By Sara Bishop, Pepco Holdings Inc., and Scott Sidney, PA Consulting
Over the past century, electric utilities in the United States constructed and expanded their bulk electric system (BES) transmission infrastructures (above 100 kV) to meet enormous load growth demand. Parts of these transmission systems are beginning to exceed expectations, and utility companies are beginning to evaluate their infrastructures to determine what needs to be done to continue to maintain a high level of reliability.
Pepco Holdings Inc. (PHI) determined it needed to assess transmission assets, looking at age, condition, overall reliability and resiliency. PHI completed the system assessment, identifying the scope of potential upgrade projects needed to continue reliable service.
As the service provider to the nation’s capital, PHI is responsible for providing safe and reliable electric service to numerous critical customers. To do so, PHI must continually maintain and enhance its transmission infrastructure, which includes more than 4,000 miles of BES assets in Washington, D.C., Maryland, Delaware and New Jersey. PHI also must be cognizant of the diverse weather events which can impact its region, including ice, wind, snow, hurricanes, tornadoes and floods (particularly in the coastal areas).
With this increased focus on reliability and resiliency, PHI undertook an initiative in late 2012 to research and develop a transmission line asset replacement model that included an in-depth study and analysis of the risk factors pertaining to its transmission infrastructure.
|Sara Bishop (co-author) and two other PHI engineers study infrastructure drawings and documents during the risk assessment process.|
The PHI transmission planning process includes input from its asset strategy and system planning department, which is responsible for transmission system capacity and reliability; and its transmission and civil engineering department. Previously, PHI primarily considered individual asset records as the dominant factor in asset replacement. The company addressed any specific condition concerns that arose from comprehensive inspections, testing programs and routine maintenance independently, without viewing the system holistically.
After completing analysis of the system and historic outage rates, PHI determined that comprehensive rebuild and upgrade decisions could not be made based solely on age, condition and reliability data. It identified additional risk variables and parameters that must be considered. PHI determined that incorporating these additional variables and parameters into the analysis was a more effective way to make rebuild and upgrade decisions.
Identifying overall risk is complicated in a transmission system because of the wide variety of components and functionality incorporated into the system. Conventionally, risk level is determined by multiplying consequence of failure and probability of occurrence. This does not work in the context of a transmission system, however. Failures are infrequent; they may occur due to a variety of causes and many do not result in financial consequences other than the cost of repair. Redundancy built into network systems keep failures from impacting customers, which makes financial cost determination difficult to quantify.
For these reasons, a new approach for identifying, scoring and ranking risk was developed to provide a balanced comparison between different transmission lines and the different risks to which each is exposed. This approach provides insight into the risk factors of each transmission line and provides mechanism for making cost-effective asset replacement decisions.
Risk criteria were separated into three major categories:
“- Line characteristics – circuit number, age, tower or cable type and location
“- Operational characteristics – percent peak loading, customer and circuit criticality, redundancy and resource availability for emergency repairs
“- Condition – For underground circuits, factors such as cable type (self-contained fluid filled, high pressure oil filled), river crossings, spare parts availability and termination condition were included. For overhead circuits, data from annual line inspection reports, providing the condition of items such as steel, wood, insulators, conductors and grounding was included.
Each criteria was scored from 1 to 5 (1 = low risk), with clearly defined criteria correlating to each possible score. Wherever conceivable, quantifiable values were used. As an example, Table 1 illustrates the scoring and criteria for peak circuit loading criteria.
Where quantification was not directly achievable, subjective criteria were used, but applied with the same rigor. For example, for the location risk factor criteria, an underground transmission line that runs under a highly sensitive facility would receive a score of 5, while those easily accessible on PHI right-of-way might receive a score of 1. Each risk criterion was also force-ranked to establish the priority on a 1 to 5 scale. The risk scores were then multiplied by their weight and summed to get the overall circuit risk score.
The risk models were built as dynamic decision support tools, not decision making tools. A high risk score does not mean automatic transmission line replacement. For example, the risk might be driven by other variables and parameters that might dictate the need for an operational contingency. Risk scores can further be evaluated to identify specific risk drivers, allowing for targeted consideration for rebuilding or contingency planning depending on the nature of the risk drivers.
The transmission and civil engineering department is responsible for asset age and condition assessment, which may or may not involve full replacement. Transmission line and operational characteristics, however, also are key inputs to rebuild/upgrade decisions. Line characteristics, such as age, construction type and location, and operational characteristics are critical factors in the overall risk assessment. This assessment indicates the need for complete, current and accurate asset data as well as a comprehensive understanding of risk variables and parameters.
At the onset of the asset assessment project, PHI realized that its transmission asset data collection, storage and retrieval processes needed to improve to increase the utility’s ability to support the dynamic nature of the risk models being built. As part of the risk model development, this situation was addressed and processes are being implemented to facilitate annual asset data updates.
For overhead transmission lines, PHI integrates its comprehensive aerial inspection program as a direct model input for overhead transmission assets. Any steel corrosion, chipped insulators, missing locknuts, wood decay, missing or damaged grounds, damaged wire strands and other problems are identified and serve as model input.
A five-year comprehensive inspection is completed and additional off-cycle inspections also are completed as deemed necessary. Inspection issues are collected through the individual line inspection reports and converted to percentage values. For example, if 25 instances of chipped insulator strings are discovered on a line with 50 towers, the insulator condition number becomes 0.5.
This number is then scaled on the 1-5 ranking system for risk criteria. As comprehensive condition reports are received, PHI engineers can update the risk model and re-evaluate risk priorities. If the inspection reports result in corrective actions, the identified issues are removed and new risk values are entered into the model.
The same approach applies to PHI underground transmission lines. On a regular basis, pumping facilities, terminations, manholes and related equipment undergo a condition assessment and the results are entered into the risk model. By these means, there is always a current view of the overall system risk profile. An annual risk review also includes a discussion with the appropriate PHI internal stakeholders, such as the asset strategy and system planning department and the system operations department.
Since developing this asset risk model, PHI can holistically review the quantified risk associated with all transmission circuits in its service territories and compare these scores with the proposed five-year capital construction program. When initially comparing the risk assessment with the capital construction plan, a few transmission circuits with high risk scores were not present in the capital program while in other instances transmission circuits with low risk scores were included.
The new risk model enabled PHI engineers to integrate transmission line project planning based on capacity, reliability, age and condition criteria. The detail in the risk model means PHI can fully review and evaluate potential projects and provided the opportunity to mitigate otherwise unknown risk to the existing transmission infrastructure.
Developing a risk-based asset management approach provides numerous other benefits to PHI and its stakeholders. This unique approach results in a risk model that is simple to use, explain and update. Most importantly, this risk assessment replaces subjective decision making with a quantifiable approach.
Limiting the subjectivity of bulk electric system asset priorities provides PHI with raw, annually updated data to justify spending. From a management perspective PHI is now able to make fully informed decisions, looking at asset risks across the system. Management can optimize the distribution of funding by allocating resources to the highest risk projects across all of PHI’s service territory.
In fact, the outputs of the risk model can be directly input into PHI’s financial planning program. This risk analysis will serve as a living repository for information, allowing management to effectively make bulk electric system asset decisions, support PHI’s transmission risk-alleviation projects and maintain reliable service for customers.
Sara Bishop, is an engineer with Pepco Holdings Inc and serves as the responsible engineer for major underground transmission engineering projects in the Washington D.C. metropolitan area plus transmission standards development.
Scott Sidney is a managing consultant with PA Consulting Group specializing in asset management risk and reliability assessment.