Distributed generation hosting capacity analysis: An approach using interval-affine arithmetic and power flow sensitivities

The climate change concerns, the decarbonization policies, and the technological advances allied to cost reduction form a set of favorable circumstances for large deployment of renewable-based distributed generation into the power distribution systems. However, the connection of distributed generation significantly affects the power system and its technical impacts must be evaluated. Therefore, the hosting capacity analysis has gained attention as it outputs the maximum amount of distributed generation that can be safely connected. The deterministic and stochastic methods are commonly found in the literature. However, there is a lack of hosting capacity studies based on interval analysis. Therefore, this paper proposes an interval/affine arithmetic-based hosting capacity framework, considering two performance indexes (overvoltage and ampacity), and uses a different approach for modeling generation and load curves as a finite set of correlated affine combinations. The proposed framework enables faster analysis and outputs results that are comparable to the ones from time series simulation. The proposed method also allows less conservative results, depending on the desired level of overvoltage or overload risk.