Power demand side management (DSM) regulations stipulate that electric power grid enterprises of cities and provinces must complete their target of power saving through efficient power plant (EPP) programs. This investigation studies power DSM and establishes a supervision and evaluation system for the EPP program. The proposed system can be used to evaluate the performance of an EPP program such as electricity saving and investment benefit. A model of EPP is established. A cuckoo search algorithm is applied for the model optimization and its result gives an optimal decision scheme. Finally, a fuzzy comprehensive evaluation method is used to assess an EPP program. The results show that the established supervision and evaluation system and the model of an EPP program are effective and applicable for power grid enterprises.

Magnetic flux leakage (MFL) inspection is one of the most important and sensitive nondestructive testing approaches. For online MFL inspection of a long-range railway track or oil pipeline, a fast and effective defect profile estimating method based on a multi-power affine projection algorithm (MAPA) is proposed, where the depth of a sampling point is related with not only the MFL signals before it, but also the ones after it, and all of the sampling points related to one point appear as serials or multi-power. Defect profile estimation has two steps: regulating a weight vector in an MAPA filter and estimating a defect profile with the MAPA filter. Both simulation and experimental data are used to test the performance of the proposed method. The results demonstrate that the proposed method exhibits high speed while maintaining the estimated profiles clearly close to the desired ones in a noisy environment, thereby meeting the demand of accurate online inspection.