Impact of battery energy storage, controllable load and network reconfiguration on contemporary distribution network under uncertain environment

2020 ◽  
Vol 14 (21) ◽  
pp. 4719-4727
Author(s):  
Sachin Sharma ◽  
Khaleequr Rehman Niazi ◽  
Kusum Verma ◽  
Tanuj Rawat
2016 ◽  
Vol 78 (10-4) ◽  
Author(s):  
Amirullah Amirullah ◽  
Mochamad Ashari ◽  
Ontoseno Penangsan ◽  
Adi Soeprijanto

Randomly installed distributed generators (DGs) in households may cause unbalanced line current in a distribution network. This research presents a battery energy system for balancing of line current in a distribution network involving multi units of single phase photovoltaic (PV) distributed generators (DGs). In this paper, the PV generators were simulated consisting of a buck-boost DC/DC converter and single phase DC/AC inverter. It was connected to the distribution line through the low voltage 220 volt 50 Hz. The proposed phase balancing system uses battery energy storage and three single phase bidirectional inverters. The inverter is capable of injecting current or absorbing power from the line to the battery. This inverter operation is arranged to balance each distribution line separately, as well as to improve other power quality parameters, such as voltage and current harmonics. Simulation results show that the system was capable of improving the unbalanced line current from 15.59 % to 11, 48 % and unbalanced line voltage from 1.76 % to 0.58 %. The system was able for increasing current harmonics from 0.98 % to 1.03% and voltage harmonics from 38.96% to 39.08%.


Batteries ◽  
2020 ◽  
Vol 6 (4) ◽  
pp. 56
Author(s):  
Panyawoot Boonluk ◽  
Apirat Siritaratiwat ◽  
Pradit Fuangfoo ◽  
Sirote Khunkitti

In this work, optimal siting and sizing of a battery energy storage system (BESS) in a distribution network with renewable energy sources (RESs) of distribution network operators (DNO) are presented to reduce the effect of RES fluctuations for power generation reliability and quality. The optimal siting and sizing of the BESS are found by minimizing the costs caused by the voltage deviations, power losses, and peak demands in the distribution network for improving the performance of the distribution network. The simulation results of the BESS installation were evaluated in the IEEE 33-bus distribution network. Genetic algorithm (GA) and particle swarm optimization (PSO) were adopted to solve this optimization problem, and the results obtained from these two algorithms were compared. After the BESS installation in the distribution network, the voltage deviations, power losses, and peak demands were reduced when compared to those of the case without BESS installation.


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