摘要
针对灰色GM(1,1)模型用于电力负荷短期预测不能有效反映负荷周期性变化及精度不高的问题,将GM(1,1)模型推广为GM(1,1,λ)模型,并用遗传算法求解λ的最佳值,同时将该模型应用于河南某电网未来24h负荷实际预测。结果表明,基于遗传算法的GM(1,1,λ)模型具有较高的预测精度,预测效果显著。
Directing against problems of using grey model GM(1,1) based on genetic algorithm in electric load prediction for a short term, namely it can't effectively reflect periodic variation of the load, and hasn't high accuracy of the load prediction, the model GM(1,1) has been extended as a model GM(1,1,λ), and the solution of optimal value λ being found by the genetic algorithm, at the same time, the said model having been used in one power gride of Henan Province for practical prediction of load in 24h of the future. Result shows, the model (1,1,λ) based on genetic algorithm to have higher accuracy of load prediction, effectiveness of prediction being obvious.
出处
《热力发电》
CAS
北大核心
2005年第12期17-19,共3页
Thermal Power Generation
