Spatio-temporal modeling of roof-top photovoltaic panels for improved technical potential assessment and electricity peak load offsetting at a municipal scale
Luis Ramirez Camargo
Integrated spatial and energy planning has become a major field of interest to meet the current renewable energy share expansion and CO2 emissions reduction targets. Geographic Information Systems (GIS) play a considerable role in supporting decision making in this field. Solar potential maps are a popular strategy to promote renewable energy generation through photovoltaic (PV) panel installations at city and municipal scales. They indicate the areas of roofs that would provide the maximum amount of energy in kW h per year. These are often used to suggest “optimal locations” for PV-panels and/or recommend system sizes to achieve a certain level of yearly autarchy. This approach is acceptable if PVs have only a minor share in the local energy supply system. However, increased PV-penetration can lead to instability of the local grid, create hazards for the security of the supply, and considerably escalate the storage and system back-up requirements. To obtain a proper understanding of the consequences for the local energy balance when selecting or rejecting a certain installation, examining the hourly and intra-hourly time series of the potential energy generation from PVs is necessary. This paper introduces a GIS-based procedure to estimate the potential PV-electricity generation time series for every roof-top section within a study area using open source software. This procedure is complemented by a series of strategies to select suitable PV-installations considering the time series analysis of supply and demand. Furthermore, thirteen technical indicators are considered to evaluate the PV-installation sets selected with every strategy. The capabilities of the procedure are tested using data from a German rural municipality. The proposed procedure constitutes an efficient and accessible way to assess solar potentials at the municipal scale and to design roof-top PV exploitation plans, which are more appropriate to fulfill the local energy requirements.