Optimal temporal-spatial PEV chargingscheduling in active power distributionnetworks

Siyang Sun; Qiang Yang; Wenjun Yan

doi:10.1186/s41601-017-0065-x

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Optimal temporal-spatial PEV chargingscheduling in active power distributionnetworks

Contents | 更新时间：2026-06-25

- Optimal temporal-spatial PEV chargingscheduling in active power distributionnetworks
- Protection and Control of Modern Power Systems Vol. 2, Issue 4, (2017)
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- DOI：10.1186/s41601-017-0065-x
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- Published：2017
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Siyang Sun, Qiang Yang, Wenjun Yan. Optimal temporal-spatial PEV chargingscheduling in active power distributionnetworks[J]. Protection and Control of Modern Power Systems, 2017, 2(4).
DOI：

Siyang Sun, Qiang Yang, Wenjun Yan. Optimal temporal-spatial PEV chargingscheduling in active power distributionnetworks[J]. Protection and Control of Modern Power Systems, 2017, 2(4). DOI： 10.1186/s41601-017-0065-x.

摘要

Background: The increasing penetration of a massive number of plug-in electric vehicles (PEVs) and distributed generators (DGs) into current power distribution networks imposes obvious challenges on power distribution network operation. Methods: This paper presents an optimal temporal-spatial scheduling strategy of PEV charging demand in the presence of DGs. The solution is designed to ensure the reliable and secure operation of the active power distribution networks

the randomness introduced by PEVs and DGs can be managed through the appropriate scheduling of the PEV charging demand

as the PEVs can be considered as mobile energy storage units. Results: As a result

the charging demands of PEVs are optimally scheduled temporally and spatially

which can improve the DG utilization efficiency as well as reduce the charging cost under real-time pricing (RTP). Conclusions: The proposed scheduling strategy is evaluated through a series of simulations and the numerical results demonstrate the effectiveness and the benefits of the proposed solution.

Abstract

the randomness introduced by PEVs and DGs can be managed through the appropriate scheduling of the PEV charging demand

as the PEVs can be considered as mobile energy storage units. Results: As a result

the charging demands of PEVs are optimally scheduled temporally and spatially

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