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Research Article

Optimal charging of electric vehicles for cost minimization in re-configurable active distribution network considering conservation voltage reduction

ORCID Icon, ORCID Icon & ORCID Icon
Pages 10135-10155 | Received 26 Apr 2022, Accepted 17 Oct 2022, Published online: 11 Nov 2022
 

ABSTRACT

This paper presents a coordinated plug-in electric vehicle (PEV) charging scheme in the presence of conservation voltage reduction (CVR) with a possibility of network re-configuration in a half-hourly based tariff environment. The information of the arrived PEVs in time slot “t” are gathered in a centralized manner, including initial and desired state of charge (SOC), rating of PEV charger, and arrival and departure times. In addition, the load forecasted data of all the nodes are also collected. A linear programming (LP) based intelligent charging framework is developed whereby an optimal global solution for EV charging is obtained that tends to minimize the charging cost, and the schedule is dispatched to all the PEVs. At first, PEV charging cost is minimized using the existing time of use (TOU) based tariff structure. After that, the charging schedule is carried out under the same TOU tariff structure but on a re-configured network with and without CVR deployment. The proposed charging strategy through re-configuration of the distribution network under CVR is implemented on a modified IEEE-33 bus test system. The results obtained from the simulation show that the proposed PEV charging scheme through network re-configuration under a TOU-based tariff structure considerably reduces the charging cost by 55.8% compared to uncoordinated charging. However, a 50.2% cost reduction is achieved in the absence of network re-configuration. Therefore, the proposed PEV charging through network re-configuration under a TOU-based tariff is more effective in cost reduction. Further, investigations were carried out on EV charging through network re-configuration under TOU-based tariff and CVR deployment. It was observed that the PEV charging cost was reduced by 51.3% compared to uncoordinated charging, where higher cost benefits were obtained through the reduction in energy consumed by constant impedance loads. It has been further observed that the proposed scheme effectively flattens the load profile by clipping the peak and filling the valley load.

Nomenclature

Symbol=

Description

X+tn=

Charging rate of nth PEV in tth time interval

Xtn=

Discharging rate of nth PEV in tth time interval

Ct=

Cost of energy in tthtime interval

LET=

Energy throughput of the battery

Lc=

Charge/discharge cycle life of the battery

E=

Energy stored in the battery

DOD=

Depth of discharge of battery at specified Lc

cbat=

Capital cost of the battery

cdn=

Battery degradation cost of nth PEV

nth PEV=

X+maxn:Maximum charging rate of

Xmaxn=

Maximum discharging rate of nth PEV

Ta=

Arrival time of PEV

Td=

Indicated departure time of PEV

SOCn=

State of Charge of the battery of nth PEV

SOCminn=

Minimum allowable SOC of the battery of nth PEV

SOCmaxn=

Maximum allowable SOC of the battery of nth PEV

SOCdn=

Indicated SOC as desired by the PEV owner

SOCin=

Initial SOC of the battery of nth PEV at the time of plug-in

ηchargingn=

Charging efficiency of nth PEV charger

ηdischargingn=

Discharging efficiency of nth PEV charger

Vti=

Voltage at ithbus in tth time instant

Vmini=

Minimum voltage limit at ithbus

Vmaxi=

Maximum voltage limit at ithbus

ECVRoff=

Energy consumed by the loads without CVR

VCVRoff=

System voltage without CVR

ECVRon=

Energy consumed by the loads with CVR

VCVRon=

System voltage with CVR

Zp=

Constant impedance coefficient of ZIP load model

Ip=

Constant current coefficient of ZIP load model

Pp=

Constant power coefficient of ZIP load model

P=

Power consumed by the load at operating system voltage V

P0=

Power consumed by the load at nominal system voltage V0

V=

Operating system voltage

V0=

Nominal system voltage

Author contributions

The authors confirm their contributions to the paper as follows: study conception and design: Shailendra Singh, Akhilesh K. Barnwal; analysis and interpretation of results: Shailendra Singh, Mitresh K. Verma; draft manuscript preparation: Shailendra Singh, Akhilesh K. Barnwal, Mitresh K. Verma. All authors reviewed the results and approved the final version of the manuscript.

Disclosure statement

No potential conflict of interest was reported by the author(s).

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