A solar community meets a significant amount of its energy demand through solar energy. In a high latitude country like Finland, the seasonal mismatch of solar availability makes it very difficult to achieve high renewable energy fractions without seasonal storage. In this study, a solar community located in Finland was optimized with respect to energy demand and life cycle cost. To gain better understanding of both technical and economical scaling effects, the optimization was done separately for four cases with 50, 100, 200 and 500 buildings. The study was performed for Finnish conditions using dynamic TRNSYS simulations and optimized with a genetic algorithm, using the MOBO optimization tool. The modeled energy system had solar thermal collectors and solar electric panels for energy generation, two centralized short-term storage tanks and a seasonal borehole thermal energy storage system (BTES) for energy storage, and a ground source heat pump for additional heat generation. The larger communities provided noticeable cost-benefits when aiming for high performance. Larger seasonal storages allowed more direct utilization of seasonally stored heat, lowering the need for the heat pump and reducing electricity demand. Comparing the best and worst performing optimal energy system, annual demand for heating electricity was reduced by 80%. Renewable energy fractions close to 90% for heating were possible for all community sizes, but the large communities could obtain them with about 20% lower costs.