Age Life, AYMs, and Renewable Generation in Alberta

Submitted by: Ryan Hayman, Ryan, Calgary, AB

Electric power generation is no longer a technologically homogeneous industry. Over the past two decades, solar photovoltaic (PV) and wind technologies have expanded rapidly while experiencing substantial capital cost declines globally (International Renewable Energy Agency [IRENA], 2024; Way et al., 2022). At the same time, traditional thermal generation technologies such as gas combustion turbines and steam turbine systems have exhibited comparatively stable or inflation driven capital cost behavior (U.S. Energy Information Administration [EIA], 2023).

In Alberta, linear assessment frameworks were largely developed during a period when generation technologies moved in broadly similar cost patterns and when thermal generation dominated installed capacity (Government of Alberta, 2025). Today, however, the economic realities of renewable technologies differ fundamentally from those of traditional generation. This divergence raises important questions about whether current age life schedules and annual year modifiers appropriately reflect replacement cost behavior.

This article argues that renewable generation should be decoupled from traditional thermal generation within Alberta’s linear assessment system. It further evaluates whether solar photovoltaic and wind generation should themselves be treated separately for depreciation purposes. Importantly, this discussion does not suggest that traditional generation assets should be assigned longer economic lives. In fact, contemporary market and policy developments suggest caution in overstating the economic life of thermal assets.

This perspective is grounded in energy market fundamentals. Competitive wholesale markets, policy risk, carbon regulation, and rapid technological change have shortened economic horizons across multiple generation types. Age life assumptions that do not reflect these realities risk overstating value and distorting competitive neutrality.

Diverging Capital Cost Trajectories

The long run capital cost behavior of solar photovoltaic systems has been extensively documented. Global installed costs for utility scale PV have declined dramatically since 2010, driven by manufacturing scale, supply chain optimization, and sustained technological innovation (IRENA, 2024).

Empirical research demonstrates that PV follows a strong learning curve pattern in which costs decline predictably as cumulative installed capacity increases (Rubin et al., 2015; Way et al., 2022). Way et al. (2022) demonstrate that solar PV costs have historically declined in line with Wright’s Law, reinforcing that cost compression is structural rather than cyclical. Similarly, Rubin et al. (2015) review learning rates across electricity supply technologies and confirm that solar exhibits one of the highest learning rates among generation technologies.

Solar’s modular design accelerates this process. Improvements in module efficiency, inverter technology, tracking systems, and balance of system components occur rapidly and are diffused globally. As a result, solar replacement cost behavior has been structurally downward over long periods, even accounting for short term volatility caused by supply chain constraints (IRENA, 2024).

Wind energy demonstrates learning curve characteristics as well, though less steep than solar. Bolinger and Wiser (2013) document wind turbine price reductions driven by cumulative deployment, while also highlighting exposure to steel prices, exchange rates, and supply chain dynamics. Wind turbine costs therefore reflect a combination of technological learning and commodity sensitivity.

In contrast, gas combustion turbines and steam turbine based generation represent mature technologies. Capital cost movements are primarily influenced by labor, commodity inputs, environmental compliance requirements, and engineering complexity (EIA, 2023). While incremental efficiency gains continue, these technologies do not exhibit the steep learning rates observed in solar PV (Rubin et al., 2015). Their capital costs tend to move with inflationary and input driven pressures rather than sustained structural decline.

Canadian construction price data reinforce this distinction. Statistics Canada’s Building Construction Price Index (BCPI) demonstrates persistent upward pressure in non-residential construction costs in recent years, reflecting material and labor cost inflation (Statistics Canada, 2024). Such indices closely resemble the cost structure faced by thermal generation development, whereas solar PV’s global manufacturing cost curve often offsets domestic construction inflation.

When indexed over time, the divergence is clear. Solar capital costs have fallen sharply since 2010 (IRENA, 2024; Way et al., 2022). Wind has declined more moderately (Bolinger & Wiser, 2013). Thermal generation capital costs have generally risen in nominal terms, influenced by construction cost inflation and regulatory compliance requirements (EIA, 2023; Statistics Canada, 2024). These differences have direct implications for how annual year modifiers function within linear assessment systems.

Structural Effects of a Single Annual Year Modifier

Alberta’s linear assessment framework applies a single annual year modifier to electric power generation assets (Government of Alberta, 2025). This modifier generally reflects inflationary movement in capital costs.

For traditional thermal generation, capital cost movements are generally influenced by commodity inputs, labor costs, and regulatory compliance requirements (EIA, 2023; Statistics Canada, 2024). In theory, an inflation-based trending factor may capture portions of these cost drivers. However, thermal generation assets are also subject to market restructuring, carbon policy exposure, and fuel price volatility that can materially affect economic value independent of construction inflation. As such, even for thermal assets, a uniform trending factor should not be assumed to fully reflect replacement cost or economic obsolescence.

For solar photovoltaic assets, however, long term learning curve effects have historically offset or exceeded general inflation (Way et al., 2022). Applying a uniform upward trending factor to PV assets during periods of structural cost decline risks overstating replacement cost relative to global manufacturing realities (IRENA, 2024). Even where nominal costs stabilize or temporarily increase, the longer-term trajectory remains learning driven.

Wind occupies an intermediate position. Its capital cost behavior reflects both learning curve effects and commodity exposure (Bolinger & Wiser, 2013). A uniform trending factor may not fully capture this dual nature.

The practical result is asymmetry. A single electric power annual year modifier assumes homogeneity where none exists. As renewable penetration increases within Alberta’s generation mix, the potential magnitude of this distortion increases as well.

Age Life Schedules and Economic Obsolescence

Alberta’s Linear Property Assessment Minister’s Guidelines explicitly provide that Schedule C depreciation factors are intended to reflect normal physical depreciation, normal functional depreciation, and normal economic depreciation for the applicable asset class (Government of Alberta, 2025). The prescribed tables are mandatory and must be applied without adjustment or modification. In principle, therefore, Schedule C is designed to account for expected economic obsolescence over the asset’s assumed life.

The critical question, however, is whether the economic assumptions embedded in those fixed tables continue to reflect contemporary competitive market realities. Depreciation schedules are intentionally static. Energy markets are inherently dynamic. Where economic risk, policy exposure, or technological displacement compress expected operating duration, fixed schedules may overstate effective economic life or lag observable market behavior.

Solar photovoltaic systems present unique depreciation characteristics. While module physical life may exceed 25 years, inverter replacement is commonly required within 10 to 15 years (IRENA, 2024). Rapid improvements in module efficiency and system design can render older installations economically disadvantaged relative to newer projects (Way et al., 2022). Economic obsolescence may therefore occur faster than physical deterioration alone would suggest.

Wind turbines follow a different pattern. Mechanical fatigue, gearbox wear, and blade stress define their life cycle. Repowering events often occur around 20 to 25 years, frequently aligned with long term contractual arrangements (Bolinger & Wiser, 2013). Depreciation patterns for wind are influenced more by mechanical aging than by rapid efficiency displacement.

Traditional thermal generation assets are often modeled with lives extending 40 to 50 years or more. While certain facilities may physically operate for extended periods, economic life in competitive markets is frequently shorter. Carbon policy exposure, fuel price volatility, evolving market design, and increasing renewable penetration have materially shortened the economic horizon for many thermal facilities in Canada (Government of Alberta, 2023). Physical life should not be conflated with economic life. In competitive markets, economic viability is often determined long before physical deterioration renders an asset inoperable.

In Alberta, the coal to gas transition provides a clear example. Coal fired generation was retired or converted earlier than originally anticipated due to legislated phase out timelines (Government of Alberta, 2023). These retirements represent accelerated economic depreciation that is not necessarily reflected in standard age life schedules. Even converted facilities remain subject to policy and market risk that may constrain long term economic life. The transition illustrates how policy risk can materially truncate expected asset lives. Depreciation schedules that assume uninterrupted multi-decade operation may not align with actual market and regulatory risk exposure.

When regulatory or market developments materially shorten expected economic duration, reliance solely on pre-set depreciation curves may not fully capture economic reality. Therefore, the concern is not that thermal assets require longer depreciation lives. Rather, the broader issue is whether fixed schedules adequately capture economic obsolescence across all generation types.

The Case for Decoupling Renewables from Traditional Generation

The argument for decoupling renewable generation from traditional thermal assets rests on structural differences in capital cost behavior, innovation cycles, and economic obsolescence patterns.

Solar photovoltaic follows a strong learning curve supported by empirical evidence (Rubin et al., 2015; Way et al., 2022). Wind exhibits moderate learning combined with commodity sensitivity (Bolinger & Wiser, 2013). Thermal generation is largely inflation and input driven, while also increasingly subject to policy risk (Government of Alberta, 2023; Statistics Canada, 2024).

Replacement cost trends are not uniform. From a market perspective, age life assumptions should reflect competitive pressures and economic risk. Overly extended depreciation horizons can overstate value just as readily as insufficient trending can. Applying a single trending factor assumes homogeneity that market evidence does not support.

At the same time, policy driven transitions such as Alberta’s coal phase out demonstrate that thermal assets are not immune to accelerated economic depreciation. Uniform schedules risk misalignment in both directions.

These differences suggest that renewable generation should not be treated merely as another subclass of electric power within a uniform linear framework built around historical thermal assumptions.

Should Solar Photovoltaic and Wind Be Treated Separately

Although both are renewable technologies, solar and wind exhibit important structural distinctions. Solar photovoltaic systems are highly modular, display higher learning rates, and demonstrate more consistent structural cost decline (Way et al., 2022). Wind turbines are integrated mechanical systems with significant commodity exposure and defined repowering cycles (Bolinger & Wiser, 2013).

From a depreciation perspective, solar’s rapid technological iteration may justify a steeper early depreciation curve reflecting accelerated economic obsolescence. Wind depreciation may align more closely with mechanical design life and fatigue characteristics.

Grouping both technologies under a single renewable depreciation schedule may simplify administration but risks obscuring economic distinctions that could become increasingly material as capital investment in renewables grows.

Policy Considerations

Modernizing linear assessment treatment does not require abandoning administrative simplicity. Several calibrated approaches are available.

Assessment authorities could consider establishing separate annual year modifiers for thermal and renewable generation. Renewable generation could be subdivided into solar and wind categories for depreciation purposes. Periodic recalibration of trending factors could incorporate Canadian construction price indices such as the BCPI (Statistics Canada, 2024) alongside global renewable cost data (IRENA, 2024).

Equally important is periodic reassessment of assumed economic life for thermal assets in light of policy transitions and market restructuring. The coal to gas transition illustrates that policy risk can materially accelerate economic depreciation.

The objective is not to advantage one generation type over another. It is to align assessment methodology with observable economic behavior. As renewable generation expands and policy transitions continue, maintaining uniform treatment may increase appeal risk, perceived inequity, and distortion of tax burdens across asset classes.

Conclusion

The electric generation sector has evolved beyond the assumptions embedded in many linear assessment frameworks. Solar photovoltaic, wind generation, and traditional thermal plants exhibit distinct capital cost trajectories, innovation cycles, and economic life patterns.

Applying uniform annual year modifiers and shared age life schedules across these divergent technologies may introduce structural distortion. Ensuring that depreciation schedules reflect realistic economic life expectations is equally important. Competitive markets reward efficiency and innovation, but they also compress asset lifespans. Assessment frameworks should reflect that reality. At the same time, traditional generation assets should not automatically be assumed to warrant extended economic lives, particularly in light of Alberta’s recent policy driven transitions.

The evidence from empirical cost studies, Canadian construction price indices, and provincial policy developments supports decoupling renewable generation from traditional thermal assets within Alberta’s linear assessment framework. There is also a defensible policy basis for evaluating whether solar photovoltaic and wind generation should receive distinct depreciation treatment.

Aligning assessment practice with economic evidence strengthens neutrality, reduces dispute risk, and preserves the credibility of Alberta’s property taxation system in an energy sector undergoing continued transformation.

References

Bolinger, M., & Wiser, R. (2013). Understanding wind turbine price trends. Energy Policy, 60, 628–641.

Government of Alberta. (2023). Coal phase-out and electricity transition overview. Government of Alberta.

Government of Alberta. (2025). Minister’s guidelines for linear property assessment. Government of Alberta.

International Renewable Energy Agency. (2024). Renewable power generation costs in 2023. IRENA.

Rubin, E. S., Azevedo, I. M. L., Jaramillo, P., & Yeh, S. (2015). A review of learning rates for electricity supply technologies. Energy Policy, 86, 198–218.

Statistics Canada. (2024). Building construction price index, fourth quarter 2024. Government of Canada.

U.S. Energy Information Administration. (2023). Capital cost and performance characteristic estimates for utility-scale electric power generating technologies. U.S. Department of Energy.

Way, R., Ives, M., Mealy, P., & Farmer, J. D. (2022). Empirically grounded technology forecasts and the energy transition. Nature Energy, 7, 1027–1036.