Presence Of Plug-in Hybrid Electric Vehicles Research Articles

A DAG-based cloud-fog layer architecture for distributed energy management in smart power grids in the presence of PHEVs

• New framework based on the directed acyclic graph and distributed multi-layer cloud-fog computing. • Finding a solution for the optimal energy management of the smart grids. • Considering a machine learning algorithm to solve augmented Lagrangian function in each agent. In this paper, a new framework based on the directed acyclic graph (DAG) and distributed multi-layer cloud-fog computing to find the optimal energy management of the smart grids, considering high penetration of plug-in hybrid electric vehicles (PHEVs). The presented distributed structure lets neighboring agents make a consensus together. The uncertainties have been modeled according to the Monte Carlo simulations, due to wide usages of diverse renewable energy resources such as photovoltaic panels and wind turbines. Three diverse charging schemes have been considered in the smart grid test system which contains controlled, uncontrolled and smart chargings. The Whale Optimization Algorithm (WOA) has been used to solve the augmented Lagrangian function in each agent. The simulation results are shown that the suggested scheme is effective.

Dynamic performance enhancement of interconnected hybrid thermal power system in the presence of electric vehicles

The prolific integration of non-synchronous distributed energy resources and energy storage systems (EES) into thermal-dominated grids significantly impact the power system's total synchronous inertia (TSI). The TSI, in turn, affects the frequency response of the electrical grid (EG). Although the EES supports frequency regulation, the cost is a vital factor in determining their role. Lately, it is realized that incorporating plug-in hybrid electric vehicles (PHEVs) as auxiliary power sources can provide inertial support if penetrated in huge numbers into the EG. This work proposes a supply and demand variation approach that integrates EVs in load frequency control (LFC). The proposed LFC uses the biogeography-based optimization (BBO) algorithm. A parallel direct current (DC)-alternating current (AC) interconnected hybrid thermal power system (IHTPS) with different types of high voltage direct current (HVDC) tie-links in the presence of PHEVs is simulated. The settling time, oscillations, and first peaks are mainly analyzed for the considered HVDC tie-links. The results show that the virtual synchronous power-HVDC tie-link offers better dynamic performance than that of the other tie-link, proving EV's presence in improving the frequency response. Thus, the investigation demonstrates the BBO based LFC role in enhancing the dynamic performance of the IHTPS.

Robust optimization of micro-grids operation problem in the presence of electric vehicles

The main objective of this paper is to optimally formulate Microgrid (MG) operation problem in a robust manner. Increasing importance of environmental issues such as Greenhouse Gases (GHGs) emissions leads to the widely use of Plug-in Hybrid Electric Vehicles (PHEVs) in recent years. The high integration of PHEVs in distribution networks may affect the operation of MGs due to their uncertain behaviors. Therefore, the uncertainties of input parameters are successfully considered in the model development. The proposed model is, therefore, a decision-making process of the MG operation in the presence of PHEVs that addresses solution robustness as well as model robustness, which is absent in the literature. The effectiveness of the model is demonstrated through a numerical example and the broad sensitivity analysis is finally done to prove the model robustness and the solution robustness.

Low-Voltage Transformer Loss-of-Life Assessments for a High Penetration of Plug-In Hybrid Electric Vehicles (PHEVs)

In the coming years, plug-in hybrid electric vehicles (PHEVs) will strongly penetrate the French car fleet. Their impact on each element of the electric distribution grid needs to be estimated. In this paper, the impact of PHEVs on the life duration of the medium-voltage/low-voltage (LV) transformer using a thermal model to estimate the hot-spot temperature is studied. Based on probabilistic algorithms, three penetration rates of PHEVs are studied. A stochastic method is applied to construct domestic daily load profiles of houses constituting an LV residential electric grid supplied by the transformer. Correlated with the initial load rate (without PHEVs) of the transformer, two indices are proposed; the DTR_PHEV_X and VTR_PHEV_X to calculate, respectively, the life duration and aging rate of transformer in the presence of PHEVs. It is shown that the aging rate of the transformer is quadratic in the presence of PHEVs.

Plug-in Hybrid Electric Vehicles in the Smart Grid Environment: An Economic Model of Load Management by Demand Response

Environmental concern regarding the consumption of fossil fuels is among the most serious challenges facing the world. As a result, utilisation of more renewable resources and promotion of a clean transport system such as the use of Plug in Hybrid Electric Vehicles (PHEVs) became the forefront of the new energy policies. However, the breakthrough of PHEVs in the automotive fleet increases concerns around the stability of power system and in particular, the power network. This research simulates the aggregate load profile of the UK with presence of PHEVs based upon different price scenarios. The results show that under the fixed rate and time of use programmes in the current grid, the extra load of the electric vehicles intensifies the consumption profile and also creates new critical points. Thus, there should always be excess standby capacity to satisfy peak demand even for a short period of time. On the other hand, when the consumers do not pay the price based on the actual cost of supply, those who consume less in peak hours subsidise the ones who consume more and this cross subsidy raises a regulatory issue. On the contrary, a smart grid can accommodate PHEVs without creating technical and regulatory problems. This positive consequence is the result of demand response to the real time pricing. From a technical point of view, the biggest chunk of PHEVs' load will be shifted to the late evening and the hours of minimum demand. Besides, from a welfare analysis standpoint, real time pricing creates no deadweight losses and corresponding demand response will limit the ability of suppliers to increase the spot market clearing price above its equilibrium level.