A Review on Plug-in Electric Vehicles:Introduction, Current Status, and Load Modeling Techniques

Plug-in electric vehicle(PEV) load modeling is very important in the operation and planning studies of modern power system nowadays. Several parameters and considerations should be taken into account in PEV load modeling, making it a complex problem that should be solved using appropriate techniques. Different techniques have been introduced for PEV load modeling and each of them has individual specifications and features. In this paper, the most popular techniques for PEV load modeling are reviewed and their capabilities are evaluated. Both deterministic and probabilistic methods are investigated and some practical and theoretical hints are presented. Moreover, the characteristics of all techniques are compared with each other and suitable methods for unique applications are proposed. Finally, some potential research areas are presented for future works.

Real-time Energy Management of Grid-connected Microgrid with Flexible and Delay-tolerant Loads

For optimal operation of microgrids,energy management is indispensable to reduce the operation cost and the emission of conventional units.The goals can be impeded by several factors including uncertainties of market price,renewable generation,and loads.Real-time energy management system(EMS)can effectively address uncertainties due to the online information of market price,renewable generation,and loads.However,some issues arise in real-time EMS as batterylimited energy levels.In this paper,Lyapunov optimization is used to minimize the operation cost of the microgrid and the emission of conventional units.Therefore,the problem is multiobjective and a Pareto front is derived to compromise between the operation cost and the emission.With a modified IEEE 33-bus distribution system,general algebraic modeling system(GAMS)is utilized for implementing the proposed EMS on two case studies to verify its applicability.

Energy Exchange Control in Multiple Microgrids with Transactive Energy Management

In recent years,the advent of microgrids with numerous renewable energy sources has created some fundamental challenges in the control,coordination,and management of energy trading between microgrids and the power grid.To respond to these challenges,some techniques such as the transactive energy(TE)technology are proposed to control energy sharing.Therefore,this paper uses TE technology for energy exchange control among the microgrids,and applies three operation cases for analyzing the energy trading control of four and ten microgrids with the aim of minimizing the energy cost of each microgrid,respectively.In this regard,Monte Carlo simulation and fast forward selection(FFS)methods are respectively exerted for scenario generation and reduction in uncertainty modeling process.The first case is assumed that all microgrids can only receive energy from the network and do not have any connection with each other.In order to maximize the energy cost saving of each microgrid,the second case is proposed to provide a positive percentage of cost saving for microgrids.All microgrids can also trade energy with each other to get the most benefit by reducing the dependency on the main grid.The third case is similar to the second case,but its target is to indicate the scalability of the models based on the proposed TE technology by considering ten commercial microgrids.Finally,the simulation results indicate that microgrids can achieve the positive amount of cost saving in the second and third cases.In addition,the total energy cost of microgrids has been reduced in comparison with the first case.