Sustainable development and mitigation of climate change have become essential and indispensable parts of energy policies at all stages (analysis, planning, production…). Today, energy accounts for two-thirds of total greenhouse gases emissions, therefore, efforts in this sector are of major importance to reduce the global impacts. This can be accomplished through the use of distributed generation to meet the increased demand. Distributed generation includes on-site renewables such as solar or wind power. The optimal integration of these sources in the network requires optimization models to accurately locate and size them based on needs. This paper proposes to use dynamic optimal power flow (OPF) modeling to localize and size the Photovoltaic (PV) production sources and storage batteries (SB) needed on an over-solicited grid by additional demand, in a spatial-temporal framework. To do so, while respecting the different constraints (solar local resources, cost analysis…), a linear optimization is performed to minimize the production costs and to define the optimal installed surface of PV to maximize the individual load factor of each PV, while respecting all the network’s constraints.