Efficient emergency material dispatch, amid the aftermath of an event, can help control spread disaster and reduce losses. Herewith, we propose a model with urgency demand as target coefficient, minimum load time transportation cost total cost. For this model, improved particle swarm optimization (PSO) algorithm is proposed means to optimize initial positions particles good point sets improve c...

In most power system studies, a major part of the problem is the finding of the voltages needed to meet a given schedule of loads and generation. Until now, iteration methods have been used to calculate the respective load flows. This paper presents a study to compare Newton method and sparse matrices with artificial neural networks regarding a load flow problem in electric distribution lines. ...

Prediction of peak loads in Iran up to year 2011 is discussed using the Radial Basis Function Networks (RBFNs). In this study, total system load forecast reflecting the current and future trends is carried out for global grid of Iran. Predictions were done for target years 2007 to 2011 respectively. Unlike short-term load forecasting, long-term load forecasting is mainly affected by economy...

Against the background of carbon neutrality, power dispatching operation mode has undergone great changes. It not only gradually realizes coordinated control source–grid–load–storage, but also strives to realize multi-level coordination transmission network, distribution network and microgrid. Disorderly charging discharging large-scale electric vehicles (EVs) will have a negative impact on agg...

Emission of greenhouse gases and depletion of fossil fuel reserves are two key drivers, which are forcing the mankind to generate the future energy demand from the renewable energy resources. These resources are generally distributed in nature and are directly integrated at distribution levels. Increasing penetration of the distributed energy resources in distribution power networks creates add...

Bus dispatching has been studied, and also the bus dispatching model is set up. Then, Genetic Algorithm is adaptively improved in order to avoid premature problem and the slow convergence, and then the keeping optimal strategy is used to the Genetic Algorithm, so formed the Improved Adaptive Genetic Algorithm,namely IAGA. Finally, the IAGA is used to optimizing the bus dispatching model, and th...