Imposing fair penalty to the harmonic sources based on the measurement data

Abstract

Improving network power quality through harmonic reduction requires recognition of Harmonic Sources (HSs) to drive them to compensate their harmonics. This paper proposes a new method for equitable distribution of the Harmonic Compensation Cost of the network among the HSs based on the Harmonic Contribution Matrix. Each element of the Harmonic Contribution Matrix is the harmonic contribution of a specific source to the harmonic voltage of a specific bus. The output of the proposed method is a penalty curve for each HS over time. The amount of the fine estimated for each individual HS per hour is a function of not only the contribution of that HS to the harmonic voltage of different buses, but also the contribution of the Harmonic Compensation Cost from the perspective of each bus, nominal voltage of each bus, and the sensitivity of each bus to the harmonic voltage. The proposed algorithm is evaluated on the IEEE 14-bus network and Esfahan regional electrical power network in Iran. The simulation results demonstrate the capability of the proposed method to allocate the hourly penalty curve to the HSs.

Enhancement of power quality issues for a hybrid AC/DC microgrid based on optimization methods

“…The output results indicate the proper performance of the above system [11]. To cope with harmonic distortions in the power grid and especially MGs, numerous harmonic compensation approaches are presented in the literature [12][13][14][15][16][17][18][19][20][21][22][23][24][25][26]. For harmonic mitigation, two elements, active power filter and super capacitor, are investigated in [12].…”

“…Furthermore, the HPQC mitigates grid side unbalance and other harmonics in a co‐phase supplied system simultaneously. [26] presented a new method for equitable distribution of the harmonic compensation cost of the network among the harmonic sources based on the harmonic contribution matrix. Studies are evaluated on the IEEE 14‐bus network and Isfahan regional electrical power network in Iran.…”

Harmonic Measurement Method Based on Artificial Neural Network

“…Some scholars built an equivalent circuit model based on the structure of CVT itself, and the equivalent models constructed were basically similar, and analyzed the related factors causing errors in the transfer ratio of CVT [9]. Some circuit models built by scholars do not consider some parameters of the intermediate transformer, so it is impossible to accurately know how these parameters affect the harmonic transmission characteristics of CVT [10]. Foreign research on transformers started relatively early.…”