Shading Analysis

Quick Facts

What is Shading Analysis?

Shading analysis is the engineering process of identifying and quantifying solar irradiance loss caused by obstructions. It informs system design, financial projections, and customer expectations.

Categories

• Near shading: Objects close enough to cast detailed shadows, trees, RTUs, chimneys, parapets, antenna masts, dormers.
• Far shading: Horizon-level obstructions, mountains, distant buildings, ridgelines.
• Self-shading: Between rows on ground-mount arrays; between roof planes; carport columns.

Output metrics

• TSRF (%): Total Solar Resource Fraction. 100% = unshaded.
• Annual shade loss (%): Equivalent energy loss.
• Per-module shade heat map: Annual hours shaded per module.

Methods

LIDAR-based (Aurora)

LIDAR data + satellite imagery → 3D site model → sun-path trace from each module location → annual shade hours.

Voxel-based (Helioscope)

Site polygon + obstructions → 3D model → voxel-by-voxel sun-path computation.

Single-diode electrical (PVsyst)

Site model + module I-V characteristics + bypass diode activation → time-step electrical shading effects. For ground-mount arrays, PVsyst’s 3D near-shading scene builder walks through constructing the obstruction scene before running the electrical shading calculation.

Handheld measurement

Solar Pathfinder, SunEye 210, Solmetric, used during site survey to confirm shading at each panel location.

Engineering Deep Dive

Bypass diode behavior

In a 60-cell module, 3 bypass diodes protect 20-cell groups. Shading one cell deactivates that 20-cell group (one-third of module output).

Practical implication: even small shadows on monofacial string-inverter systems can cause disproportionate losses without MLPE.

MLPE mitigation

Microinverter per module: each module runs at its own MPP. Shading isolates to the shaded module(s) only. DC optimizer: each optimizer maintains MPP per module, with the string operating at the parallel-combined MPP at the inverter.

Tree growth projection

For 25-year design life, project tree height at year 10-15. Aurora’s growth model: 0.5-2 ft/yr depending on species.

Worked Example, Residential

A San Diego rooftop with 14 modules. Aurora analysis:

• TSRF = 82% (3 modules with > 15% annual shade).
• Removing 3 shaded modules: TSRF = 95%, total production +6%.
• Adding microinverter to existing string-inverter design: TSRF effectively 92% (shaded modules contribute their reduced output without dragging the string).

Best Practices

• Run shading analysis during site survey, not after design.
• Use LIDAR or photogrammetry; manual tree-height estimation under-counts.
• Apply tree-growth projection for at least 10 years.
• Choose MLPE for shaded sites (TSRF < 90%).
• Validate software shading against on-site measurements for high-value projects.

Common Mistakes

1. Skipping shading analysis on apparently unobstructed sites.
2. Ignoring tree growth over project lifetime.
3. Assuming string inverter sufficient on shaded rooftops.
4. Using outdated LIDAR (new construction not captured).
5. Treating partial cell shading as proportional yield loss.

Standards & Certifications

• NREL Total Solar Resource Fraction methodology.
• IEC 61853-3, Energy rating including shading.

Key Takeaways

• Shading analysis quantifies annual yield loss from obstructions using sun-path geometry.
• TSRF (Total Solar Resource Fraction) is the standard metric; ≥ 75% residential, ≥ 85% commercial.
• Bypass diodes cause disproportionate losses on shaded strings; MLPE mitigates.
• LIDAR + 3D modeling (Aurora, Helioscope, PVsyst) is the standard analysis approach.
• Always project tree growth for 10-25 years.

Related Reading

Choosing a shading engine matters as much as running the study: our 8,760-hour benchmark of solar shading analysis software compares how Aurora, Helioscope, and PVsyst handle the near-shading and bypass-diode scenarios described above. On tracker projects, self-shading is usually designed out rather than measured after the fact, see how the backtracking algorithm for solar trackers keeps row-to-row shadows off adjacent rows through the day.

Because unresolved shading loss shows up directly as yield uncertainty in financing, it’s worth reading how shading assumptions flow into P50/P90/P99 solar yield reports that lenders rely on. For a second opinion on tooling, SurgePV’s shadow analysis software and Qbits Energy’s shading analysis software guide are worth comparing against the workflow covered here.

3D tools such as SketchUp are also used for early shade studies on residential sites.

Disclosure: Qbits Energy and SurgePV are Heaven Designs group companies.