Two-Stage Fuzzy Logic Inference Algorithm for Maximizing the Quality of Performance under the Operational Constraints of Power Grid in Electric Vehicle Parking Lots

Hussain, Shahid; Lee, Ki-Beom; Ahmed, Mohamed A.; Hayes, Barry; Kim, Young-Chon

doi:10.3390/en13184634

Cited by 35 publications

(20 citation statements)

References 52 publications

(79 reference statements)

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“…The trajectory and demand allocation have been considered decision variables for the least-cost routing of vehicular traffic and the optimal sizing of the charging station. In [24], the path of vehicles is considered based on realistic trip patterns; however, considering a rigid trip pattern reduces much of the size of the analysis space, i.e., a starting and ending point is considered, reducing the sample size where multiple users participating in the road network can recharge their batteries. Therefore, this article studies the most significant vehicular density that a zone could experience to give the necessary resources for CS distributed in the study and to guarantee the possibility of recharging users who use the road network.…”

Section: Ev Charging Station Infrastructurementioning

confidence: 99%

Optimal Sizing of Electric Vehicle Charging Stations Considering Urban Traffic Flow for Smart Cities

2021

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Achieving high penetration of electric vehicles (EVs) is one of the objectives proposed by the scientific community to mitigate the negative environmental impact caused by conventional mobility. The limited autonomy and the excessive time to recharge the battery discourage the final consumer from opting for new environmentally friendly mobility alternatives. Consequently, it is essential to provide the urban road network with charging infrastructure (CI) to ensure that the demand generated by EV users is met. The types of terminals to be considered in charging stations (CS) are fast and ultra-fast. The high energy requirements in these types of terminals could stress the electrical systems, reducing the quality of service. To size and forecast the resources needed in CI, it is of great interest to model and predict the maximum number of EVs, in each hour, that each CS will have to serve according to the geographic area in which they are located. Our proposal is not based on an assumed number of vehicles to be served by each CS, but rather it is based on the analysis of vehicular traffic in geo-referenced areas, so that the load managers can design the topology of the CS. The maximum vehicular concentration is determined by some considerations such as the road system, direction of the route, length of the road segment, the intersections, and the economic zone to which it belongs. The topology of the road map is freely extracted from OpenStreetMap to know the latitude and longitude coordinates. Vehicular traffic will be modeled through the topology obtained from OpenStreetMap and other microscopic variables to understand the traffic engineering constraints. In addition, the Hungarian algorithm is used as a minimum cost decision tool to allocate demand to the CS by observing vehicular traffic as a cost variable. The multi commodity flow problem (MCFP) algorithm aims to make commodities flow through the road network with the minimum cost without exceeding the capacities of the road sections. Therefore, it is proposed to solve the transportation problem by directing the vehicular flow to the CS while minimizing the travel time. This situation will contribute significantly to the design of the topology of each CS, which will be studied in future research.

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Section: Ev Charging Station Infrastructurementioning

confidence: 99%

Optimal Sizing of Electric Vehicle Charging Stations Considering Urban Traffic Flow for Smart Cities

2021

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“…Consider manipulator dynamics (1) with Property 1, 2 and impedance dynamics (3). If the finitetime command filter and the error compensation mechanism are chosen as ( 7), (12), and the adaptive FLS control law ( 16) with updating laws ( 17)-( 19) are chosen, the tracking error z 1 converges to a small enough region with the radius max c/a, 2(c/2b)…”

Section: Stability Analysismentioning

confidence: 99%

“…During the past years, many research results show that fuzzy logic control plays a significant role in estimating the dynamic model of complex nonlinear systems [11], [12], and various impedance control approaches based on the adaptive control [13], [14] and fuzzy logic control [15]- [17] have been proposed for uncertain manipulators. Among these works, an impedance sliding mode control with adaptive fuzzy compensation scheme was proposed in [15] which employing adaptive fuzzy to estimate uncertain model.…”

Section: Introductionmentioning

confidence: 99%

Adaptive Fuzzy Finite-Time Command Filtered Impedance Control for Robotic Manipulators

Lin

Liu

2021

IEEE Access

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In order to improve the security and compliance of physical human-robot interaction (pHRI), an adaptive fuzzy impedance control for robotic manipulators based on finite-time command filtered method is proposed in this paper. Firstly, robots usually encounter system uncertainties in practical applications, and the adaptive fuzzy control is introduced to approximate the system uncertainties. Secondly, the finite-time control method is used to improve the interaction performance of the system. Then, the command filtered control technique is used to deal with the "computational complexity " of traditional backstepping. Finally, simulations are conducted to illustrate the effectiveness of the proposed control method in physical human-robot interaction.

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“…This will encourage a change in the demand based on the price signals [5]. There are multiple issues connected with the integration of Distributed Resources (DRs) into the system: The challenges of charging and discharging electric vehicles [6], finding an appropriate optimization technique in wind farms [7], finding an adequate optimization technique in EVs [2] or coordination of wind energy and pumped storage power plants [8]. Contracting strategies of renewable sources and hybrid power sources are strongly investigated in the research [9].…”

Section: Literature Reviewmentioning

confidence: 99%

“…In the case of variability of renewable energy sources the operator has no possibility to store energy generated simultaneously, whereas in the case of EVs it is possible to manage the load on the level of particular facility or a group of facilities. An example of EVs facility management is presented in [2]. The operation of energy storage and the demand response may be planned and executed with high certainty.…”

Section: Introductionmentioning

confidence: 99%

Advanced Flexibility Market for System Services Based on TSO–DSO Coordination and Usage of Distributed Resources

Niewiadomski

Baczynska

2021

Energies

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The high and growing share of renewable sources and the more important role of Distributed Energy Resources (DERs) in the Distribution System (DS) is leading to a need for more efficient coordination of those sources. In future power systems, TSO–DSO coordination will play a key role in providing flexibility services. Lack of proper coordination of sources may lead to congestion in the network or to a lack of possibility to generate or consume energy on a requested level. The crucial aspect is that the TSO–DSO coordination must be based on an active role of all participants: TSO, DSO, generation units and the demand. This paper presents the possible application of the TSO–DSO coordination by providing the flexibility services from DS to the Transmission System (TS). The paper presents the complex optimization of TS, DS and its coordination. The main goal of the paper is to show the possibility of the application of the flexibility market into the current system design. It requires the creation of a new platform, where the offers of the flexibility services could be submitted and then exchanged between entities. The paper shows that the usage of flexibility services may decrease the operational cost of the system, and the DERs providing those services may benefit from an additional source of income.

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Two-Stage Fuzzy Logic Inference Algorithm for Maximizing the Quality of Performance under the Operational Constraints of Power Grid in Electric Vehicle Parking Lots

Cited by 35 publications

References 52 publications

Optimal Sizing of Electric Vehicle Charging Stations Considering Urban Traffic Flow for Smart Cities

Optimal Sizing of Electric Vehicle Charging Stations Considering Urban Traffic Flow for Smart Cities

Adaptive Fuzzy Finite-Time Command Filtered Impedance Control for Robotic Manipulators

Advanced Flexibility Market for System Services Based on TSO–DSO Coordination and Usage of Distributed Resources

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