Economic Planning of Energy System Equipment

The asset wall (AW) model is widely used by energy companies to forecast the retirement size of equipment. AW a method arranging historical data in chronological order and then using extrapolation predict trends volumes over time. However, most studies treat all equipment as whole perform flat mechanically, ignoring impact technological improvements price fluctuations. Furthermore, there are relatively few on assetization replacement scale. This paper fits Weibull distribution density function uses Monte Carlo stochastic simulation determine age each piece equipment, reducing ambiguity randomness generated approach treating whole. modified noted this Weibull–Monte (WMCAW). investigated size, comparing three error indicators Mean Absolute Error (MAE), Percentage (MAPE), Root Square (RMSE) select appropriate optimization for forecasting from several combinations models. Finally, verified feasibility WMCAW various types decommissioned 1970 compared effects WMCAW. It found that curve scale predicted smoother than AW, results more stable scientific.