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Opening the Black Box
A new approach to utility asset management.
their shareholders, our methodology can provide greater assurance that asset management decisions are prudent, so that the costs can be recovered from ratepayers, thus reducing uncertainty. For utility regulators, the methodology provides greater assurance that utilities are providing required levels of safety and reliability at the lowest cost, thus benefitting ratepayers. Moreover, the methodology can also provide regulators with an objective ability to independently verify utility asset management strategies, rather than accept black-box approaches they can’t assess independently.
First, we describe six common errors in models used to make asset management decisions for transmission and distribution (T&D), and how these errors lead to inferior decisions about equipment repair and replacement. Second, we explain the four uncertainties that increase the complexity of asset management strategies. Third, we describe the analytical method we developed that addresses these uncertainties in a statistically and mathematically correct way. We conclude with a real-world application of the methodology, showing how it’s been used by one regional transmission organization (RTO) to evaluate optimal numbers and locations of spare transformers.
The Cost-Risk Tradeoff
Decisions regarding whether to repair or replace specific assets, or simply leave them in place, share common characteristics and tradeoffs. The basic tradeoff is well-known to anyone who owns a car: putting off replacement to postpone the cost of buying a new one must be tempered against the increasing cost of likely repairs. For utilities, which operate assets over the indefinite future, an asset management strategy based on extending the life of an asset reduces the present value of the cost of asset replacement over the indefinite and foreseeable future. However, as assets age, they tend to require more expensive and more frequent repairs. Further, taken to its logical conclusion, extending the life of an asset tends to provide a “run-to-failure” asset management strategy. Therefore, evaluation of life extension or run-to-failure strategies must address the cost of unplanned failures. These concepts are illustrated in Figure 1.
Figure 1 illustrates the decreasing present value cost associated with planned asset replacements as a function of asset retirement age: the greater the age at which an asset is retired, the lower the present value cost of a timed sequence of asset replacements over the indefinite future. However, as an asset’s retirement age increases, the higher the risk (and unplanned costs) associated with repairs or asset failure that could occur in each increasingly large replacement cycle. The costs shown are only expected values, because when (or if) an asset fails is uncertain. The likelihood of an asset’s failure sometime in the future is called the asset’s “hazard rate.” 1
The optimal retirement age is defined as the one for which the expected total cost is minimized. This is shown in Figure 2. The expected total cost is the sum of the planned replacement costs and the expected cost of asset failures (risk). In the example presented in Figure 2, the minimum expected cost occurs at a planned retirement age of 35 years for this type of asset. 2
Defining and identifying the optimal replacement strategy is conceptually straightforward, as shown in