In this chapter of the guide, key questions were categorized in eight sections. These sections are:
The existing transit systems vary in age and size and can be classified as small, medium, and large. In this guide, different types of transit systems were investigated with various examples. The lifespan of cables is affected by electrical parameters such as jacketing, cable size, diameter, and the method of insulation, overhead/underground, operating voltage, and weathering. Several attempts have been made to determine the factors associated with the influence on the life cycle of wire and cable insulation and jacketing.
One of the most prevalent causes of degradation in cables are changes in weather conditions, including air moisture, ground, and temperature. The research conducted by Hyvoonen (2008) predicts the insulation condition of MV cable insulation. Different electrical measurements and chemical analyses are tested to find out the most representative combination. A largescale test program was carried out on field-aged and oil-impregnated paper insulated cables.
Based on the size structures and the type of power supply of various transit agencies, there are vast numbers of indicators used to test and verify the aging of cables. One of the most common techniques is cable monitoring (CM), and it detects damage and measure the extent of degradation in electric cable insulation. Factors considered in selecting appropriate CM inspection guidance include intrusiveness, cable characteristics, and degradation mechanisms. The commonly used condition monitoring techniques include visual inspection, compressive modulus, dielectric loss measurement, insulation resistance, polarization index, AC voltage withstands test, partial discharge test, DC high voltage test, step voltage test, and a time-domain reflectometry test.
Cables are critical assets for transit systems and cable lifetime is generally estimated from the temperature change and associated lifetime reduction. However, determining lifetime reduction is intricate due to the complex physics-of-failure (PoF) degradation mechanism of the cable. This is further complicated with the different sources of uncertainty that affect the cable lifetime estimation. Generally, simplified, or deterministic PoF models are adopted, resulting in non-accurate decision-making under uncertainty. In contrast, the integration of uncertainties leads to a probabilistic decision-making process impacting the flexibility to adopt decisions.
Physical and visual inspections are the most common methods of detecting cable failures. The faults determined with the physical and visual inspections are generally at an advanced stage of the failure. Inspections are generally used to detect faults in overhead cables while having limited ability to detect faults in underground cables (Gouveia, 2014). Bloom et al. (2006) outlined a general decision model that enables utilities to generate business cases for asset management policies, with a specific application to underground distribution cables.
Monitoring strategies are crucial to extend the life of cables. Bicen (2017) presented a trend-based method to estimate the remaining service life of underground cables in which acceleration, and cumulative loss of life (LOL) can be calculated continuously in small time intervals in the model. The main novelty of this method is to determine the remaining service life of the underground cables considering the LOL trend on an annual basis. Electrical insulation failures occur as a result of aging caused by the presence of stresses. It is critical to determine the stress values to define the loading conditions. The other important issue is checking the insulation conditions.
Cable failure is a rising concern among utilities, particularly underground cables. They are harder to access and more costly to replace, as their installation cost is ten times higher than overhead lines. The expected higher failure rates in a cable’s life cycle occur in premature failures or aging failures. This curve is known as the “bathtub” curve, because of its shape. The explanation for early or premature failures is mostly with bad installation or cable defects from manufacturing or transport. Aging results from cable operation and exposure to aging mechanisms. Generally, premature failures are not considered assuming that this part of the cable lifetime is lived in the manufacture’s lab or detected during installation and testing procedures.
Failures of cable systems are disruptive, expensive, hazardous, and result in loss of vital evidence. Cables, joints, terminations, and connectors that are properly installed and have not been subjected to mechanical forces, moisture, or extreme temperatures have a predictable long service lifetime. Cable life is mainly determined by the aging of the cable insulation. The cables can fail from any combination of electrical, mechanical, and thermal factors.
In this chapter answers to key questions are given. Several research findings determined the lifetime and the replacement time spent in replacing underground cables. The estimated lifetime of the cables is around 35 to 40 years based on the experimental research results. To detect the failure in the cables, there are various test methods available. Visual inspections are performed in manholes and taps, and hi-pot, meggering and thumb tests are run in certain periods to determine and fix the cable faults. In addition, the Blavier test can be performed when there is a ground fault in one cable and there are no other faulted cables. The Blavier test is the measurement of resistance from the end of one segment or the other when there is no sound cable. This method is considered a cost-effective test method used for cables to identify what may need replacement. Although the tests are relatively straight forward, repair or replacement can be challenging and complex work and may need more equipment to detect faults in traction cables. Fast and effective cable failure detection is critical and reduces the higher risks. The key features for installing underground cables are the distance between the cables, insulation size, depth of burial, ground thermal resistivity, temperature, and the cable support system. The guide has reviewed the parameters to be taken care of during the installation of underground cables. In addition, the parameters that are required to test the cable resistivity based on aging have been summarized thoroughly. New insulation materials brought a new aspect to cable service life. In addition, condition assessment and failure prediction are important for a longer cable service life. Even the failure mechanisms are different in various cases, and as such monitoring is very important in cable service life. Table 2.1. presents the summary of the Literature Review.
Table 2.1. A Summary for Literature Review
| Useful Life of Cables | |
| Zhou et al. (2017) | The proportion of joint failures, termination failures, and cable body failures was 37%, 32%, and 31%, respectively. |
| Levi and Shah (2018) | Typical Construction of a Medium Voltage cable. |
| Aldhuwaian (2015), and Reid (2013) | The underground insulation material Chart. |
| Altamirano et al. (2010), and Densley (2001) | Cable Aging, Mechanisms, and Consequences. |
| Terezia (2013) | The growth of water trees in insulation systems play an important role in cable degradation. |
| Mashikian and Szarkowski (2006) | Water treeing will not inherently cause a fault in the cable. A water tree could even bore through the whole insulation and not cause a fault. |
| Lanz (2017), and Dodds (2017) | Electrical trees are usually visible to the naked eye if found within the insulation. |
| Laurent (2013) | If a water tree is present, it can hinder the growth of the electrical tree. Another factor is the voltage level when the electrical tree starts to discharge. |
| Cloud (2012) | Overheating is an agent that can affect underground cable systems. |
| Lanz (2017) | One of the most common, yet most preventable agents of cable faults is the installation errors. |
| Degree of Degradation | |
| Chan and Mosleh (2018) | Give the predictive model of the degradation of cable insulation subject to radiation and temperature. |
| Liu (2013) | The virtual degradation rate is determined by fitting experimental data with physics-based equations. |
| Neier (2019) | The method of degradation measurement used permittivity of polymers and the dielectric and mechanical measurements on aged wire insulation. |
| Szatmari et al. (2015) | The degradation process starts by bio deterioration of the outer polyethylene layer which can be prevented to some extent by cathodic protection. |
| Detect Degradation of Cables | |
| Meijer et al. (2015) | Health Monitoring Index (HMI) tool was introduced to assess a cable system’s health and to evaluate maintenance strategies. |
| Sidhu (2010) | Proposed a scheme for early detection of underground cables’ faults. |
| Sachan et al. (2018) | Developed a probabilistic dynamic programming model to find the optimal maintenance policy for cables using the degradation level and failure distribution of cables. |
| Orille-Fernandez et al. (2006) | Used artificial intelligence (Artificial Neural Networks ANN) to predict the cable’s failure risk. |
| Kauhaniem et al. (2019) | Proposed that the wave propagation velocity of the cable be determined experimentally to enable locating of the PD faults with increasing accuracy. |
| Zhang et al. (2018) | Proposes a strategy of utilizing infrared temperature estimation to accurately decide the type and degree of cable defects. |
| Ocuon et al. (2015) | Presents a thermal examination with FEM for underground cable systems. Application of momentum-type Particle Swarm Optimization. |
| Kruizinga (2017) | The replacement of grid sections only takes place after repeated outages in the same section, as there are no methods available to perform diagnosis on LV grids. |
| Nemati et al. (2019) | The effects of control cables’ reparability characteristic on failure rate estimation are displayed. |
| Factors Influencing the Lifespan | |
| Sutton (2010) | Various environmental factors influence the life span of cables. |
| Kim et al. (2014) | Economic feasibility evaluation and simulation study results helped determine the appropriate type of cables. |
| Jones and Mcmanus (2010) | Define the life-cycle effects of five different types of electrical cables. |
| Gouda (2010) | Study the dry zone phenomena linked to various parameters impacting underground cables. |
| Neier et al. (2019) | After weak spots are cleared, the general aging condition of the cable can be judged, and the remaining lifetime can be estimated. |
| Ildstd et al. (2004) | Explored factors influencing the lifespan of cables. |
| Aizpurua et al. (2020) | Developed a novel cable lifetime estimation framework that connects data-driven probabilistic uncertainty models with physics-of-failure (pof)-based operation. |
| Tobias et al. (2019) | Studied an approach to estimate underground cables remaining life. It depends on defining the weak points. |
| Zawaira (2017) | Power transmission line model. It combined wavelets and the Neuro-fuzzy technique for fault location and identification in underground cables. |
| Metwally (2011) | Discussed some preventive maintenance techniques for cables. |
| Cost-Effective Methods to Extend the Life Span | |
| Gouveia (2014) | Inspections are generally used to detect faults in overhead cables while having limited ability to detect faults in underground cables. |
| Bloom et al. (2006) | Decision model that enables utilities to generate business cases for asset management policies. |
| Zarchi and Vahidi (2018) | Novel algorithm for the optimal placement of underground cables in a concrete duct bank to simultaneously maximize ampacity and minimize cable system cost for the first time. |
| Larsen (2016) | Method to estimate the costs and benefits of underground cables. |
| Sachan and Zhou (2019) | Degradation percentage in planning horizons is demonstrated. |
| Smart Replacement Strategy | |
| Bicen (2017) | A trend-based method to estimate the remaining service life of underground cables. |
| Zhang et al. (2021) | Explore latest advances in research and development toward cables including smart strategies for cable inspection. |
| Griffiths et al. (2002) | Quick estimation of the life expectancy of cables. |
| Sachan (2016) | Stochastic dynamic programming-based model for cables replacement optimization. Stochastic dynamic programming- based model. |
| Installation Concerns | |
| Sachan and Zhou (2019) | The degradation can be quantified in terms of percentage with the advancement of age for a group of cables with similar installation years, design, and operation. |
| Dong et al. (2017) | Transportation of cable to site and installation activities can cause damage. |
| Cable Failures Process | |
| Densley (2001) | Represented reasons for aging degradation and can be accelerated in medium voltage cables. Aging and deterioration result from environmental conditions. |
| Villaran and Lofara (2009) | Represented cable conditions inspection methods. |