Unit Commitment Considering Large-scale Integration of Electric Vehicles

Chen Jing-hua; Ding Lin-jun; Guo Zhuang-zhi; Liang Li-li; Li Jin-bei

doi:10.12052/gdutxb.160084

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Unit Commitment Considering Large-scale Integration of Electric Vehicles

更新时间：2026-05-27

- Unit Commitment Considering Large-scale Integration of Electric Vehicles
- Vol. 34, Issue 2, Pages: 63-68(2017)
- 作者机构：
- 作者简介：
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- DOI：10.12052/gdutxb.160084
  CLC： TM731
- Online First：09 March 2017，
  
  Published：2017
- 稿件说明：
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陈璟华, 丁林军, 郭壮志, 粱丽丽, 李锦焙. 计及电动汽车规模化入网的电力系统机组组合优化[J]. 广东工业大学学报, 2017, 34(2): 63-68.

Chen Jing-hua, Ding Lin-jun, Guo Zhuang-zhi, et al. Unit Commitment Considering Large-scale Integration of Electric Vehicles[J]. 2017, 34(2): 63-68.
陈璟华, 丁林军, 郭壮志, 粱丽丽, 李锦焙. 计及电动汽车规模化入网的电力系统机组组合优化[J]. 广东工业大学学报, 2017, 34(2): 63-68. DOI： 10.12052/gdutxb.160084.

Chen Jing-hua, Ding Lin-jun, Guo Zhuang-zhi, et al. Unit Commitment Considering Large-scale Integration of Electric Vehicles[J]. 2017, 34(2): 63-68. DOI： 10.12052/gdutxb.160084.

摘要

针对混合电动汽车（Hybird Electric Vehicle，HEV）规模化接入电力系统后的机组组合优化进行了研究.把各个时段内HEVs充放电数量和火电机组出力作为可优化调度变量，以火电机组的燃煤费用最小为目标函数，利用互补约束和最优化极值理论，将机组组合问题转化为连续空间的非线性规划，构建了计及HEVs规模化入网的电力系统机组组合互补约束优化模型.进而采用光滑NCP函数对建立的互补约束优化模型进行光滑处理，将其转化为一般的非线性规划问题，利用原对偶内点法进行求解.以10机组系统24 h内的机组最优组合为算例进行仿真实验，验证了所提算法的有效性和可行性.

Abstract

Research is conducted on the unit commitment optimization after HEVs mass connected to the power system. HEVs charge and discharge quantity and thermal power unit output in each period are used as optimizable scheduling variables and the coal-fired minimum cost of thermal power generating unit as the objective function. And under the use of complementary constraints and optimization extreme value theory

transforming unit combination problem into nonlinear programming for continuous space

a complementary constraint optimization model of power system unit combining HEVs mass into the network is established. Then the smooth NCP function is used to deal with the complementary constraint optimization model

which is transformed into a general nonlinear programming problem

and the solution is solved by using the primal dual interior point method. A simulation experiment is carried out with the optimal combination of the units in the 10 unit system 24 h as an example to verify the validity and feasibility of the proposed algorithm.

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references

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