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Energies
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18 October 2022

An Integrated Lightning Risk Assessment of Outdoor Air-Insulated HV Substations

,
and
Faculty of Engineering, Multimedia University, Cyberjaya 63100, Malaysia
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Author to whom correspondence should be addressed.
This article belongs to the Section F: Electrical Engineering

Abstract

Although various lightning protection methods have been used in the industry, many outdoor high-voltage (HV) substations are still experiencing high failure rates due to lightning strikes. The applications of these rule-of-thumb-based methods generally lack coherence among the practitioners. IEC 62305-2 provides a systematic way for practitioners to assess the lightning risk for buildings or structures in a probabilistic way. However, this standard has not explicitly covered the application of HV substations. Moreover, IEC 62305-2 involves a tedious set of risk factors which may hinder many practitioners from applying the aforementioned standards while other preferred rule-of-thumb methods are available. As IEC 62305-2 does not specify the applicability to lightning risk assessment in HV substations, this paper proposes a novel approach to complement the standard-based risk assessment process. During this integrated risk assessment process, significant risks are identified, followed by ambiguous risks that will be adjusted in subsequent phases. The significant ambiguous risk factors such as fire load function (rf), environmental factor (CE), LPL class, and other governing factors have been analyzed and discussed. By adjusting these significant risk factors, the practitioners will understand the adjusted risk factors in relation to the practical implementation of lightning protection system (LPS). Therefore, integrating the substation characteristics, assumptions, and findings of ambiguous risk factors can result in a successful integrated lightning risk assessment process.

1. Introduction

Lightning is the electrostatic charges built up in the clouds, producing enormous discharge energy that potentially transfers in high current to the tall structures or ground surface [1]. The outdoor air-insulated HV substations are one of the structures that are exposed to lightning strikes. The substations serve the purpose of switching, converting, diverting, measuring, and protecting the power transmission networks to provide a stable power supply to the consumers [2]. Although the substations are equipped with a lightning protection system (LPS), it is found that lightning strikes are still causing substation failures even in modern times [3,4]. Consequently, this has caused the substation practitioners to seek an alternative approach to assess the risk of lightning strikes via the probabilistic method [5].
IEC 62305-2 has outlined the lightning risk assessment process for the general structures [6]. Recent progress in lightning risk assessment was discussed in [7,8]. Due to the rigorous nature of risk assessment, a tool has been developed to simplify the process [9]. In spite of the fact that IEC 62305-2 does not specifically refer to the risk assessment of outdoor HV substations, the lightning risk assessment process can be conducted by incorporating assumptions with similar representations to those used for building structures [10,11].
As mentioned, despite the fact that presumably all HV substations are equipped with LPS, many failure cases were still reported in the past. Table 1 shows the failure cases that caused outages and damages due to lightning incidents [12,13,14,15,16,17,18].
Table 1. Failure Cases due to Lightning Incidents.

2. Literature Review

2.1. Tolerable Risk Values

IEC 62305-2 [19] provides a process for estimating the risk of loss of human life or permanent injuries (R1) and loss of service to the public (R2). The tolerable risk values (RT) for R1 and R2 are shown in Table 2. The risk of loss of cultural heritage (R3) is excluded as HV substations are not cultural heritage buildings. Moreover, due to the complexity of equipment procurement and electricity tariffs, the risk of loss of economic value (R4) is excluded as well.
Table 2. Tolerable Risk Values.
The general equation of the risk value (R) consists of the components of the number of dangerous events per annum (N), probability of damage to a structure (P), and consequent loss value (L):
R = N × P × L

2.2. Lightning Strike Distance (S)

IEC 62305-2 uses striking distance (S) to determine the lightning protection level (LPL) of an LPS. The striking distance is the final jump of the stepped leader in air space to a structure or ground plane. As a result of various lightning strike distance formulas proposed by researchers over the course of history, electro-geometrical methods (EGM) such as rolling sphere methods (RSM) lack coherence of application [20,21,22]. The most widely used formulas are based on Love’s and Mousa’s as shown in (2) and (3) respectively [23,24]:
S = 10 × I0.65
S = 8 × I0.65
where I is lightning stroke current in kA.
As shown in Table 3, Equation (2) shows a closer match to the striking distances based on the LPL table presented in IEC 62305-3 [25]. Thus, the results of (2) will be compared with the LPL table in IEC 62305-3 to determine the LPL to apply in the integrated risk assessment process.
Table 3. Comparison of Striking Distance (S) to LPL.

2.2.1. Basic Impulse Level (BIL)

Basic impulse level (BIL) is one of the fundamental factors to determine the allowable lightning stroke current. It is the standardized withstand impulse voltage level of electrical insulation without causing the equipment to experience flashover and damage due to lightning strikes. It is the reference levels expressed in impulse crest voltage with a standard wave not longer than 1.2 by 50 µs wave and the tests applied on the equipment shall be equal to or greater than the BIL [26,27]. The common BIL ratings of the substation are based on the voltage systems of the substations.

2.2.2. Lightning Stroke Current (I)

The allowable lightning stroke current which will not cause the flashover or back-flashover for the equipment is based on (4) [3]. The equation is proportional to the BIL rating of the specified equipment which was connected to the system voltage lines.
I = BIL × 2.2/Zs
where Zs is the surge impedance, commonly assumed as 300 Ω unless specified [22].

2.3. Lightning Flash Density

The ground flash density (NG) is the key factor that determines the risk assessment result. The general formula stated in IEC 62305-2 which was originally suggested by Anderson [28], estimated that 10% of thunderstorm days per year (TD) is the number of lightning flashes per km2 per year, with an allowance for reduced numbers of flashes to lines due to shielding by trees and undulating terrain. The formula for calculating the ground flash density is shown in (5).
NG = 0.1 × TD
When compared to the tropical and equatorial zone such as Brazil, Columbia and Mexico, NG is closer to (5) and considered as practical as the annual thunderstorm days are normally recorded higher [29].
In the real case, obtaining specific local meteorological data such as TD is not a straightforward task. There is an alternative method that uses optical transient density measurement, a space-based earth orbit sensor, which was suggested in IEC 62858 that the ground flash density as shown in (6) is proportional to the total cloud-to-ground and inter-cloud optical recorded flashes per km2 per year (NT) [30,31].
NG = 0.25 × NT
NT in flashes per km2 per year can be based on NASA’s space-based earth orbit sensor data as shown in [32]. By considering the case in Malaysia for example, the TD range is 50 to 350 thunderstorm days per km2 per year as compared to the NT range of 10 to 70 optical flashes per km2 per year. It is noticeable that the ground strike-point (NSG), as shown in (7), for new optical transient density measurement based on NASA’s data is very similar to the lightning density formula stipulated in (5) [33,34]. Thus, this method can be considered for risk assessment if the local meteorological data is unavailable.
NSG = 2 × 0.25 × NT

3. Methodology

Figure 1 outlines the lightning risk assessment for HV substations based on IEC 62305-2 [19]. By incorporating the assumptions to resemble the outdoor substations as the “structures” [18], the lightning risk assessment for HV substations based on IEC 62305-2 can be performed. Five HV substations with different characteristics will be selected for the case study. The actual HV substation layouts will be overlaid in CAD tools to calculate the collection areas. After that, the lightning risk assessment based on IEC 62305-2 will be performed and several significant risk factors will be identified. Among the significant risk factors, some ambiguous risk factors will be identified. Lastly, the simplified integrated risk assessment process will be proposed.
Figure 1. Process Flow of Lightning Risk Assessment.

3.1. Risk Components

The risk components are similarly evaluated based on IEC 62305-2, in which R1 and R2 will be calculated based on the summation of the individual risk components as shown in Table 4. These risk components are calculated based on the tabulated risk factor values suggested in the same standard. The numbers after the alphabetical character of risk components represent the type of losses. For example, RB1 is risk component for loss of human life due to physical damage inside the structures due to lightning. On the other hand, RB2 is the risk component for loss of service to the public due to the same cause. The brief explanations of the risk components are explained in Table 5.
Table 4. Risk Values of R1 and R2 (IEC 62305-2).
Table 5. Definitions of Risk Components (IEC 62305-2).

3.2. Collection Areas

The collection areas are determined by the horizontal span of the land surface area of the substations and the height of the structures. The outer radius of the collection area is either dependent on the height of structures or the fixed values suggested by IEC 62305-2. Based on IEC 62305-2, the collection area of the shielding structures (AD) such as gantry and lightning masts, the area covers the horizontal span of ground surface area radially which is three times the structure’s height. Besides that, the collection area near the structures (AM) covers a 500 m radius of the ground area. For the collection areas to the line (AL) and near to the line (AI) such as bare conductors and busbars within the substations, the radial span distances are 20 m and 1000 m respectively. This measurement can be performed by using CAD tools to measure the footprint of the relevant installed structures in the substations. The collection areas possess the risk and shall normally cover the interest area where the equipment and human activities are located. As a result, the maximum collection areas are only up to the substations’ fence boundary.

3.3. Case Studies

Five cases of substations from three different countries have been chosen for the lightning risk assessment. The characteristics of the HV substation cases have been recorded as shown in Table 6. The substation characteristics primarily cover the location, voltage system (Ur), layout design, types of shielding, and sources of lightning flash density. LPL classes are determined based on Table 3.
Table 6. Characteristics of the HV Substation Cases.

4. Results and Discussions

The results of R1 and R2 for five substation cases are shown in Table 7 and Table 8. The bolded results indicate the cumulative risk values or the individual risk components which exceeds the tolerable risk RT as shown in Table 2. It is found that RB1, RC1, RV1, and RW1 are the significant risk components which exceeds RT for R1 in some cases. On the other hand, RB2, RC2, RV2, and RW2 are the significant risk factors that contribute to high values in results for the R2 case. RZ1 and RZ2 are zero values due to the risk factor selection that the earth bonding for the aerial power line shields to the internal equipment bonding bar (CLI) are commonly joint. Besides that, RM1 and RM2 have shown less significant risk values due to the selection of the continuously covered shields for internal equipment (KS2) and bonded metal cable trays to lay the internal cabling (KS3).
Table 7. Result of Risk Value of Loss of Human Life (R1).
Table 8. Result of Risk Value of Loss of Service to the Public (R2).

4.1. Risk Factor Characteristics

Based on IEC 62305-2, the characteristics of the risk factors can be summarized in Table 9. The characteristics are basically divided into three main categories: fixed value factors, measurable risk factors, and ambiguous risk factors.
Table 9. Risk Factors Characteristics.
The fixed value factors are uniform in selection due to the clear descriptions of the risk factors shown in the standard. For measurable risk factors, practitioners are required to perform the calculation such as identifying the collection areas by using CAD tools. Lastly, there is a group of risk factors that may be found ambiguous for practitioners to select when performing the risk assessment.

4.1.1. Common Values of Risk Factors

The risk factors that are having common fixed values for outdoor HV substation cases are shown in Table 10.
Table 10. Common Risk Factors.

4.1.2. Significant Range of Risk Factors

The range of risk factors can be estimated by registering the highest to lowest values of the risk factors, and by estimating the ratio of the factor values to obtain the approximate range of risk values for each component. Some of the significant range of risk factors based on IEC 62305-2 are shown in Table 11. The value of these risk factors varies depending on the substations’ characteristics. For example, the environmental factor (CE) and function of fire and explosion risk of structure (rf) have shown the potential of change of risk values in the maximum range of 100 and 1000.
Table 11. Major Significant Range of Risk Factors.
After tabulating the major risk factors as shown in Table 11, the ratio of the factor values can be registered as shown in Table 12 to estimate the approximate range of the risk values for each component in the power of ten. For example, it is shown that RV is having the highest variation of risk values mainly due to CE and rf. Besides that, KS3 is the risk factor with the highest range in variation of value which mainly affects RM.
Table 12. Accumulated Variation of Risk Values for Risk Components.

4.1.3. Ambiguity of Risk Criteria

The ambiguity in the risk criteria arises due to the lack of risk factor criteria selection options to represent substation case. For example, the probability of persons being injured because of the failure of internal systems (Lo) has a limited set of selection options, which limits them to select the only “risks of explosion”. In addition, in fact, that the operators find it much easier and more frequent to access urban substations in the aspect of CE than rural substations, which carry a greater risk of injury. The ambiguous risk criteria which are commonly found in a typical HV substation are shown in Table 13. Note that typical HV substation means a conventional HV substation that is outdoors.
Table 13. Ambiguous Risk Criteria.

4.1.4. Ambiguity of Risk Values

The risk values published by IEC 62305-2 are very comprehensive and critically useful to perform the risk assessment. In spite of the convenience of applying straightforward risk values to the risk assessment process, practitioners may find it difficult to comprehend the basis of the risk values provided by the standard. Moreover, the current standard also lacks specific guidance for practitioners to apply in the HV substation context. The ambiguous risk values based on IEC 62305-2 for a typical HV substation are shown in Table 14.
Table 14. Ambiguous Risk Values.

4.1.5. Ambiguity Level of Risk Factors

In order to identify the ambiguous risk factors that potentially influence the significance level of risk values, Table 13 and Table 14 are analyzed. The risk factors which are mentioned in both Table 13 and Table 14 are summarized in Table 15. As a result, RU, RV, and RZ have shown a high level of ambiguity. It is known that the results shown in Table 7 and Table 8 indicate that RB, RC, RV, and RW have higher risk values, which are towards exceeding the tolerable risk. Due to this, when comparing the actual results with Table 15, RB and RV with ambiguous risk factors in the range of 10 and 10,000, respectively, could potentially bring the results to exceed the tolerable risk values. Practitioners will be made aware of these ambiguous risk factors through subsequent risk assessments.
Table 15. Risk Factors Shown in Both Table 13 and Table 14.
On the other hand, Table 16 has shown the risk factors which are only mentioned in either Table 13 or Table 14. RB, RM, and RV have shown a high level of ambiguity when the risk assessment is performed. Similarly, when comparing the actual results, the ambiguous risk factors found in RB and RV are considered significant and will be highlighted in subsequent risk assessments.
Table 16. Risk Factors Only Shown in Either Table 13 or Table 14.
In conclusion, the ambiguous risk factors will impact the results of the risk values. Table 13 and Table 14 summarise the risk factors which practitioners would find ambiguous if they are to conduct the risk assessment as per IEC 62305-2. These ambiguities and the lengthiness of the process of IEC 62305-2 may potentially cause the inaccurate representation of lightning risk on substations. However, the onerous summarized findings of the significant ambiguous risk factors can be emphasized for future assessments and research.

4.1.6. Comparison of Ambiguous Factors to Actual Cases

Based on the actual results shown in Table 7 and Table 8, RB, RC, RV, and RW are the prominent risk components for all cases. RB, RV, and RW have a high level of ambiguity. Furthermore, the significant risk factors such as CE, PLD, PLI, KS3, rt, and rf have to be emphasized and selected carefully while performing the lightning risk assessment.

4.2. Integrated Process of Lightning Risk Assessment

The integrated process is based on the required inputs to perform the lightning risk assessment. This process can be summarized in the flowchart shown in Figure 2. Furthermore, the process can be simplified by creating the risk assessment sheets by identifying the groups of risk factors as discussed earlier. Besides that, integration such as adopting IEEE 998 to determine the rolling sphere radius is crucial to determining the LPL risk values. By having CAD tools, the collection areas can be determined as well. In addition, the ambiguous risk factors can be adjusted to run the iterations of risk assessments.
Figure 2. Integrated Process of Lightning Risk Assessment.

Iterations of Lightning Risk Assessment

After obtaining the required inputs, practitioners can proceed to perform the lightning risk assessment by using the process flow and risk tables based on IEC 62305-2. The selection of risk factors should be taken into consideration when considering ambiguous risk factors as described in earlier sections. It is imperative to test the sensitivity of the result values in successive iterations with the range of probable changes in risk factors.
It is known that the previously generated results have shown some risk components exceeding the tolerable risk values. Thus, it is important for designers and practitioners to identify the risk factors that can be adjusted to improve the design. In principle, it is unlikely to change the fixed geographical aspects to improve the risk values. However, some other risk factors such as substation design such as LPS class and installations can be improved. Although the improvement measures will reduce the lightning risk values, it is noted that the additional materials and installations will incur higher costs. Based on these adjustments, the utilities and designers can at least make a fair decision to consider the exposed risk values and the incurred cost. The adjusted factors to improve the risk results are shown in Table 17. The improved-case results are shown in Table 18 and Table 19. The bolded results indicate the cumulative risk values or the individual risk components which exceeds the tolerable risk RT.
Table 17. Proposed Adjustment of Risk Factors-Improved-case.
Table 18. Result of Risk Value of Loss of Human Life (R1) -Improved-case.
Table 19. Result of Risk Value of Loss of Service to the Public (R2) -Improved-case.
For example, R1 for Case 3 is still exceeding RT, mainly due to the large collection areas and the risk of fire or explosions. Although the on-site autotransformers are generally having higher oil volume due to their higher MVA ratings, the comparison of fire spread area around the hazardous oil-filled autotransformers is relatively small compared to the overall switchyard. This has also shown that selecting the fire risk factors due to lightning strikes as discussed earlier remains ambiguous. The improved results have narrowed the list of concerned risk components, and this will help the practitioners to pay close attention to those risk factors.
Conversely, practitioners can expect worse-case risk results by assuming some less stringent designs. By adjusting the ambiguous risk factors to higher values, the practitioners can notice the changes in results. As discussed, some of the ambiguous factors such as CE has been interpreted wrongly in the text. The practitioners shall revisit the actual risk values to suit the actual case. Moreover, by applying higher risk values of LPS due to the leniency of selecting the next higher striking distance, practitioners can predict the potential increase of risk values due to human mistakes and aging installations. Besides that, there is a potential that conditions of actual bonding and shielding are not fully established in the substations. It could be due to broken connections after many years. The adjustment of risk factors is shown in Table 20. The worst-case results are shown in Table 21 and Table 22. The bolded results indicate the cumulative risk values or the individual risk components which exceeds the tolerable risk RT.
Table 20. Proposed Adjustment Risk Factors-Worse-case.
Table 21. Result of Risk Value of Loss of Human Life (R1) -Worse-case.
Table 22. Result of Risk Value of Loss of Service to the Public (R2) -Worse-case.
After both improved and worse-case iterations have been performed, the practitioners will be able to identify the adjusted ambiguous risk factors which significantly affect the result. As the process reaches completion, it is considered satisfactory when no further adjustments of risk factors are required to improve the situation for the HV substations.

5. Conclusions

Historically, many HV substations have experienced lightning shielding failures in the past, despite various lightning protection methods that have been implemented in the design, such as RSM, direct angles, and empirical curves. This has made designers and practitioners face difficulties to analyze the adequacy of the designs which are fundamentally conducted incoherently. IEC 62305-2 has provided an alternative method for practitioners to estimate the risk values via the risk assessment process. As discussed in earlier sections, although IEC 62305-2 has not specifically stated the applicability of the lightning risk assessment on the HV substations, a similar representation of the substations to the structures [11] can be made. Besides that, the characteristics of the outdoor HV substations such as BIL will be used as the inputs to determine the LPL of the LPS. Apart from that, this integrated risk assessment process requires some inputs which are generated from the CAD tools and based on some external resources such as meteorological data and other international standards. Moreover, the integrated process will also involve identifying the significant risk factors which are governing the results. IEC 62305-2 specifies a limited selection of risk factors for HV substations. It is crucial that practitioners adjust any ambiguous risk factors in subsequent assessments to estimate the significance of the results. The adjustment of the significant risk factors is crucial for the practitioners to identify the risk factors that can be brought forward to improve the LPS designs.

Author Contributions

Conceptualization, S.C.L. and O.C.S.; methodology, O.C.S.; software, S.C.L. and O.C.S.; validation, S.C.L., O.C.S. and N.E.E.; formal analysis, O.C.S.; investigation, O.C.S.; data curation, O.C.S.; writing—original draft preparation, O.C.S.; writing—review and editing, S.C.L., O.C.S. and N.E.E.; visualization, O.C.S.; supervision, S.C.L. and N.E.E.; project administration, S.C.L.; funding acquisition, S.C.L. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding and the APC was funded by Multimedia University.

Institutional Review Board Statement

Not applicable.

Data Availability Statement

Not applicable.

Acknowledgments

The authors would like to thank the Faculty of Engineering, Multimedia University for the support provided for this research.

Conflicts of Interest

The authors declare no conflict of interest.

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