Application of Spark Chain Network and Random Forest Algorithm in Electric Energy System Dispatching
In order to provide strong data support for energy dispatching through accurate power system load forecasting and re-duce execution time,the application of spark chain network and random forest algorithm in electric energy system dispatching is studied.The spark chain network and random forest algorithm are used to predict the short-term load and long-term load of the power system,respectively.Taking the long-term and short-term total load balance of the system,the output of conventional units and line power flow as constraints,a electric power new energy scheduling model is constructed,and the demodulation degree model is calculated based on ant colony algorithm to realize the optimal scheduling of the power energy system.The ex-perimental results show that the short-term load forecasting error of this method is less than 3.19％,the long-term load fore-casting curve is almost consistent with the actual load curve,and the error is not more than 50 kW,which can accurately pre-dict the short-term and long-term load of power energy.The scheduling execution time of this method is less than 38 005.5 s,which effectively reduces the time of executing scheduling tasks.
electric energyenergy dispatchingrandom forestload forecasting
万方数据
维普
