A Bifacial Photovoltaic Energy Yield Model with 3D Shading: Development, Validation, and Applications in Tracked and Mid-to-High Latitude Systems

Abstract

As of 2030, bifacial photovoltaic (PV) modules – which collect light on both the front and rear sides – are predicted to make up 60% of annual global PV expansion, exceeding 375 GW of installed capacity per year. Therefore, accurate and accessible bifacial PV performance models are crucial in enabling rapid global PV expansion. This thesis proposes a highly-parameterized, physics-based bifacial PV performance model that: (a) reduces uncertainty with respect to two-dimensional (2D) view factor models by eliminating key user-defined loss parameters, and (b) achieves greater computational efficiency than a ray tracing approach. The model computes shade-inclusive 2D front and rear irradiance profiles which interface with a cell-to-array level electrical model, producing per-timestamp current-voltage curves. A validation against measured power in fixed-tilt and single- axis tracked systems demonstrates a mean absolute error in modelled hourly power of 14.2 mW and 17.3 mW per watt of installed capacity, for each system respectively. Due to its flexible parameterization, the model can be used to both predict and better understand PV system performance. To exemplify such use cases, this thesis includes a chapter on the energy yield impact of three physical effects in tracked bifacial PV, namely: (1) brightening at the edges of a row of PV modules, (2) angle of incidence losses in light reflected off of supportive racking, and (3) the addition of a secondary tracking axis in double-axis tracked bifacial modules. A subsequent chapter discusses the model’s applicability in emerging PV markets at mid-to-high latitude locations, presenting another three studies on the energy yield impact of: (1) time-varying air mass, (2) latitude-dependent row spacing, and (3) ground accumulated snow. Such studies contribute to the global effort to reduce bifacial PV energy yield modelling uncertainty in both established and emerging markets and to de-risk bifacial PV investment around the world.