Optimal Control Framework and Scheme for Integrating Plug-in Hybrid Electric Vehicles into Grid

Gao, Shuang; Chau, K. T.; Chan, C. C.; Liu, Chunhua; Wu, Dan

doi:10.4130/jaev.9.1473

Cited by 20 publications

(10 citation statements)

References 14 publications

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“…Some studies have been specifically reported on the impact of management of PHEVs charging on distribution system loss . It is shown that by using of managed charging policies of PHEVs it is possible to reduce distribution system power losses .…”

Section: Introductionmentioning

confidence: 99%

“…Some studies have been specifically reported on the impact of management of PHEVs charging on distribution system loss [5,11,[21][22][23]. It is shown that by using of managed charging policies of PHEVs it is possible to reduce distribution system power losses [11,[21][22][23]. In [5,11], it is shown that minimizing distribution system losses using managed charging of PHEVs has a significant advantage over minimizing the voltage impact of PHEVs integration.…”

Section: Introductionmentioning

confidence: 99%

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Energy loss minimization using PHEVs as distributed active and reactive power resources: a convex quadratic local optimal solution

Nafisi

Abyaneh

Abedi

2015

Int. Trans. Electr. Energ. Syst.

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SUMMARYPlug-in hybrid electric vehicles (PHEVs) are becoming more prevalent day by day. The batteries of these electric vehicles may be charged from a standard outlet at home. These extra electrical loads have several impacts on distribution networks, e.g. network energy loss. This paper presents a convex quadratic local optimal solution, instead of non-convex global optimal approach, to minimize the energy loss of distribution system with the different penetration levels of PHEVs. In this paper, it is assumed that vehicle owners can charge their vehicles either at workplace or at home. Furthermore, daily needed energy of PHEVs is simulated based on stochastic modeling of PHEV owners' behavior at any time. Moreover, in this paper it is supposed that PHEVs can be used as reactive power resources in vehicle to grid (V2G) operation mode. The proposed methodology is applied to a realistic distribution network. The results show that network energy loss may be remarkably increases, as the penetration of PHEVs increases without smart charging strategy. Managed and smart charging of PHEVs is needed to minimize the extent of network energy loss. As revealed by the results, smart charging of PHEVs with consideration of V2G operation mode in conjunction with charging at workplace may have the most effect on the network energy loss reduction.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Energy loss minimization using PHEVs as distributed active and reactive power resources: a convex quadratic local optimal solution

Nafisi

Abyaneh

Abedi

2015

Int. Trans. Electr. Energ. Syst.

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“…Qian et al [37] propose a charging process model which links the power of the charger and SoC. Gao et al [38] link the SoC and the charging time. Different authors use the specific EV charging profile of a real EV.…”

Section: Battery and Charging Processmentioning

confidence: 99%

Probabilistic Agent-Based Model of Electric Vehicle Charging Demand to Analyse the Impact on Distribution Networks

et al. 2015

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Electric Vehicles (EVs) have seen significant growth in sales recently and it is not clear how power systems will support the charging of a great number of vehicles. This paper proposes a methodology which allows the aggregated EV charging demand to be determined. The methodology applied to obtain the model is based on an agent-based approach to calculate the EV charging demand in a certain area. This model simulates each EV driver to consider its EV model characteristics, mobility needs, and charging processes required to reach its destination. This methodology also permits to consider social and economic variables. Furthermore, the model is stochastic, in order to consider the random pattern of some variables. The model is applied to Barcelona's (Spain) mobility pattern and uses the 37-node IEEE test feeder adapted to common distribution grid characteristics from Barcelona. The corresponding grid impact is analyzed in terms of voltage drop and four charging strategies are compared. The case study indicates that the variability in scenarios without control is relevant, but not in scenarios with control. Moreover, the voltages do not reach the minimum voltage allowed, but the MV/LV substations could exceed their capacities. Finally, it is determined that all EVs can charge during the valley without any Energies 2015, 8 4161 negative effect on the distribution grid. In conclusion, it is determined that the methodology presented allows the EV charging demand to be calculated, considering different variables, to obtain better accuracy in the results.

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“…When a large number of PEVs are 263 integrated into the grid, the total charging demand constitutes a 264 significant load which does not only increase the existing peak 265 load demand, but may also introduce new peaks to the daily 266 load profile [37]. DR and smart charging can play a major role 267 in mitigating the effect of the increasing adoption of PEVs in 268 households on the grid by providing proper incentives for shift-269 ing the charging times of PEVs.…”

mentioning

confidence: 99%

“…DR and smart charging can play a major role 267 in mitigating the effect of the increasing adoption of PEVs in 268 households on the grid by providing proper incentives for shift-269 ing the charging times of PEVs. This control mechanism can 270 reduce supply and customer side cost and enhance power sys-271 tem operating conditions [37]. Several studies have examined 272 various aspects for PEVs charging scheduling in [21, [38][39][40][41].…”

mentioning

confidence: 99%

Reputation-based joint scheduling of households appliances and storage in a microgrid with a shared battery

AlSkaif

Luna

Zapata

et al. 2017

Energy and Buildings

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Due to the decreasing revenues from the surplus renewable energy injected into the grid, mechanisms promoting self-consumption of this energy are becoming increasingly important. Demand Response (DR) and local storage are among the widely used mechanisms for reaching higher self-consumption levels. Deploying a shared storage unit in a residential microgrid is an alternative scenario that allows households to store their surplus renewable energy for a later use. However, this creates some challenges in managing the battery and the available energy resource in a fair way. In this paper, a reputation-based centralized Energy Management System (EMS) is proposed to deal with these issues by considering households' reputations in the reallocation of available energy in the shared storage unit. This framework is used in an optimization problem, in which the EMS jointly schedules households' appliances power consumption and the energy that each household can receive from the storage unit. The scheduling problem is formulated as a Mixed Integer Linear Programming (MILP) with the objective of minimizing the amount and price of energy absorbed from the main grid. The MILP problem is coded in GAMS and solved using CPLEX. Numerical analysis is conducted using real data of renewable energy production and appliances' demand profiles for different classes of households and different annual periods in Spain. Simulation results of the different scenarios show that by using the proposed framework higher cost savings can be achieved, in comparison with the classical scheduling scenario. The saving can reach up to 68% when different classes of households exist in the microgrid. The results also show that the fairness in energy allocation is guaranteed by the reputation-based policy, and that the total power absorbed from the main grid by the whole microgrid is significantly decreased.

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Optimal Control Framework and Scheme for Integrating Plug-in Hybrid Electric Vehicles into Grid

Abstract: With the growing plug-in hybrid electric vehicles (PHEVs)

Cited by 20 publications

References 14 publications

Energy loss minimization using PHEVs as distributed active and reactive power resources: a convex quadratic local optimal solution

Energy loss minimization using PHEVs as distributed active and reactive power resources: a convex quadratic local optimal solution

Probabilistic Agent-Based Model of Electric Vehicle Charging Demand to Analyse the Impact on Distribution Networks

Reputation-based joint scheduling of households appliances and storage in a microgrid with a shared battery

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