| 引用本文: | 姚蓝霓,张勇军,唐渊,杨景旭,周星月.考虑响应程度反馈和昼夜充电分布的公交车站双阶段响应模型[J].电力自动化设备,2022,42(10): |
| YAO Lanni,ZHANG Yongjun,TANG Yuan,YANG Jingxu,ZHOU Xingyue.Two-stage response model of bus station considering response degree feedback and day-night charging distribution[J].Electric Power Automation Equipment,2022,42(10): |
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| 摘要: |
| 大规模电动公交车充电负荷接入电网导致负荷峰值攀升，电网安全性和经济性下降，为此提出了一种考虑响应程度反馈和昼夜充电分布的双阶段充电响应模型。建立了电动公交车双阶段充电负荷模型，基于电动公交车的排班模型确定调控时段，并将各调控时段的充电状态作为控制变量；提出了行程裕度系数的概念，将电动公交车的充电需求分配到夜间和白天，实现双阶段充电；制定了基于响应程度的削峰响应分段激励结算机制，依据响应系数将响应分为欠响应、有效响应、过响应，并通过惩罚系数和饱和系数引导公交车站实现有效响应；在此基础上，建立了电动公交车夜间-日间双阶段充电响应模型，以单位电量净支出作为指标实现公交车站效益最大化；基于粒子群优化算法，通过定义约束偏离程度函数，给出了带约束条件的优化策略。通过仿真验证了所提策略能可靠完成响应任务，电动公交车的单位电量净支出大幅下降，且电网的响应经济负担较固定激励方式更轻。 |
| 关键词: 电动公交车 需求响应 双阶段充电 激励结算 间歇补电 |
| DOI：10.16081/j.epae.202204063 |
| 分类号:U469.72 |
| 基金项目:国家自然科学基金资助项目(52177085) |
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| Two-stage response model of bus station considering response degree feedback and day-night charging distribution |
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YAO Lanni, ZHANG Yongjun, TANG Yuan, YANG Jingxu, ZHOU Xingyue
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School of Electric Power Engineering, South China University of Technology, Guangzhou 510640, China
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| Abstract: |
| The connection of large-scale electric bus charging load to the power grid leads to the increase of peak load and the decrease of power grid’s safety and economy. Therefore, a two-stage charging response model considering the response degree feedback and day-night charging distribution is proposed. A two-stage charging load model of electric buses is established, the control periods are determined based on the scheduling model of electric buses, and the charging state of each control period is taken as the control variable. The concept of travel margin coefficient is proposed, and the charging demand of electric buses is allocated between night and day to realize two-stage charging. The segmental incentive settlement mechanism of peak load shifting response based on the response degree is formulated. According to the response coefficient, the response is divided into under-response, effective response and over-response, and the bus station is guided to realize effective response through penalty coefficient and saturation coefficient. On this basis, the night-day two-stage charging response model is established, and the net expenditure per unit power is used as an index to maximize the bus station’s benefit. Based on particle swarm optimization algorithm, the optimization strategy with constraints is given by defining the constraint deviation degree function. Simulative results show that the proposed strategy can reliably complete the response task, the net expenditure per unit power of electric bus decreases significantly, and the response economic burden of the power grid is lighter than that of the fixed incentive method. |
| Key words: electric bus demand response two-stage charging incentive settlement intermittent power supply |
