A flat rate feed-in tariff (FiT) is a traditional incentive offered by many utilities around the world to encourage their customers to invest in electricity generation from renewable sources such as rooftop photovoltaic systems (RPVs). It is designed by financial techniques that mostly consider the initial capital cost and electricity spot price. However, such an incentive cannot help the utilities to address the technical challenges in networks with large renewable penetration. In this paper, a dynamic FiT is designed based on the value of electricity, hosting capacity, ambient temperature, and time of day (ToD). The developed method uses fuzzy logic to convert these parameters into a time-varying FiT. This FiT will specifically support utilities that experience challenges in the electrification of remote areas or observe excessive stress on their networks at demand peak periods. The proposed FiT encourages the rural customers to install RPVs while discouraging the urban customers from installing RPVs without battery storages. The performance of the developed FiT is validated numerically and its capability is evaluated by analyzing the annual revenue, net present value, and payback periods.