Urban-scale distributed power generation – Forecast methods for the estimation of electricity exchange profiles for grid-connected solar photovoltaic (PV) systems

Photovoltaic powered distributed generation (PV-DG) is increasingly being embedded into electricity distribution networks worldwide with fast penetration rates. Among various elements which can limit a substantial dissemination of the PV-DG, one is the paucity of reliable forecasting methods for estimating production and exchange profiles of non-programmable sources with particular reference to solar photovoltaic generators. In facts, forecasting PV power allows to optimize user's energy management, for example scheduling electric loads and operating energy storages. Thus, the presented research work has been focused on the development of a methodology aimed at forecasting the electricity exchange of grid-connected PV systems up to 48 hours ahead. Different forecast techniques have been analyzed and, subsequently, a methodology based on physical models is proposed and tested on a real case study, represented by a residential nearly zero energy building (NZEB) equipped with an electric ground source heat pump (GSHP) and demand-side management solutions