Smart management of distinct plug-in hybrid electric vehicle charging stations considering mobility pattern and site characteristics

Abstract

Summary Management of plug‐in hybrid electric vehicles (PHEVs) is an important alternative energy solution to accord the prevailing environmental depletion. However, adding PHEVs to the existing distribution network may stimulate issues such as increase in peak load, power loss, and voltage deviation. Addressing the aforementioned issues by incorporating distinct mobility patterns together will develop an attractive energy management. In this paper, suitable location of the charging station is presented for a novel 2‐area distribution system following distinct mobility patterns. A comprehensive study by considering the optimal, midst, and unfit site for placing the charging station is incorporated. For managing the charging sequence of PHEVs, a meta‐heuristic solving tool is developed. The main contribution of this programming model is its ability to schedule the vehicles simultaneously in both the areas. The efficiency of the proposed energy management framework is evaluated on the IEEE 33‐bus and IEEE 69‐bus distribution systems. The test system is subjected to different scenarios for demonstrating the superior performance of the proposed solving tool in satisfying the convenience of vehicle owner along with reducing the peak demand. The results show that charging at low electricity price period and discharging at high electricity price period enables the minimum operational cost.

Smart utilization of renewable energy sources in a microgrid system integrated with plug-in hybrid electric vehicles

“…11 Uncontrolled charging/discharging 12 and minimum power loss strategies have been compared to show the benefits of managed applications of PHEVs. An investigation has been done to evaluate 3 scheduling methods for PHEVs in distribution network.…”

“…A commercial mobility pattern is defined for the vehicles with morning arrival and evening departure c. A mixed mobility pattern is defined for the vehicles with random arrival and departure time A group of works have been conducted by considering the above patterns separately in their case studies. 11,25 However, this paper considers all mobility patterns together. This is achieved by dividing the single distribution system into 3 zones, assigning a specific mobility pattern each as detailed in Table 1.…”

“…An investigation has been done to evaluate 3 scheduling methods for PHEVs in distribution network. 11 Uncontrolled charging/discharging 12 and minimum power loss strategies have been compared to show the benefits of managed applications of PHEVs. An investigation of single smart home is attempted to improve variance of the household load using 2 personal PHEVs driven by residents.…”

Bidding for Preferred Timing: An Auction Design for Electric Vehicle Charging Station Scheduling

“…U pdate f inal state and join round t; 12: end for 13: Aucti oneer : update isT erminated and do round t; 14: if (isT erminated) then break; 15: end if 16:…”

A Deploying Method for Predicting the Size and Optimizing the Location of an Electric Vehicle Charging Stations

“…Ge [35] proposed a model to solve the sizing and locating problem for charging stations of electric vehicles based on grid partition, which is also solved by the genetic algorithm. Suganya [36] developed two modes of random distribution and centralized distribution, which considers the electric vehicle charging load. It is pointed out that the system will display different voltage characteristics when the electric vehicle charging load is connected to different nodes.…”