Pub Date : 2024-10-19DOI: 10.1016/j.ijepes.2024.110275
Edgar Mauricio Salazar Duque , Juan S. Giraldo , Pedro P. Vergara , Phuong H. Nguyen , Han (J.G.) Slootweg
In this paper, we present two multidimensional power flow formulations based on a fixed-point iteration (FPI) algorithm to efficiently solve hundreds of thousands of Power flows (PFs) in distribution systems. The presented algorithms are the base for a new TensorPowerFlow (TPF) tool and shine for their simplicity, benefiting from multicore Central processing unit (CPU) and Graphics processing unit (GPU) parallelization. We also focus on the mathematical convergence properties of the algorithm, showing that its unique solution is at the practical operational point. The proof is validated using numerical simulations showing the robustness of the FPI algorithm compared to the classical Newton–Raphson (NR) approach. In the case study, a benchmark with different PF solution methods is performed, showing that for applications requiring a yearly simulation at 1-minute resolution, the computation time is decreased by a factor of 164, compared to the NR in its sparse formulation. Finally, a set of applications is described, highlighting the potential of the proposed formulations over a wide range of analyses in distribution systems.
{"title":"Tensor power flow formulations for multidimensional analyses in distribution systems","authors":"Edgar Mauricio Salazar Duque , Juan S. Giraldo , Pedro P. Vergara , Phuong H. Nguyen , Han (J.G.) Slootweg","doi":"10.1016/j.ijepes.2024.110275","DOIUrl":"10.1016/j.ijepes.2024.110275","url":null,"abstract":"<div><div>In this paper, we present two multidimensional power flow formulations based on a fixed-point iteration (FPI) algorithm to efficiently solve hundreds of thousands of Power flows (PFs) in distribution systems. The presented algorithms are the base for a new TensorPowerFlow (TPF) tool and shine for their simplicity, benefiting from multicore Central processing unit (CPU) and Graphics processing unit (GPU) parallelization. We also focus on the mathematical convergence properties of the algorithm, showing that its unique solution is at the practical operational point. The proof is validated using numerical simulations showing the robustness of the FPI algorithm compared to the classical Newton–Raphson (NR) approach. In the case study, a benchmark with different PF solution methods is performed, showing that for applications requiring a yearly simulation at 1-minute resolution, the computation time is decreased by a factor of 164, compared to the NR in its sparse formulation. Finally, a set of applications is described, highlighting the potential of the proposed formulations over a wide range of analyses in distribution systems.</div></div>","PeriodicalId":50326,"journal":{"name":"International Journal of Electrical Power & Energy Systems","volume":"162 ","pages":"Article 110275"},"PeriodicalIF":5.0,"publicationDate":"2024-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142537865","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-19DOI: 10.1016/j.ijepes.2024.110310
Danyang Xu, Zhigang Wu
This paper introduces an enhanced frequency aware microgrid scheduling (E-FAMS) model designed to achieve seamless islanding (SI) for microgrids after experiencing an unintentional islanding event (UIE). The model addresses uncertainties in load forecasting and demand-side resources’ (DSRs) frequency support, described using a Wasserstein-metric ambiguity set, through the distributionally robust chance constrained (DRCC) approach. It concurrently optimizes unit commitment, generation dispatch, reserve capacity, power exchange, and the frequency response of heterogeneous frequency support resources (HFSRs). A quadratic frequency (QF) approach is proposed to derive sufficient conditions for the maximum frequency deviation (MFD) constraints, which are then convexified using the piecewise linear of multivariable functions (PWL-MFs) technique and integrated into the proposed model. Case study results confirm the effectiveness of the proposed model, providing a novel solution for SI in microgrids.
本文介绍了一种增强型频率感知微电网调度（E-FAMS）模型，旨在实现微电网在经历无意孤岛事件（UIE）后的无缝孤岛（SI）。该模型通过分布式稳健机会约束（DRCC）方法，解决了负荷预测和需求侧资源（DSR）频率支持中的不确定性问题，这些不确定性使用瓦瑟斯坦计量模糊集进行描述。该方法可同时优化机组承诺、发电调度、储备容量、电力交换以及异构频率支持资源（HFSR）的频率响应。提出了一种二次频率（QF）方法来推导最大频率偏差（MFD）约束的充分条件，然后使用多变量函数的分片线性（PWL-MFs）技术对其进行凸化，并将其集成到所提出的模型中。案例研究结果证实了所提模型的有效性，为微电网中的 SI 提供了一种新的解决方案。
{"title":"Enhanced frequency aware microgrid scheduling towards seamless islanding under frequency support of heterogeneous resources: A distributionally robust chance constrained approach","authors":"Danyang Xu, Zhigang Wu","doi":"10.1016/j.ijepes.2024.110310","DOIUrl":"10.1016/j.ijepes.2024.110310","url":null,"abstract":"<div><div>This paper introduces an enhanced frequency aware microgrid scheduling (E-FAMS) model designed to achieve seamless islanding (SI) for microgrids after experiencing an unintentional islanding event (UIE). The model addresses uncertainties in load forecasting and demand-side resources’ (DSRs) frequency support, described using a Wasserstein-metric ambiguity set, through the distributionally robust chance constrained (DRCC) approach. It concurrently optimizes unit commitment, generation dispatch, reserve capacity, power exchange, and the frequency response of heterogeneous frequency support resources (HFSRs). A quadratic frequency (QF) approach is proposed to derive sufficient conditions for the maximum frequency deviation (MFD) constraints, which are then convexified using the piecewise linear of multivariable functions (PWL-MFs) technique and integrated into the proposed model. Case study results confirm the effectiveness of the proposed model, providing a novel solution for SI in microgrids.</div></div>","PeriodicalId":50326,"journal":{"name":"International Journal of Electrical Power & Energy Systems","volume":"162 ","pages":"Article 110310"},"PeriodicalIF":5.0,"publicationDate":"2024-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142538615","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-19DOI: 10.1016/j.ijepes.2024.110295
Jisoo Kim, Jean Mahseredjian
In this paper, a study is conducted to solve voltage problems that may occur, when large-scale Distributed Generations (DGs) and Electric Vehicles (EVs) are connected to the distribution system, through coordinated control between DGs and EVs. Using the Graph Search Method (GSM), the voltage problem was solved through the reactive power control of EVs and DGs in the near area where the voltage problem occurred. As a result, it was possible to obtain a result with high robustness against the change of the topology and reduction of the total loss of distribution system. In addition, when the voltage problem cannot be solved by only reactive power control, the active power control was performed for EVs and DGs included in a specific divided system of the conventional distribution system using the GSM to maintain the voltage within the normal range. Finally, to verify the performance of the proposed method, the whole algorithm was implemented by linking the Open Source Distribution System Simulator (OpenDSS), and the MATLAB.
{"title":"Development of coordinated control method based on Graph search method between EV and DG for voltage regulation","authors":"Jisoo Kim, Jean Mahseredjian","doi":"10.1016/j.ijepes.2024.110295","DOIUrl":"10.1016/j.ijepes.2024.110295","url":null,"abstract":"<div><div>In this paper, a study is conducted to solve voltage problems that may occur, when large-scale Distributed Generations (DGs) and Electric Vehicles (EVs) are connected to the distribution system, through coordinated control between DGs and EVs. Using the Graph Search Method (GSM), the voltage problem was solved through the reactive power control of EVs and DGs in the near area where the voltage problem occurred. As a result, it was possible to obtain a result with high robustness against the change of the topology and reduction of the total loss of distribution system. In addition, when the voltage problem cannot be solved by only reactive power control, the active power control was performed for EVs and DGs included in a specific divided system of the conventional distribution system using the GSM to maintain the voltage within the normal range. Finally, to verify the performance of the proposed method, the whole algorithm was implemented by linking the Open Source Distribution System Simulator (OpenDSS), and the MATLAB.</div></div>","PeriodicalId":50326,"journal":{"name":"International Journal of Electrical Power & Energy Systems","volume":"162 ","pages":"Article 110295"},"PeriodicalIF":5.0,"publicationDate":"2024-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142538715","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-19DOI: 10.1016/j.ijepes.2024.110266
Rizk M. Rizk-Allah , Davut Izci , Serdar Ekinci , Ali Diabat , Absalom E. Ezugwu , Laith Abualigah
The widespread utilization of direct current (DC) motors in real-life engineering applications has led to the need for precise speed control, making controllers a crucial aspect of DC motor systems. Proportional-integral-derivative (PID) controllers have been widely adopted due to their simplicity and effectiveness. However, recent advancements have introduced fractional order PID (FOPID) controllers that offer improved control performance for complex systems with nonlinear dynamics. To fully leverage FOPID controller’s benefits, an efficient tuning method is essential. In this study, we propose artificial rabbits optimization (ARO) algorithm with enhanced strategies, called IARO, to optimize the FOPID controller for DC motor speed regulation. The IARO algorithm incorporates an adaptive local search (ALS) mechanism and an experience-based perturbed learning (EPL) strategy, addressing the shortcomings of ARO and providing better exploration–exploitation balance. We validate the superiority of IARO over competitive algorithms on the CEC2020 benchmark functions, showcasing improved solution stability and consistency. The IARO algorithm is then applied to tune the FOPID controller for DC motor speed regulation. The problem is formulated as a constraint minimization task, optimizing the integral of time-weighted absolute error cost function while adhering to critical design requirements. Comparative simulations demonstrate the IARO algorithm’s ability to achieve superior cost function values and faster convergence compared to other algorithms' based FOPID controllers. The IARO-based FOPID controller exhibits enhanced stability, smoother speed response, larger gain margin, and wider bandwidth compared to other reported algorithms. Additionally, a hardware implementation is also conducted to further validate the practical applicability of IARO based design method. The IARO-based FOPID controller showed remarkable accuracy in tracking multi-step reference inputs and robustly rejected external disturbances, outperforming other recent optimization-based controllers. Additionally, the IARO-based PID controller achieved better performance in key time-domain metrics, including lower overshoot, faster rise time, shorter settling time, and minimized peak time.
{"title":"Incorporating adaptive local search and experience-based perturbed learning into artificial rabbits optimizer for improved DC motor speed regulation","authors":"Rizk M. Rizk-Allah , Davut Izci , Serdar Ekinci , Ali Diabat , Absalom E. Ezugwu , Laith Abualigah","doi":"10.1016/j.ijepes.2024.110266","DOIUrl":"10.1016/j.ijepes.2024.110266","url":null,"abstract":"<div><div>The widespread utilization of direct current (DC) motors in real-life engineering applications has led to the need for precise speed control, making controllers a crucial aspect of DC motor systems. Proportional-integral-derivative (PID) controllers have been widely adopted due to their simplicity and effectiveness. However, recent advancements have introduced fractional order PID (FOPID) controllers that offer improved control performance for complex systems with nonlinear dynamics. To fully leverage FOPID controller’s benefits, an efficient tuning method is essential. In this study, we propose artificial rabbits optimization (ARO) algorithm with enhanced strategies, called IARO, to optimize the FOPID controller for DC motor speed regulation. The IARO algorithm incorporates an adaptive local search (ALS) mechanism and an experience-based perturbed learning (EPL) strategy, addressing the shortcomings of ARO and providing better exploration–exploitation balance. We validate the superiority of IARO over competitive algorithms on the CEC2020 benchmark functions, showcasing improved solution stability and consistency. The IARO algorithm is then applied to tune the FOPID controller for DC motor speed regulation. The problem is formulated as a constraint minimization task, optimizing the integral of time-weighted absolute error cost function while adhering to critical design requirements. Comparative simulations demonstrate the IARO algorithm’s ability to achieve superior cost function values and faster convergence compared to other algorithms' based FOPID controllers. The IARO-based FOPID controller exhibits enhanced stability, smoother speed response, larger gain margin, and wider bandwidth compared to other reported algorithms. Additionally, a hardware implementation is also conducted to further validate the practical applicability of IARO based design method. The IARO-based FOPID controller showed remarkable accuracy in tracking multi-step reference inputs and robustly rejected external disturbances, outperforming other recent optimization-based controllers. Additionally, the IARO-based PID controller achieved better performance in key time-domain metrics, including lower overshoot, faster rise time, shorter settling time, and minimized peak time.</div></div>","PeriodicalId":50326,"journal":{"name":"International Journal of Electrical Power & Energy Systems","volume":"162 ","pages":"Article 110266"},"PeriodicalIF":5.0,"publicationDate":"2024-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142538716","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-17DOI: 10.1016/j.ijepes.2024.110314
Haishu Gao , Feng Zhang , Lei Ding , Gang Zhang , Libin Yang , Athuman Salimu
Currently, when renewable generation participates in frequency regulation, the traditional control method is to emulate synchronous generators through virtual inertia control. However, virtual inertia has a time delay, so essentially, it is a fast power response. Meanwhile, virtual inertia control is likely to be affected by frequency fluctuation since it responds to the derivative of frequency. Hence, it’s worth exploring non-virtual inertia control for renewable energy when participating in frequency regulation. For this reason, a novel two-segment droop control scheme for renewable energy frequency regulation is proposed in this research. Firstly, the extended system frequency regulation (SFR) model, which contains virtual inertia with time delay, is built and analytically solved by order decrement based on the Routh approximation method. Afterwards, according to the analytical solution, time delay affects the frequency response of renewable energy. It can also be analytically proved that the non-virtual inertia control, e.g., sole droop control, could replace virtual inertia under the same frequency deviation. Still, more energy may be needed for frequency regulation. Furthermore, a novel two-segment droop control is presented, and to analytically prove its ability to replace virtual inertia, the impulse function balancing principle and the integration by parts algorithm were adopted to address the initial conditions of the differential equation. Based on the analytical expression, it can be analytically proved that a lower frequency deviation can be obtained under the same frequency regulation energy. Accordingly, a parameter-setting method for two-segment droop control was proposed. Finally, the effectiveness of the proposed method is verified by using a two-area system frequency response model, and the results reveal that it can be used to replace virtual inertia and has better performance.
{"title":"Towards non-virtual inertia control of renewable energy for frequency regulation: Modeling, analysis and new control scheme","authors":"Haishu Gao , Feng Zhang , Lei Ding , Gang Zhang , Libin Yang , Athuman Salimu","doi":"10.1016/j.ijepes.2024.110314","DOIUrl":"10.1016/j.ijepes.2024.110314","url":null,"abstract":"<div><div>Currently, when renewable generation participates in frequency regulation, the traditional control method is to emulate synchronous generators through virtual inertia control. However, virtual inertia has a time delay, so essentially, it is a fast power response. Meanwhile, virtual inertia control is likely to be affected by frequency fluctuation since it responds to the derivative of frequency. Hence, it’s worth exploring non-virtual inertia control for renewable energy when participating in frequency regulation. For this reason, a novel two-segment droop control scheme for renewable energy frequency regulation is proposed in this research. Firstly, the extended system frequency regulation (SFR) model, which contains virtual inertia with time delay, is built and analytically solved by order decrement based on the Routh approximation method. Afterwards, according to the analytical solution, time delay affects the frequency response of renewable energy. It can also be analytically proved that the non-virtual inertia control, e.g., sole droop control, could replace virtual inertia under the same frequency deviation. Still, more energy may be needed for frequency regulation. Furthermore, a novel two-segment droop control is presented, and to analytically prove its ability to replace virtual inertia, the impulse function balancing principle and the integration by parts algorithm were adopted to address the initial conditions of the differential equation. Based on the analytical expression, it can be analytically proved that a lower frequency deviation can be obtained under the same frequency regulation energy. Accordingly, a parameter-setting method for two-segment droop control was proposed. Finally, the effectiveness of the proposed method is verified by using a two-area system frequency response model, and the results reveal that it can be used to replace virtual inertia and has better performance.</div></div>","PeriodicalId":50326,"journal":{"name":"International Journal of Electrical Power & Energy Systems","volume":"162 ","pages":"Article 110314"},"PeriodicalIF":5.0,"publicationDate":"2024-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142446511","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-17DOI: 10.1016/j.ijepes.2024.110311
M. Oinonen, W.G. Morsi
Substation Automation Systems (SASs) integrate communication networks with physical equipment and are vulnerable to cyberattacks. A subset of these attacks, namely Insider attacks, are launched from knowledgeable insiders and therefore they are typically difficult to detect. This paper presents a new method for detecting and classifying Insider cyberattacks as well as power disturbances on SASs using short-length orthogonal wavelet filters in real-time using an OPAL-Real-Time (OPAL-RT) simulator. An Intrusion Detection System (IDS) is proposed in which custom-designed wavelet filters of short length are developed to better extract both the network and physical data of the SASs into time–frequency spectrograms. The advantage of using the short length filters is to provide fast detection of these time-sensitive Insider attacks and disturbances in real-time, which is a key requirement for mitigation to be possible. The generated spectrograms are fed to a Convolutional Neural Network (CNN) that automates the classification process. An experimental dataset is developed from real-time testing using OPAL-RT that implements several types of cyberattacks including Insider attacks and other popular attacks such as Denial-of-Service and False Data Injection as well as challenging attacks such as Replay and Message Suppression attacks. The results of experimentally testing the proposed method in real-time using OPAL-RT demonstrate that the use of the short-length custom-designed orthogonal wavelet filters achieves a detection accuracy of 97.37 % compared to other methods as well as a low runtime of 33.786 ms.
变电站自动化系统 (SAS) 将通信网络与物理设备集成在一起，很容易受到网络攻击。这些攻击的一个子集，即内部攻击，是由见多识广的内部人员发起的，因此通常很难被检测到。本文提出了一种新方法，利用 OPAL-Real-Time (OPAL-RT) 模拟器，使用短长正交小波滤波器实时检测 SAS 上的内部网络攻击和电力干扰，并对其进行分类。我们提出了一种入侵检测系统 (IDS)，其中开发了定制设计的短小波滤波器，以更好地将 SAS 的网络和物理数据提取到时频谱图中。使用短小波滤波器的好处是可以实时快速地检测到这些对时间敏感的内幕攻击和干扰，而这正是采取缓解措施的关键要求。生成的频谱图被送入卷积神经网络（CNN），从而自动完成分类过程。利用 OPAL-RT 实时测试开发了一个实验数据集，该数据集实现了多种类型的网络攻击，包括内部攻击和其他流行攻击（如拒绝服务和虚假数据注入），以及具有挑战性的攻击（如重播和信息抑制攻击）。使用 OPAL-RT 对所提出的方法进行实时实验测试的结果表明，与其他方法相比，使用定制设计的短长正交小波滤波器可实现 97.37 % 的检测准确率，并且运行时间仅为 33.786 毫秒。
{"title":"Real-time detection of insider attacks on substation automation systems using short length orthogonal wavelet filters and OPAL-RT","authors":"M. Oinonen, W.G. Morsi","doi":"10.1016/j.ijepes.2024.110311","DOIUrl":"10.1016/j.ijepes.2024.110311","url":null,"abstract":"<div><div>Substation Automation Systems (SASs) integrate communication networks with physical equipment and are vulnerable to cyberattacks. A subset of these attacks, namely Insider attacks, are launched from knowledgeable insiders and therefore they are typically difficult to detect. This paper presents a new method for detecting and classifying Insider cyberattacks as well as power disturbances on SASs using short-length orthogonal wavelet filters in real-time using an OPAL-Real-Time (OPAL-RT) simulator. An Intrusion Detection System (IDS) is proposed in which custom-designed wavelet filters of short length are developed to better extract both the network and physical data of the SASs into time–frequency spectrograms. The advantage of using the short length filters is to provide fast detection of these time-sensitive Insider attacks and disturbances in real-time, which is a key requirement for mitigation to be possible. The generated spectrograms are fed to a Convolutional Neural Network (CNN) that automates the classification process. An experimental dataset is developed from real-time testing using OPAL-RT that implements several types of cyberattacks including Insider attacks and other popular attacks such as Denial-of-Service and False Data Injection as well as challenging attacks such as Replay and Message Suppression attacks. The results of experimentally testing the proposed method in real-time using OPAL-RT demonstrate that the use of the short-length custom-designed orthogonal wavelet filters achieves a detection accuracy of 97.37 % compared to other methods as well as a low runtime of 33.786 ms.</div></div>","PeriodicalId":50326,"journal":{"name":"International Journal of Electrical Power & Energy Systems","volume":"162 ","pages":"Article 110311"},"PeriodicalIF":5.0,"publicationDate":"2024-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142446112","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-17DOI: 10.1016/j.ijepes.2024.110312
Diju Gao , Long Chen , Yide Wang
This paper addresses the energy management problem of hybrid ships by proposing an event-triggered model predictive control (ET-MPC) method. The novelty in this work lies in the establishment of an event-triggered mechanism and a state prediction model for energy management of hybrid ships. First, torque models of the internal combustion engine (ICE) and electric machine (EM) are developed using a data-driven approach, followed by the construction of fuel consumption and carbon emission models. Second, an event-triggered mechanism, dependent on state prediction error, is introduced and updated at each time step based on the system’s current state. Additionally, a cubature Kalman filter (CKF) is employed to estimate and correct the state prediction error, minimizing inaccuracies. A trade-off coefficient is incorporated to optimize the balance between fuel consumption and carbon emissions. The ET-MPC method results in a 0.68% difference in fuel consumption and 3.43% increase emissions compared to the traditional MPC method. However, ET-MPC significantly reduces computational overhead by 56.66. The ET-MPC method effectively allocates the ship’s energy according to the varying trade-off coefficient, achieving optimal energy management under different constraints.
{"title":"An energy trade-off management strategy for hybrid ships based on event-triggered model predictive control","authors":"Diju Gao , Long Chen , Yide Wang","doi":"10.1016/j.ijepes.2024.110312","DOIUrl":"10.1016/j.ijepes.2024.110312","url":null,"abstract":"<div><div>This paper addresses the energy management problem of hybrid ships by proposing an event-triggered model predictive control (ET-MPC) method. The novelty in this work lies in the establishment of an event-triggered mechanism and a state prediction model for energy management of hybrid ships. First, torque models of the internal combustion engine (ICE) and electric machine (EM) are developed using a data-driven approach, followed by the construction of fuel consumption and carbon emission models. Second, an event-triggered mechanism, dependent on state prediction error, is introduced and updated at each time step based on the system’s current state. Additionally, a cubature Kalman filter (CKF) is employed to estimate and correct the state prediction error, minimizing inaccuracies. A trade-off coefficient is incorporated to optimize the balance between fuel consumption and carbon emissions. The ET-MPC method results in a 0.68% difference in fuel consumption and 3.43% increase emissions compared to the traditional MPC method. However, ET-MPC significantly reduces computational overhead by 56.66. The ET-MPC method effectively allocates the ship’s energy according to the varying trade-off coefficient, achieving optimal energy management under different constraints.</div></div>","PeriodicalId":50326,"journal":{"name":"International Journal of Electrical Power & Energy Systems","volume":"162 ","pages":"Article 110312"},"PeriodicalIF":5.0,"publicationDate":"2024-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142446113","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-17DOI: 10.1016/j.ijepes.2024.110284
Paul Frutos , Juan Manuel Guerrero , Iker Muniategui , Aitor Endemaño , David Ortega , Fernando Briz
Dynamic interactions among the AC railway power supply network and power electronic converters feeding the trains can result in low-frequency oscillation (LFO) of the catenary voltage, leading to a power outage of the substation and the shutdown of train traffic. To determine the low-frequency stability of the railway traction power systems, the impedance of the power supply network and the total differential admittance of the trains are required. This paper addresses the development of an analytical small-signal model of the train input admittance. For this purpose, small-signal models of each dynamic element involved are obtained. Specifically, the small-signal vector transformation from the actual -frame to the estimated -frame is presented to model the dynamics due to errors in the coordinate rotation of the single-phase four-quadrant converter (4QC) control system. Furthermore, the quadrature signal generator second-order generalized integrator (QSG-SOGI) model is calculated in the synchronous frame. The developed admittance model is intended to accurately predict various types of instabilities and serve as a powerful tool for conducting sensitivity analyses. The validation of the proposed models will be carried out through numerical simulations involving the power supply network and train systems.
{"title":"Low-frequency oscillations in AC railway traction power systems: Train input admittance calculation and stability analysis","authors":"Paul Frutos , Juan Manuel Guerrero , Iker Muniategui , Aitor Endemaño , David Ortega , Fernando Briz","doi":"10.1016/j.ijepes.2024.110284","DOIUrl":"10.1016/j.ijepes.2024.110284","url":null,"abstract":"<div><div>Dynamic interactions among the AC railway power supply network and power electronic converters feeding the trains can result in low-frequency oscillation (LFO) of the catenary voltage, leading to a power outage of the substation and the shutdown of train traffic. To determine the low-frequency stability of the railway traction power systems, the impedance of the power supply network and the total differential admittance of the trains are required. This paper addresses the development of an analytical small-signal model of the train input admittance. For this purpose, small-signal models of each dynamic element involved are obtained. Specifically, the small-signal vector transformation from the actual <span><math><mrow><mi>d</mi><mi>q</mi></mrow></math></span>-frame to the estimated <span><math><mover><mrow><mi>d</mi><mi>q</mi></mrow><mrow><mo>̂</mo></mrow></mover></math></span>-frame is presented to model the dynamics due to errors in the coordinate rotation of the single-phase four-quadrant converter (4QC) control system. Furthermore, the quadrature signal generator second-order generalized integrator (QSG-SOGI) model is calculated in the synchronous frame. The developed admittance model is intended to accurately predict various types of instabilities and serve as a powerful tool for conducting sensitivity analyses. The validation of the proposed models will be carried out through numerical simulations involving the power supply network and train systems.</div></div>","PeriodicalId":50326,"journal":{"name":"International Journal of Electrical Power & Energy Systems","volume":"162 ","pages":"Article 110284"},"PeriodicalIF":5.0,"publicationDate":"2024-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142446111","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-16DOI: 10.1016/j.ijepes.2024.110272
Zhanhong Huang , Tao Yu , Zhenning Pan , Bairong Deng , Xuehan Zhang , Yufeng Wu , Qiaoyi Ding
Reinforcement learning, as an efficient method for solving uncertainty decision making in power systems, is widely used in multi-stage stochastic power dispatch and dynamic optimization. However, the low generalization and practicality of traditional reinforcement learning algorithms limit their online application. The dispatch strategy learned offline can only adapt to specific scenarios, and its policy performance degrades significantly if the sample drastically change or the topology variation. To fill these gaps, a novel contextual meta graph reinforcement learning (Meta-GRL) method a more general contextual Markov decision process (CMDP) modeling are proposed. The proposed Meta-GRL adopts CMDP scheme and graph representation, extracts and encodes the differentiated scene context, and can be extended to various scene changes. The upper meta-learner embedded in context in Meta-GRL is proposed to realize scene recognition. While the lower base-earner is guided to learn generalized context-specified policy. The test results in IEEE39 and open environment show that the Meta-GRL achieves more than 90% optimization and entire period applicability under the premise of saving computing resources.
{"title":"Stochastic dynamic power dispatch with high generalization and few-shot adaption via contextual meta graph reinforcement learning","authors":"Zhanhong Huang , Tao Yu , Zhenning Pan , Bairong Deng , Xuehan Zhang , Yufeng Wu , Qiaoyi Ding","doi":"10.1016/j.ijepes.2024.110272","DOIUrl":"10.1016/j.ijepes.2024.110272","url":null,"abstract":"<div><div>Reinforcement learning, as an efficient method for solving uncertainty decision making in power systems, is widely used in multi-stage stochastic power dispatch and dynamic optimization. However, the low generalization and practicality of traditional reinforcement learning algorithms limit their online application. The dispatch strategy learned offline can only adapt to specific scenarios, and its policy performance degrades significantly if the sample drastically change or the topology variation. To fill these gaps, a novel contextual meta graph reinforcement learning (Meta-GRL) method a more general contextual Markov decision process (CMDP) modeling are proposed. The proposed Meta-GRL adopts CMDP scheme and graph representation, extracts and encodes the differentiated scene context, and can be extended to various scene changes. The upper meta-learner embedded in context in Meta-GRL is proposed to realize scene recognition. While the lower base-earner is guided to learn generalized context-specified policy. The test results in IEEE39 and open environment show that the Meta-GRL achieves more than 90% optimization and entire period applicability under the premise of saving computing resources.</div></div>","PeriodicalId":50326,"journal":{"name":"International Journal of Electrical Power & Energy Systems","volume":"162 ","pages":""},"PeriodicalIF":5.0,"publicationDate":"2024-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142441787","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-10-16DOI: 10.1101/2023.06.29.547014
Alexandre Segers, Jeroen Gilis, Mattias Van Heetvelde, Davide Risso, Elfride De Baere, Lieven Clement
RNA-seq data analysis relies on many different tools, each tailored to specific applications and coming with unique assumptions and restrictions. Indeed, tools for differential transcript usage, or diagnosing patients with rare diseases through splicing and expression outliers, either lack in performance, discard information, or do not scale to massive data compendia. Here, we show that replacing the normalisation offsets unlocks bulk RNA-seq workflows for scalable differential usage, aberrant splicing and expression analyses. Our method, saseR, is much faster than state-of-the-art methods, dramatically outperforms these to detect aberrant splicing, and provides a single workflow for various short- and long-read RNA-seq applications.
{"title":"saseR: Juggling offsets unlocks RNA-seq tools for fast and Scalable differential usage, Aberrant Splicing and Expression Retrieval.","authors":"Alexandre Segers, Jeroen Gilis, Mattias Van Heetvelde, Davide Risso, Elfride De Baere, Lieven Clement","doi":"10.1101/2023.06.29.547014","DOIUrl":"10.1101/2023.06.29.547014","url":null,"abstract":"<p><p>RNA-seq data analysis relies on many different tools, each tailored to specific applications and coming with unique assumptions and restrictions. Indeed, tools for differential transcript usage, or diagnosing patients with rare diseases through splicing and expression outliers, either lack in performance, discard information, or do not scale to massive data compendia. Here, we show that replacing the normalisation offsets unlocks bulk RNA-seq workflows for scalable differential usage, aberrant splicing and expression analyses. Our method, saseR, is much faster than state-of-the-art methods, dramatically outperforms these to detect aberrant splicing, and provides a single workflow for various short- and long-read RNA-seq applications.</p>","PeriodicalId":50326,"journal":{"name":"International Journal of Electrical Power & Energy Systems","volume":"62 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11507730/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76189396","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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