For the correction problem of day-ahead plan deviation caused by energy prediction deviation in day-ahead scheduling stage of photovoltaic greenhouses, an exergy analysis method is used to propose the deviation model of heat required for photovoltaic greenhouses. Based on the deviation model, a real-time optimization scheduling model is established. The deviation model not only considers the non-negligible exergy loss during heating process of pipes, but also considers the difference between heat and thermal exergy affected by the actual indoor temperature. The goal of the real-time scheduling model is to minimize the absolute value of the difference between the energy supply and demand prediction deviation to be corrected and the adjustment of multi-form energy storage and electric loads, so that develop the real-time adjustment plan of energy storage and electric loads. The analysis results of the actual photovoltaic greenhouse show that of the heat required by a greenhouse based on the exergy theory calculation, the exergy loss of the heating process accounts for about 10%–20% of the total thermal exergy required and it cannot be ignored, so the calculation results can reflect the actual heat required more accurately and the greenhouse temperature is more suitable for plant growth. Moreover, the proposed real-time scheduling model can correct the deviation of the day-ahead plan and improve local consumption. The promotion ratio can reach 7%. Finally, the farmers’ electricity purchases cost is reduced. Thereby the effectiveness of the proposed heat deviation model and real-time scheduling model is verified.

To analyze quantitatively the voltage beyond limits of power system including wind farms, based on the establishment of probabilistic model of wind generation output and load, proposes a model of probabilistic evaluation to voltage beyond limits of power system taking account of zero output state of wind power farm. Considers the state of zero power output of WPG to be an incident, which occurs with a given probabilistic, with computational tools based on probabilistic load flow of cumulant method, calculate the conditional probabilistic to voltage beyond limits of system under a single incident occurred, then obtain the probabilistic to voltage beyond limits of system according to total probability formula. Example of IEEE30 system calculates the probabilistic to voltage beyond limits of system under the zero output states of wind farms at different nodes, analyzes the impact on the probabilistic to voltage beyond limits of system coused by every wind farm by sorting. Simulation results shows that the model and algorithm can provide a reference for the operation department. Keywords-stochastic model; cumulant method; zero output state of wind power farm; probabilistic to voltage beyond limits