Multi‐criteria decision‐making approach for optimal and probabilistic planning of passive harmonic filters in harmonically polluted industrial network with photovoltaic resources

Author:

Khajouei Javad1ORCID,Shakeri Sina1ORCID,Esmaeili Saeid1ORCID,Nosratabadi Seyyed Mostafa23ORCID

Affiliation:

1. Electrical Engineering Department Shahid Bahonar University of Kerman Kerman Iran

2. Department of Electrical Engineering Sirjan University of Technology Sirjan Iran

3. School of Engineering University of Edinburgh Edinburgh UK

Abstract

AbstractNowadays, nonlinear loads are widely employed within the industrial applications that cause harmonic distortions in the network. Passive harmonic filters stand out as the preeminent and cost‐efficient remedy for mitigating the impact of harmonic distortions. Any changes in power system conditions such as load variability and photovoltaic resources uncertainty have a significant impact on the harmonic conditions which can affect the quantity and positioning of passive harmonic filters. Hence, in this paper, a method including an innovative optimization problem is proposed for probabilistic planning of passive harmonic filters considering system conditions variability, which is solved by heuristic methods and multi‐criteria decision‐making techniques. By doing this, a solution is obtained where grid losses and the passive harmonic filter costs are minimized and the power factor and frequency response are improved on selected buses. Also, in this paper, the index that gauges the severity of total harmonic distortion is proposed to determine the worst case of the network in terms of harmonic distortions which is so vital for system operators, especially the systematic approach to designing passive harmonic filters. To indicate the efficiency of the proposed approach, the electrical system of an actual Iranian copper mine of significant scale is employed, featuring the integration of non‐linear loads.

Publisher

Institution of Engineering and Technology (IET)

Subject

Renewable Energy, Sustainability and the Environment

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