Assessing the Economic Value for Grid Operators of Quantified Smoothing Effects from PV Systems with Varying Orientations

As the number of solar photovoltaic (PV) installations grows rapidly, accurate registry data and efficient use of existing grid capacity are increasingly critical for stable and cost-effective distribution grid operation, as well as for enabling further PV deployment without unnecessary physical grid reinforcement. This study employs an innovative remote sensing method that combines aerial imagery, machine learning, and Light Detection and Ranging (LiDAR) data to identify, validate, and simulate PV power generation. The method can detect discrepancies between grid operator registries and actual PV installations and quantify the orientation-based smoothing effects that arise when distributed PV systems have varying azimuths and tilt angles. By accounting for these effects, it can free up significant existing capacity in low-voltage distribution grids, reducing the need for costly reinforcements. Application of the method in three Swedish low-voltage grids demonstrated tangible economic benefits, with planned investments of 400,000 (~€36k) and 1.5 million SEK (~€136k) avoided. The study evaluates the value creation of inventory-based PV mapping and PV orientation smoothing effect analysis from the perspective of grid operators, highlighting the method’s potential as a cost-effective, data-driven tool for grid planning, investment prioritization, and integration of distributed PV power generation.