International Journal of Electrical Power & Energy Systems最新文献

英文中文

A multiple choice relaxation model to solve the AC optimal power flow

IF 5 2区工程技术 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC

International Journal of Electrical Power & Energy Systems

Pub Date : 2025-02-18 DOI: 10.1016/j.ijepes.2025.110533

Fatemeh Zadehmohammadi, Hossein Sharifzadeh

Mathematically speaking, AC optimal power flow (OPF), seeking an optimal state of a power system, is an NP-hard nonconvex optimization problem. In the past two decades, many researchers have attempted to accurately solve the AC OPF problem, that is, derive its globally optimal solution, primarily using relaxation methods. This paper presents a mixed-integer relaxation of AC OPF relying on polyhedral envelopes and a multiple choice model. To this end, first, we recast all nonlinear terms in the AC OPF as bilinear and quadratic terms having known linear approximation errors. Then, all these terms are replaced with their polyhedral envelopes. Last, the polyhedral envelopes are represented as a mixed-integer linear relaxation model using the multiple choice modeling technique. We also design an iterative solution method with a bound-tightening technique where one can improve the approximate functions and derive tighter relaxations progressively. The conducted computational experiment shows that the presented method can tightly relax the AC OPF and accurately solve the adopted case studies. The presented comparisons with 43 previous studies show that the proposed method can outperform earlier AC OPF solution techniques in solution optimality in the adopted case studies.

{"title":"A multiple choice relaxation model to solve the AC optimal power flow","authors":"Fatemeh Zadehmohammadi, Hossein Sharifzadeh","doi":"10.1016/j.ijepes.2025.110533","DOIUrl":"10.1016/j.ijepes.2025.110533","url":null,"abstract":"<div><div>Mathematically speaking, AC optimal power flow (OPF), seeking an optimal state of a power system, is an NP-hard nonconvex optimization problem. In the past two decades, many researchers have attempted to accurately solve the AC OPF problem, that is, derive its globally optimal solution, primarily using relaxation methods. This paper presents a mixed-integer relaxation of AC OPF relying on polyhedral envelopes and a multiple choice model. To this end, first, we recast all nonlinear terms in the AC OPF as bilinear and quadratic terms having known linear approximation errors. Then, all these terms are replaced with their polyhedral envelopes. Last, the polyhedral envelopes are represented as a mixed-integer linear relaxation model using the multiple choice modeling technique. We also design an iterative solution method with a bound-tightening technique where one can improve the approximate functions and derive tighter relaxations progressively. The conducted computational experiment shows that the presented method can tightly relax the AC OPF and accurately solve the adopted case studies. The presented comparisons with 43 previous studies show that the proposed method can outperform earlier AC OPF solution techniques in solution optimality in the adopted case studies.</div></div>","PeriodicalId":50326,"journal":{"name":"International Journal of Electrical Power & Energy Systems","volume":"166 ","pages":"Article 110533"},"PeriodicalIF":5.0,"publicationDate":"2025-02-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143437275","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}

引用次数: 0

Improved cross-entropy-based power system reliability evaluation using GMM with highly-efficient closed-form parameter updating

IF 5 2区工程技术 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC

International Journal of Electrical Power & Energy Systems

Pub Date : 2025-02-18 DOI: 10.1016/j.ijepes.2025.110535

Yuan Zhao, Jiaqin Hu, Kaigui Xie, Junjie Tang

The reliability evaluation of composite generation and transmission systems (CSRE) is essential for power system planning and operation but often faces significant computational challenges. To accelerate CSRE, the Gaussian mixture model (GMM), known for its ability to model arbitrary probability densities, has been incorporated into the Cross-Entropy Method (CEM) to estimate the importance sampling probability density function (IS-PDF) of continuous random variables, such as correlated wind speeds and system load. However, the classical CEM produces a non-closed-form solution for the GMM-based IS-PDF, resulting in an alternating parameter updating procedure for the GMM parameter set and larger pre-simulation cost. To address this issue and enhance the simulation speed of CEM-based CSRE, an improved CEM with a highly efficient closed-form parameter updating mechanism is proposed. By developing an equivalent variant of the GMM that belongs to the exponential family, a closed-form solution is derived, eliminating the need for alternating updates. The improved CEM achieves higher efficiency and simplifies the modeling of the GMM-based IS-PDF. Numerical tests are conducted to validate the performance and advantages of the proposed method.

{"title":"Improved cross-entropy-based power system reliability evaluation using GMM with highly-efficient closed-form parameter updating","authors":"Yuan Zhao, Jiaqin Hu, Kaigui Xie, Junjie Tang","doi":"10.1016/j.ijepes.2025.110535","DOIUrl":"10.1016/j.ijepes.2025.110535","url":null,"abstract":"<div><div>The reliability evaluation of composite generation and transmission systems (CSRE) is essential for power system planning and operation but often faces significant computational challenges. To accelerate CSRE, the Gaussian mixture model (GMM), known for its ability to model arbitrary probability densities, has been incorporated into the Cross-Entropy Method (CEM) to estimate the importance sampling probability density function (IS-PDF) of continuous random variables, such as correlated wind speeds and system load. However, the classical CEM produces a non-closed-form solution for the GMM-based IS-PDF, resulting in an alternating parameter updating procedure for the GMM parameter set and larger pre-simulation cost. To address this issue and enhance the simulation speed of CEM-based CSRE, an improved CEM with a highly efficient closed-form parameter updating mechanism is proposed. By developing an equivalent variant of the GMM that belongs to the exponential family, a closed-form solution is derived, eliminating the need for alternating updates. The improved CEM achieves higher efficiency and simplifies the modeling of the GMM-based IS-PDF. Numerical tests are conducted to validate the performance and advantages of the proposed method.</div></div>","PeriodicalId":50326,"journal":{"name":"International Journal of Electrical Power & Energy Systems","volume":"166 ","pages":"Article 110535"},"PeriodicalIF":5.0,"publicationDate":"2025-02-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143437168","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}

引用次数: 0

An efficient approach for diagnosing faults in photovoltaic array using 1D-CNN and feature selection Techniques

IF 5 2区工程技术 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC

International Journal of Electrical Power & Energy Systems

Pub Date : 2025-02-18 DOI: 10.1016/j.ijepes.2025.110526

Yousif Mahmoud Ali , Lei Ding , Shiyao Qin

Diagnosing faults in Photovoltaic (PV) systems is essential for operation and maintenance. Selecting relevant features is necessary for successful fault diagnosis because redundant and irrelevant features reduce fault diagnosing accuracy. This paper proposes a novel and efficient approach to diagnosing faults in PV systems. The Feature Selection and Fault Diagnosis (FSFD) method is executed for diagnosing five types of faults in PV array (PVA): partial shading condition, line-line fault, arc fault, open-circuit fault, and degradation fault. Firstly, a PVA modeling method using MATLAB/Simulink is employed to simulate I-V curves and extract their features. Next, a feature permutation technique-based method is proposed for selecting the most relevant features. A simple and accurate one-dimensional convolutional neural network (1D-CNN) model is developed to classify the faults based on the selected features. Finally, a confusion matrix is utilized to evaluate the performance of the trained model. Three datasets of PVAs have been utilized to evaluate the effectiveness of the proposed FSFD method. The results indicate that the FSFD method has effectively identified the best five features out of eight for training the 1D-CNN model. The trained model has achieved diagnosing accuracy rates of 99.85%, 99.73%, and 99.97% in series–parallel PVA, total cross-tied PVA, and series PVA datasets, respectively. The proposed method accurately diagnoses single faults in three PVA configurations. Therefore, we recommend conducting additional studies to improve the proposed method for diagnosing hybrid faults.

{"title":"An efficient approach for diagnosing faults in photovoltaic array using 1D-CNN and feature selection Techniques","authors":"Yousif Mahmoud Ali , Lei Ding , Shiyao Qin","doi":"10.1016/j.ijepes.2025.110526","DOIUrl":"10.1016/j.ijepes.2025.110526","url":null,"abstract":"<div><div>Diagnosing faults in Photovoltaic (PV) systems is essential for operation and maintenance. Selecting relevant features is necessary for successful fault diagnosis because redundant and irrelevant features reduce fault diagnosing accuracy. This paper proposes a novel and efficient approach to diagnosing faults in PV systems. The Feature Selection and Fault Diagnosis (FSFD) method is executed for diagnosing five types of faults in PV array (PVA): partial shading condition, line-line fault, arc fault, open-circuit fault, and degradation fault. Firstly, a PVA modeling method using MATLAB/Simulink is employed to simulate I-V curves and extract their features. Next, a feature permutation technique-based method is proposed for selecting the most relevant features. A simple and accurate one-dimensional convolutional neural network (1D-CNN) model is developed to classify the faults based on the selected features. Finally, a confusion matrix is utilized to evaluate the performance of the trained model. Three datasets of PVAs have been utilized to evaluate the effectiveness of the proposed FSFD method. The results indicate that the FSFD method has effectively identified the best five features out of eight for training the 1D-CNN model. The trained model has achieved diagnosing accuracy rates of 99.85%, 99.73%, and 99.97% in series–parallel PVA, total cross-tied PVA, and series PVA datasets, respectively. The proposed method accurately diagnoses single faults in three PVA configurations. Therefore, we recommend conducting additional studies to improve the proposed method for diagnosing hybrid faults.</div></div>","PeriodicalId":50326,"journal":{"name":"International Journal of Electrical Power & Energy Systems","volume":"166 ","pages":"Article 110526"},"PeriodicalIF":5.0,"publicationDate":"2025-02-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143437165","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}

引用次数: 0

Study on the mechanism of horizontally striped contamination distribution along the surface of dry-type transformers and its influence on electric field characteristics

IF 5 2区工程技术 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC

International Journal of Electrical Power & Energy Systems

Pub Date : 2025-02-18 DOI: 10.1016/j.ijepes.2025.110542

Xinhan Qiao , Wei Li , Yue Ming , Zishang Zhu , Wentian Zeng , Yijiao Wang

Dry-type transformers have the advantages of strong anti-short circuit ability, low maintenance workload, and low noise. They are commonly used in places with high performance requirements for fire and explosion prevention. However, due to the direct exposure of its insulation material to air, surface discharge in specific environments poses a threat to the safe operation of transformers. This paper observed a special contamination distribution of “horizontally striped contamination on the surface of high-voltage windings” in engineering practice, and discovered a corresponding new phenomenon of “surface discharge along a circular path”. Therefore, this paper systematically studied this special phenomenon through finite element and micro mechanical analysis. This paper found that a specific winding connection sequence can lead to a larger local electric field. The electric field force exerted on contaminated particles after being charged is the main reason for the formation of “horizontally striped contamination”. The “horizontally striped contamination” further leads to an increase in electric field, ultimately forming a new phenomenon of “surface discharge along a circular path”. In addition, wet contamination can create dry areas, and wet contamination with dry areas can cause more severe distortion of the electric field on the surface of transformers. The surface electric field of wet inorganic salt contamination with dry areas is the most severely distorted. The maximum electric field strength can reach 3.6562 kV/cm. Compared to the maximum electric field strength of 1.1581 kV/cm without pollution, it increases by 215.71 %. The research results of this paper can provide theoretical basis for the optimization design of winding structure of dry-type transformers in polluted regions.

{"title":"Study on the mechanism of horizontally striped contamination distribution along the surface of dry-type transformers and its influence on electric field characteristics","authors":"Xinhan Qiao , Wei Li , Yue Ming , Zishang Zhu , Wentian Zeng , Yijiao Wang","doi":"10.1016/j.ijepes.2025.110542","DOIUrl":"10.1016/j.ijepes.2025.110542","url":null,"abstract":"<div><div>Dry-type transformers have the advantages of strong anti-short circuit ability, low maintenance workload, and low noise. They are commonly used in places with high performance requirements for fire and explosion prevention. However, due to the direct exposure of its insulation material to air, surface discharge in specific environments poses a threat to the safe operation of transformers. This paper observed a special contamination distribution of “horizontally striped contamination on the surface of high-voltage windings” in engineering practice, and discovered a corresponding new phenomenon of “surface discharge along a circular path”. Therefore, this paper systematically studied this special phenomenon through finite element and micro mechanical analysis. This paper found that a specific winding connection sequence can lead to a larger local electric field. The electric field force exerted on contaminated particles after being charged is the main reason for the formation of “horizontally striped contamination”. The “horizontally striped contamination” further leads to an increase in electric field, ultimately forming a new phenomenon of “surface discharge along a circular path”. In addition, wet contamination can create dry areas, and wet contamination with dry areas can cause more severe distortion of the electric field on the surface of transformers. The surface electric field of wet inorganic salt contamination with dry areas is the most severely distorted. The maximum electric field strength can reach 3.6562 kV/cm. Compared to the maximum electric field strength of 1.1581 kV/cm without pollution, it increases by 215.71 %. The research results of this paper can provide theoretical basis for the optimization design of winding structure of dry-type transformers in polluted regions.</div></div>","PeriodicalId":50326,"journal":{"name":"International Journal of Electrical Power & Energy Systems","volume":"166 ","pages":"Article 110542"},"PeriodicalIF":5.0,"publicationDate":"2025-02-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143437167","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}

引用次数: 0

Distributed coordinated control for voltage regulation in active distribution networks based on robust model predictive control

IF 5 2区工程技术 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC

International Journal of Electrical Power & Energy Systems

Pub Date : 2025-02-18 DOI: 10.1016/j.ijepes.2025.110529

Guocheng Song , Qiuwei Wu , Wenshu Jiao , Lina Lu

As the integration of renewable energy sources increases, the uncertainty of wind power and photovoltaics bring new challenges to the voltage control problem of active distribution networks (ADNs). To address these challenges, this paper proposes a double-time-scale distributed voltage control strategy for ADNs based on robust model predictive control (RMPC), which considers the coordination between multiple voltage regulation devices. In the slow-time-scale control (STC), on-load Tap changers (OLTC), step voltage regulators (SVR), and capacitor banks (CBs) are optimized to minimize long-term voltage deviations and reduce tap operations of these traditional regulation devices. On this basis, in the fast-time-scale control (FTC), the active and reactive power outputs of distributed generators (DGs) are further optimized based on RMPC to regulate the fast voltage fluctuations while considering the uncertainty of DG outputs. The RMPC model is formulated as a minimum–maximum convex optimization problem, which is transformed into a quadratic programming problem. Moreover, by equivalently processing of adjacent control areas in ADNs, the distribution network model established based on voltage sensitivity method is decomposed to accelerate the solving process. The effectiveness of the proposed double-time-scale distributed RMPC voltage control scheme has been verified in a modified Italia 54-bus system. Results demonstrate that, compared to conventional deterministic centralized control, the proposed scheme achieves 63% reduction for the maximum voltage deviation.

{"title":"Distributed coordinated control for voltage regulation in active distribution networks based on robust model predictive control","authors":"Guocheng Song , Qiuwei Wu , Wenshu Jiao , Lina Lu","doi":"10.1016/j.ijepes.2025.110529","DOIUrl":"10.1016/j.ijepes.2025.110529","url":null,"abstract":"<div><div>As the integration of renewable energy sources increases, the uncertainty of wind power and photovoltaics bring new challenges to the voltage control problem of active distribution networks (ADNs). To address these challenges, this paper proposes a double-time-scale distributed voltage control strategy for ADNs based on robust model predictive control (RMPC), which considers the coordination between multiple voltage regulation devices. In the slow-time-scale control (STC), on-load Tap changers (OLTC), step voltage regulators (SVR), and capacitor banks (CBs) are optimized to minimize long-term voltage deviations and reduce tap operations of these traditional regulation devices. On this basis, in the fast-time-scale control (FTC), the active and reactive power outputs of distributed generators (DGs) are further optimized based on RMPC to regulate the fast voltage fluctuations while considering the uncertainty of DG outputs. The RMPC model is formulated as a minimum–maximum convex optimization problem, which is transformed into a quadratic programming problem. Moreover, by equivalently processing of adjacent control areas in ADNs, the distribution network model established based on voltage sensitivity method is decomposed to accelerate the solving process. The effectiveness of the proposed double-time-scale distributed RMPC voltage control scheme has been verified in a modified Italia 54-bus system. Results demonstrate that, compared to conventional deterministic centralized control, the proposed scheme achieves 63% reduction for the maximum voltage deviation.</div></div>","PeriodicalId":50326,"journal":{"name":"International Journal of Electrical Power & Energy Systems","volume":"166 ","pages":"Article 110529"},"PeriodicalIF":5.0,"publicationDate":"2025-02-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143429650","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}

引用次数: 0

Multi-perspective collaborative planning of DN and distribution energy stations with stepped carbon trading and adaptive evolutionary game

IF 5 2区工程技术 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC

International Journal of Electrical Power & Energy Systems

Pub Date : 2025-02-17 DOI: 10.1016/j.ijepes.2025.110522

Xiong Peng , Yudi Ding , Jiayan Liu , Yong Li , Kai Yuan

Distributed energy stations (DES), coupled with multiple energy equipment, can participate in the distribution network (DN) regulation. Thus, a multi-perspective collaborative planning method considering DES is proposed in this paper. Firstly, a double layer DN planning structure from the overall perspective is proposed. By considering the planning layer and the operation layer, the overall planning cost can be minimized. Then, the benefit relationships among DN operators, DG operators, and energy station (ES) operators are analyzed, and the benefit models of different stakeholders are established. On this basis, the multi-agent game planning model of DN considering the limited rationality of stakeholders is constructed. And then, the optimal planning and operation scheme of the DN with DES is determined through the adaptive evolutionary game method. Finally, the effectiveness of the proposed method is verified through the simulation of a certain 42-node distribution system.

引用次数: 0

IGDT-based demand response strategy for an integrated energy system considering its interactions with multi-energy markets

IF 5 2区工程技术 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC

International Journal of Electrical Power & Energy Systems

Pub Date : 2025-02-17 DOI: 10.1016/j.ijepes.2025.110516

Biao Wu, Shaohua Zhang, Chenxin Yuan, Xian Wang, Fei Wang, Shengqi Zhang

An integrated energy system (IES) can achieve multi-energy complementarity via its integrated demand response (IDR) program. With the continuous development of IES and the advancement of its marketization, investigating the IDR strategy of IES when it acts as a price maker in multi-energy markets holds significant importance. In this paper, we propose a bi-level model to determine the IDR strategy of an IES by considering its interactions with multi-energy markets. The upper-level formulates the IES’s IDR decision-making in response to the electricity and natural gas prices, including electricity purchases from the electricity market (EM), natural gas purchases from the natural gas market (NGM), electricity and heat consumption. The lower-level describes the games of supply function bidding among the power generators (PGs) in EM and the natural gas companies (NGCs) in NGM. Specifically, using ordinal potential game (OPG) theory, we construct an ordinal potential function (OPF) for the OPG model of multi-energy markets. This enables us to find the Nash equilibrium (NE) of the games in EM and NGM through the multi-energy markets’ OPF. The information gap decision theory (IGDT) is employed to address the severe uncertainty of wind power. Furthermore, the existence and uniqueness of the solution for the bi-level model are theoretically proven. Based on this, we develop a distributed algorithm to handle the information asymmetry. Simulation results demonstrate the effectiveness of the proposed model and algorithm, revealing that when IES acts as a price maker in multi-energy markets, it can mitigate the market power of both PGs and NGCs.

{"title":"IGDT-based demand response strategy for an integrated energy system considering its interactions with multi-energy markets","authors":"Biao Wu, Shaohua Zhang, Chenxin Yuan, Xian Wang, Fei Wang, Shengqi Zhang","doi":"10.1016/j.ijepes.2025.110516","DOIUrl":"10.1016/j.ijepes.2025.110516","url":null,"abstract":"<div><div>An integrated energy system (IES) can achieve multi-energy complementarity via its integrated demand response (IDR) program. With the continuous development of IES and the advancement of its marketization, investigating the IDR strategy of IES when it acts as a price maker in multi-energy markets holds significant importance. In this paper, we propose a bi-level model to determine the IDR strategy of an IES by considering its interactions with multi-energy markets. The upper-level formulates the IES’s IDR decision-making in response to the electricity and natural gas prices, including electricity purchases from the electricity market (EM), natural gas purchases from the natural gas market (NGM), electricity and heat consumption. The lower-level describes the games of supply function bidding among the power generators (PGs) in EM and the natural gas companies (NGCs) in NGM. Specifically, using ordinal potential game (OPG) theory, we construct an ordinal potential function (OPF) for the OPG model of multi-energy markets. This enables us to find the Nash equilibrium (NE) of the games in EM and NGM through the multi-energy markets’ OPF. The information gap decision theory (IGDT) is employed to address the severe uncertainty of wind power. Furthermore, the existence and uniqueness of the solution for the bi-level model are theoretically proven. Based on this, we develop a distributed algorithm to handle the information asymmetry. Simulation results demonstrate the effectiveness of the proposed model and algorithm, revealing that when IES acts as a price maker in multi-energy markets, it can mitigate the market power of both PGs and NGCs.</div></div>","PeriodicalId":50326,"journal":{"name":"International Journal of Electrical Power & Energy Systems","volume":"166 ","pages":"Article 110516"},"PeriodicalIF":5.0,"publicationDate":"2025-02-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143421383","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}

引用次数: 0

Modeling and application of DQ-sequence dynamic phasors under unbalanced AC conditions

IF 5 2区工程技术 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC

International Journal of Electrical Power & Energy Systems

Pub Date : 2025-02-16 DOI: 10.1016/j.ijepes.2025.110524

Xiaoming Mao , Hongbo Luo , Wenda Zhong , Liang Wu , Zhiyong Yuan

Increasing unbalanced AC operating conditions generates the need of developing models for power electronic equipment in such situations. The dq-sequence dynamic phasor method is proposed in this paper to model power electronic devices controlled in dq-rotating coordinates. Firstly, the instantaneous symmetric component decomposition and Park transformation are sequentially performed on a set of three-phase time-domain signals to define the dq-sequence dynamic phasors. Then, the multiplication property is derived. Next, the general steps for forming the state equations are provided, and the specific expressions of the state matrices are derived. Furthermore, a method is provided for quickly separating the real and imaginary parts of the complex-form state equations, as well as obtaining their simplest real-form. Case study on a two-terminal Modular Multilevel Converter − High Voltage Direct Current system verifies the effectiveness of the proposed modeling method. And the developed state space model is compared with existing similar models to show its advantages.

{"title":"Modeling and application of DQ-sequence dynamic phasors under unbalanced AC conditions","authors":"Xiaoming Mao , Hongbo Luo , Wenda Zhong , Liang Wu , Zhiyong Yuan","doi":"10.1016/j.ijepes.2025.110524","DOIUrl":"10.1016/j.ijepes.2025.110524","url":null,"abstract":"<div><div>Increasing unbalanced AC operating conditions generates the need of developing models for power electronic equipment in such situations. The <em>dq</em>-sequence dynamic phasor method is proposed in this paper to model power electronic devices controlled in <em>dq</em>-rotating coordinates. Firstly, the instantaneous symmetric component decomposition and Park transformation are sequentially performed on a set of three-phase time-domain signals to define the <em>dq</em>-sequence dynamic phasors. Then, the multiplication property is derived. Next, the general steps for forming the state equations are provided, and the specific expressions of the state matrices are derived. Furthermore, a method is provided for quickly separating the real and imaginary parts of the complex-form state equations, as well as obtaining their simplest real-form. Case study on a two-terminal Modular Multilevel Converter − High Voltage Direct Current system verifies the effectiveness of the proposed modeling method. And the developed state space model is compared with existing similar models to show its advantages.</div></div>","PeriodicalId":50326,"journal":{"name":"International Journal of Electrical Power & Energy Systems","volume":"166 ","pages":"Article 110524"},"PeriodicalIF":5.0,"publicationDate":"2025-02-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143421381","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}

引用次数: 0

A multi-modal feature combination mechanism for identification of harmonic load in distribution networks based on artificial intelligence models

IF 5 2区工程技术 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC

International Journal of Electrical Power & Energy Systems

Pub Date : 2025-02-14 DOI: 10.1016/j.ijepes.2025.110519

Renzeng Yang , Shuang Peng , Gang Yao

The challenge of harmonic pollution in active distribution networks is inherently complex, a data-driven approach being necessitated to comprehensively capture the nonlinear and non-stationary characteristics of harmonic power sequence signals, thereby enhancing recognition accuracy. To achieve intelligent identification of harmonic loads within distribution networks, an innovative methodology that integrates parameter-optimized variational mode decomposition with sequential neural networks is proposed. Firstly, based on IEEE Std. 1459-2010 power theory, the harmonic apparent power distortion caused by nonlinear loads is calculated. Secondly, using an optimization algorithm, the penalty parameter and the number of intrinsic mode functions in variational mode decomposition are fine-tuned to decompose the harmonic power sequence and extract intrinsic mode functions. The most suitable intrinsic mode sequences are selected as input features for sequential neural networks training. Finally, a multi-modal feature tensor combination mechanism that integrates reshaped vector layers into the sequential neural networks architecture is introduced, enabling adaptive extraction of spatial–temporal characteristics and significantly improving the accuracy of harmonic load identification without prior knowledge of their spectral features.

{"title":"A multi-modal feature combination mechanism for identification of harmonic load in distribution networks based on artificial intelligence models","authors":"Renzeng Yang , Shuang Peng , Gang Yao","doi":"10.1016/j.ijepes.2025.110519","DOIUrl":"10.1016/j.ijepes.2025.110519","url":null,"abstract":"<div><div>The challenge of harmonic pollution in active distribution networks is inherently complex, a data-driven approach being necessitated to comprehensively capture the nonlinear and non-stationary characteristics of harmonic power sequence signals, thereby enhancing recognition accuracy. To achieve intelligent identification of harmonic loads within distribution networks, an innovative methodology that integrates parameter-optimized variational mode decomposition with sequential neural networks is proposed. Firstly, based on IEEE Std. 1459-2010 power theory, the harmonic apparent power distortion caused by nonlinear loads is calculated. Secondly, using an optimization algorithm, the penalty parameter and the number of intrinsic mode functions in variational mode decomposition are fine-tuned to decompose the harmonic power sequence and extract intrinsic mode functions. The most suitable intrinsic mode sequences are selected as input features for sequential neural networks training. Finally, a multi-modal feature tensor combination mechanism that integrates reshaped vector layers into the sequential neural networks architecture is introduced, enabling adaptive extraction of spatial–temporal characteristics and significantly improving the accuracy of harmonic load identification without prior knowledge of their spectral features.</div></div>","PeriodicalId":50326,"journal":{"name":"International Journal of Electrical Power & Energy Systems","volume":"166 ","pages":"Article 110519"},"PeriodicalIF":5.0,"publicationDate":"2025-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143421380","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}

引用次数: 0

Synthetic inertia estimation in the presence of measurement noise and delays: An application to wind turbine generators

IF 5 2区工程技术 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC

International Journal of Electrical Power & Energy Systems

Pub Date : 2025-02-13 DOI: 10.1016/j.ijepes.2025.110511

Valentina Baruzzi, Alessandro Rosini, Matteo Lodi, Andrea Bonfiglio, Alberto Oliveri

Synthetic inertia generation is essential in power grids with high penetration of renewable energy sources (RES). The inverters interfacing the RES with the grid are equipped with dedicated controllers that set a power reference proportional to the rate of change of the electrical frequency (RoCoF) of the grid. In the grid following configuration, the RoCoF must be evaluated in real-time, but measurement noise and delays make the real provided inertia deviate from the imposed one. This work aims to quantify the effects of measurement noise and delays on the synthetic inertia provided by a grid-following inverter equipped with a virtual hidden inertia emulator, connected to a wind farm. Both simulations and experimental tests exploiting a hardware prototype and a real-time simulator are carried out in different scenarios.

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全部化学•材料生命科学医学物理工程技术环境•农林材料科学地球科学法学管理学化学环境科学与生态学计算机科学教育学经济学农林科学人文科学生物学数学物理与天体物理心理学综合性期刊其他工业工程理学历史学农学文学信息工程

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International Journal of Electrical Power & Energy Systems

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