Electric Power Systems Research最新文献_第4页

MSGCN: Multi-task Spectral Graph Convolutional model for identification of branch parameters considered grid topology

IF 3.3 3区工程技术

Electric Power Systems Research Pub Date : 2025-02-16 DOI: 10.1016/j.epsr.2025.111525

Ziheng Liu , Bochao Zheng , Min Xia , Jun Liu

{"title":"MSGCN: Multi-task Spectral Graph Convolutional model for identification of branch parameters considered grid topology","authors":"Ziheng Liu , Bochao Zheng , Min Xia , Jun Liu","doi":"10.1016/j.epsr.2025.111525","DOIUrl":"10.1016/j.epsr.2025.111525","url":null,"abstract":"<div><div>This paper addresses issues associated with existing methods for power system branch parameter identification, such as the inability to consider transmission line topology, handling large-scale power grid data, and high sensitivity to data contamination. A method called Multi-Task Spectral Graph Convolutional Network (MSGCN) is proposed for power system branch parameter identification tasks. This method utilizes a novel aggregation method called Simplified Spectral Graph Convolution (SSGConv) to simplify graph convolution operations. It introduces graph adaptive normalization and a learnable skip-connection mechanism to enhance the model’s robustness and scalability. Additionally, the method incorporates a graph attention mechanism, enabling our model to automatically learn the power grid branch topology, reducing the influence of data contamination on branch parameter identification accuracy. It adopts a self-balancing loss function of the multi-task model based on homoscedastic uncertainty to simultaneously identify multiple branch parameters, improving both the accuracy and training speed of the model. Experimental results demonstrate that this method outperforms traditional approaches and other graph neural network methods in terms of efficiency and accuracy in branch parameter identification.</div></div>","PeriodicalId":50547,"journal":{"name":"Electric Power Systems Research","volume":"243 ","pages":"Article 111525"},"PeriodicalIF":3.3,"publicationDate":"2025-02-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143419617","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Canyon load curve management and network loss reduction using Virtual Storage Bank

IF 3.3 3区工程技术

Electric Power Systems Research Pub Date : 2025-02-14 DOI: 10.1016/j.epsr.2025.111496

Shubham Verma , Sanjeev Pannala , Ankush Sharma , Noel Schulz , Prabodh Bajpai

{"title":"Canyon load curve management and network loss reduction using Virtual Storage Bank","authors":"Shubham Verma , Sanjeev Pannala , Ankush Sharma , Noel Schulz , Prabodh Bajpai","doi":"10.1016/j.epsr.2025.111496","DOIUrl":"10.1016/j.epsr.2025.111496","url":null,"abstract":"<div><div>This work focuses on establishing a Virtual Storage Bank (VSB) utilizing electric vehicle (EVs) and electric bus (e-bus) fleets located in various places such as households, office parking areas, EV charging stations, and school parking lots. These assets can be used as a source or load during their idle state. This work introduces the VSB, a novel concept offering dynamic storage resource sharing within clusters and beyond in the distribution network(DN). The VSB helps maintain the power balance for managing the canyon load curve and minimizing network loss by intelligently distributing storage based on availability and network requirements. This collaborative approach to storage management unlocks new possibilities for optimized power sharing within and across clusters, contributing to a more efficient and resilient power grid. The VSB formation process considers feature states such as power demand, storage capacity, and owner participation willingness. Coordination of e-fleets is achieved by focusing on Time-of-Use (ToU) pricing. The study validated a standard IEEE 13-bus distribution network, demonstrating the success of VSB formation in meeting power demand and reducing network losses. Sensitivity analysis was performed on the IEEE 13-bus distribution network, and the study was extended to the IEEE 34-bus system for scalability and practicality.</div></div>","PeriodicalId":50547,"journal":{"name":"Electric Power Systems Research","volume":"243 ","pages":"Article 111496"},"PeriodicalIF":3.3,"publicationDate":"2025-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143419960","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Energy capture efficiency enhancement for PMVG based-wind turbine systems through yaw control using wind direction prediction

IF 3.3 3区工程技术

Electric Power Systems Research Pub Date : 2025-02-14 DOI: 10.1016/j.epsr.2025.111490

Ameerkhan Abdul Basheer , Jeong Jae Hoon , Lee Seong Ryong , Song Dongran , Joo Young Hoon

{"title":"Energy capture efficiency enhancement for PMVG based-wind turbine systems through yaw control using wind direction prediction","authors":"Ameerkhan Abdul Basheer , Jeong Jae Hoon , Lee Seong Ryong , Song Dongran , Joo Young Hoon","doi":"10.1016/j.epsr.2025.111490","DOIUrl":"10.1016/j.epsr.2025.111490","url":null,"abstract":"<div><div>Accurate wind direction prediction is fundamental for the efficient operation of wind turbines and is also important for optimizing the performance and efficiency of the wind turbine system (WTS). In this study, we present a wind time-series-based prediction technique using a deep neural network (NN) approach to predict the wind direction and also aim to do the maximum power extraction (MPE) of a permanent magnet vernier generator (PMVG)-based WTS using the proposed model predictive control (MPC)-based yaw control method to improve its energy capture efficiency. To do this, an echo state network (ESN) approach is designed with a non-linear function and extended Kalman filter (EKF) to handle the non-linearities and improve prediction accuracy by eliminating noisy measurements, thus predicting the wind direction at an effective rate. Next, the performance of the proposed direction prediction model is compared with other prediction methods. The predicted wind direction is utilized in a finite control set model predictive control (FCS-MPC)-based yaw control strategy, enabling optimal turbine alignment and maximizing energy capture efficiency. Finally, superiority and robust performance of the proposed controller are evaluated and compared to existing control methods such as proportional–integral (PI), proportional–integral–derivative (PID) and baseline MPC using simulation of 4.8 MW PMVG-based benchmark WTS.</div></div>","PeriodicalId":50547,"journal":{"name":"Electric Power Systems Research","volume":"243 ","pages":"Article 111490"},"PeriodicalIF":3.3,"publicationDate":"2025-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143419962","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Droop-based power routers for enhanced resilience in networked grids

IF 3.3 3区工程技术

Electric Power Systems Research Pub Date : 2025-02-14 DOI: 10.1016/j.epsr.2025.111475

Joan-Marc Rodriguez-Bernuz , Vinicius Gadelha , Eduard Bullich-Massagué , Andreas Sumper

{"title":"Droop-based power routers for enhanced resilience in networked grids","authors":"Joan-Marc Rodriguez-Bernuz , Vinicius Gadelha , Eduard Bullich-Massagué , Andreas Sumper","doi":"10.1016/j.epsr.2025.111475","DOIUrl":"10.1016/j.epsr.2025.111475","url":null,"abstract":"<div><div>The design and operation of the current power system are characterized by the integration of distributed energy resources and the evolving dynamics of modern electrical grids. Recent studies have explored the design of a novel concept for a fully controllable network: the Power Router Grid (PRG). This innovative grid concept uses power electronics devices to fully control the system’s power flows. These power electronic assets are commonly referred to as Power Routers (PRs). While the conceptual grid offers numerous advantages, its operation depends on the specific functionality of the converters, which may not always be guaranteed. This can result in reduced resilience during system contingencies or device failures.</div><div>In this context, this article proposes a new control design option for the PRG by introducing an adjustable droop regulator approach to manage the internal DC bus energy of PRs, enhancing the functionality of PRG designs. The flexibility of the system is expected to be improved by developing a mode of operation for the PRG based on the energy of the PR node. Additionally, the proposed strategy is formulated to reduce energy dispatch errors caused by the droop action during steady-state operation while enhancing system resilience, without compromising the tracking capabilities of PR devices. The proposed approach has been validated through dynamic simulations and tested in representative scenarios with varying operating conditions and contingencies. The results demonstrate the PRG’s ability to continue operating even with the loss of a PR in the power flow path, highlighting its potential to enhance system resilience.</div></div>","PeriodicalId":50547,"journal":{"name":"Electric Power Systems Research","volume":"243 ","pages":"Article 111475"},"PeriodicalIF":3.3,"publicationDate":"2025-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143419961","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A bidirectional charging system with the capability to charge electric vehicles with low-voltage powered batteries

IF 3.3 3区工程技术

Electric Power Systems Research Pub Date : 2025-02-14 DOI: 10.1016/j.epsr.2025.111501

Utsav Sharma, Bhim Singh

{"title":"A bidirectional charging system with the capability to charge electric vehicles with low-voltage powered batteries","authors":"Utsav Sharma, Bhim Singh","doi":"10.1016/j.epsr.2025.111501","DOIUrl":"10.1016/j.epsr.2025.111501","url":null,"abstract":"<div><div>Due to the freedom to choose battery voltage levels in the absence of standardisation in the industry, electric two/three wheelers are available with distinct voltage rating batteries. In addition, interest in vehicle-to-grid (V2 G) operations has recently increased. Considering this, a bidirectional charger circuit is realised in this work, which operates effectively with a wide range of electric two/three wheelers. Moreover, the charger circuit is capable of bidirectional operation. Furthermore, the charger's operation with a wide range of batteries, high voltage step-down, and controlled ripple content in battery current and low switch count is achieved. This charger's topology uses a voltage source converter and a single-ended primary-inductance converter (SEPIC) with a modification. Since the modified SEPIC maintains the continuous current at the output, the battery current ripples are kept within 10 % of the battery charging current. The effectiveness of the designed charger is validated, and an experimental investigation is presented. A test bench set up in the laboratory achieves >90 % efficiency throughout the operation. Moreover, the charger's efficacy is validated under distinct conditions. Furthermore, the charger's behaviour during the V2 G function is conferred. Finally, the charger's circuit is assessed by comparing operational features.</div></div>","PeriodicalId":50547,"journal":{"name":"Electric Power Systems Research","volume":"243 ","pages":"Article 111501"},"PeriodicalIF":3.3,"publicationDate":"2025-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143419959","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Online optimization of integrated energy systems based on deep learning predictive control

IF 3.3 3区工程技术

Electric Power Systems Research Pub Date : 2025-02-13 DOI: 10.1016/j.epsr.2025.111510

Yuefen Gao , Yiying Zhang , Chengbo Yun , Lizhuang Huang

{"title":"Online optimization of integrated energy systems based on deep learning predictive control","authors":"Yuefen Gao , Yiying Zhang , Chengbo Yun , Lizhuang Huang","doi":"10.1016/j.epsr.2025.111510","DOIUrl":"10.1016/j.epsr.2025.111510","url":null,"abstract":"<div><div>With the large-scale grid connection of new energy sources, their high randomness and volatility bring great challenges to the grid. Using deep learning to predict uncertain renewable energy resources has emerged as a promising technology. This paper presents a deep learning-based approach to forecast the power generation of wind and photovoltaic power with the aim of reducing the adverse effects of uncertainty in optimal scheduling problems. Meanwhile, the multi-objective optimization model of the regionally integrated energy system is established by combining the system operation and maintenance cost and system revenue. The system is optimized online by an accelerated particle swarm optimization. The results show that compared to the online optimization with the single APSO method, the operation and maintenance costs are reduced by 60.8 CNY on a typical cooling day and 52.01 CNY on a typical heating day. The utilization rate of renewable energy in the cooling and heating periods is improved by 5.88 % and 0.65 % and the CO2 emission reduction rate is 6.99% in the system. The integrated energy system online optimization method proposed in this study based on deep learning and accelerated particle swarm optimization can reduce operation and maintenance costs, improve the utilization rate of renewable energy.</div></div>","PeriodicalId":50547,"journal":{"name":"Electric Power Systems Research","volume":"243 ","pages":"Article 111510"},"PeriodicalIF":3.3,"publicationDate":"2025-02-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143394794","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Iterative matrix fitting approach of frequency dependent matrices based on vector fitting

IF 3.3 3区工程技术

Electric Power Systems Research Pub Date : 2025-02-13 DOI: 10.1016/j.epsr.2025.111499

E.S. Bañuelos-Cabral , J.A. Gutiérrez-Robles , J.J. Nuño-Ayón , M.G. Vega-Grijalva , J.L. Naredo , J. Sotelo-Castañón

{"title":"Iterative matrix fitting approach of frequency dependent matrices based on vector fitting","authors":"E.S. Bañuelos-Cabral , J.A. Gutiérrez-Robles , J.J. Nuño-Ayón , M.G. Vega-Grijalva , J.L. Naredo , J. Sotelo-Castañón","doi":"10.1016/j.epsr.2025.111499","DOIUrl":"10.1016/j.epsr.2025.111499","url":null,"abstract":"<div><div>Rational fitting techniques are the basis for modeling the physical behaviors of systems with respect to their input and output characteristics. Due to its robustness and accuracy, Vector Fitting (VF) has been widely used to obtain rational models from tabulated frequency domain responses. Three types of systems could be approximated: 1) A scalar function or scalar fitting (SF) case, 2) A column vector function or column fitting (CF) case, and 3) A matrix function or matrix fitting (MF) case. A common set of poles is desired for physical and implementation reasons. This is a fact in the SF case, and the mathematical formulation of VF allows obtaining a rational function-based model with a common set of poles in the CF case. However, as this is not possible in the MF case, a methodology based on the VF iteration is proposed, which ensures a common set of poles. The advantages are demonstrated in three test cases: 1) Multi-phase transmission-line modeling using the Universal Line Model (ULM), 2) Multi-block data analysis, and 3) Printed Circuit Board (PCB) transmission-line characterization.</div></div>","PeriodicalId":50547,"journal":{"name":"Electric Power Systems Research","volume":"243 ","pages":"Article 111499"},"PeriodicalIF":3.3,"publicationDate":"2025-02-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143403561","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

The total accommodation capability curve for a distribution network considering N-1 criterion

IF 3.3 3区工程技术

Electric Power Systems Research Pub Date : 2025-02-12 DOI: 10.1016/j.epsr.2025.111508

Jun Xiao , Luyan Xue , Xun Jiang , Chuanqi Wang , Haishen Liang , Kangli Wang

{"title":"The total accommodation capability curve for a distribution network considering N-1 criterion","authors":"Jun Xiao , Luyan Xue , Xun Jiang , Chuanqi Wang , Haishen Liang , Kangli Wang","doi":"10.1016/j.epsr.2025.111508","DOIUrl":"10.1016/j.epsr.2025.111508","url":null,"abstract":"<div><div>The total accommodation capability curve (TAC curve) can completely describe the DG accommodation capability of a distribution network. The urban distribution network generally adopts the security constraints under N-1 criterion, but the formulation of the TAC curve in the existing studies only considers the network constraints under normal operation conditions considering N-0 criterion. To fill this gap, this paper develops a TAC curve model considering security constraints under N-1 criterion in distribution networks. The model is based on alternating current (AC) power flow because the problem of voltage override after DG integration cannot be ignored. Then, the solution and plotting method of the TAC curve are proposed. The method is based on the DC power flow model combined with voltage calibration correction, which is easy to solve and accurate. Finally, test systems are used to verify the proposed model and method. The rules between the N-1 TAC curve and the N-0 TAC curve and the main factors affecting the TAC curve are analyzed. The application of the TAC curve to planning is also provided.</div></div>","PeriodicalId":50547,"journal":{"name":"Electric Power Systems Research","volume":"243 ","pages":"Article 111508"},"PeriodicalIF":3.3,"publicationDate":"2025-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143394795","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Ultra-short-term Wind power prediction algorithm based on bidirectional neural controlled differential equations

IF 3.3 3区工程技术

Electric Power Systems Research Pub Date : 2025-02-12 DOI: 10.1016/j.epsr.2025.111479

Chu Li , Bingjia Xiao , Qiping Yuan

{"title":"Ultra-short-term Wind power prediction algorithm based on bidirectional neural controlled differential equations","authors":"Chu Li , Bingjia Xiao , Qiping Yuan","doi":"10.1016/j.epsr.2025.111479","DOIUrl":"10.1016/j.epsr.2025.111479","url":null,"abstract":"<div><div>Against the backdrop of the continuous growth of the new energy electricity trading market, improving the accuracy of ultra-short-term electricity forecasting and reducing lag are crucial for new energy enterprises. This article proposes a ultra-short-term wind power prediction model (Bi-NDCE-UPF) based on bidirectional neural control differential equations to explore ways to improve prediction accuracy and lag. It has two innovative points: 1. A bidirectional neural controllable ordinary differential model for ultra-short-term power forecasting has been proposed. Compared with Bi-GRU and Bi-LSTM, this model has significantly improved the accuracy and delay of the third point in ultra-short-term forecasting. 2. A prediction delay mitigation structure has been designed to effectively alleviate the lag and distortion of prediction data. This algorithm has been validated in four wind farms in central China and has unique advantages. We use four metrics to evaluate all models: MSE, MAE, Dynamic Time Warping (DTW), and Time Distortion Index (TDI). Compared with Bi-GRU, Bi-LSTM, and CNN-LSTM, the text model has significantly improved in terms of MSE and DTW. Compared with DLlinear and PatchTST models, the DTW and TDI models in this paper have better advantages.</div></div>","PeriodicalId":50547,"journal":{"name":"Electric Power Systems Research","volume":"243 ","pages":"Article 111479"},"PeriodicalIF":3.3,"publicationDate":"2025-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143386378","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Short-term photovoltaic power prediction with CPO-BILSTM based on quadratic decomposition

IF 3.3 3区工程技术

Electric Power Systems Research Pub Date : 2025-02-12 DOI: 10.1016/j.epsr.2025.111511

Jinjiang Zhang , Tianle Sun , Xiaolong Guo , Min Lu

{"title":"Short-term photovoltaic power prediction with CPO-BILSTM based on quadratic decomposition","authors":"Jinjiang Zhang , Tianle Sun , Xiaolong Guo , Min Lu","doi":"10.1016/j.epsr.2025.111511","DOIUrl":"10.1016/j.epsr.2025.111511","url":null,"abstract":"<div><div>To address the challenges of volatility and unpredictability in photovoltaic (PV) power, a short-term combined prediction model named EMD-VMD-CPO-BILSTM is proposed. The process begins with the selection of a similar day using the K-means algorithm, followed by the decomposition of historical PV power data into several signal components. The Empirical Mode Decomposition (EMD) method is employed to denoise the signal, and the residual signal is further decomposed using Variational Mode Decomposition (VMD) to minimize mode aliasing and improve accuracy. Subsequently, the parameters of the Bidirectional Long Short-Term Memory (BILSTM) model are optimized using the Crested Porcupine Optimization (CPO) algorithm. The optimized BILSTM model is subsequently applied to power prediction. The experiment was conducted using observation data from the Australian Desert Knowledge (DKA) Solar Energy Centre, located in Australia. The numerical outcomes demonstrate that the proposed EMD-VMD-CPO-BILSTM model reduces mean absolute error (MAE) and root mean square error (RMSE) by 6.67 % and 3.76 %, respectively.</div></div>","PeriodicalId":50547,"journal":{"name":"Electric Power Systems Research","volume":"243 ","pages":"Article 111511"},"PeriodicalIF":3.3,"publicationDate":"2025-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143386320","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0