Scenario Generation of Annual PV and Load Correlated Time Series Considering Meteorological Influences

An accurate annual photovoltaic (PV) and load time series is essential for the assessment of PV accommodation capacity. This paper proposes a scenario generation model for annual correlated time series of PV output and load, incorporating meteorological factors. First, weather types are classified based on the clearness index and solar irradiance fluctuation indicators, and daily PV output time series models are constructed for different weather types. Second, based on load decomposition, temperature-sensitive load components are analyzed in terms of temperature characteristics, and a daily load time series model is developed based on temperature characteristic coefficients. Next, a joint probability distribution model of meteorological factors, based on the clearness index and temperature, is constructed using Copula function. On the basis of a weather-type Markov chain, an annual meteorological scenario is generated, considering meteorological correlations, and corresponding annual PV and load time series are produced. Case study results demonstrate that the series generated by the proposed model accurately simulate the statistical and temporal characteristics of PV output and load, while correctly capturing the correlation between the series.