A framework for regional smart energy planning using volunteered geographic information

摘要

Abstract. This study presents a framework for regional smart energyplanning for the optimal location and sizing of small hybrid systems. Byusing an optimization model – in combination with weather data – variouslocal energy systems are simulated using the Calliope and PyPSA energysystem simulation tools. The optimization and simulation models are fed withGIS data from different volunteered geographic information projects,including OpenStreetMap. These allow automatic allocation of specific demandprofiles to diverse OpenStreetMap building categories. Moreover, based onthe characteristics of the OpenStreetMap data, a set of possible distributedenergy resources, including renewables and fossil-fueled generators, isdefined for each building category. The optimization model can be appliedfor a set of scenarios based on different assumptions on electricity pricesand technologies. Moreover, to assess the impact of the scenarios on thecurrent distribution infrastructure, a simulation model of the low- andmedium-voltage network is conducted. Finally, to facilitate theirdissemination, the results of the simulation are stored in a PostgreSQLdatabase, before they are delivered by a RESTful Laravel Server anddisplayed in an angular web application.