Flexibility in plug-in electric vehicle(PEV) charging can reduce the ancillary cost effects of wind variability and uncertainty on electric power systems. In this paper, we study these benefits of PEV charging, demons...Flexibility in plug-in electric vehicle(PEV) charging can reduce the ancillary cost effects of wind variability and uncertainty on electric power systems. In this paper, we study these benefits of PEV charging, demonstrating that controlled PEV charging can reduce costs associated with wind uncertainty and variability. Interestingly, we show that the system does not require complete control of PEV-charging loads to mitigate the negative cost impacts of wind variability and uncertainty. Rather, PEV owners giving the system a two-hour window of flexibility in which to recharge their vehicles provides much of the benefits that giving full charging control does.展开更多
Global warming and climate change are two key probing issues in the present context.The electricity sector and transportation sector are two principle entities propelling both these issues.Emissions from these two sec...Global warming and climate change are two key probing issues in the present context.The electricity sector and transportation sector are two principle entities propelling both these issues.Emissions from these two sectors can be offset by switching to greener ways of transportation through the electric vehicle (EV) and renewable energy technologies (RET).Thus,effective scheduling of both resources holds the key to sustainable practice.This paper presents a scheduling scenario-based approach in the smart grid.Problem formulation with dual objective function including both emissions and cost is developed for conventional unit commitment with EV and RET deployment.In this work,the scheduling and commitment problem is solved using the fireworks algorithm which mimics explosion of fireworks in the sky to define search space and the distance between associated sparks to evaluate global minimum.Further,binary coded fireworks algorithm is developed for the proposed scheduling problem in the smart grid.Thereafter,possible scenarios inconventional as well as smart grid are put forward.Following that,the proposed methodology is simulated using a test system with thermal generators.展开更多
基金financially supported by the National Science Foundation(No.1548015)
文摘Flexibility in plug-in electric vehicle(PEV) charging can reduce the ancillary cost effects of wind variability and uncertainty on electric power systems. In this paper, we study these benefits of PEV charging, demonstrating that controlled PEV charging can reduce costs associated with wind uncertainty and variability. Interestingly, we show that the system does not require complete control of PEV-charging loads to mitigate the negative cost impacts of wind variability and uncertainty. Rather, PEV owners giving the system a two-hour window of flexibility in which to recharge their vehicles provides much of the benefits that giving full charging control does.
文摘Global warming and climate change are two key probing issues in the present context.The electricity sector and transportation sector are two principle entities propelling both these issues.Emissions from these two sectors can be offset by switching to greener ways of transportation through the electric vehicle (EV) and renewable energy technologies (RET).Thus,effective scheduling of both resources holds the key to sustainable practice.This paper presents a scheduling scenario-based approach in the smart grid.Problem formulation with dual objective function including both emissions and cost is developed for conventional unit commitment with EV and RET deployment.In this work,the scheduling and commitment problem is solved using the fireworks algorithm which mimics explosion of fireworks in the sky to define search space and the distance between associated sparks to evaluate global minimum.Further,binary coded fireworks algorithm is developed for the proposed scheduling problem in the smart grid.Thereafter,possible scenarios inconventional as well as smart grid are put forward.Following that,the proposed methodology is simulated using a test system with thermal generators.
