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Stochastic Operation of Multi-Terminal Soft Open Points in Distribution Networks With Distributionally Robust Chance-Constrained Optimization 配电网络中多终端软开路点的随机运行与分布稳健的偶然性约束优化
IF 8.6 1区 工程技术 Q1 ENERGY & FUELS Pub Date : 2024-07-22 DOI: 10.1109/TSTE.2024.3431616
Changhee Han;Ramesh R. Rao;Seokheon Cho
To achieve flexible operation of modern distribution networks with increasing renewable energy sources (RESs), this study proposes a stochastic operation method for a novel energy management platform that combines energy storage with a power flow controller, which is presented as a multi-terminal soft open point (MT-SOP). A Wasserstein metric-based distributionally robust chance-constrained optimization for the operation of the MT-SOP is proposed under the assumption that there is no prior knowledge about the distribution of forecast errors for both the load and RES outputs. The proposed method stochastically relaxes the reliability constraints on the bus voltage and branch power flow to maximize the cost-benefit of the distribution system operator (DSO). The proposed problem was reformulated into a tractable convex program using the concept of conditional value-at-risk. Based on case studies using modified IEEE-33 systems, the trade-offs between operational risks and cost–benefits were analyzed using parameters on the risk level and radius of the ambiguity set. Through numerical comparisons of the simulation results, we show that the DSO can achieve economic efficiency for imported electricity by relaxing conservativeness in distribution network reliability.
为了实现可再生能源不断增加的现代配电网的灵活运行,本研究提出了一种将储能与潮流控制器相结合的新型能量管理平台的随机运行方法,该平台以多终端软开点(MT-SOP)的形式呈现。在负荷和RES输出预测误差分布不存在先验知识的前提下,提出了一种基于Wasserstein度量的MT-SOP运行分布鲁棒机会约束优化方法。该方法通过随机放宽对母线电压和支路潮流的可靠性约束,使配电系统运营商的成本效益最大化。利用条件风险值的概念,将该问题重新表述为一个可处理的凸规划。基于使用改进的IEEE-33系统的案例研究,使用风险水平和模糊集半径参数分析了操作风险和成本效益之间的权衡。通过对仿真结果的数值比较,表明分布式存储系统可以通过放宽配电网可靠性的保守性来达到进口电力的经济效益。
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引用次数: 0
Resilience Improving Strategy for Power Systems With High Wind Power Penetration Against Uncertain Attacks 提高风电渗透率高的电力系统应对不确定攻击的复原力策略
IF 8.6 1区 工程技术 Q1 ENERGY & FUELS Pub Date : 2024-07-19 DOI: 10.1109/TSTE.2024.3430844
Min Du;Jinning Zhang;Chenghong Gu;Xin Zhang
This paper aims to produce a practical and efficient decision for the system operator to harden critical components in power systems with high wind power penetration against uncertain attacks. Thus, an adjustable robust tri-level defender-attacker-defender (ART-DAD) model is proposed to improve the resilience of power systems by hardening critical transmission lines. The proposed ART-DAD model considers both uncertain attacks and uncertain wind power output, which provides meaningful insights into the resilience improvement of power systems that involve uncertainties. More specifically, the proposed defense model integrates dynamic N-K criterion for attack budgets and the polyhedral uncertainty set for wind power output to develop resilient line hardening strategies. The proposed defense model can be formulated as a mixed integer tri-level programming problem that is decoupled into a master and sub-problem. Then, a constraint-generation based solution algorithm is proposed to solve the overall ART-DAD model with a master and sub-problem scheme. Simulation results on IEEE RTS-79 and RTS-96 systems validate the effectiveness of the proposed resilience improving strategy.
本文旨在为系统运营商提供一个实用高效的决策,以加固风电渗透率高的电力系统中的关键组件,抵御不确定的攻击。因此,本文提出了一个可调整的鲁棒三层防御-攻击-防御(ART-DAD)模型,通过加固关键输电线路来提高电力系统的抗灾能力。所提出的 ART-DAD 模型同时考虑了不确定的攻击和不确定的风电输出,为涉及不确定因素的电力系统弹性改进提供了有意义的见解。更具体地说,所提出的防御模型综合了攻击预算的动态 N-K 准则和风电输出的多面体不确定性集,从而制定出有弹性的线路加固策略。所提出的防御模型可表述为一个混合整数三级编程问题,该问题被解耦为主问题和子问题。然后,提出了一种基于约束生成的求解算法,利用主问题和子问题方案求解整个 ART-DAD 模型。在 IEEE RTS-79 和 RTS-96 系统上的仿真结果验证了所提出的弹性改进策略的有效性。
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引用次数: 0
Model-Free Fast Frequency Support of Wind Farms for Tracking Optimal Frequency Trajectory 风电场的无模型快速频率支持以跟踪最佳频率轨迹
IF 8.6 1区 工程技术 Q1 ENERGY & FUELS Pub Date : 2024-07-19 DOI: 10.1109/TSTE.2024.3430972
Yubo Zhang;Songhao Yang;Zhiguo Hao;Baohui Zhang
The fast frequency support (FFS) towards frequency trajectory optimization provides a system view for the frequency regulation of wind farms (WFs). However, the existing frequency trajectory optimization-based FFS generally relies on the accurate governor dynamics model of synchronous generators (SGs), which aggrandizes the difficulty of controller implementation. In this paper, a proportional-integral (PI) based FFS of WFs is designed for tracking the optimal frequency trajectory, which gets rid of the dependence on the governor model. Firstly, the prototypical PI-based FFS of WFs is proposed and its feasibility for tracking the optimal frequency trajectory is analyzed and demonstrated. Then, based on the “frequency-RoCoF” form of the optimal frequency trajectory, a more practical PI controller is constructed, avoiding the time dependence of the prototypical PI controller. Besides, an adaptive gain associated with PI parameters is designed for multi-WF coordination. Finally, the validity of the proposed method is verified in both the single-WF system and the multi-WF system.
面向频率轨迹优化的快速频率支持(FFS)为风电场(WFs)的频率调节提供了系统视图。然而,现有的基于频率轨迹优化的 FFS 通常依赖于同步发电机 (SG) 的精确调速器动力学模型,这增加了控制器实现的难度。本文设计了一种基于比例积分(PI)的风力发电机 FFS,用于跟踪最优频率轨迹,摆脱了对调速器模型的依赖。首先,提出了基于 PI 的 WFs FFS 原型,并分析和论证了其跟踪最佳频率轨迹的可行性。然后,根据最佳频率轨迹的 "频率-RoCoF "形式,构建了一个更实用的 PI 控制器,避免了原型 PI 控制器的时间依赖性。此外,还为多 WF 协调设计了与 PI 参数相关的自适应增益。最后,在单 WF 系统和多 WF 系统中验证了所提方法的有效性。
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引用次数: 0
Reliability Indexes for Variable Energy Resource Generation in IEEE Standard 762-2023 IEEE 标准 762-2023 中的可变能源资源发电可靠性指标
IF 8.6 1区 工程技术 Q1 ENERGY & FUELS Pub Date : 2024-07-18 DOI: 10.1109/TSTE.2024.3430321
Douglas M. Logan;Fred Beasom;Murty P. Bhavaraju;Francis J. Bell;Lee Thaubald;Kai Jiang;Chris J. Dent
IEEE Standard Definitions for Use in Reporting Electric Generating Unit Reliability, Availability, and Productivity has recently been revised to extend the standard to variable energy resource (VER) generating facilities. The revision includes definitions of energy resource and resource unavailability, indexes that distinguish between equipment performance and the availability of a generator for system reliability analysis purposes, and generation-based reliability indexes for VER units corresponding to the traditional time-based indexes in previous versions of the standard. The revision also includes definition of critical period indexes, where the critical period is specified as hours of high system need. This paper describes the new terms and outlines issues with their definition.
最近,IEEE 修订了用于报告发电设备可靠性、可用性和生产率的标准定义,以将该标准扩展至可变能源资源 (VER) 发电设备。此次修订包括能源资源和资源不可用性的定义、用于系统可靠性分析的区分设备性能和发电机可用性的指标,以及可变能源资源机组基于发电量的可靠性指标,与之前版本标准中传统的基于时间的指标相对应。修订版还包括关键期指数的定义,其中关键期被指定为系统需求量大的时段。本文介绍了这些新术语,并概述了其定义方面的问题。
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引用次数: 0
A Novel GAN Architecture Reconstructed Using Bi-LSTM and Style Transfer for PV Temporal Dynamics Simulation 利用 Bi-LSTM 和样式转移重构用于光伏时动态模拟的新型 GAN 架构
IF 8.6 1区 工程技术 Q1 ENERGY & FUELS Pub Date : 2024-07-17 DOI: 10.1109/TSTE.2024.3429781
Xueqian Fu;Chunyu Zhang;Xiurong Zhang;Hongbin Sun
The stochastic production simulation of photovoltaic (PV) power is crucial for the analysis of power balance in power planning, annual or monthly operational planning, and long-term transactions in the electricity market, especially in power systems with a high share of PVs. To model the uncertainty and temporal characteristics inherent in PV power, this letter introduces the style transfer and innovatively establishes bi-directional long short-term memory generative adversarial networks (GAN). Simulation results confirm the advantages of the proposed GAN over traditional convolutional neural network-based GANs in simulating the diversity and temporal characteristics of PV power.
光伏(PV)电力的随机生产模拟对于电力规划中的电力平衡分析、年度或月度运营规划以及电力市场中的长期交易至关重要,尤其是在光伏占比较高的电力系统中。为模拟光伏发电固有的不确定性和时间特性,本文引入了样式转移,并创新性地建立了双向长短期记忆生成式对抗网络(GAN)。仿真结果证实,与传统的基于卷积神经网络的 GAN 相比,所提出的 GAN 在模拟光伏发电的多样性和时间特性方面更具优势。
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引用次数: 0
Transient Stability of Synchronous Condenser Co-Located With Renewable Power Plants Under High-Resistance Faults and Risk Mitigation 与可再生能源发电站同地运行的同步凝汽器在高阻故障下的暂态稳定性与风险缓解
IF 8.6 1区 工程技术 Q1 ENERGY & FUELS Pub Date : 2024-07-16 DOI: 10.1109/TSTE.2024.3429210
Xinyu Liu;Huanhai Xin;Yongpeng Shan;Di Zheng;Dong Chen
Synchronous condensers (SynCons) are widely used in supporting the integration of renewable power plants (RPPs) in weak grids. However, recent research suggests that a SynCon co-located with RPPs may be prone to transient rotor angle instability due to the excessive active power injected by nearby RPPs during metallic faults. This paper further discovers that the transient stability of the SynCon may be lost even it generates electrical power during high-resistance faults. This novel mechanism of instability is investigated by deriving power-angle characteristics in different fault scenarios, and then the effect of the system parameters on the stability is analyzed via a proposed index based on the critical clearance time (CCT). It reveals that inappropriate parameters of SynCons, weak grid, and voltage support during fault ride-through (FRT) all contribute to such transient instability. To mitigate such instability, an adaptive FRT strategy is proposed. The electromagnetic transient (EMT) simulations based on the PSCAD are carried out to validate the effectiveness of the theoretical analysis and the proposed adaptive control strategy.
同步电容器(SynCons)被广泛用于支持弱电网中可再生能源发电厂(RPP)的整合。然而,最近的研究表明,由于附近的可再生能源发电厂在金属故障时注入了过多有功功率,与可再生能源发电厂共址的 SynCon 可能容易出现转子角度瞬态不稳定。本文进一步发现,在高阻故障期间,即使 SynCon 产生了电力,其瞬态稳定性也可能会丧失。本文通过推导不同故障情况下的功率角特性,研究了这种新的不稳定性机制,然后通过基于临界清除时间(CCT)的指标分析了系统参数对稳定性的影响。结果表明,不适当的 SynCons 参数、弱电网和故障穿越 (FRT) 期间的电压支持都会导致这种瞬态不稳定性。为缓解这种不稳定性,提出了一种自适应故障穿越策略。基于 PSCAD 的电磁暂态 (EMT) 仿真验证了理论分析和所提自适应控制策略的有效性。
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引用次数: 0
Reduced-Dimensional Controllable Region-Assisted Optimal Rotor Current Control Strategy of DFIG-Based WTGs During Asymmetrical Faults 基于双馈变流器的风电机组在非对称故障期间的减维可控区域辅助优化转子电流控制策略
IF 8.6 1区 工程技术 Q1 ENERGY & FUELS Pub Date : 2024-07-16 DOI: 10.1109/TSTE.2024.3429152
Xuesong Gao;Zhihao Wang;Xianzhuo Sun;Lei Ding
Doubly-fed induction generator (DFIG)-based wind turbine generators (WTGs) are required to provide grid support during asymmetrical faults and the corresponding asymmetrical current control strategy (AsymCCS) is of great importance. However, the output capability of the rotor-side converter (RSC) under asymmetrical faults lacks a concise expression. This deficiency hinders the optimal allocation of current references in AsymCCSs and may further cause RSC overcurrent and over-modulation. To address these issues, a reduced-dimensional RSC asymmetrical controllable region (AsymCR) is firstly established in this paper, describing the characteristics of the RSC output capability. The AsymCR points out that the negative sequence current output should hold a higher priority to ensure the positive sequence current output capability. Based on an AsymCR-assisted optimal stator equivalent negative sequence reactance, a novel RSC AsymCCS is then proposed. The control strategy can offer sufficient negative sequence support to the grid while enlarging the positive sequence support capability, optimally allocating the positive and negnative sequence output and effectively avoiding overcurrent and over-modulation problems. Simulations are conducted in an electromagnetic transient test system to verify the effectiveness and improved performance of the proposed method.
基于双馈感应发电机(DFIG)的风力发电机组(WTGs)需要在不对称故障时提供电网支持,其相应的不对称电流控制策略(AsymCCS)非常重要。然而,转子侧变流器(RSC)在不对称故障下的输出能力缺乏一个简明的表达式。这一缺陷阻碍了电流参考的最佳分配,并可能进一步导致RSC过流和过调制。为了解决这些问题,本文首先建立了一个降维RSC不对称可控区域(AsymCR),描述了RSC输出能力的特征。asynmcr指出,为保证正序电流输出能力,负序电流输出应具有较高的优先级。在非对称辅助最优定子等效负序电抗的基础上,提出了一种新的非对称辅助定子等效负序电抗。该控制策略能够在扩大正序支持能力的同时,为电网提供足够的负序支持,优化分配正、负序输出,有效避免过流和过调制问题。在一个电磁瞬变测试系统中进行了仿真,验证了该方法的有效性和改进的性能。
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引用次数: 0
Distributionally Robust Chance Constrained Optimization Method for Risk-Based Routing and Scheduling of Shared Mobile Energy Storage System With Variable Renewable Energy 基于风险的可再生能源共享移动储能系统路由和调度的分布稳健机会约束优化方法
IF 8.6 1区 工程技术 Q1 ENERGY & FUELS Pub Date : 2024-07-16 DOI: 10.1109/TSTE.2024.3429310
Zhuoxin Lu;Xiaoyuan Xu;Zheng Yan;Mohammad Shahidehpour;Weiqing Sun;Dong Han
This paper proposes a pricing and scheduling method for shared mobile energy storage systems (SMSs) in coupled power distribution and transportation networks. Different from existing shared energy storage studies, which mostly focus on stationary resources, the paper investigates the SMS operation considering the negotiation of rental prices as well as mobility and charging/discharging among SMS owners and different users. Specifically, the SMS pricing and scheduling with variable renewable energy are established as a bilevel mixed-integer chance-constrained distributionally robust optimization problem. In the upper-level problem, the SMS owner determines pricing and day-ahead mobility strategy to maximize its payoff. In the lower-level problem, the SMS users, i.e., distribution grid operators, determine the SMS charging/discharging power according to the SMS day-ahead pricing results and intra-day distribution grid operation strategies for accommodating variable renewable energy. The distributionally robust chance constraint is designed to cope with the intra-day operational risk caused by the variability of renewable power generation. To cope with the solution difficulty in the proposed bilevel optimization problem, the chance constraint is reformulated as second-order cone constraints, which are further transformed into a set of linear constraints, and then the reformulated bilevel mixed-integer linear programming problem is decomposed and iteratively solved to avoid enumerating lower-level integer variables. Simulation results show that the utilization rate of SMS batteries is increased and the excess renewable power is fully consumed when SMSs are shared among different distribution grids. The proposed distributionally robust optimization achieves higher revenue for the SMS owner and smaller operating costs of distribution grids than robust optimization under uncertain environments.
本文针对耦合配电和运输网络中的共享移动储能系统(SMS)提出了一种定价和调度方法。现有的共享储能研究大多集中在固定资源上,与之不同的是,本文研究了 SMS 的运行,考虑到了租赁价格的协商以及 SMS 所有者和不同用户之间的流动性和充放电问题。具体来说,可再生能源可变的 SMS 定价和调度被确定为一个双级混合整数机会约束分布式鲁棒优化问题。在上层问题中,SMS 所有者决定定价和日前移动策略,以实现其收益最大化。在下层问题中,SMS 用户(即配电网运营商)根据 SMS 的日前定价结果和日内配电网运行策略确定 SMS 的充放电功率,以适应可变可再生能源。分布式稳健机会约束的设计是为了应对可再生能源发电的可变性所带来的日内运行风险。为了应对所提出的双级优化问题的求解难度,将偶然性约束重新表述为二阶锥形约束,并进一步转化为一组线性约束,然后对重新表述的双级混合整数线性规划问题进行分解和迭代求解,以避免枚举低级整数变量。仿真结果表明,当 SMS 在不同配电网间共享时,SMS 电池的利用率得到了提高,多余的可再生能源电力得到了充分利用。与不确定环境下的稳健优化相比,所提出的分布式稳健优化为 SMS 所有者带来了更高的收益,同时降低了配电网的运营成本。
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引用次数: 0
An Adaptive Controller of a Hybrid Storage System for Power Smoothing With Enlarged Battery Lifetime 一种混合存储系统的自适应控制器,可在延长电池寿命的同时实现功率平滑
IF 8.6 1区 工程技术 Q1 ENERGY & FUELS Pub Date : 2024-07-12 DOI: 10.1109/TSTE.2024.3426917
Pavlos G. Papageorgiou;Panagiotis T. Papafilippou;Konstantinos O. Oureilidis;Georgios C. Christoforidis
The volatility of grid-coupled photovoltaics can cause local voltage deviations, while the impact on frequency becomes obvious in isolated weak grids. Thus, a standalone battery is usually proposed for smoothing purposes. However, the frequent cycles and abrupt power variations shrink its life and impair control performance. To this end, this study introduces a controller for a hybrid system composed of a superconducting magnetic energy storage (SMES) and a battery. The proposed method establishes an idling zone for battery to eliminate its short-term activity, while SMES handles any power mismatch. The zone limits are dynamically adjusted in case of power balance detection, while an adaptive saturation is applied to them for maximal SMES utilization and minimal battery degradation. When SMES current deviates from this zone, battery operates with an adaptive ramp rate (i.e., di/dt) depending on the state of charge of SMES, to further optimize its life. Additionally, to prevent unnecessary power circulation among SMES and battery, supervisory control loops are implemented. Finally, to evaluate this scheme against preceding controllers regarding battery life extension, a real-time approach is followed using a dedicated simulator, while a hardware-in-the-loop verification is presented using an actual controller.
与电网耦合的光伏发电的波动性会导致局部电压偏差,而在孤立的弱电网中,对频率的影响会变得非常明显。因此,通常建议使用独立电池来达到平滑目的。然而,频繁的循环和突然的功率变化会缩短电池的使用寿命,损害控制性能。为此,本研究为由超导磁能存储(SMES)和电池组成的混合系统引入了一种控制器。所提出的方法为电池建立了一个空闲区,以消除其短期活动,而 SMES 则处理任何功率失配。在检测到功率平衡的情况下,可动态调整区域限制,同时对其应用自适应饱和度,以实现 SMES 的最大利用率和最小的电池损耗。当 SMES 电流偏离该区域时,电池会根据 SMES 的充电状态以自适应斜率(即 di/dt)运行,以进一步优化电池寿命。此外,为了防止 SMES 和电池之间不必要的电力循环,还实施了监督控制回路。最后,为了评估该方案与之前的控制器在延长电池寿命方面的差异,我们使用专用模拟器采用了实时方法,并使用实际控制器进行了硬件在环验证。
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引用次数: 0
Towards Improving Unit Commitment Economics: An Add-On Tailor for Renewable Energy and Reserve Predictions 改进单位承诺经济学:可再生能源和储备预测的附加定制工具
IF 8.6 1区 工程技术 Q1 ENERGY & FUELS Pub Date : 2024-07-10 DOI: 10.1109/TSTE.2024.3426337
Xianbang Chen;Yikui Liu;Lei Wu
Generally, day-ahead unit commitment (UC) is conducted in a predict-then-optimize process: it starts by predicting the renewable energy source (RES) availability and system reserve requirements; given the predictions, the UC model is then optimized to determine the economic operation plans. In fact, predictions within the process are raw. In other words, if the predictions are further tailored to assist UC in making the economic operation plans against realizations of the RES and reserve requirements, UC economics will benefit significantly. To this end, this paper presents a cost-oriented tailor of RES-and-reserve predictions for UC, deployed as an add-on to the predict-then-optimize process. The RES-and-reserve tailor is trained by solving a bi-level mixed-integer programming model: the upper level trains the tailor based on its induced operating cost; the lower level, given tailored predictions, mimics the system operation process and feeds the induced operating cost back to the upper level; finally, the upper level evaluates the training quality according to the fed-back cost. Through this training, the tailor learns to customize the raw predictions into cost-oriented predictions. Moreover, the tailor can be embedded into the existing predict-then-optimize process as an add-on, improving the UC economics. Lastly, the presented method is compared to traditional, binary-relaxing, neural network-based, stochastic, and robust methods.
一般来说,日前机组承诺(UC)是在预测-优化过程中进行的:首先预测可再生能源(RES)的可用性和系统储备要求;然后根据预测结果优化 UC 模型,以确定经济运行计划。事实上,该过程中的预测是原始的。换句话说,如果能进一步调整预测,帮助 UC 根据可再生能源和储备要求的实现情况制定经济运营计划,那么 UC 的经济效益将大大提高。为此,本文介绍了以成本为导向的可再生能源和储备预测裁剪器,作为预测--优化流程的附加组件部署在联合调度中心。可再生能源和储备跟踪器是通过求解一个双层混合整数编程模型来训练的:上层根据其诱导的运行成本来训练跟踪器;下层在得到跟踪预测后,模拟系统运行过程,并将诱导的运行成本反馈给上层;最后,上层根据反馈的成本来评估训练质量。通过这种训练,"裁缝 "学会将原始预测定制为以成本为导向的预测。此外,"裁缝 "还可以作为附加功能嵌入现有的 "预测--优化 "流程,从而提高统一通信的经济性。最后,介绍的方法与传统方法、二元松弛方法、基于神经网络的方法、随机方法和稳健方法进行了比较。
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引用次数: 0
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IEEE Transactions on Sustainable Energy
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