<p>This paper will review on the existing techniques and methodologies of harmonic load diagnostic system. The increasingly amount of harmonic producing load used in power system are the main contribution in quantifying each harmonic disturbance effects of the multiple harmonic producing loads and it became very important. Literature proposes two different techniques and methods on the harmonic source identification under the soft computing technique classification. The advantages and disadvantages of harmonic load identification techniques and methods are discussed in this paper. In the proposed method, the issue on the harmonic contribution is determine and transformed to a data correlation analysis. Several techniques to identify the sources of harmonic signals in electric power systems are described and reviewed based on previous paper. Comparative studies of the methods are also done to evaluate the performance of each techniques. However, without sufficient information in this inconsistent environment on the property of the power system, accurate harmonic producing load diagnosis methods are important and further investigations in this regard assumes great implication.</p>
Fast and accurate detection of the harmonic and interharmonic contribution of electric arc furnace (EAF) is crucial in identifying and to mitigate the undesired effects to the system. In this paper, periodogram, a fast and accurate technique is introduced for the analysis of the contribution. Based on a rule-based classifier and the threshold settings that referred to the IEEE Standard 1159 2009, the analysis of the harmonic and interharmonic contribution of EAF are carried out successfully. Moreover, the impact of contribution is measured using total harmonic distortion (THD) and total non-harmonic distortion (TnHD). In addition, periodogram also gives 100 percent correct detection and able to analyze the contribution impact. It is proven that the proposed method is accurate, fast and cost efficient for analyzing the impact of harmonic and interharmonic of EAF.
<span lang="EN-GB">This paper presents a diagnostic analytics of harmonic source signature recognition of rectifier and inverter-based load in the distribution system with single-point measurement at the point of common coupling by utilizing Periodogram. Signature recognition pattern is used to distinguish the harmonic sources accurately by obtaining the distribution of harmonic and interharmonic components and the harmonic contribution changes. This is achieved by using the significant signature recognition of harmonic producing load obtained from analysing the harmonic contribution changes. </span><span>Based on voltage and current signature analysis, the distribution of harmonic components can be divided into three zones. To distinguish between the harmonic producing loads, the harmonic components are observed at these zones to get the signature recognition pattern.</span><span lang="EN-GB"> The result demonstrate that periodogram technique accurately diagnose and distinguish the type of harmonic sources in the distribution system.</span>
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