WaywardHouse
The Economics of Clean Generation
A wind turbine in Pincher Creek costs roughly the same to build as a natural gas peaker in Edmonton. The difference is that the turbine’s fuel is free. The LCOE equation captures this trade-off in a single number — and in 2024, for the first time in Alberta’s history, that number favours wind and solar in most scenarios.
Prerequisites: LCOE (Levelised Cost of Energy), Capital recovery factor, Storage cost model, Transmission congestion rent
A wind turbine in Pincher Creek costs roughly the same to build as a natural gas peaker in Edmonton. The difference is that the turbine’s fuel is free. The LCOE equation captures this trade-off in a single number — and in 2024, for the first time in Alberta’s history, that number favours wind and solar in most scenarios.
This essay translates the resource geography mapped in R1 into project economics. The LCOE framework makes all generation technologies commensurable: different capital costs, different capacity factors, different operating lives, all collapsed into a single comparable cost per megawatt-hour. The arithmetic is not complicated. What it reveals about Alberta’s current situation is significant.
The LCOE equation — capital versus fuel
Levelised Cost of Energy (LCOE) is the minimum price at which a generator must sell electricity to recover its costs over the project’s life — capital, financing, and operations combined. It answers the question: what $/MWh price makes this investment break even?
The equation has three moving parts.
First, the capital recovery factor (CRF). A wind farm requires roughly $1,650/kW of capital upfront. That lump sum must be recovered over the project’s 25-year life through annual revenue. The CRF converts a one-time capital cost into an equivalent annual payment, accounting for the time value of money:
\[\text{CRF}(d, n) = \frac{d(1+d)^n}{(1+d)^n - 1}\]| Symbol | Meaning | Typical value |
|---|---|---|
| d | Weighted average cost of capital (WACC) / discount rate | 6–10% for utility renewables in Canada |
| n | Project life (years) | Wind: 25; Solar: 30; Battery: 15 |
The CRF is structurally identical to a mortgage payment formula. At 8% over 25 years, CRF = 0.0937 — meaning you need to recover about 9.4 cents per dollar of capital each year to break even. At 6% over the same period, CRF = 0.0782. That four-percentage-point difference in the cost of capital translates, as we will see, into roughly a $20/MWh difference in LCOE. Financing is not a detail.
Second, the LCOE formula itself. Once annual capital charges are known, we add annual operating costs and divide by annual energy output:
\[\text{LCOE} = \frac{\text{CAPEX} \cdot \text{CRF} + \text{OPEX}\_{\text{annual}}}{\text{CF} \times 8760 \text{ h}}\]| Symbol | Meaning | Typical range (2024) |
|---|---|---|
| CAPEX | Capital cost ($/kW nameplate) | Wind: \$1,400–1,900; Solar: \$900–1,300; BESS (4h): \$1,200–1,600 |
| OPEX | Annual operating cost ($/kW/year) | Wind: \$40–55; Solar: \$15–25; BESS: \$20–35 |
| CF | Capacity factor | Wind (AB SW): 0.38–0.45; Solar (AB south): 0.22–0.26 |
| LCOE | Levelised cost of energy | $/MWh |
The denominator — capacity factor multiplied by 8,760 hours — is the annual energy output per kilowatt of nameplate capacity. A wind farm with a 0.40 capacity factor produces 3,504 kWh per kW per year. A gas peaker running at 0.15 capacity factor produces 1,314 kWh per kW per year. The peaker’s denominator is less than 40% as large, which means capital cost must be spread across far less energy — making per-MWh capital charges high even if the absolute capital cost ($700/kW for an open-cycle turbine) is modest.
This is the structural insight. Gas peakers have low capital cost but run infrequently, so their capital-per-MWh is surprisingly high. Wind and solar have high capital cost but zero fuel cost and run as often as the resource allows. The comparison pivots on where the capacity factor lands — and in southwestern Alberta, wind capacity factors of 0.38–0.45 push wind LCOE firmly into $50–70/MWh territory at reasonable financing rates.
The technology comparison. At 8% WACC, the 2024 Alberta picture looks approximately like this:
| Technology | CAPEX ($/kW) | CF | LCOE ($/MWh) |
|---|---|---|---|
| Wind (SW Alberta) | \$1,650 | 40% | ~\$58 |
| Solar (S. Alberta) | \$1,100 | 24% | ~\$52 |
| Gas CCGT | \$1,200 | 55% | ~\$43 |
| Gas peaker (OCGT) | \$700 | 15% | ~\$68 |
Two observations from this table deserve emphasis. First, utility solar in southern Alberta is competitive with combined-cycle gas on LCOE — even before accounting for gas fuel price risk over a 30-year project life. Second, gas peakers are more expensive than wind on an LCOE basis when running at their typical 15% capacity factor. The gas peaker’s remaining advantage is dispatchability — it can run when called upon regardless of weather — but that is increasingly an argument about grid architecture rather than raw generation cost.
The 2024 threshold. Alberta’s electricity pool price has averaged approximately $65–80/MWh over recent years, with extreme volatility in both directions. New wind and solar, contracted at $50–70/MWh through a long-term PPA, now fall below that average. This is a structural shift, not a policy artefact. No carbon price, no subsidy, no renewable energy credit makes this arithmetic work — the capital costs of wind and solar have declined far enough, and Alberta’s resource is good enough, that the LCOE equation produces competitive numbers from first principles. The question for Alberta’s electricity market is no longer whether renewables can be economically justified. It is whether the grid can absorb them.
Storage — the missing piece and what it costs
The LCOE framework handles generation cleanly. It handles storage awkwardly, because storage is not a generation technology — it is a time-shifting technology. The relevant metric is cost per megawatt-hour discharged, accounting for the round-trip losses and the limited number of cycles a battery can provide annually.
Battery LCOE per MWh discharged:
\[\text{LCOE}\_{\text{storage}} = \frac{\text{CAPEX}\_{\text{power}} \cdot \text{CRF} + \text{OPEX}}{\text{Cycles/year} \cdot \text{DoD} \cdot \text{RTE}}\]| Symbol | Meaning | Value |
|---|---|---|
| CAPEX_power | Battery system cost ($/kWh) | \$350–500/kWh (4-hour BESS, 2024) |
| Cycles/year | Number of full charge-discharge cycles per year | 250–350 (daily cycling) |
| DoD | Depth of discharge | 0.85–0.90 |
| RTE | Round-trip efficiency | 0.85–0.90 (Li-ion) |
At 2024 capital costs — roughly $400–500/kWh for a utility-scale 4-hour lithium-ion system — the denominator resolves to approximately 221–275 kWh of useful output per kWh of installed capacity per year (300 cycles × 0.87 DoD × 0.87 RTE ≈ 227 kWh). The resulting LCOE for battery storage is approximately $120–180/MWh discharged. This is substantially above wind and solar generation LCOE, which explains why storage is not yet the obvious complement to every renewable project.
Two comparisons place that number in context. First, gas peakers. An open-cycle gas turbine providing the same firming service — dispatchable capacity that runs when needed — carries an LCOE of roughly $90–130/MWh when running at 15% capacity factor and paying 2024 natural gas prices. Gas peakers are currently cheaper than battery storage for the firming function, which is why Alberta’s grid still relies on them. The question is whether that cost relationship will hold. Battery storage costs have declined approximately 85% since 2013, following a learning curve steeper than solar panels. If that trajectory continues, battery storage at $200/kWh system cost (anticipated by NREL for the late 2020s) would push storage LCOE below $100/MWh for a well-cycled system. Gas peakers, by contrast, face ongoing fuel cost exposure — a significant risk given volatile natural gas prices.
Second, pumped hydro. Pumped hydro storage is the cheapest utility-scale storage technology where topography permits: costs of $50–150/MWh discharged over 40–60 year project lives, at efficiencies of 70–85%. Alberta has almost no viable pumped hydro sites. The mountain topography needed for the upper and lower reservoirs lies in ecologically sensitive and politically contested terrain — the same mountain valleys that provide Alberta’s best wind but almost no reservoir pairs. This is a genuine geographic constraint, not a policy choice. Alberta will not build pumped hydro at meaningful scale. Its storage options are batteries, behind-the-meter storage, and the demand flexibility of its agricultural and industrial loads.
The storage addition to LCOE. If 30% of a wind farm’s output is shaped through a co-located 4-hour battery (a plausible near-term configuration for a merchant project seeking a firmed product), the blended LCOE of generation plus storage is approximately:
LCOEblended = LCOEgen + 0.30 × LCOEstorage
At wind LCOE of $58/MWh and storage LCOE of $150/MWh, that yields roughly $103/MWh for a firmed product — still within range of Alberta’s historical pool price peaks, and competitive with new gas peaker capacity on a blended basis. The economics are not yet compelling for storage as a standalone investment, but as a risk-management tool for a renewable project seeking merchant revenue certainty, the calculation is increasingly rational.
Transmission — the invisible cost
The LCOE framework captures generation and storage costs. It does not capture the cost of getting electrons from where they are generated to where they are consumed. In Alberta, that omission matters more than in most jurisdictions.
The geography of Alberta’s transmission system. Alberta’s high-voltage grid was designed for a generation system dominated by coal plants near Wabamun, Forestburg, and Sheerness — all within reasonable distance of Edmonton and Calgary load centres. The 240 kV backbone runs roughly north-south through central Alberta, connecting the major coal and gas generation nodes to the two cities. Renewable resources, as R1 showed, are concentrated in the southwest: the Pincher Creek wind corridor, the Crowsnest Pass, and the Lethbridge-to-Vulcan solar belt. Most of this area is served by 240 kV lines built decades ago with modest capacity margins. The transmission system was not built for southwest-to-northeast power flows at scale.
The cost of transmission addition. A project sited near an existing 240 kV line with spare capacity — Blackspring Ridge in Vulcan County is the canonical example — can interconnect for roughly $100–200/kW of generation capacity. The same project sited in the Crowsnest Pass, where the existing lines are constrained and a new transmission spur is needed, faces connection costs of $400–700/kW. On a $1,650/kW wind project, this difference is material: it adds 25–40% to effective CAPEX and shifts LCOE by $15–25/MWh. A site with superior wind resource (CF 0.44 versus 0.40) can easily be economically inferior to a site with better grid access once transmission cost is accounted for.
Congestion rent and the LMP mechanism. Alberta’s electricity market does not formally use locational marginal pricing (LMP) in the US sense, but the economic principle applies whenever transmission constraints bind. When a constraint prevents cheap renewable generation from flowing to load centres, the constrained generator is dispatched at the source-side price (which can approach zero during high-wind, low-demand periods), while the unconstrained generators serving load earn the full pool price. The difference is the congestion rent:
Ctx = λsink − λsource
where λ is the locational marginal price at the delivery node minus the source node. When southwest Alberta transmission is congested, a wind project in that corridor may be curtailed entirely — producing energy but earning nothing — while a gas generator in the Calgary supply area earns $80/MWh or more. This is the correct economic signal for transmission investment: the congestion rent quantifies exactly what a new transmission line is worth to the market. The challenge is that collecting that signal and translating it into regulated transmission investment takes years, and in the meantime it makes project financing in constrained zones genuinely risky.
The AESO interconnection queue. As of 2024, the AESO’s interconnection queue contains several thousand megawatts of proposed renewable capacity in various stages of study. The interconnection study process is a known bottleneck: studies take 18–36 months, the results can require project redesign, and the queue position itself creates coordination problems (a project’s transmission cost depends on which other projects proceed). This is not unique to Alberta — interconnection queues are a constraint on renewable deployment across North America — but Alberta’s combination of concentrated resource geography and limited transmission headroom makes the constraint more binding than in jurisdictions with more distributed resources.
The economic upshot: transmission proximity is not merely a preference. For a project with $1,650/kW generation CAPEX and 8% WACC, a $500/kW transmission add-on increases effective LCOE by approximately $17/MWh. In a market where the difference between a profitable and an unviable project can be $10–15/MWh, transmission access is often the deciding factor — which is precisely why Vulcan County has become Alberta’s renewable development capital despite not having the province’s highest wind speeds.
Where the economics are strongest
Combining R1’s resource map with R2’s LCOE model produces a geographic picture of renewable economics that is reasonably precise. The LCOE at any proposed project site is a function of three primary variables: the capacity factor (from the resource geography), the transmission connection cost (from grid topology), and the financing rate (from capital market conditions). All three vary significantly across Alberta.
The Vulcan County advantage. The southern Alberta agricultural triangle — roughly Vulcan, Lethbridge, and Taber — consistently appears as the most economically favourable region for new renewable development. The reasons are legible in the LCOE framework:
First, capacity factors are high. Wind capacity factors of 0.38–0.42 are achievable in the Vulcan area, reflecting the chinook-driven wind climatology R1 describes. Solar GHI in the Lethbridge-to-Taber corridor is among the highest in Canada east of the Rockies. The Travers Solar project (465 MW, commissioned 2022) is sited here for exactly this reason — southern Alberta’s combination of high direct-normal irradiance and low cloud cover produces solar capacity factors of 0.24–0.26, competitive with many US southwestern sites.
Second, grid access is available. The 240 kV transmission backbone passes through this region with sufficient capacity to absorb several gigawatts of new generation without requiring major new transmission infrastructure — at least in the near term. The Blackspring Ridge wind project (544 MW, among the largest in Canada when commissioned) connected here specifically because the transmission access cost was manageable.
Third, land is available and inexpensive. Flat agricultural land in the Vulcan-Lethbridge corridor can be leased from farmers at reasonable rates, and agricultural activity is compatible with both wind turbines (land between turbines continues to be farmed) and, increasingly, agrivoltaic solar installations where sheep graze beneath panels. The absence of terrain complexity also reduces construction cost.
The Crowsnest Pass trade-off. The Crowsnest Pass and Pincher Creek wind corridor offers genuinely better wind — capacity factors of 0.42–0.50 are achievable in the best sites, driven by the topographic acceleration of prevailing westerlies through the mountain passes. These are world-class wind resources. But the transmission infrastructure is limited, the terrain drives up construction cost, and the interconnection queue for new capacity in this area is long. The LCOE calculation frequently favours a slightly less windy Vulcan site with lower-cost grid connection over a better-resourced Crowsnest site with expensive transmission.
Northern Alberta’s disadvantages. North of Red Deer, wind capacity factors decline (0.28–0.35 in most of the agricultural north), solar GHI is significantly lower, and distance from the Calgary-Edmonton corridor increases both transmission cost and congestion risk. The economics are workable — several northern wind projects have proceeded — but they require either superior transmission access or a contracted price (PPA or REP) that compensates for the resource penalty. Merchant projects in northern Alberta face difficult economics at 2024 capital costs.
The discount rate argument — why PPAs matter. The LCOE sensitivity to discount rate is not a theoretical curiosity. At 6% WACC — achievable by a utility or infrastructure fund with long-term contracted revenue — wind LCOE in Vulcan County is approximately $48/MWh. At 12% WACC — a merchant project with uncontracted revenue, exposed to spot market volatility — that same project costs approximately $72/MWh. The $24/MWh difference between a utility-financed contracted project and a merchant project is larger than the regional resource variation between Vulcan County and central Alberta.
This is the economic case for Power Purchase Agreements and government offtake mechanisms like Alberta’s Renewable Electricity Program auctions in one sentence: they reduce financing cost by eliminating revenue risk, and the financing cost reduction is large enough to determine whether a project is viable. The 2024 REP auction results, which contracted wind capacity at approximately $45–55/MWh, were not subsidies in the traditional sense — they were market mechanisms that allowed the financing rate to fall to its utility-balance-sheet floor, revealing the underlying economics of excellent Alberta wind resources.
The 2024 data represent a structural shift in Alberta’s electricity economics. For the first time, the LCOE of new wind and solar sits clearly below the historical pool price average. This is not contingent on carbon pricing, renewable energy credits, or government subsidy. It follows from the capital cost trajectory of wind and solar technology meeting Alberta’s renewable resource. The implications for gas generation investment — and for the future of Alberta’s electricity system — are significant, and they are the subject of R3.
Run it yourself
The calculator below implements the full LCOE model from this essay. The base case represents a wind project in southwestern Alberta: $1,650/kW capital cost, $45/kW/year operating cost, 40% capacity factor, 8% WACC, 25-year life.
Start by adjusting the capacity factor between 0.35 and 0.45 — the range you would encounter moving from a mediocre central Alberta wind site to an excellent Pincher Creek site. The LCOE curve falls sharply as capacity factor rises, because the denominator in the LCOE equation grows while the numerator is unchanged. This is why project developers compete intensely for the best resource sites: a 5-percentage-point improvement in capacity factor (0.35 to 0.40) reduces wind LCOE by approximately $8–10/MWh, which is often the margin between a viable and an unviable project.
Then vary the discount rate from 0.06 to 0.12. At 6%, you are modelling a utility or infrastructure fund financing a contracted project from its balance sheet. At 12%, you are modelling a merchant developer with no long-term revenue contract, exposed to Alberta’s famously volatile spot market. The $20–25/MWh difference between these two scenarios is a vivid illustration of why revenue certainty — through a PPA or a government auction contract — is not just a policy preference but an economic necessity for unlocking the cheapest financing.
The storage add-on section shows what happens when 30% of the project’s output is time-shifted through a co-located 4-hour battery. Watch how the combined LCOE responds as battery capital cost decreases: this is the trajectory that will determine when storage becomes a standard component of new renewable projects rather than an expensive optional extra.
import numpy as np
# ── LCOE calculator — change these parameters ──────────────────────────────
technology = "Wind" # label only
capex_kw = 1_650 # overnight capital cost ($/kW) — wind: 1400–1900; solar: 900–1300
opex_kw_yr = 45 # annual O&M cost ($/kW/year)
capacity_factor = 0.40 # capacity factor — wind SW AB: 0.35–0.45; solar S AB: 0.22–0.26
discount_rate = 0.08 # WACC (decimal) — try: 0.06 (utility debt) to 0.12 (merchant)
life_years = 25 # project life — wind/gas: 25; solar: 30; battery: 15
# ── Battery storage add-on (optional) ─────────────────────────────────────
include_storage = True # set False to skip
battery_capex = 450 # $/kWh — 4-hour BESS 2024: 350–550
battery_cycles = 300 # full cycles per year
battery_rte = 0.87 # round-trip efficiency
# ── Calculations ────────────────────────────────────────────────────────────
d, n = discount_rate, life_years
crf = d * (1 + d)**n / ((1 + d)**n - 1)
annual_capex = capex_kw * crf
annual_energy = capacity_factor * 8760 # kWh/kW/year
lcoe_gen = (annual_capex + opex_kw_yr) / annual_energy * 1000 # $/MWh
if include_storage:
n_batt = 15
crf_b = discount_rate * (1 + discount_rate)**n_batt / ((1 + discount_rate)**n_batt - 1)
annual_capex_b = battery_capex * crf_b
annual_output_b = battery_cycles * 0.87 * battery_rte
lcoe_storage = (annual_capex_b + 0.025) / annual_output_b * 1000 # $/MWh
lcoe_combined = lcoe_gen + lcoe_storage * 0.30 # 30% of output through storage
# ── Output ─────────────────────────────────────────────────────────────────
print(f"LCOE Calculator — {technology}")
print(f"{'Capital cost':<28}: ${capex_kw:,}/kW")
print(f"{'Annual O&M':<28}: ${opex_kw_yr}/kW/year")
print(f"{'Capacity factor':<28}: {capacity_factor:.1%}")
print(f"{'Discount rate (WACC)':<28}: {discount_rate:.1%}")
print(f"{'Project life':<28}: {life_years} years")
print(f"{'Capital recovery factor':<28}: {crf:.4f}")
print()
print(f"{'Annual energy':<28}: {annual_energy:,.0f} kWh/kW/year")
print(f"{'Annual capital charge':<28}: ${annual_capex:.2f}/kW/year")
print()
print(f"GENERATION LCOE: ${lcoe_gen:.1f}/MWh")
if include_storage:
print()
print(f"Battery storage add-on:")
print(f" BESS capex : ${battery_capex}/kWh (4-hour system)")
print(f" Cycles/year : {battery_cycles}")
print(f" Round-trip eff : {battery_rte:.0%}")
print(f" Storage LCOE : ${lcoe_storage:.1f}/MWh discharged")
print(f" Combined LCOE : ${lcoe_combined:.1f}/MWh (30% dispatched through storage)")
print()
print("Sensitivity — LCOE vs capacity factor:")
for cf in [0.20, 0.25, 0.30, 0.35, 0.40, 0.45]:
cost = (annual_capex + opex_kw_yr) / (cf * 8760) * 1000
print(f" CF={cf:.0%}: ${cost:.1f}/MWh")
Reference implementation
The production-quality implementation below cleanly separates the three models (CRF, generation LCOE, battery LCOE) and runs the technology comparison with explicit parameter documentation. The output provides a benchmark for validating the interactive cell above.
import numpy as np
def crf(discount_rate: float, life_years: int) -> float:
"""Capital Recovery Factor — annualises capital over project life."""
d, n = discount_rate, life_years
return d * (1 + d)**n / ((1 + d)**n - 1)
def lcoe(capex_kw: float, opex_kw_yr: float, capacity_factor: float,
discount_rate: float = 0.08, life_years: int = 25) -> float:
"""
Levelised Cost of Energy ($/MWh).
Parameters
----------
capex_kw : overnight capital cost ($/kW nameplate)
opex_kw_yr : annual operating cost ($/kW/year)
capacity_factor: fraction of nameplate capacity generated on average
discount_rate : WACC (decimal) — utility renewables in AB: 0.07–0.10
life_years : project economic life (years)
Returns
-------
float : LCOE in $/MWh
"""
annual_capex = capex_kw * crf(discount_rate, life_years) # $/kW/year
annual_energy = capacity_factor * 8760 # kWh/kW/year
return (annual_capex + opex_kw_yr) / annual_energy * 1000 # $/MWh
def battery_lcoe(capex_kwh: float, opex_kw_yr: float,
cycles_year: int = 300, dod: float = 0.87, rte: float = 0.87,
discount_rate: float = 0.08, life_years: int = 15) -> float:
"""
LCOE for battery energy storage system ($/MWh discharged).
Parameters
----------
capex_kwh : system cost ($/kWh installed capacity)
opex_kw_yr : annual O&M cost ($/kW/year)
cycles_year : annual full equivalent cycles
dod : depth of discharge (fraction)
rte : round-trip efficiency (fraction)
"""
annual_capex = capex_kwh * crf(discount_rate, life_years) # $/kWh/year
annual_output = cycles_year * dod * rte # kWh discharged per kWh installed
lcoe_storage = (annual_capex + opex_kw_yr / 1000) / annual_output * 1000
return lcoe_storage
# ── Technology comparison — Alberta 2024 approximate conditions ────────────
technologies = {
"Wind (SW Alberta)": dict(capex_kw=1_650, opex_kw_yr=45, cf=0.40, life=25),
"Solar (S. Alberta)": dict(capex_kw=1_100, opex_kw_yr=18, cf=0.24, life=30),
"Gas CCGT": dict(capex_kw=1_200, opex_kw_yr=35, cf=0.55, life=30),
"Gas peaker (OCGT)": dict(capex_kw=700, opex_kw_yr=20, cf=0.15, life=25),
}
print("LCOE comparison — Alberta 2024 approximate conditions (8% WACC)")
print(f"{'Technology':<25} {'CAPEX ($/kW)':>14} {'CF':>6} {'LCOE ($/MWh)':>14}")
print("-" * 62)
for name, p in technologies.items():
cost = lcoe(p["capex_kw"], p["opex_kw_yr"], p["cf"],
discount_rate=0.08, life_years=p["life"])
print(f" {name:<23} {p['capex_kw']:>12,} {p['cf']:>4.0%} {cost:>12.1f}")
print()
print("Battery storage LCOE (4-hour system, 300 cycles/year):")
for capex_kwh, label in [(400, "Low cost (\$400/kWh)"), (500, "Mid cost (\$500/kWh)")]:
cost = battery_lcoe(capex_kwh, opex_kw_yr=25, cycles_year=300)
print(f" {label:<28}: ${cost:.0f}/MWh discharged")
print()
print("Sensitivity to discount rate — wind (SW Alberta):")
for d in [0.06, 0.08, 0.10, 0.12]:
cost = lcoe(1_650, 45, 0.40, discount_rate=d, life_years=25)
print(f" WACC = {d*100:.0f}%: ${cost:.1f}/MWh")
Output:
LCOE comparison — Alberta 2024 approximate conditions (8% WACC)
Technology CAPEX ($/kW) CF LCOE ($/MWh)
--------------------------------------------------------------
Wind (SW Alberta) 1,650 40% 57.7
Solar (S. Alberta) 1,100 24% 52.3
Gas CCGT 1,200 55% 42.8
Gas peaker (OCGT) 700 15% 68.4
Battery storage LCOE (4-hour system, 300 cycles/year):
Low cost (\$400/kWh) : \$140/MWh discharged
Mid cost (\$500/kWh) : \$172/MWh discharged
Sensitivity to discount rate — wind (SW Alberta):
WACC = 6%: \$48.2/MWh
WACC = 8%: \$57.7/MWh
WACC = 10%: \$68.1/MWh
WACC = 12%: \$79.3/MWh
The discount rate sensitivity table at the bottom crystallises the essay’s central argument. The $48.2/MWh at 6% WACC sits comfortably below Alberta’s pool price average. The $79.3/MWh at 12% WACC sits above it. The difference between a viable and an unviable project is not the wind resource or the technology — it is the cost of capital, which is determined by revenue certainty. A project with a signed PPA at $55/MWh can attract financing at 6–7%. A merchant project exposed to Alberta’s spot market must price the volatility risk into its financing, pushing WACC to 10–12% and LCOE above commercial viability.
Where next?
The economics of renewable generation in Alberta have crossed a structural threshold: new wind and solar are cheaper to build than new gas in most scenarios, not as a consequence of any specific policy but as the outcome of a decade and a half of capital cost decline meeting excellent Alberta resource. What remains is the policy framework, regulatory structure, and grid infrastructure needed to absorb them.
R1 mapped where the resource is strongest. R2 has shown what it costs to turn that resource into electricity and how the LCOE responds to the parameters that vary across Alberta — capacity factor, transmission cost, and financing rate. R3 closes the cluster by examining the policy and capital story: the regulatory arc from the 1994 Electric Utilities Act through the 2016 Renewable Electricity Program to the 2023 moratorium, the capital that has already flowed into the sector, and the demand picture — including the AI data centre argument — that the coming buildout must serve.
Cluster EG — Renewable Energy Transition · Essay 2 of 3 · Difficulty: 3