Application of rough sets theory in forecast of power generation for grid-connected photovoltaic system

With photovoltaic technology development and application of the expansion of photovoltaic, the accuracy of power generation forecast will directly affect the grid load frequency, grid stability, system reliability, power quality, investment and the system operating efficiency. The short-term forecasting research of photovoltaic power generation will help to stabilize power system operation, to optimize grid dispatching and to provide effective protection for the distribution load management. The rough sets theory was first proposed to the forecast of photovoltaic power generation and given the forecast mathematical models in this paper. The redundant attribute was removed from the decision table with the attribute reduction algorithm of Pawlak attribute importance. The continuous attributes of PV systems is discrete by the improved greedy algorithm. Results comparison of actual operation data and the simulation of week, month, season and year shows that rough sets forecast models is more correct and accuracy.