Improving reliability of distribution networks using plug-in electric vehicles and demand response

Nowadays,utilities aim to find methods for improving the reliability of distribution systems and satisfying the customers by providing the continuity of power supply.Different methodologies exist for utilities to improve the reliability of network.In this paper,demand response(DR)programs and smart charging/discharging of plug-in electric vehicles(PEVs)are investigated for improving the reliability of radial distribution systems adopting particle swarm optimization(PSO)algorithm.Such analysis is accomplished due to the positive effects of both DR and PEVs for dealing with emerging challenges of the world such as fossil fuel reserves reduction,urban air pollution and greenhouse gas emissions.Additionally,the prioritization of DR and PEVs is presented for improving the reliability and analyzing the characteristics of distribution networks.The reliability analysis is performed in terms of loss of load expectation(LOLE)and expected energy not served(EENS)indexes,where the characteristics contain load profile,load peak,voltage profile and energy loss.Numerical simulations are accomplished to assess the effectiveness and practicality of the proposed scheme.

Multi-objective short-term scheduling of active distribution networks for benefit maximization of DisCos and DG owners considering demand response programs and energy storage system

This paper proposes a multi-objective benefit function for operation of active distribution systems considering demand response program(DRP)and energy storage system(ESS).In the active distribution system,active network management(ANM)is applied so that the distribution system equipment is controlled in real-time status based on the real-time measurements of system parameters(voltages and currents).The multi-objective optimization problem is solved using e-constraint method,and a fuzzy satisfying approach has been employed to select the best compromise solution.Two different objective functions are considered as follows:benefit maximization of distribution company(DisCo);benefit maximization of distributed generation owner(DGO).To increase the benefits and efficient implementation of distributed generation(DG),DGO has installed battery as energy storage system(ESS)in parallel with DG unit.Consequently,DGO decides for the battery charging/discharging.DisCo has the ability to exchange energy with the upstream network and DGO.Also,DisCo focuses to study the effect of demand response program(DRP)on total benefit function and consequently its influence on the load profile has been discussed.This model is successfully applied to a 33-bus radial distribution network.

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.