Transmission Line Reliability

Transmission Line Reliability

DOI: 10.4018/978-1-5225-4941-3.ch004
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The fourth chapter deals with transmission line reliability evaluation. For carrying out reliability studies, regression and Markov methods are applied to the field data. Regression approach is applied to predict the future performance based on the past data obtained from the field. Markov method is used to compute the reliability indices such as availability, unavailability, failure rate, repair rate for performance evaluation of the power transmission system. Transmission line performance assessment depends on data collection capabilities and performance metrics to ensure continued grid adequacy and security.
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The basic function of an electric power system is to supply electrical energy to consumers as economically as possible with an acceptable level of reliability. Bulk power system planning and operation procedures include reliability as one of the essential measures of system performance. Reliability evaluation of an electrical power system can be divided into two basic elements, past performance assessment and future performance prediction. Both qualitative and quantitative assessment can be used to achieve system reliability. Qualitative assessment is often referred to as an engineering judgement and it is not suitable to compare alternative configurations or perform economic analysis. Reliability is an inherent characteristic of a power system and therefore it should be expressed in quantitative terms.

Quantitative reliability evaluation invariably leads to the consideration of the data available and the data required for supporting such studies. It should be noticed that in the long-term planning, it will be even more expensive if data is not properly collected and consolidated. Reliability studies cannot be conducted if data is not available. Data collection and reliability evaluation must evolve together and therefore the process is iterative. At the same time, it is inefficient and undesirable to collect, analyze and store more data than required for the purpose intended. It is essential to identify how the data will be used before deciding what data to collect.

Collection of data is essential as it forms the input to relevant reliability models, techniques and equations. The data should be able to reflect and respond to the factors that affect reliability, so that reliability can be modeled and analyzed.

This limited use of long-distance connections aided system reliability, because the physical complexities of power transmission rise rapidly as distance and the complexity of interconnections grow. Power in an electric network does not travel along a set path, as coal does, for example. When utility A agrees to send electricity to utility B, utility A increases the amount of power generated while utility B decreases production or has an increased demand. The power then flows from the “source” (A) to the “sink” (B) along all the paths that can connect them. This means that changes in generation and transmission at any point in the system will change loads on generators and transmission lines at every other point often in ways not anticipated or easily controlled.

To avoid system failures, the amount of power flowing over each transmission line must remain below the line’s capacity. Exceeding capacity generates too much heat in a line, which can cause the line to sag or break or can create power-supply instability such as phase and voltage fluctuations. Capacity limits vary, depending on the length of the line and the transmission voltage (Table 1). Longer lines have less capacity than shorter ones.

Table 1.
Capacity limits for electrical transmission lines
Voltage (kV)Length (Kms)Maximum Capacity (MW)

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