Research On Power System Optimal Dispatch With Wind-PV-Hydro-Storage Power Source

With the shortage of energy and environmental pollution becoming more and more serious, it is urgent to utilize renewable energy, such as wind energy, solar energy and water energy, in a large scale. The wind power generation and photovoltaic power generation is easily affected by the season, topography and climate factors and the output is random, intermittent and instability, which limits the development of wind power and photovoltaic power. In recent years, there have been a lot of researches on how to improve the utilization of renewable energy and reduce the impact of wind power and solar power’s connection to power grid.In order to reduce the intermittent, fluctuation and reduce the output fluctuation on power grid after wind power and solar power’s connection to power grid, the wind power, solar power, hydro power and pumped storage power are considered as an entire complementary generation system consisting of wind, PV, water, storage, considering the natural complementary characteristics of wind and PV, as well as the favorable adjusting performance of hydro power and pumped storage. Taking mu ltiple power constraint conditions into consideration, two optimization models are established to minimize the output fluctuation of complementary system and opti mize the same change tendency between the complementary system and predicted loads. Then the particle swarm optimization algorithm is used to solve the m odel. Simulation results show that the proposed models have a good performance in tracking the optimization target and reducing the output fluctuation on power grid after wind power and solar power’s connection to power grid.Based on the optimization result of wind-photovoltaic-hydro-storage complementary system and day-ahead predicted load, the equivalent loads are calculated. Considering power balance constraint of the system, the upper and lower output bounds of thermal power units, climbing power constraint and rotation reserve co nstraint, the day-ahead scheduling model for thermal power plant in a wind-photovoltaic-hydro-storage complementary system contained power system is established to minimize the coal consumption cost and the air pollutant emission cost. And then the genetic algorithm is used to solve this model. Simulation results show that it can reduce the impact on thermal power on the basis of full acceptance of wind power and photovoltaic power generation.Considering that the prediction accuracy of wind, PV and load increases as the time span for prediction decreases, the intraday rolling schedule is carried out to reduce the day-ahead schedule deviation resulting from the big day-ahead prediction error. The day-ahead dispatch plan is updated and corrected according to the latest forecasting information and real-time units output, which improves the accuracy of power generation plan.