Wenqian Yin , Kun Zhuang , Pengcheng Fan , Zhengyang Sun , Jing Zhu , Jilei Ye
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引用次数: 0
摘要
随着极端寒冷事件发生频率的增加,由于对温度敏感的电动汽车负载的变化,集成电动汽车(EV)的电力系统将不断面临资源不足的挑战。尽管电动汽车负载具有提供紧急需求响应(DR)以应对此类挑战的潜力,但电动汽车响应 DR 的意愿和实际响应量并不确定。此外,电动汽车响应的不确定性水平随 DR 激励决策的变化而变化,这进一步加剧了运营挑战。本文针对电动汽车集成电力系统提出了一种抗极端寒冷事件的弹性单位承诺(UC)模型。具体来说,首先,考虑到电动汽车的实际行驶里程和空调负荷,我们模拟了对温度敏感的电动汽车充电负荷在极寒事件下的变化情况。然后,对电动汽车响应量的不确定性与 DR 激励决策之间的相互耦合关系进行建模。为了克服与决策无关的不确定性的传统建模方法的局限性,我们提出了一种基于仿射函数的可处理电动汽车响应中与决策有关的不确定性(DDU)的模型重构方法。随后,我们在两阶段随机框架内建立了弹性统一通信模型,其中考虑了对温度敏感的电动汽车负载和电动汽车响应行为中的 DDU。通过对修改后的 IEEE 30 总线系统进行案例研究,验证了所提出的统一通信模型在极端寒冷事件下经济、可靠地适应增加的电动汽车负载方面的有效性。
Resilient unit commitment against extreme cold events considering decision-dependent uncertainty-featured EV demand response
With the escalating frequency of extreme cold events, power systems integrating electric vehicles (EVs) will continually confront resource inadequacy challenges due to the changes of temperature-sensitive EV loads. Despite the potential of EV loads offering emergency demand response (DR) for addressing such challenges, the willingness of EVs to respond to DR and the actual response quantity are uncertain. Furthermore, the uncertainty level in EV response varies along with DR incentive decisions, which further aggravates operation challenges. This paper proposes a resilient unit commitment (UC) model for EV-integrated power systems against extreme cold events. Specifically, first, we model how the temperature-sensitive EV charging loads change under extreme cold events considering the actual driving range and air conditioning load in EVs. Then, the inter-coupling relationship between uncertainties in EV response quantity and the DR incentive decisions is modeled. To overcome the limitations of conventional modeling approaches for decision-independent uncertainty, an affine function-based tractable model reformulation is presented addressing decision-dependent uncertainty (DDU) in EV response. Subsequently, we establish the resilient UC model within a two-stage stochastic framework considering temperature-sensitive EV loads and DDU in EVs’ response behaviors. Case studies on a modified IEEE 30-bus system verify the effectiveness of the proposed UC model in cost-efficiently and reliably accommodating increased EV loads under extreme cold events.
期刊介绍:
The journal covers theoretical developments in electrical power and energy systems and their applications. The coverage embraces: generation and network planning; reliability; long and short term operation; expert systems; neural networks; object oriented systems; system control centres; database and information systems; stock and parameter estimation; system security and adequacy; network theory, modelling and computation; small and large system dynamics; dynamic model identification; on-line control including load and switching control; protection; distribution systems; energy economics; impact of non-conventional systems; and man-machine interfaces.
As well as original research papers, the journal publishes short contributions, book reviews and conference reports. All papers are peer-reviewed by at least two referees.