Explore the vast range of titles available.

Considering the widespread use of PHEVs in advanced societies and the issues ahead, researchers’ thinking has focused more on this issue. The important issue is that the use of EVs is increasing due to the advantages, but the necessary infrastructure for their charging stations in the distribution networks does not exist. The high penetration level of EVs can create a potential risk for the existing distribution network; the fair charging of EVs has a special value. This paper presents a new model for the fair charging management of EVs at the medium voltage level of a distribution network equipped with dispatchable and non-dispatchable distributed generation (DG) resources. A fuzzy controller is used to adjust the charging rate of EVs within the permissible periods for charging stations, At the same time, the voltage control and reactive power management tool is also available for the distribution network operator through DG resources that can be dispatched, such as diesel generators. Numerical studies are used on a 25-bus IEEE test distribution system in the presence and absence of DG resources. The simulation results show that the presence of DG resources and voltage control and reactive power management at the different buses along the feeder causes a larger number of electric vehicles in different charging stations of the distribution network can be provided their consumption energy from network. In addition, the time difference for EV charging is minimized, and only the number of EVs that can be charged at the various stations will be different. Volt/Var control tools through DSO cause an increase in the number of charged EVs at various stations.

This paper presents a unit commitment formulation for micro-grid that includes a significant number of grid parallel Proton Exchange Membrane-Fuel Cell Power Plants (PEM-FCPPs) with ramping rate and minimum up/down time constraints. The aim of this problem is to determine the optimum size of energy storage like battery storages and use the efficient hydrogen and thermal energy storages and to schedule the committed units' output power while satisfying practical constraints and electrical/thermal load demand over one day with 15 min time step. In order to best use of multiple PEM-FCPPs, hydrogen storage management is carried out. Also, since the electrical and heat load demand are not synchronised, it could be useful to store the extra heat of PEM-FCPPs in the peak electrical load in order to satisfy delayed heat demands. Due to uncertainty nature of electrical/thermal load, photovoltaic and wind turbine output power and market price, a two-stage scenario-based stochastic programming model, where the first stage prescribes the here-and-now variables and the second stage determines the optima value of wait-and-see variables under cost minimization is implemented. For solving the problem, a new enhanced cuckoo optimisation algorithm is presented and successfully applied to two typical micro-grids. Quantitative results show its usefulness.