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Semi-Peer-to-Peer Safety Coordination Control for Distributed Battery Energy Storage System in DC Microgrids via Saturated Limitation 通过饱和限制实现直流微电网中分布式电池储能系统的半对等安全协调控制
IF 8.6 1区 工程技术 Q1 ENERGY & FUELS Pub Date : 2024-08-08 DOI: 10.1109/TSTE.2024.3440331
Ting Yang;Jilin Lang;Hao Li
This paper presents a semi-peer coordination control strategy to ensure the bus voltage stability and effectively constrain the power trajectory, thereby mitigating safety concerns arising from excessive unit power and communication failures in distributed battery energy storage systems (DBESS) based DC microgrids. Firstly, the primary controller is employed a saturated feedforward design to maintain bus voltage stability and address the excessive part of power allocation with droop control. The saturation results enable flexible switching of the reference state, allowing energy storage units (ESUs) to autonomously transition between voltage tracking and power tracking modes. Secondly, the dual-dynamic power allocation strategy is introduced with distributed consensus and saturation allocation.The power allocation with distributed consensus aims to achieve synchronous proportional charging and discharging for SOC balancing. For the offline ESUs of communication failures, saturation power allocation is designed with arrived operation point to avoid the over-utilization of offline ESUs. To address potential communication failures in offline ESUs, the saturation power allocation strategy based on the current operational point is devised to mitigate the risk of over-utilization of offline ESUs. Finally, simulations and experimental results verify the effectiveness of the proposed method.
本文提出了一种半对等协调控制策略,以确保母线电压稳定并有效约束功率轨迹,从而减轻基于分布式电池储能系统(DBESS)的直流微电网中因单元功率过大和通信故障而引起的安全问题。首先,主控制器采用饱和前馈设计,以维持总线电压稳定,并通过下垂控制解决功率分配的过度部分。饱和结果实现了参考状态的灵活切换,允许储能装置(ESU)在电压跟踪和功率跟踪模式之间自主转换。其次,引入了分布式共识和饱和分配的双动态功率分配策略。分布式共识功率分配旨在实现同步比例充放电,以实现 SOC 平衡。针对通信故障的离线 ESU,设计了到达操作点的饱和功率分配,以避免离线 ESU 的过度使用。针对离线 ESU 可能出现的通信故障,设计了基于当前运行点的饱和功率分配策略,以降低离线 ESU 过度使用的风险。最后,模拟和实验结果验证了所提方法的有效性。
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引用次数: 0
Deriving Sufficient Conditions for Exact Relaxation of Complementarity Constraints in Optimization Problems With Energy Storage 在有储能功能的优化问题中得出精确放松互补性约束的充分条件
IF 8.6 1区 工程技术 Q1 ENERGY & FUELS Pub Date : 2024-08-07 DOI: 10.1109/TSTE.2024.3438457
Hongyuan Liang;Zhigang Li;Mohammad Shahidehpour;Nianjie Tian;Youquan Jiang;J. H. Zheng;Jisong Zhu
Energy storage is becoming increasingly important in power and energy systems. However, its strongly nonconvex complementarity constraints, which prevent simultaneous charging or discharging behavior, hinder its application in optimization-based decision making. One remedy is to relax these constraints, but the existing relaxation methods are specific to power system applications with limited universality. To bridge this gap, we provide a methodology to derive the general form of sufficient conditions for the exact relaxation of a general energy storage-concerned optimization problem (ESCOP). Specific sufficient conditions for a wide range of ESCOPs can be easily accessed via the proposed methodology. This paper provides mathematical proofs and analyses of the proposed conditions, where sufficient conditions obtained from specific forms of ESCOPs are numerically validated to guarantee exact relaxation and significantly improve the ESCOP solution efficiency.
在电力和能源系统中,储能正变得越来越重要。然而,其强烈的非凸互补约束阻止了同时充电或放电行为,阻碍了其在基于优化的决策中的应用。一种补救方法是放松这些约束,但现有的放松方法仅限于电力系统应用,普遍性有限。为了弥补这一缺陷,我们提供了一种方法,用于推导出精确放松一般储能优化问题(ESCOP)的一般形式的充分条件。通过所提出的方法,我们可以轻松获得各种 ESCOP 的具体充分条件。本文对提出的条件进行了数学证明和分析,其中从特定形式的 ESCOP 中获得的充分条件经过数值验证,保证了精确松弛,并显著提高了 ESCOP 的求解效率。
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引用次数: 0
Joint Electricity and Carbon Sharing With PV and Energy Storage: A Low-Carbon DR-Based Game Theoretic Approach 利用光伏和储能联合分享电力和碳:基于低碳 DR 的博弈论方法
IF 8.6 1区 工程技术 Q1 ENERGY & FUELS Pub Date : 2024-08-06 DOI: 10.1109/TSTE.2024.3439512
Jie Wang;Xiaolong Jin;Hongjie Jia;Marcos Tostado-Véliz;Yunfei Mu;Xiaodan Yu;Shuo Liang
This paper proposes a joint electricity and carbon sharing framework with photovoltaic (PV) and energy storage system (ESS) for deep decarbonization, allowing distributed PV prosumers to participate in a sharing network established by aggregator of prosumers (AOP). The ESS-equipped AOP plays multiple roles as a carbon aggregator, an ESS operator, and an energy-sharing provider at the same time. First, a demand response (DR)-based model that incorporates the multi-strategy of ESS is proposed to optimize energy-carbon transaction. A low-carbon DR with consideration of electricity-carbon coupling is developed to incentivize prosumers to adjust consumption behavior for costs and emissions reduction. Second, a joint optimization based on Stackelberg game is proposed, where AOP is leader, and prosumers act as followers. A dynamic pricing mechanism is proposed for AOP to determine the electricity-carbon coupled selling and buying prices simultaneously. Meanwhile, prosumers would adjust their energy consumption as response to different sharing prices. In addition, a distributed optimization algorithm with interactions is used to reach the Stackelberg game equilibrium. Finally, through a practical testing case, the effectiveness of the method is validated in terms of economic benefits and PV sharing enhancement, as well as the reduction of carbon emissions.
本文为深度脱碳提出了一个光伏与储能系统(ESS)联合电力与碳共享框架,允许分布式光伏发电用户参与由用户聚合器(AOP)建立的共享网络。配备 ESS 的 AOP 同时扮演着碳汇集者、ESS 运营者和能源共享提供者的多重角色。首先,提出了一个基于需求响应(DR)的模型,该模型结合了 ESS 的多重策略,以优化能源-碳交易。考虑到电力与碳的耦合,开发了低碳需求响应,以激励消费者调整消费行为,从而降低成本,减少排放。其次,提出了一种基于 Stackelberg 博弈的联合优化方法,其中 AOP 为领导者,消费者为追随者。建议 AOP 采用动态定价机制,同时确定电力与碳的耦合销售价格和购买价格。与此同时,消费者会根据不同的分享价格调整其能源消耗。此外,还采用了一种具有交互作用的分布式优化算法来达到斯塔克尔伯格博弈均衡。最后,通过一个实际测试案例,从经济效益、提高光伏共享以及减少碳排放等方面验证了该方法的有效性。
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引用次数: 0
Net-Zero Scheduling of Multi-Energy Building Energy Systems: A Learning-Based Robust Optimization Approach With Statistical Guarantees 多能源建筑能源系统的净零调度:基于学习的鲁棒性优化方法与统计保证
IF 8.6 1区 工程技术 Q1 ENERGY & FUELS Pub Date : 2024-08-02 DOI: 10.1109/TSTE.2024.3437210
Yijie Yang;Jian Shi;Dan Wang;Chenye Wu;Zhu Han
Buildings produce a significant share of greenhouse gas (GHG) emissions, making homes and businesses a major factor in climate change. To address this critical challenge, this paper explores achieving net-zero emission through the carbon-aware optimal scheduling of the multi-energy building integrated energy systems (BIES). We integrate advanced technologies and strategies, such as the carbon capture system (CCS), power-to-gas (P2G), carbon tracking, and emission allowance trading, into the traditional BIES scheduling problem. The proposed model enables accurate accounting of carbon emissions associated with building energy systems and facilitates the implementation of low-carbon operations. Furthermore, to address the challenge of accurately assessing uncertainty sets related to forecasting errors of loads, generation, and carbon intensity, we develop a learning-based robust optimization approach for BIES that is robust in the presence of uncertainty and guarantees statistical feasibility. The proposed approach comprises a shape learning stage and a shape calibration stage to generate an optimal uncertainty set that ensures favorable results from a statistical perspective. Numerical studies conducted based on both synthetic and real-world datasets have demonstrated that the approach yields up to 8.2% cost reduction, compared with conventional methods, in assisting buildings to robustly reach net-zero emissions.
建筑物产生了大量温室气体(GHG)排放,使住宅和企业成为气候变化的主要因素。为应对这一严峻挑战,本文探讨了如何通过多能源建筑一体化能源系统(BIES)的碳感知优化调度实现净零排放。我们将碳捕集系统(CCS)、电转气(P2G)、碳追踪和排放配额交易等先进技术和策略整合到传统的 BIES 调度问题中。所提出的模型能够准确计算与建筑能源系统相关的碳排放量,并促进低碳运营的实施。此外,为了应对准确评估与负荷、发电量和碳强度预测误差相关的不确定性集的挑战,我们为 BIES 开发了一种基于学习的鲁棒优化方法,该方法在存在不确定性时具有鲁棒性,并能保证统计可行性。所提出的方法包括形状学习阶段和形状校准阶段,以生成最佳不确定性集,确保从统计角度获得有利结果。基于合成数据集和实际数据集进行的数值研究表明,与传统方法相比,该方法在帮助建筑物稳健地实现净零排放方面最多可降低 8.2% 的成本。
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引用次数: 0
Ultra-Short-Term Wind Power Forecasting Based on the Strategy of “Dynamic Matching and Online Modeling” 基于 "动态匹配和在线建模 "策略的超短期风电预测
IF 8.6 1区 工程技术 Q1 ENERGY & FUELS Pub Date : 2024-08-02 DOI: 10.1109/TSTE.2024.3424932
Yuhao Li;Han Wang;Jie Yan;Chang Ge;Shuang Han;Yongqian Liu
Ultra-short-term wind power forecasting plays a vital role in real-time scheduling, frequency regulation, and intraday market transactions. Due to the complexity of weather systems, unit aging, wind farm control strategies, etc., the temporal dependency relationship in wind power series changes from time to time (known as concept drift), which leads to the low forecasting accuracy of the commonly used offline modeling methods. Online modeling can effectively deal with concept drift by utilizing the latest information in the flow data and capturing the latest concepts during the modeling process. However, the existing online modeling methods cannot meet the timeliness requirements of the power grid for ultra-short-term wind power forecasting. Therefore, a strategy of “dynamic matching and online modeling” for ultra-short-term wind power forecasting is proposed in this paper. Training samples are dynamically selected according to the characteristic similarity of amplitude and fluctuation, aiming to improve the representativeness of samples and reduce the training time simultaneously. In addition to historical power, Numerical Weather Prediction wind speed is also introduced in the process of “dynamic matching” to improve the forecasting accuracy. Operation data from three wind farms in China is used to validate the effectiveness and robustness of the proposed method. The results show that the forecasting accuracy can be improved by 1.18%–4.32% for 4 hours in advance.
超短期风电预测在实时调度、频率调节和日内市场交易等方面发挥着重要作用。由于天气系统的复杂性、机组老化、风电场控制策略等原因,风电系列的时间依赖关系会不断变化(称为概念漂移),导致常用的离线建模方法预测精度较低。在线建模通过利用流数据中的最新信息,在建模过程中捕获最新的概念,可以有效地处理概念漂移问题。然而,现有的在线建模方法不能满足电网超短期风电预测的时效性要求。为此,本文提出了一种“动态匹配+在线建模”的超短期风电预测策略。根据振幅和波动的特征相似度动态选择训练样本,提高样本的代表性,同时减少训练时间。数值天气预报在“动态匹配”过程中,除历史功率外,还引入了数值天气预报风速,以提高预报精度。利用中国三个风电场的运行数据验证了该方法的有效性和鲁棒性。结果表明,提前4 h预报精度可提高1.18% ~ 4.32%。
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引用次数: 0
Coordinated Frequency Regulation of Active Distribution Networks Considering Dimension-Augmented Power Flow Constraints 考虑维度增强电力流约束的有源配电网协调频率调节
IF 8.6 1区 工程技术 Q1 ENERGY & FUELS Pub Date : 2024-08-02 DOI: 10.1109/TSTE.2024.3437758
Jiaqing Zhai;Li Guo;Zhongguan Wang;Xialin Li;Yixin Liu;Chengshan Wang
Distributed energy resources (DERs) integrated in active distribution networks (ADNs) participating in primary frequency regulation (PFR) service can enhance frequency safety and stability of power systems. However, PFR service can result in power flow (PF) insecurity issues, especially in low and medium-voltage networks without accurate line parameters. To address the problem, this paper proposes a coordinated control architecture based on the Koopman data-driven power flow. The cluster model training layer uses Koopman operator theory to transform the original complex nonlinear PF model into a dimension-augmented linear PF model. The online PFR optimization layer constructs an optimization model of PFR based on the data-driven PF, considering security constraints of ADNs. The local frequency response layer responds to frequency change in real-time and ensures fast frequency support. This method is validated using a modified IEEE 82-node test case, which demonstrates that it has the advantages of fast online solving, and independence on model parameters. The proposed method can fully exploit PFR capability of ADN and achieve the optimal PF profiles while ensuring the aggregate PFR characteristics.
将分布式能源集成到有源配电网中参与一次调频服务,可以提高电力系统频率的安全性和稳定性。然而,PFR服务可能会导致潮流(PF)不安全问题,特别是在没有准确线路参数的中低压电网中。为了解决这一问题,本文提出了一种基于Koopman数据驱动潮流的协调控制体系结构。聚类模型训练层利用Koopman算子理论将原有的复杂非线性PF模型转化为增维线性PF模型。在线PFR优化层考虑adn的安全约束,构建了基于数据驱动PF的PFR优化模型。本地频率响应层实时响应频率变化,保证快速的频率支持。采用改进的IEEE 82节点测试用例对该方法进行了验证,结果表明该方法具有在线求解速度快、与模型参数无关等优点。该方法可以充分利用ADN的PFR特性,在保证聚合PFR特性的前提下实现最优的PFR分布。
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引用次数: 0
Resilience-Oriented Two-Stage Restoration Considering Coordinated Maintenance and Reconfiguration in Integrated Power Distribution and Heating Systems 考虑到综合配电和供热系统的协调维护和重新配置,以复原力为导向的两阶段恢复
IF 8.6 1区 工程技术 Q1 ENERGY & FUELS Pub Date : 2024-08-02 DOI: 10.1109/TSTE.2024.3434995
Ke Wang;Yixun Xue;Mohammad Shahidehpour;Xinyue Chang;Zening Li;Yue Zhou;Hongbin Sun
The inherent linkage between a power distribution system (PDS) and a district heating system (DHS) necessitates coordinated load restoration after natural disasters. To guarantee optimal load restoration during a recovery process, a coordinated dispatch strategy of the maintenance crew for the PDS/DHS considering the optimal reconfiguration of their respective networks is proposed in this paper. The proposed solution focuses on the intricate mutual interaction of the DHS and PDS and coordinates the fault isolation and service restoration stages. The proposed optimization is modeled as a mixed-integer second-order cone problem (MISOCP), which contains numerous integer variables. To lessen the computational burden, a two-stage acceleration algorithm is proposed, which divides the solution procedure into two stages based on two types of integer variables: load status variables and variables associated with the maintenance path and network topology. Then, the acceleration principles are proposed to determine the load status variables. The effectiveness and accuracy of the proposed model are validated by extensive cases, which demonstrate the performance of the coordinated maintenance and reconfiguration in integrated energy systems for fault recovery.
配电系统与区域供热系统之间的内在联系要求在自然灾害发生后协调恢复负荷。为了保证恢复过程中的最佳负荷恢复,本文提出了一种考虑各自网络最优重构的PDS/DHS维修人员协调调度策略。该解决方案关注DHS和PDS之间复杂的相互作用,协调故障隔离和业务恢复阶段。该优化模型是一个包含大量整数变量的混合整数二阶锥问题(MISOCP)。为了减少计算量,提出了一种两阶段加速算法,该算法基于负载状态变量和与维护路径和网络拓扑相关的变量两类整数变量将求解过程分为两阶段。然后,提出了确定载荷状态变量的加速度原理。通过大量实例验证了该模型的有效性和准确性,验证了综合能源系统故障恢复协调维护与重构的有效性。
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引用次数: 0
A Bayesian Deep Learning-Based Adaptive Wind Farm Power Prediction Method Within the Entire Life Cycle 基于贝叶斯深度学习的全生命周期自适应风电场功率预测方法
IF 8.6 1区 工程技术 Q1 ENERGY & FUELS Pub Date : 2024-07-30 DOI: 10.1109/TSTE.2024.3435936
Xiaoming Liu;Jun Liu;Yu Zhao;Yongxin Nie;Jiacheng Liu;Tao Ding
Accurate wind power prediction (WPP) is crucial to the secure and stable operation of large-scale power systems, and data-driven WPP methods have recently been widely studied and applied. However, existing data-driven methods cannot be applied to new wind farms due to the lack of operational data. This paper presents a novel Bayesian deep learning-based adaptive wind farm power prediction (BDL-AWFPP) method, which is the first time to utilize the computational fluid dynamics (CFD) simulation results as the prior of BDL-based method, thus avoiding the problem that data-driven approaches cannot be applied to newly constructed wind farms. Firstly, a CFD-based wind farm numerical simulation database and a wind turbine power curve database are established to construct a multi-source heterogeneous prior dataset. Then, the BDL-AWFPP model is proposed to utilize the multi-source heterogeneous prior dataset, which can be updated adaptively with newly acquired operational data and saved periodically throughout the life cycle. And an auxiliary aging assessment method for wind turbines is also developed according to the periodically-saved models. Finally, a stochastic variational inference (SVI)-based parameter updating algorithm is derived for the proposed BDL-AWFPP model. Case studies on an actual wind farm validate the effectiveness of the proposed method.
准确的风功率预测(WPP)对大型电力系统的安全稳定运行至关重要,数据驱动的风功率预测方法近年来得到了广泛的研究和应用。然而,由于缺乏运行数据,现有的数据驱动方法无法应用于新风场。本文提出了一种新颖的基于贝叶斯深度学习的自适应风电场功率预测(BDL-AWFPP)方法,首次将计算流体动力学(CFD)仿真结果作为基于BDL方法的先验,从而避免了数据驱动方法无法应用于新建风电场的问题。首先,建立基于 CFD 的风电场数值模拟数据库和风机功率曲线数据库,构建多源异构先验数据集。然后,提出 BDL-AWFPP 模型来利用多源异构先验数据集,该数据集可根据新获取的运行数据进行自适应更新,并在整个生命周期内定期保存。根据定期保存的模型,还开发了风力涡轮机的辅助老化评估方法。最后,为所提出的 BDL-AWFPP 模型推导出了一种基于随机变量推理(SVI)的参数更新算法。对实际风电场的案例研究验证了所提方法的有效性。
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引用次数: 0
Adaptive Multi-Mode Single-Step Power Tracking for Microinverter-Based Photovoltaic System 基于微型逆变器的光伏系统的自适应多模式单步功率跟踪
IF 8.6 1区 工程技术 Q1 ENERGY & FUELS Pub Date : 2024-07-26 DOI: 10.1109/TSTE.2024.3434493
Derick Mathew;J. Prasanth Ram;Jihun Ha;Jung-Wook Park;Young-Jin Kim
The conventional de-load power tracking algorithm, utilizing a perturb and observe method, manifests deficiencies in terms of speed, stability, and efficacy in identifying operating points within the inverter's voltage range. In this article, the Adaptive Multi-Mode Single-Step Power Tracking (AMSPT) algorithm is introduced, showcasing rapid adaptability to varying solar irradiation conditions, while mitigating energy losses and enhancing overall operational stability. Its key innovation lies in efficiently pinpointing the operating point within the inverter's specified voltage range through a single step. Upon achieving the desired operating point, the algorithm promptly suppresses oscillatory behavior, expediting the settling process and minimizing deviations around the set-point. This article substantiates the superiority of the AMSPT algorithm over existing methods, showcasing remarkable advancements in tracking accuracy, power fluctuations, and energy discrepancies across diverse PV system case studies. Comprehensive validation through theoretical analysis, simulations, and experimental setups meticulously confirms the claimed benefits of the proposed method.
传统的去负载功率跟踪算法采用扰动和观察法,在逆变器电压范围内识别工作点的速度、稳定性和有效性方面存在不足。本文介绍了自适应多模式单步功率跟踪(AMSPT)算法,该算法可快速适应不同的太阳辐照条件,同时减少能量损失并提高整体运行稳定性。该算法的主要创新点在于,通过一个步骤就能在逆变器的指定电压范围内有效地精确定位工作点。在达到所需的工作点后,该算法会迅速抑制振荡行为,加快稳定过程,并将设定点附近的偏差降至最低。这篇文章证实了 AMSPT 算法优于现有方法,在各种光伏系统案例研究中展示了跟踪精度、功率波动和能量差异方面的显著进步。通过理论分析、模拟和实验设置进行的全面验证细致地证实了所提方法的优势。
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引用次数: 0
Analysis of the Existence of Stable Equilibrium Points in the WPP-MMC System Under Symmetrical AC Fault 对称交流故障下 WPP-MMC 系统稳定平衡点的存在性分析
IF 8.6 1区 工程技术 Q1 ENERGY & FUELS Pub Date : 2024-07-25 DOI: 10.1109/TSTE.2024.3433611
Haihan Ye;Wu Chen;Heng Wu
Under the scenario of offshore wind power trans- mission, the system the wind power plant connecting to a modular multilevel converter (WPP-MMC) under faults is investigated, the fault interactions are modeled, and its impact on the existence of stable equilibrium point (SEP) is revealed, as a prerequisite for maintaining synchronization during fault ride-through. Consider- ing that both WPP and MMC have their own control dynamics, e.g., reactive current limiting mode or low voltage ride-through mode for WPP and voltage source mode or current source mode for MMC, the WPP-MMC system may exhibit multiple operating conditions, based on which the fault interactions inside the system become more complex and diverse. Focusing on this phenomenon, this paper analyzes the existence of SEP under each operating condition, so that the optimal parameter settings for maintaining synchronization can be obtained. Moreover, this paper finds an interesting phenomenon that multiple SEPs may exist under the same fault, which brings fresh reflections on the application of classic theoretical tools in WPP-MMC systems. Finally, the correctness of the theoretical analysis and parameter settings is verified by simulation results.
在海上风电输电场景下,研究了风电场与模块化多电平变流器(WPP-MMC)在故障情况下的系统,建立了故障相互作用模型,揭示了故障相互作用对稳定平衡点(SEP)存在的影响,SEP是故障穿越时保持同步的先决条件。考虑到WPP和MMC都有各自的控制动态,如WPP为无功限流模式或低电压贯穿模式,MMC为电压源模式或电流源模式,WPP-MMC系统可能呈现多种运行状态,基于此,系统内部的故障相互作用变得更加复杂和多样化。针对这一现象,本文分析了各工况下SEP的存在性,从而得到维持同步的最优参数设置。此外,本文还发现了一个有趣的现象,即在同一断层下可能存在多个sep,这给经典理论工具在WPP-MMC系统中的应用带来了新的思考。最后,通过仿真结果验证了理论分析和参数设置的正确性。
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引用次数: 0
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IEEE Transactions on Sustainable Energy
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