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Resonance Characterization and Frequency-Divided Compensation Strategy for Heterogeneous Inverters-Paralleled System
IF 5.7 1区 工程技术 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC Pub Date : 2024-11-28 DOI: 10.35833/MPCE.2024.000416
Hongbin Lin;Pingjuan Ge;Hailiang Xu;Yuhan Duan
Currently, the dominant trend in new energy power supply systems is the heterogeneous inverters-paralleled system (HIPS), which is a combination of grid-following (GFL) and grid-forming (GFM) inverters. The dynamic characteristics of different inverters in HIPS and the differences between GFL and GFM inverters undoubtedly increase the difficulty of the stability analysis and coordinated control. This paper establishes an interactive admittance matrix model of HIPS, fully considers the interactive effects among different inverters, and explores the multi-dimensional resonance characteristics of HIPS by utilizing the modal analysis method. To achieve the coordi-nated control and oscillation suppression among different inverters, a frequency-divided compensation strategy is proposed, which divides the operation modes of HIPS into three catego-ries, i. e., GFM, GFL, and hybrid modes. Specifically, the frequency division boundary is determined based on the resonance characteristics of GFL and GFM inverters, with the operation modes of HIPS being dynamically adjusted according to the harmonic power ratio. Finally, the simulation and experimental results demonstrate that the HIPS can flexibly adjust the operation modes to adapt to the complex conditions after adopting the frequency-divided compensation strategy and suppressing the oscillation frequency ratio to less than 2%, ensuring the safe and reliable operation of HIPS.
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引用次数: 0
Hybrid Frequency-domain Modeling and Stability Analysis for Power Systems with Grid-following and Grid-forming Converters
IF 5.7 1区 工程技术 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC Pub Date : 2024-11-27 DOI: 10.35833/MPCE.2023.000842
Ni Liu;Hong Wang;Weihua Zhou;Jie Song;Yiting Zhang;Eduardo Prieto-Araujo;Zhe Chen
With the increase of the renewable energy generator capacity, the requirements of the power system for grid-connected converters are evolve, which leads to diverse control schemes and increased complexity of systematic stability analysis. Although various frequency-domain models are developed to identify oscillation causes, the discrepancies between them are rarely studied. This study aims to clarify these discrepancies and provide circuit insights for stability analysis by using different frequency-domain models. This study emphasizes the limitations of assuming that the transfer function of the self-stable converter does not have right half-plane (RHP) poles. To ensure that the self-stable converters are represented by a frequency-domain model without RHP poles, the applicability of this model of grid-following (GFL) and grid-forming (GFM) converters is discussed. This study recommends that the GFM converters with ideal sources should be represented in parallel with the $P/Q-theta/V$ admittance model rather than the V-I impedance model. Two cases are conducted to illustrate the rationality of the $P/Q-theta/V$ admittance model. Additionally, a hybrid frequency-domain modeling framework and stability criteria are proposed for the power system with several GFL and GFM converters. The stability criteria eliminates the need to check the RHP pole numbers in the non-passive subsystem when applying the Nyquist stability criterion, thereby reducing the complexity of stability analysis. Simulations are carried out to validate the correctness of the frequency-domain model and the stability criteria.
随着可再生能源发电机容量的增加,电力系统对并网变流器的要求也在不断提高,这就导致控制方案的多样化和系统稳定性分析的复杂性增加。虽然人们开发了各种频域模型来识别振荡原因,但很少研究它们之间的差异。本研究旨在澄清这些差异,并通过使用不同的频域模型为稳定性分析提供电路见解。本研究强调了假设自稳定转换器的传递函数没有右半平面(RHP)极点的局限性。为确保自稳定转换器由无 RHP 极点的频域模型表示,本研究讨论了该模型对电网跟随 (GFL) 和电网形成 (GFM) 转换器的适用性。本研究建议,具有理想源的 GFM 转换器应并联使用 $P/Q-theta/V$ 导纳模型,而不是 V-I 阻抗模型。通过两个案例说明了 $P/Q-theta/V$ 导纳模型的合理性。此外,还为具有多个 GFL 和 GFM 转换器的电力系统提出了混合频域建模框架和稳定性标准。在应用奈奎斯特稳定性准则时,该稳定性准则无需检查非无源子系统中的 RHP 极数,从而降低了稳定性分析的复杂性。通过仿真验证了频域模型和稳定性准则的正确性。
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引用次数: 0
Power Switching Based on Trajectory Planning and Sliding Mode Control for Solid Oxide Fuel Cell Systems 基于轨迹规划和滑模控制的固体氧化物燃料电池系统功率切换
IF 5.7 1区 工程技术 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC Pub Date : 2024-11-07 DOI: 10.35833/MPCE.2024.000284
Zhen Wang;Guoqiang Liu;Xingbo Liu;Jie Wang;Zhiyang Jin;Xiaowei Fu;Zhuo Wang;Bing Jin;Zhonghua Deng;Xi Li
To improve the safety of the solid oxide fuel cell (SOFC) systems and avoid the generation of large amounts of pollutants during power switching, this paper designs a power switching strategy based on trajectory planning and sliding mode control (TP-SMC). The design elements of the power switching strategy are proposed through simulation analysis at first. Then, based on the gas transmission delay time and the change of gas flow obtained from testing, trajectory planning (TP) is implemented. Compared with other power switching strategies, it has been proven that the power switching strategy based on TP has significantly better control performance. Furthermore, considering the shortcomings and problems of TP in practical application, this paper introduces sliding mode control (SMC) on the basis of TP to improve the power switching strategy. The final simulation results also prove that the TP-SMC can effectively suppress the impact of uncertainty in gas flow and gas transmission delay time. Compared with TP, TP-SMC can ensure that under uncertain conditions, the SOFC system does not experience fuel starvation and temperature exceeding limit during power switching. Meanwhile, the NOx emissions are also within the normal and acceptable range. This paper can guide the power switching process of the actual SOFC systems to avoid safety issues and excessive generation of NOx, which is very helpful for improving the performance and service life of the SOFC systems.
为了提高固体氧化物燃料电池(SOFC)系统的安全性,避免功率切换时产生大量污染物,本文设计了一种基于轨迹规划和滑模控制(TP-SMC)的功率切换策略。首先通过仿真分析提出了功率切换策略的设计要素。然后,根据测试得到的气体传输延迟时间和气体流量变化,实现了轨迹规划(TP)。实践证明,与其他功率切换策略相比,基于 TP 的功率切换策略具有明显更好的控制性能。此外,考虑到 TP 在实际应用中的缺点和问题,本文在 TP 的基础上引入了滑模控制(SMC),以改进功率切换策略。最终的仿真结果也证明,TP-SMC 能有效抑制气体流量和输气延迟时间不确定性的影响。与 TP 相比,TP-SMC 可确保在不确定条件下,SOFC 系统在功率切换过程中不会出现燃料过剩和温度超限现象。同时,氮氧化物的排放也在正常和可接受的范围内。本文可以指导实际 SOFC 系统的功率切换过程,避免安全问题和氮氧化物的过量产生,这对提高 SOFC 系统的性能和使用寿命非常有帮助。
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引用次数: 0
Low-Frequency Oscillations and Resonance Analysis of VSG-Controlled PMSG-based Wind Generation Systems
IF 5.7 1区 工程技术 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC Pub Date : 2024-10-24 DOI: 10.35833/MPCE.2024.000465
Yizhuo Ma;Jin Xu;Chenxiang Gao;Guojie Li;Keyou Wang
With good adaptability to weak power grids, the grid-forming inverter becomes the foundation of future power grids with high-proportion renewable energy. Moreover, the virtual synchronous generator (VSG) control is recognized as the mainstream control strategy for grid-forming inverters. For permanent magnet synchronous generator (PMSG) based wind generation systems connected to power grid via VSG-controlled grid-forming inverters, some novel impacts on the low-frequency oscillations (LFOs) emerge in power grids. The first impact involves the negative/positive damping effect on LFOs. In this paper, the small-signal torque model of VSG-controlled PMSG-based wind generation systems is established based on the damping torque analysis method, revealing the influence mechanism of machine-side dynamics on LFOs and proving the necessity of the double-mass model for accurate stability analysis. The second impact is the resonance effect between torsional oscillation and LFOs. Subsequently, this paper uses the open-loop resonance analysis method to study the resonance mechanism and to predict the root trajectory. Then, a damping enhancement strategy is proposed to weaken and eliminate the negative damping effect of machine-side dynamics on LFOs and the resonance effect between torsional oscillation and LFOs. Finally, the analysis result is validated through a case study involving the connection of the VSG-controlled PMSG-based wind generation system to the IEEE 39-bus AC grid, supporting the industrial application and stable operation of VSG-controlled PMSG-based wind generation systems.
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引用次数: 0
Graph Attention Network Based Deep Reinforcement Learning for Voltage/var Control of Topologically Variable Power System
IF 5.7 1区 工程技术 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC Pub Date : 2024-10-04 DOI: 10.35833/MPCE.2023.000712
Xiaofei Liu;Pei Zhang;Hua Xie;Xuegang Lu;Xiangyu Wu;Zhao Liu
The high proportion of renewable energy integration and the dynamic changes in grid topology necessitate the enhancement of voltage/var control (VVC) to manage voltage fluctuations more rapidly. Traditional model-based control algorithms are becoming increasingly incompetent for VVC due to their high model dependence and slow online computation speed. To alleviate these issues, this paper introduces a graph attention network (GAT) based deep reinforcement learning for VVC of topologically variable power system. Firstly, combining the physical information of the actual power grid, a physics-informed GAT is proposed and embedded into the proximal policy optimization (PPO) algorithm. The GAT-PPO algorithm can capture topological and spatial correlations among the node features to tackle topology changes. To address the slow training, the ReliefF -S algorithm identifies critical state variables, significantly reducing the dimensionality of state space. Then, the training samples retained in the experience buffer are designed to mitigate the sparse reward issue. Finally, the validation on the modified IEEE 39-bus system and an actual power grid demonstrates superior performance of the proposed algorithm compared with state-of-the-art algorithms, including PPO algorithm and twin delayed deep deterministic policy gradient (TD3) algorithm. The proposed algorithm exhibits enhanced convergence during training, faster solution speed, and improved VVC performance, even in scenarios involving grid topology changes and increased renewable energy integration. Meanwhile, in the adopted cases, the network loss is reduced by 6.9%, 10.80%, and 7.70%, respectively, demonstrating favorable economic outcomes.
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引用次数: 0
Voltage Sag Monitor Placement for Fault Location Detection Based on Precise Determination of Areas of Vulnerability 基于精确确定易受影响区域的故障定位检测电压波动监测器安置方法
IF 5.7 1区 工程技术 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC Pub Date : 2024-09-13 DOI: 10.35833/MPCE.2023.001022
Mojtaba Hajiahmadi;Rahmat-Allah Hooshmand;Arash Kiyoumarsi
The increase in the number of sensitive loads in power systems has made power quality, particularly voltage sag, a prominent problem due to its effects on consumers from both the utility and customer perspectives. Thus, to evaluate the effects of voltage sag caused by short circuits, it is necessary to determine the areas of vulnerability (AOVs). In this paper, a new method is proposed for the AOV determination that is applicable to large-scale networks. The false position method (FPM) is proposed for the precise calculation of the critical points of the system lines. Furthermore, a new method is proposed for the voltage sag monitor (VSM) placement to detect the fault locations. A systematic placement scheme is used to provide the highest fault location detection (FLD) index at buses and lines for various short-circuit fault types. To assess the efficiency of the proposed methods for AOV determination and VSM placement, simulations are conducted in IEEE standard systems. The results demonstrate the accuracy of the proposed method for AOV determination. In addition, through VSM placement, the fault locations at buses and lines are detected.
电力系统中敏感负载数量的增加使电能质量,尤其是电压下陷成为一个突出的问题,因为从电力公司和客户的角度来看,电压下陷都会对消费者产生影响。因此,要评估短路造成的电压下陷影响,就必须确定易受影响的区域(AOV)。本文提出了一种适用于大规模网络的 AOV 确定新方法。为精确计算系统线路的临界点,提出了错误位置法(FPM)。此外,还提出了一种新的电压下陷监控器(VSM)布置方法,用于检测故障位置。针对各种短路故障类型,采用了一种系统化的放置方案,以在母线和线路上提供最高的故障位置检测(FLD)指数。为了评估所提出的 AOV 确定和 VSM 布置方法的效率,在 IEEE 标准系统中进行了模拟。结果表明,所提出的 AOV 确定方法非常准确。此外,通过 VSM 布置,还检测到了总线和线路的故障位置。
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引用次数: 0
Resonance Assessment of Large-scale Wind Park Connected to Primary Distribution Network
IF 5.7 1区 工程技术 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC Pub Date : 2024-09-02 DOI: 10.35833/MPCE.2024.000127
Andrés Argüello;Ricardo Torquato;Walmir Freitas
On-shore wind parks are typically connected to the high-voltage (HV) transmission system through a bulk transformer. However, wind generators may be connected directly at a medium-voltage (MV) level, such as a utility-owned primary distribution network, if the network is capable of sustaining the power flow and ensuring adequate power quality for its users. This paper presents the findings of a comprehensive study on the management of resonance in a utility-owned wind park in Costa Rica. The wind park is connected directly to the MV primary distribution network and has no shunt capacitor for power factor correction. The results demonstrate that such configuration has a higher immunity to resonances, as the total grid equivalent impedance perceived by the wind park is typically dominated by the absent HV/MV transformer and shunt capacitor bank. Moreover, the capacitance provided by the underground feeders of the wind park did not result in natural oscillation frequencies in the range of typical harmonic distortions observed in MV distribution networks that violated power quality standards.
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引用次数: 0
DistFlow Safe Reinforcement Learning Algorithm for Voltage Magnitude Regulation in Distribution Networks
IF 5.7 1区 工程技术 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC Pub Date : 2024-08-26 DOI: 10.35833/MPCE.2024.000253
Shengren Hou;Aihui Fu;Edgar Mauricio Salazar Duque;Peter Palensky;Qixin Chen;Pedro P. Vergara
The integration of distributed energy resources (DERs) has escalated the challenge of voltage magnitude regulation in distribution networks. Model-based approaches, which rely on complex sequential mathematical formulations, cannot meet the real-time demand. Deep reinforcement learning (DRL) offers an alternative by utilizing offline training with distribution network simulators and then executing online without computation. However, DRL algorithms fail to enforce voltage magnitude constraints during training and testing, potentially leading to serious operational violations. To tackle these challenges, we introduce a novel safe-guaranteed reinforcement learning algorithm, the DistFlow safe reinforcement learning (DF-SRL), designed specifically for real-time voltage magnitude regulation in distribution networks. The DF-SRL algorithm incorporates a DistFlow linearization to construct an expert-knowledge-based safety layer. Subsequently, the DF-SRL algorithm overlays this safety layer on top of the agent policy, recalibrating unsafe actions to safe domains through a quadratic programming formulation. Simulation results show the DF-SRL algorithm consistently ensures voltage magnitude constraints during training and real-time operation (test) phases, achieving faster convergence and higher performance, which differentiates it apart from (safe) DRL benchmark algorithms.
{"title":"DistFlow Safe Reinforcement Learning Algorithm for Voltage Magnitude Regulation in Distribution Networks","authors":"Shengren Hou;Aihui Fu;Edgar Mauricio Salazar Duque;Peter Palensky;Qixin Chen;Pedro P. Vergara","doi":"10.35833/MPCE.2024.000253","DOIUrl":"https://doi.org/10.35833/MPCE.2024.000253","url":null,"abstract":"The integration of distributed energy resources (DERs) has escalated the challenge of voltage magnitude regulation in distribution networks. Model-based approaches, which rely on complex sequential mathematical formulations, cannot meet the real-time demand. Deep reinforcement learning (DRL) offers an alternative by utilizing offline training with distribution network simulators and then executing online without computation. However, DRL algorithms fail to enforce voltage magnitude constraints during training and testing, potentially leading to serious operational violations. To tackle these challenges, we introduce a novel safe-guaranteed reinforcement learning algorithm, the DistFlow safe reinforcement learning (DF-SRL), designed specifically for real-time voltage magnitude regulation in distribution networks. The DF-SRL algorithm incorporates a DistFlow linearization to construct an expert-knowledge-based safety layer. Subsequently, the DF-SRL algorithm overlays this safety layer on top of the agent policy, recalibrating unsafe actions to safe domains through a quadratic programming formulation. Simulation results show the DF-SRL algorithm consistently ensures voltage magnitude constraints during training and real-time operation (test) phases, achieving faster convergence and higher performance, which differentiates it apart from (safe) DRL benchmark algorithms.","PeriodicalId":51326,"journal":{"name":"Journal of Modern Power Systems and Clean Energy","volume":"13 1","pages":"300-311"},"PeriodicalIF":5.7,"publicationDate":"2024-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10648969","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143105722","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Power System Reliability Evaluation Based on Sequential Monte Carlo Simulation Considering Multiple Failure Modes of Components 基于顺序蒙特卡洛模拟的电力系统可靠性评估(考虑组件的多种失效模式
IF 5.7 1区 工程技术 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC Pub Date : 2024-08-26 DOI: 10.35833/MPCE.2023.000939
Wei Huang;Bo Hu;Changzheng Shao;Wei Li;Xiaozhe Wang;Kaigui Xie;C. Y. Chung
The component aging has become a significant concern worldwide, and the frequent failures pose a serious threat to the reliability of modern power systems. In light of this issue, this paper presents a power system reliability evaluation method based on sequential Monte Carlo simulation (SMCS) to quantify system reliability considering multiple failure modes of components. First, a three-state component reliability model is established to explicitly describe the state transition process of the component subject to both aging failure and random failure modes. In this model, the impact of each failure mode is decoupled and characterized as the combination of two state duration variables, which are separately modeled using specific probability distributions. Subsequently, SMCS is used to integrate the three-state component reliability model for state transition sequence generation and system reliability evaluation. Therefore, various reliability metrics, including the probability of load curtailment (PLC), expected frequency of load curtailment (EFLC), and expected energy not supplied (EENS), can be estimated. To ensure the applicability of the proposed method, Hash table grouping and the maximum feasible load level judgment techniques are jointly adopted to enhance its computational performance. Case studies are conducted on different aging scenarios to illustrate and validate the effectiveness and practicality of the proposed method.
{"title":"Power System Reliability Evaluation Based on Sequential Monte Carlo Simulation Considering Multiple Failure Modes of Components","authors":"Wei Huang;Bo Hu;Changzheng Shao;Wei Li;Xiaozhe Wang;Kaigui Xie;C. Y. Chung","doi":"10.35833/MPCE.2023.000939","DOIUrl":"https://doi.org/10.35833/MPCE.2023.000939","url":null,"abstract":"The component aging has become a significant concern worldwide, and the frequent failures pose a serious threat to the reliability of modern power systems. In light of this issue, this paper presents a power system reliability evaluation method based on sequential Monte Carlo simulation (SMCS) to quantify system reliability considering multiple failure modes of components. First, a three-state component reliability model is established to explicitly describe the state transition process of the component subject to both aging failure and random failure modes. In this model, the impact of each failure mode is decoupled and characterized as the combination of two state duration variables, which are separately modeled using specific probability distributions. Subsequently, SMCS is used to integrate the three-state component reliability model for state transition sequence generation and system reliability evaluation. Therefore, various reliability metrics, including the probability of load curtailment (PLC), expected frequency of load curtailment (EFLC), and expected energy not supplied (EENS), can be estimated. To ensure the applicability of the proposed method, Hash table grouping and the maximum feasible load level judgment techniques are jointly adopted to enhance its computational performance. Case studies are conducted on different aging scenarios to illustrate and validate the effectiveness and practicality of the proposed method.","PeriodicalId":51326,"journal":{"name":"Journal of Modern Power Systems and Clean Energy","volume":"13 1","pages":"202-214"},"PeriodicalIF":5.7,"publicationDate":"2024-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10648964","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143184067","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Simulation-Based Approach to Assessing Short-Term Power Variations of PV Power Plants Under Cloud Conditions 基于仿真的云条件下光伏电站短期功率变化评估方法
IF 5.7 1区 工程技术 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC Pub Date : 2024-08-26 DOI: 10.35833/MPCE.2024.000460
Eric Bernard Dilger;Ricardo Vasques de Oliveira
The output power variability of photovoltaic (PV) power plants (PVPPs) is one of the major challenges for the operation and control of power systems. The short-term power variations, mainly caused by cloud movements, affect voltage magnitude and frequency, which may degrade power quality and power system reliability. Comprehensive analyses of these power variations are crucial to formulate novel control approaches and assist power system operators in the operation and control of power systems. Thus, this paper proposes a simulation-based approach to assessing short-term power variations caused by clouds in PV power plants. A comprehensive assessment of the short-term power variations in a PV power plant operating under cloud conditions is another contribution of this paper. The performed analysis evaluates the individual impact of multiple weather condition parameters on the magnitude and ramp rate of the power variations. The simulation-based approach synthesizes the solar irradiance time series using three-dimensional fractal surfaces. The proposed assessment approach has shown that the PVPP nominal power, timescale, cloud coverage level, wind speed, period of the day, and shadow intensity level significantly affect the characteristics of the power variations.
光伏电站(PVPP)的输出功率变化是电力系统运行和控制面临的主要挑战之一。主要由云层移动引起的短期功率变化会影响电压幅值和频率,从而降低电能质量和电力系统的可靠性。全面分析这些功率变化对于制定新型控制方法和协助电力系统运营商运行和控制电力系统至关重要。因此,本文提出了一种基于仿真的方法来评估光伏电站中由云层引起的短期功率变化。本文的另一个贡献是全面评估了在云条件下运行的光伏电站的短期功率变化。所进行的分析评估了多种天气条件参数对功率变化幅度和斜率的单独影响。基于模拟的方法使用三维分形曲面合成了太阳辐照度时间序列。所提出的评估方法表明,PVPP 标称功率、时间尺度、云层覆盖水平、风速、一天中的时段和阴影强度水平对功率变化的特征有显著影响。
{"title":"Simulation-Based Approach to Assessing Short-Term Power Variations of PV Power Plants Under Cloud Conditions","authors":"Eric Bernard Dilger;Ricardo Vasques de Oliveira","doi":"10.35833/MPCE.2024.000460","DOIUrl":"https://doi.org/10.35833/MPCE.2024.000460","url":null,"abstract":"The output power variability of photovoltaic (PV) power plants (PVPPs) is one of the major challenges for the operation and control of power systems. The short-term power variations, mainly caused by cloud movements, affect voltage magnitude and frequency, which may degrade power quality and power system reliability. Comprehensive analyses of these power variations are crucial to formulate novel control approaches and assist power system operators in the operation and control of power systems. Thus, this paper proposes a simulation-based approach to assessing short-term power variations caused by clouds in PV power plants. A comprehensive assessment of the short-term power variations in a PV power plant operating under cloud conditions is another contribution of this paper. The performed analysis evaluates the individual impact of multiple weather condition parameters on the magnitude and ramp rate of the power variations. The simulation-based approach synthesizes the solar irradiance time series using three-dimensional fractal surfaces. The proposed assessment approach has shown that the PVPP nominal power, timescale, cloud coverage level, wind speed, period of the day, and shadow intensity level significantly affect the characteristics of the power variations.","PeriodicalId":51326,"journal":{"name":"Journal of Modern Power Systems and Clean Energy","volume":"12 6","pages":"1837-1848"},"PeriodicalIF":5.7,"publicationDate":"2024-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10648966","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142844607","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
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Journal of Modern Power Systems and Clean Energy
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