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Solar energy is one of important renewable energy sources and simulation ofsolar irradiance can be used as input for simulation of photovoltaic (PV)generation. This paper proposes a simulation algorithm of multi-station solarirradiance data considering temporal correlations. First of all, we group allthe days of the observed data to k clusters for each station based on theirdaily features of solar irradiance and the daily states constitute Markov chainof days. Then, we reduce state permutations of different stations beforegetting Markov Transition Probability Matrix (MTPM). In terms of the observeddata and MTPM, the simulation approach is proposed. Finally, we test ourapproach by applying to solar irradiance data of three stations and show thatthe properties of simulated data match those of the observed data.

A Simulation Approach to Multi-station Solar Irradiance Data Considering Temporal Correlations