The methodology presented in this paper demonstrates the potential of image processing and MINLP optimization methods to evaluate rooftop solar energy potential and layout design. The results suggest that shading interactions play a critical role in the design choices of optimized layouts, particularly at locations far from the equator.
Prioritising rooftop solar can also avoid planning disputes and gradually remove the need for large greenfield schemes. The government has set a national target of 70GW of solar energy generation by 2035.
This paper describes a fully automated approach that employs 0.31 m RGB Worldview-3 satellite imagery to identify rooftops and subsequently generate complex solar panel layouts with detailed energy estimates that dynamically account for shading between panels during the optimization process.
We have published research by the UCL Energy Institute into the true potential for meeting our energy needs if we made full use of the rooftop space available for solar panels across the country.
Finally, we evaluate a few specific heuristics from the literature and propose a potential new rule of thumb that may help improve rooftop solar energy potential when shading effects are considered.
If the government fails to kickstart a rooftop solar revolution, an area of countryside larger than the size of Greater London will be required for ground-mounted schemes. CPRE’s view is that this land could be much better used for either nature recovery, public amenity or low impact food production; or a mixture of these.