Characterizing Pollution Severity Needs More than Simply Relying on ESDD

Scene from China

Properly characterizing and measuring the pollution affecting overhead lines and substations is of great importance when specifying insulators to minimize risk of pollution flashover. While there are several relevant parameters to assess pollution severity, the most common are equivalent salt deposit density (ESDD), leakage current and surface conductivity – each with advantages and drawbacks. Measuring ESDD is the most popular and allows pollution maps to be correlated with appropriate insulator selection criteria for each pollution zone. Unlike ESDD, which aims to characterize the amount of pollution deposited on insulators, surface conductivity reflects both pollution deposition and the wetting impacting an insulator. Leakage current, by contrast, is a pollution severity parameter that’s easy to monitor on-line under dry band conditions resulting from the combined effects of pollution, wetting and operating voltage.

The widespread use of ESDD as a parameter to characterize pollution severity is in large part due to its simplicity, with no need for any expensive measuring equipment. The methodology involves washing pollution deposits from the insulator surface with a specified volume of de-ionized water. Conductivity of the resulting solution is measured and, after correction to a standard temperature, the equivalent effective salt content needed to arrive at this conductivity value can be calculated.

ESDD has been used for years as an insulator selection tool by power supply utilities and this parameter is applied across the globe with large amounts of accumulated data. In China, for example, it has also become the primary basis for quantitatively plotting pollution levels across the country and influencing decisions on required insulation levels. Indeed, utilities here also regularly measure ESDD and, if necessary re-plot pollution level in each area based on the values obtained. The insulation configuration of affected transmission lines and substation equipment is also adjusted accordingly.

In recent years, many refinements have been made with regard to improving pollution area plotting based on ESDD. For example, it has been proposed that this should be done based on accumulated ESDD values over years (referred to as ‘saturated ESDD’) rather than on only one value measured each year. Pollution area plotting based on saturated ESDD levels is more practical, given the impossibility of washing every year, and also allows operators to specify greater insulation margins.

Research has found that Non-Soluble Deposit Density (NSDD) also impacts pollution flashover voltage of an insulator. Moreover, since the effects of NSDD and ESDD are to a large extent independent, pollution area plotting must also take this parameter into consideration. Indeed, pollution mapping must be comprehensive and based on several factors, including service experience and presence of relevant wetting phenomena. In fact, these are even more important factors to consider than ESDD value alone, which should serve mostly as a reference. But because service experience and pollution wetting are by nature qualitative, the role of ESDD has perhaps been exaggerated and accorded too much importance due to it being quantifiable and easy to measure.

ESDD as a parameter also suffers from the fact that its value does not necessarily correspond directly to insulator pollution flashover voltage. This is because the composition of soluble salts in natural pollution can be complex. For example, numerous measurements across China have shown that soluble salts in the pollution of most areas are dominated by CaSO4, which is a relatively difficult compound to dissolve. Since the volume of water specified in the ESDD measurement methodology is high, the CaSO4 dissolves and contributes to conductivity of the solution. However, in reality, insulators in service are under a state of ‘saturated wetting’. The quantity of water on their surfaces is very small and generally equals only about one percent of the water used during an ESDD measurement. With such a small quantity of water, very little CaSO4 is dissolved; the majority does not contribute to solution conductivity and therefore will not directly correlate to pollution flashover voltage. Artificial pollution testing uses NaCl to simulate soluble salts and that is the reason that, even with the same ESDD, the pollution flashover voltage of a naturally-polluted insulator is often much higher than for an artificially-polluted test sample. Moreover, since soluble salt compositions vary significantly by region, pollution flashover voltage testing of natural samples having the same ESDD value can see a high dispersion in results.      Indeed, the most important criterion to assess whether any parameter describing pollution severity is suitable or not is whether it correlates closely to pollution flashover voltage – and this is something that ESDD unfortunately lacks.

To overcome some of these defects in the ESDD measurement method, researchers have analyzed the chemical composition of soluble salts in natural pollution deposits. They then ‘corrected’ the ESDD value obtained using the traditional methodology on the basis of the percentages of monovalent and bivalent salts in the soluble layer. These corrected ESDD values, referred to as ‘effective ESDD’, more closely correlate to pollution flashover voltage.

Unfortunately, chemical analysis of ingredients within soluble salts on insulators in service is costly and also time and energy consuming. Moreover, it is virtually impossible to do such an analysis for each ESDD measurement taken. It is for this reason that this concept of effective ESDD has not yet been well popularized. It seems clear that in order to achieve a high correlation of ESDD values with pollution flashover voltages, much works still needs to be done.

Of course, the above comments are not intended to entirely negate the value of this ESDD parameter but rather only to ensure that insulator users have a better appreciation of its relative benefits and weaknesses.

Prof. Guan Zhicheng
(retired) Tsinghua University Shenzhen Campus