Research On Economic Dispatching Of Power System Containing Wind Power Fields And Photoltaic Power Stations

The construction of large-scale wind power fields, photovoltaic power stations greatly improve the utilization of clean energy, but the randomness and volatility also brought many new problems to the grid system. In order to reduce the impact of wind power fields and photovoltaic power stations after the output power grid fluctuations. Researching the large-scale economic dispatch of power system, under the premise ensure the safe and stable operation of the system, considering the system in various constraint conditions, make the system required the best economic benefits, is a hot pot of the research contentFirstly, this paper based on analysis the characteristics of wind and solar energy about the intermittency and volatility, so adopts the chance constrained programming theory, established two grid power system scheduling models including wind power fields and photovoltaic power stations, the system’s total power purchase cost minimum as the target model. The objective function has three parts about the thermal power unit operation cost, environmental punishment cost, wind power and photovoltaic power purchase cost, the other objective function including the amount of coal consumption, pollution emissions and so on. Then, for characteristics about intermittency and volatility of wind fields and photovoltaic power stations output, constraints such as spinning reserve capacity and climbing ability, taking into account the balance between supply and demand of the power system. Synthetically considering various constraints, scheduling scheme to obtain different confidence level, to discuss the model of environmental economic relations.Because the model contains multiple random variables, this paper uses the genetic algorithm based on Monte-Carlo simulation technique, directly solution the grid system included the wind power fields, photovoltaic power stations with optimized scheduling model scenery. The method can better describe the random variables, with the objective functions and constraint conditions. Through the analysis of experimental results show that the model can better balance of various benefits to achieve the optimal.