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2023 IEEE PES Grid Edge Technologies Conference & Exposition (Grid Edge)最新文献

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Training A Deep Reinforcement Learning Agent for Microgrid Control using PSCAD Environment 基于PSCAD环境的微电网控制深度强化学习智能体训练
Pub Date : 2023-04-10 DOI: 10.1109/GridEdge54130.2023.10102740
A. Soofi, Reza Bayani, Mehrdad Yazdanibiouki, Saeed D. Manshadi
The accessibility of real-time operational data along with breakthroughs in processing power have promoted the use of Machine Learning (ML) applications in current power systems. Prediction of device failures, meteorological data, system outages, and demand are among the applications of ML in the electricity grid. In this paper, a Reinforcement Learning (RL) method is utilized to design an efficient energy management system for grid-tied Energy Storage Systems (ESS). We implement a Deep Q-Learning (DQL) approach using Artificial Neural Networks (ANN) to design a microgrid controller system simulated in the PSCAD environment. The proposed on-grid controller coordinates the main grid, aggregated loads, renewable generations, and Advanced Energy Storage (AES). To reduce the cost of operating AESs, the designed controller takes the hourly energy market price into account in addition to physical system characteristics.
实时运行数据的可访问性以及处理能力的突破促进了机器学习(ML)应用在当前电力系统中的应用。预测设备故障、气象数据、系统中断和需求是机器学习在电网中的应用。本文利用强化学习(RL)方法设计了一种高效的并网储能系统(ESS)能量管理系统。我们使用人工神经网络(ANN)实现深度q -学习(DQL)方法来设计在PSCAD环境中模拟的微电网控制器系统。所提出的并网控制器协调主电网、聚合负荷、可再生发电和先进储能(AES)。为了降低AESs的运行成本,所设计的控制器除了考虑系统的物理特性外,还考虑了每小时的能源市场价格。
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引用次数: 0
Safety, Reliability and Efficiency – beyond the grid edge 安全、可靠、高效——超越电网边缘
Pub Date : 2023-04-10 DOI: 10.1109/GridEdge54130.2023.10102704
H. Borland, M. Mccormack
Regardless of how the Grid Edge is perceived, grid users and the society it serves, demand a grid that is safe, reliable and efficient. This goes far beyond the physical ‘grid edge’ and permeates the totality of the distribution system in particular. Earth faults at Medium Voltage have a great impact on safety and reliability. In this paper, the selection of compensated neutral treatment is shown to provide optimized performance. Augmentation with Faulted Phase Earthing or Augmented Residual Current Compensation adds further to the safety performance. This is advantageous in high-risk areas and in wildfire mitigation. Efficiency in returning supply to customers after outages is addressed, including the use of Synchronised Line Monitoring. This paper presents fundamental solutions to deliver safety, reliability and efficiency at and beyond the Grid Edge.
不管人们如何看待网格边缘,电网用户和它所服务的社会都需要一个安全、可靠和高效的电网。这远远超出了物理的“电网边缘”,特别是渗透到整个配电系统。中压接地故障对设备的安全可靠性有很大的影响。在本文中,选择补偿中性处理可以提供最佳的性能。采用故障相接地或增强剩余电流补偿的增强电路进一步提高了安全性能。这在高风险地区和缓解野火方面是有利的。解决了在停电后向客户恢复供电的效率问题,包括使用同步线路监控。本文提出了在网格边缘及边缘之外提供安全性、可靠性和效率的基本解决方案。
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引用次数: 0
Incremental Subgradient Method for EVs Smart Charging Flexibility in Wholesale Energy Markets 能源批发市场电动汽车智能充电灵活性的增量亚梯度法
Pub Date : 2023-04-10 DOI: 10.1109/GridEdge54130.2023.10102709
S. M. de Oca, P. Monzón, P. Belzarena
The electricity and transportation sectors are in a transformation process, in which both can benefit from working together. In particular, more than half of electric vehicle (EV) users have similar consumption behaviors and will use charging infrastructure at home, creating a great challenge for different stakeholders. Digital platforms allow automatic control of end devices, enabling users to be more active and committed to a sustainable system. Motivated by large-scale and online optimization approaches, we formulate a smart charging mechanism for coordinating a large population of residential EVs based on a price-responsive model. We used a stochastic subgradient method to deal with synchrony problems and communication overload. The Utility decides the energy price that maximizes its profit in a day-ahead flexibility market with available information, while the clients fulfill theirs consumption expectations.
电力和运输部门正处于转型过程中,双方都可以从合作中受益。特别是,超过一半的电动汽车(EV)用户有类似的消费行为,并且会在家中使用充电基础设施,这对不同的利益相关者来说是一个巨大的挑战。数字平台允许对终端设备进行自动控制,使用户更加活跃,并致力于可持续发展的系统。在大规模和在线优化方法的激励下,我们制定了一个基于价格响应模型的智能充电机制,以协调大量住宅电动汽车。我们使用随机次梯度方法来处理同步问题和通信过载。公用事业公司根据可获得的信息在日前弹性市场上决定其利润最大化的能源价格,而客户则满足他们的消费预期。
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引用次数: 0
A Resilience-Driven Battery Energy Storage System Sizing Strategy for Grid Edge Radial Supplies 电网边缘径向供电的弹性驱动电池储能系统尺寸策略
Pub Date : 2023-04-10 DOI: 10.1109/GridEdge54130.2023.10102731
Alex Nassif
Non-wire alternatives are gaining acceptance in areas where traditional reliability improvement methods are of difficult adoption or not cost effective. Declining costs of energy storage systems favor the adoption of electrochemical batteries if supported by a sound value proposition. This paper presents a practical method to size battery storage systems based on minimizing the cost to the distribution system operator. The method is based on an exhaustive search and considers only practical aspects faced by electric utilities, leaving out parameters that are either not visible or impactful. The proposed approach was adopted in a real distribution network slated for reconfiguration just few years following the study, but poor reliability has favored the adoption of the storage system as an interim solution with minimum environmental impact and improved metrics.
在传统可靠性改进方法难以采用或成本效益不高的领域,非电缆替代方案正得到越来越多的认可。如果有合理的价值主张支持,储能系统成本的下降有利于电化学电池的采用。本文提出了一种实用的基于最小化配电系统运营商成本的电池储能系统尺寸的方法。该方法基于详尽的搜索,只考虑电力公司面临的实际方面,省略了不可见或不具影响力的参数。该研究仅在几年后就在一个实际的配电网中采用了所提出的方法,该配电网计划进行重新配置,但由于可靠性较差,因此倾向于采用储能系统作为对环境影响最小且改进指标的临时解决方案。
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引用次数: 0
EV Hosting Capacity and Voltage Unbalance: An Australian Case Study 电动汽车托管容量和电压不平衡:一个澳大利亚的案例研究
Pub Date : 2023-04-10 DOI: 10.1109/GridEdge54130.2023.10102721
Yushan Hou, Jing Zhu, Michael Z. Liu, W. J. Nacmanson, L. Ochoa
The widespread adoption of residential electric vehicles (EVs) will result in larger voltage drops due to the extra demand. Since most residential EV chargers are single-phase, they might also contribute to voltage unbalance which, in turn, can make voltage drop issues on certain phases worse. This paper investigates the extent to which voltage unbalance affects the EV hosting capacity of distribution networks using a Monte Carlo-based time-series analysis to capture the uncertainties of EV location, charger size, and charging behavior. Using a realistically modeled Australian MV-LV network with 1,300+ customers, results show that with increasing EV penetrations, the voltage unbalance keeps increasing too, even for 100% EV penetration. Moreover, it is demonstrated that large voltage unbalance significantly limits EV hosting capacity, suggesting the need for considering balancing strategies when possible.
随着家用电动汽车(ev)的广泛采用,由于额外的需求,将导致更大的电压降。由于大多数住宅电动汽车充电器是单相的,它们也可能导致电压不平衡,这反过来又会使某些阶段的电压下降问题变得更糟。本文研究了电压不平衡对配电网电动汽车承载能力的影响程度,采用基于蒙特卡罗的时间序列分析来捕捉电动汽车位置、充电器大小和充电行为的不确定性。通过对澳大利亚1300多个客户的MV-LV网络进行仿真,结果表明,随着电动汽车渗透率的增加,即使在100%的电动汽车渗透率下,电压不平衡也在不断增加。此外,研究还表明,电压不平衡严重限制了电动汽车的承载能力,因此有必要在可能的情况下考虑平衡策略。
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引用次数: 0
Adaptive approach for primary frequency support by wind turbines based on grid code requirements and turbines limitations 基于电网规范要求和风力涡轮机限制的风力涡轮机一次频率支持自适应方法
Pub Date : 2023-04-10 DOI: 10.1109/GridEdge54130.2023.10102734
Bashar Mousa Melhem, Steven Liu
Based on the provisions of grid support published in the latest network codes (NC), wind turbines (WTs), among other renewable energy units, must regulate their output power to actively participate in supporting the grid frequency. However, the most frequently utilized wind turbines with doubly fed induction generators (DFIG) have limitations regarding rotor speed and converter power in addition to issues related to their power output resulting from wind speed fluctuation and model-plant mismatch. In this paper, rotor side converter of WT operated in de-loading mode is controlled adaptively. The objective is to provide transmission system operator (TSO) with an accurate available power and mitigate the influence of wind disturbances while following TSO variable power set-point. The limitations of both rotor speed and rotor side converter are considered in the proposed control approach.
根据最新电网规范(NC)发布的电网支持规定,风力发电机组等可再生能源机组必须调节其输出功率,积极参与电网频率支持。然而,最常用的带有双馈感应发电机(DFIG)的风力涡轮机在转子转速和变流器功率方面存在局限性,此外还有与风速波动和模型-工厂不匹配相关的功率输出问题。本文采用自适应控制的方法,对小波变换转子侧变换器进行了减载控制。目标是为输电系统运营商(TSO)提供准确的可用功率,并在遵循TSO可变功率设定点的同时减轻风干扰的影响。该控制方法考虑了转子转速和转子侧变换器的局限性。
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引用次数: 0
Real-Time T&D Co-Simulation for Testing Grid Impact of High DER Participation 高DER参与下电网冲击测试的实时T&D联合仿真
Pub Date : 2023-02-02 DOI: 10.1109/GridEdge54130.2023.10102714
Victor Paduani, Rahul Kadavil, H. Hooshyar, A. Haddadi, A. Jakaria, A. Huque
This paper presents the development of a real-time T&D co-simulation testbed for simulating large grids under high DER penetration. By integrating bulk power system, distribution feeders, and distributed energy resources (DER) models into one simulation environment, the testbed enables the performance analysis and validation of DER management systems (DERMS) algorithms. This work proposes a co-simulation timestep sequence for the cross-platform data exchange and time synchronization, with a communication framework based on MQTT communication protocol. The proposed strategy is tested with a 5,000 buses model of part of the North American bulk power system (BPS) and a 9,500 nodes distribution feeder model obtained from a local utility. Simulations are carried out to demonstrate the capability of the proposed framework to propagate events between the transmission and distribution models. Results are used to quantify how the co-simulation timestep size can affect the propagation of dynamics between the models.
本文介绍了一种用于模拟大电网高穿深条件下输配电实时联合仿真试验台的研制。通过将大容量电力系统、配电馈线和分布式能源(DER)模型集成到一个仿真环境中,该试验台能够对DER管理系统(DERMS)算法进行性能分析和验证。本文提出了一种基于MQTT通信协议的通信框架,用于跨平台数据交换和时间同步的联合仿真时间步长序列。用北美部分大容量电力系统(BPS)的5000总线模型和当地公用事业公司的9500节点配电馈线模型对所提出的策略进行了测试。通过仿真验证了所提出的框架在传输和分配模型之间传播事件的能力。结果用于量化联合模拟时间步长如何影响模型之间的动态传播。
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引用次数: 3
Maximum likelihood estimation of distribution grid topology and parameters from Smart Meter data 从智能电表数据的配电网拓扑和参数的最大似然估计
Pub Date : 2022-10-05 DOI: 10.1109/GridEdge54130.2023.10102720
Lisa Laurent, Jean-Sébastien Brouillon, G. Ferrari-Trecate
This paper defines a Maximum Likelihood Estimator (MLE) for the admittance matrix estimation of distribution grids, utilising voltage magnitude and power measurements collected only from common, unsychronised measuring devices (Smart Meters). First, we present a model of the grid, as well as the existing MLE based on voltage and current phasor measurements. Then, this problem formulation is adjusted for phase-less measurements using common assumptions. The effect of these assumptions is compared to the initial problem in various scenarios. Finally, numerical experiments on a popular IEEE benchmark network indicate promising results. Missing data can greatly disrupt estimation methods. Not measuring the voltage phase only adds 30% of error to the admittance matrix estimate in realistic conditions. Moreover, the sensitivity to measurement noise is similar with and without the phase.
本文定义了配电网导纳矩阵估计的最大似然估计器(MLE),利用仅从普通的非同步测量设备(智能电表)收集的电压幅度和功率测量。首先,我们提出了一个网格模型,以及现有的基于电压和电流相量测量的最大似然估计。然后,使用一般假设对该问题公式进行无相测量调整。在各种情况下,将这些假设的效果与初始问题进行比较。最后,在一个常用的IEEE基准网络上进行了数值实验,得到了良好的结果。缺少数据会极大地破坏估计方法。在实际情况下,不测量电压相位只会给导纳矩阵估计增加30%的误差。此外,在有无相位的情况下,对测量噪声的灵敏度相似。
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2023 IEEE PES Grid Edge Technologies Conference & Exposition (Grid Edge)
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