Solar energy (SE), either via PV or concentrating solar power, has a great impact on the current energy market. The SE availability, stability, and associated energy storage capacity for meeting the continuous demand (constant or varying) becomes a very important issue. It is proposed that through a good planning of energy collection and storage, a continued power supply can be made possible. Assuming SE being the only energy supply and the sky cover condition in a long period being predictable from statistics, the needed energy inventory (stored) to meet the consumption can then be predicted for a given area of solar field. It requires to determine the minimum required solar field (SFAmr) for solar energy collection when it is available in order to provide energy demand when solar energy is not available or insufficient. We developed an algorithm that uses the year-round SE forecasting of 10 years of a location of interest along with an assumed load in order to decide the needed energy storage capacity (ESC). The obtained results include the SFAmr that can meet the energy demand under the specified conditions, and also the required ESC. It is observed that a start date of operation of the energy storage system (ESS) may affect the SFAmr. The algorithm can also combine solar and wind energy for better energy collection and storage. The predictions can find a map of locations showing the feasibility of fully relying on renewable energy as a non-interrupted power supply with the help of energy storage.