Fuzzy-based Monte Carlo simulation for harmonic load flow in distribution networks

The power flow calculation considering uncertainty is common way of determining harmonic analysis of the system under uncertain conditions. Distributed generation and load are characterised by randomness. Hence, this study introduces uncertainty to the distribution network analysis. Three similar methodologies are proposed for distribution power flow, which calculate active power losses, voltage drops and voltage total harmonic distortion. The first methodology uses fuzzy logic in order to address uncertainties. Generation, active power loss variation and elasticity of power quality constraints are presented in a form of fuzzy numbers (FNs). The second methodology uses Monte Carlo simulation (MCS) to vary the values of the same variables, which are FN. The third methodology combines MCS and FN. The proposed methodologies are verified using case studies based on IEEE 33-bus system. The results of all three methodologies are compared graphically and numerically. Analysing the distribution harmonic load-flow results, one can find out the weak links of the network, which can provide references for making electrical accident premeditation and power quality problems.