According to the US Energy and Information Administration, between 2022-2023 60% of planned new electricity generation consists of solar farms with a battery energy storage system . The demand for these paired systems has increased since batteries can be charged during the day with the energy captured from the solar farm then released to the customer in the evening during peak energy demand. This achieves peak load shaving which reduces the cost of electricity for the customer and is ecologically friendly. This thesis aims to create an efficient solar farm with a battery energy storage system for a farmer in California that achieves peak load shaving. Full cell modules and half-cell modules were explored to determine the type that best suits this project. The half-cell modules were best suited because of the increased efficiency. Six different solar farm designs were created, four fixed tilt designs and two single axis tracking designs. Two types of software, System Advisor Model (SAM) and REopt, were compared to determine which would be most useful in simulating these designs. It was concluded that System Advisor Model (SAM) would be the most accurate to simulate the six designs and produce metrics such as the annual energy production, capacity factor, DC to AC ratio, and levelized cost of energy. The final design, design 6, a 2-string single axis tracking design produced the best metrics that met the project requirements and a battery energy storage system was sized for the design.