Inertia monitoring and forecasting with deeppenetration of photovoltaic source. A case studyof the Republic of Mauritius power grid

This paper aims at monitoring and forecasting the system inertia for the Republic of Mauritius power grid based on a novel stochastic dynamic grid model under an extreme weather event. As the island has set the target of connecting 60% of photovoltaic source to the network by 2030 as a measure to reduce carbon emissions, it is expected that the grid inertia to reduce, leading to unstable conditions. Accordingly, we use the Auto Regressive Integrated Moving Average forecasting method to study the inertia behavior. We demonstrate this method by using an IEEE 9-bus for our study. The percentage of penetration of the photovoltaic source is set at 60% and we forecast the inertia for a period of 5 hours under a rainy period. Our findings establish a minimum power generation to maintain stability, below which operators are required to connect other generating sources in the mix to avoid peak shaving. With this research, utilities can anticipate future disturbances.