to avoid a locally optimal solution. By combining the merits of DPSO and CVR, the restoration time will be improved while maintaining an acceptable operating condition. To verify the algorithm, two simulations are performed. The first simulation compares the proposed algorithm with the tabu search (TS), which shows the improvement in the total restoration time of the system. Then, the second simulation shows an improvement in the restoration time and the ability to maintain the operating voltage during the restoration process by including the CVR in the service restoration. K E Y W O R D S cold load pickup, conservation voltage reduction, discrete particle swarm optimization, service restoration, tabu search LIST OF SYMBOLS AND ABBREVIATIONS: BW, bandwidth of the OLTC; D V , voltage deviation (p.u.) of the bus voltage from its rated voltage; gbest, the current global best solution; I kl , current flow from bus k to bus l; I Limit kl

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Voltage Regulation in Private Environment: Opportunity or Threat

Cited by 6 publications

References 4 publications

Impact study of demand response program on the resilience of dynamic clustered distribution systems

Impact study of demand response program on the resilience of dynamic clustered distribution systems

Optimal reliable and resilient construction of dynamic self‐adequate multi‐microgrids under large‐scale events

Development of service restoration algorithm under cold load pickup condition using conservation voltage reduction and particle swarm optimization

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