Situational awareness indices of solar PV power generation under temporal weather conditions for near real-time planning and operation

Abstract

Solar photovoltaic (PV) plant development and utilization is increasing worldwide but remains intrinsically challenged by its large dependence on highly variable weather conditions and operating states. This paper presents a framework to leverage three new situational awareness indices (SAIs), namely: weather condition index (WCI) to gauge operational performance based on environmental states, operational complexity index (OCI) to indicate the severity of power generation reductions, and photovoltaic generation index (PVGI) to provide a final determination of the impact on power generation and to bolster situational awareness in planning and operational contexts for solar PV plants. This is accomplished by exploiting the effects of weather conditions, operating states, and solar PV power generation performance in high spatial-temporal resolution contexts residing in solar PV power generation data with independent fuzzy inference systems (FISs) for each index. SAIs provide additional operational insights to evaluate solar PV plant performance over both short-term (minute(s)) and long-term (24 h) time intervals in a variety of areas, including weather condition classification studies, energy dispatch controllers, and power system voltage and frequency stability assurance. The proposed SAI framework is developed, demonstrated, and evaluated for a 1MWp solar plant located in Clemson, South Carolina, USA.