An optimal dispatching strategy for a multi-source complementary power generation system taking source–load uncertainty into account is proposed, in order to address the effects of large-scale intermittent renewable energy consumption and load instability on grid dispatching. The problem first converted common situations study, such as forecasting solar wind power. backward scenario reduction L...

With the expansion of power grid scale and deepening component coupling, operation behavior system becomes more complex, traditional function decoupling dispatching architecture is not available anymore. Firstly, this paper studies corresponding relationship between reinforcement learning method decision problem, constructs artificial intelligent knowledge model based on (AIDLM). Then, a data-d...

Wafer fabrication is a capital-intensive high-tech sector with highly complex manufacturing processes. Therefore, most of the fabs resort to production dispatching as a means to enhancing production efficiency. The commonly seen methods of production dispatching at the present time are devised to meet single performance indicators. Few methods take into account multiple, or even conflicting per...

By analyzing a large of history data and predicting load variance trend of host, We can offer the important basis to load balance and decide load balance strategy for effective load balance. However most load prediction re-search focus on flow prediction of the network or load prediction algorithm it-self used classical time series prediction method, usually it is ignored on load balance after ...

Real-time vehicle dispatching operations in traditional car-sharing systems is an already computationally challenging scheduling problem. Electrification only exacerbates the computational difficulties as charge level constraints come into play. To overcome this complexity, we employ online minimum drift plus penalty (MDPP) approach for SAEV that (i) does not require a priori knowledge of custo...

Review and classification of electric load forecasting (LF) techniques based on artificial neuralnetworks (ANN) is presented. A basic ANNs architectures used in LF reviewed. A wide range of ANNoriented applications for forecasting are given in the literature. These are classified into five groups:(1) ANNs in short-term LF, (2) ANNs in mid-term LF, (3) ANNs in long-term LF, (4) Hybrid ANNs inLF,...

transmission network expansion planning (tnep) is an important component of power system planning. itdetermines the characteristics and performance of the future electric power network and influences the powersystem operation directly. different methods have been proposed for the solution of the static transmissionnetwork expansion planning (stnep) problem till now. but in all of them, stnep pr...