Solar–Hydro Complementarity Profile

Summary

The hour-by-hour and month-by-month numbers that make Solar–Hydro Complementarity visible. Two figures should make this profile visible as time curves.

Monthly complementarity (normalised output)

Index: monthly mean = 100 for each technology at its own annual peak. Shows shape, not absolute magnitude.

Observations the numbers force:

• Solar's worst month (June/July) is hydro's best month and demand's highest month. No substitution gain here — the system is already long, and solar adds monsoon surplus that must be absorbed by dispatch management.
• Solar's best months (March/April) are hydro's second-worst months. Clean substitution gain — solar directly offsets the dry-season shortfall.
• January–February, the structural crisis months for hydro (RoR at ~30% of peak), are 75–82% of solar's peak in the Terai and 95–100% of solar's peak in Mustang. This is the single sharpest complementarity number in Nepal energy.

Month-by-month system balance (GWh, FY 2024/25 approximate)

Converting the shape into volumes, with NEA FY 2024/25 actual generation as the base:

(Numbers are illustrative, not ledger-exact; Terai 3 GW solar assumed at CF 16–18% with winter uplift, using monthly shape from table above.)

System Balance Observations

• January–February remain net-deficit even with 3 GW solar, because evening peak shifts the gap from energy to capacity. This is what Storage Deficit and Solar–Hydro Complementarity identify as the "solar closes energy gap but not evening capacity gap" problem.
• March–April nearly balance, a dramatic improvement over current state.
• Monsoon months are double-surplus. The export / demand-creation challenge (Seasonal Arbitrage Trap) intensifies as solar scales.

For the strategic argument that solar-plus-BESS should be sequenced ahead of additional RoR for the evening-peak problem, see Solar's Role in the Winter Deficit.

Diurnal complementarity — a typical winter weekday

A February Friday in Kathmandu region, demand shape from NEA Load Dispatch Center. Values normalized; evening peak = 100.

The data suggests that 4-hour BESS paired with reservoir-hydro peaking would bridge the evening gap shown in the winter diurnal profile, while additional RoR would not address the evening capacity shortfall. For the strategic argument that this combination should be prioritized over more RoR, see Solar's Role in the Winter Deficit.

Rainy-day / partial-monsoon day profile

Solar variance is the fair critique. An overcast August day in Kathmandu:

On a monsoon overcast day, hydro covers. On a winter clear-sky day, solar + BESS covers. On a winter cloudy day (rare but real), the system falls back to stored water. The three resources covering each other is the system. No single one carries the load.

Variance and forecast error

• Solar day-ahead forecast error (typical, Nepal Terai, current atmospheric model skill): ~8–12% RMS.
• Hydro day-ahead forecast error: ~3–5% (inflow is highly persistent).
• Combined system forecast error with 30% solar penetration: ~5–7% — manageable with existing dispatch.

System-operator burden grows non-linearly past ~35% solar penetration. Nepal's current ~4% solar share has enormous headroom before forecast-management becomes expensive. By the time it does, BESS deployment will have caught up.

Capacity credit

A widely misquoted number: "solar has zero capacity credit." This is misleading for Nepal specifically.

The honest read: standalone solar does not replace reservoir hydro on capacity. Solar + BESS does, roughly half, at current BESS costs. By 2030 (Solar and Hydro LCOE) the replacement is near-complete for the 4-hour evening peak window.

Coverage / Method

• Monthly shape indices: Derived from NEA FY 2024/25 system operation data (hydro output, demand) and satellite-based GHI modeling (solar). Normalized to 100 = annual peak for shape comparison.
• Volume projections (GWh): Illustrative only. Applied monthly shape indices to NEA FY 2024/25 actual generation totals, then scaled to hypothetical 3 GW Terai solar at CF 16–18% with winter uplift.
• Diurnal profile: Based on NEA Load Dispatch Center winter weekday demand shape and clear-sky solar generation model. RoR hydro assumed flat at dry-season floor.
• Capacity credit: Derived from dry-season output share and BESS discharge duration. Not from formal reliability analysis.

Caveats

• Monthly GWh numbers are illustrative projections, not ledger-exact operational data.
• Diurnal profile assumes clear-sky conditions; overcast days reduce solar contribution significantly.
• Capacity credit estimates are order-of-magnitude approximations based on seasonal output share, not formal loss-of-load-probability analysis.
• Forecast error assumptions are based on published atmospheric model skill for the Terai; actual Nepal grid-operator experience may differ.

Chart specifications

Three figures, in order of priority:

1. Monthly dual-curve — normalized hydro output vs solar (Terai) output, bar chart of demand. The core complementarity image.
2. Winter-day stacked hourly — demand (line) with hydro (filled area), solar (filled area), and BESS discharge (filled area) on a sample February day. Shows where the pieces plug in.
3. Annual volume swap — two Sankey panels showing current (hydro dominant, monsoon-surplus exported) vs 2030 (hydro + solar complementary, smaller seasonal swings).

Related

• Solar–Hydro Complementarity — the concept page this operationalises
• Nepal Peak Load Curve FY 2024/25 — the demand-side pattern
• Firm Power — the capacity-credit frame
• Seasonal Mismatch — the problem this profile solves
• Solar and Hydro LCOE — the price driving deployment
• Solar Fleet Inventory — the MW this profile applies to
• Solar's Role in the Winter Deficit — the strategic argument for solar + BESS sequencing

Sources

• WECS River Basin Plans and Hydropower Development Master Plan (2024)
• NEA Annual Report FY 2024/25
• World Bank ESMAP Nepal Solar and Wind Resource Measurement