Profitability Optimization of Photovoltaic Storage Systems Using Simulation of Hourly Production and Load Profiles and a Total Cash Flow Model

Abstract

Photovoltaic (PV) systems are increasingly popular in Germany due to high electricity prices and decreasing costs of PV components. Self-generation of electricity becomes attractive, but excess energy production fed into the grid is less valuable due to low feed-in tariff. Adding battery storage can increase self-consumption, reducing both grid dependency and minimizing excess production. However, profitability depends on the cost-benefit ratio of batteries, influenced by the hourly electricity consumption profile and seasonal efficiency of production.
A new method using a simulation framework is introduced to assess the profitability of PV systems and optimal battery sizes. This combines hourly weather data from a typical meteorological year (TMY) with hourly electricity consumption profiles to simulate generation, storage, and grid dependency. The resulting data informs financial cash flow plans and delivers profitability indicators based on system design and size. This approach improves traditional methods by employing high-resolution hourly data for precise battery and PV sizing to maximize returns. Instead of the usual Net Present Value (NPV), the method uses Final Asset Value (FAV) for its insights into parameter development over an investment's lifespan.
A case study of a farming enterprise in Saxony-Anhalt, which already operates a profitable PV system, demonstrates the new method's application. An investment in additional battery storage is considered, and the battery capacity (kWh) is optimized.