This paper proposes a continuous control set model predictive control (CCS-MPC) algorithm of a modular multilevel matrix converter (M3C) for low-frequency AC transmission (LFAC), via which the offshore wind farm (OWF) is integrated. The M3C is operated with a 16.7 Hz frequency at the OWF side and a 50 Hz frequency at the onshore grid side. The balance of the capacitor voltages and the regulation of circulating currents in the M3C are performed using the proposed CCS-MPC algorithm, which is based on the online solution of a cost function with constraints. Simulation and experimental work (with a 5 kW M3C prototype) are provided, showing the performance of the LFAC system to operate with symmetrical and asymmetrical voltage dips, active and reactive power steps, and optimal limitation of currents and voltages using constraints. Unlike previous publications, the predictive control system in this paper allows seamless operation under balanced and unbalanced conditions, for instance, during asymmetrical voltage dips.
{"title":"Continuous Control Set Model Predictive Control of Modular Multilevel Matrix Converters for Low-frequency AC Transmission","authors":"Matias Uriarte;Roberto Cardenas-Dobson;Yeiner Arias-Esquivel;Matias Diaz;Oriol Gomis-Bellmunt","doi":"10.35833/MPCE.2024.000654","DOIUrl":"https://doi.org/10.35833/MPCE.2024.000654","url":null,"abstract":"This paper proposes a continuous control set model predictive control (CCS-MPC) algorithm of a modular multilevel matrix converter (M3C) for low-frequency AC transmission (LFAC), via which the offshore wind farm (OWF) is integrated. The M3C is operated with a 16.7 Hz frequency at the OWF side and a 50 Hz frequency at the onshore grid side. The balance of the capacitor voltages and the regulation of circulating currents in the M3C are performed using the proposed CCS-MPC algorithm, which is based on the online solution of a cost function with constraints. Simulation and experimental work (with a 5 kW M3C prototype) are provided, showing the performance of the LFAC system to operate with symmetrical and asymmetrical voltage dips, active and reactive power steps, and optimal limitation of currents and voltages using constraints. Unlike previous publications, the predictive control system in this paper allows seamless operation under balanced and unbalanced conditions, for instance, during asymmetrical voltage dips.","PeriodicalId":51326,"journal":{"name":"Journal of Modern Power Systems and Clean Energy","volume":"13 4","pages":"1468-1480"},"PeriodicalIF":5.7,"publicationDate":"2025-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10944522","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144716275","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Power system optimal dispatch with transient security constraints is commonly represented as transient security-constrained optimal power flow (TSC-OPF). Deep reinforcement learning (DRL)-based TSC-OPF trains efficient decision-making agents that are adaptable to various scenarios and provide solution results quickly. However, due to the high dimensionality of the state space and action spaces, as well as the non-smoothness of dynamic constraints, existing DRL-based TSC-OPF solution methods face a significant challenge of the sparse reward problem. To address this issue, a fast-converging DRL method for optimal dispatch of large-scale power systems under transient security constraints is proposed in this paper. The Markov decision process (MDP) modeling of TSC-OPF is improved by reducing the observation space and smoothing the reward design, thus facilitating agent training. An improved deep deterministic policy gradient algorithm with curriculum learning, parallel exploration, and ensemble decision-making (DDPG-CL-PE-ED) is introduced to drastically enhance the efficiency of agent training and the accuracy of decision-making. The effectiveness, efficiency, and accuracy of the proposed method are demonstrated through experiments in the IEEE 39-bus system and a practical 710-bus regional power grid. The source code of the proposed method is made public on GitHub.
{"title":"Fast-Converging Deep Reinforcement Learning for Optimal Dispatch of Large-Scale Power Systems Under Transient Security Constraints","authors":"Tannan Xiao;Ying Chen;Han Diao;Shaowei Huang;Chen Shen","doi":"10.35833/MPCE.2024.000624","DOIUrl":"https://doi.org/10.35833/MPCE.2024.000624","url":null,"abstract":"Power system optimal dispatch with transient security constraints is commonly represented as transient security-constrained optimal power flow (TSC-OPF). Deep reinforcement learning (DRL)-based TSC-OPF trains efficient decision-making agents that are adaptable to various scenarios and provide solution results quickly. However, due to the high dimensionality of the state space and action spaces, as well as the non-smoothness of dynamic constraints, existing DRL-based TSC-OPF solution methods face a significant challenge of the sparse reward problem. To address this issue, a fast-converging DRL method for optimal dispatch of large-scale power systems under transient security constraints is proposed in this paper. The Markov decision process (MDP) modeling of TSC-OPF is improved by reducing the observation space and smoothing the reward design, thus facilitating agent training. An improved deep deterministic policy gradient algorithm with curriculum learning, parallel exploration, and ensemble decision-making (DDPG-CL-PE-ED) is introduced to drastically enhance the efficiency of agent training and the accuracy of decision-making. The effectiveness, efficiency, and accuracy of the proposed method are demonstrated through experiments in the IEEE 39-bus system and a practical 710-bus regional power grid. The source code of the proposed method is made public on GitHub.","PeriodicalId":51326,"journal":{"name":"Journal of Modern Power Systems and Clean Energy","volume":"13 5","pages":"1495-1506"},"PeriodicalIF":6.1,"publicationDate":"2025-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10944544","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145089985","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-03-27DOI: 10.35833/MPCE.2024.000768
Damià Gomila;Benjamín A. Carreras;José-Miguel Reynolds-Barredo;María Martínez-Barbeito;Pere Colet;Oriol Gomis-Bellmunt
The utilization of high-voltage direct current (HVDC) lines for the segmentation of the European power grid has been demonstrated to be a highly effective strategy for the mitigation of the risk of cascading blackouts. In this study, an accurate and efficient method for determining the optimal power flow through HVDC lines is presented, with the objective of minimizing load shedding. The proposed method is applied to two distinct scenarios: first, the segmentation of the power grid along the Pyrenees, with the objective of segmenting the Iberian Peninsula from the rest of Europe; and second, the segmentation of the power grid into Eastern and Western Europe, approximately in half. In both scenarios, the method effectively reduces the size of blackouts impacting both sides of the HVDC lines, resulting in a 46% and 67% reduction in total blackout risk, respectively. Furthermore, we have estimated the cost savings from risk reduction and the expenses associated with converting conventional lines to HVDC lines. Our findings indicate that segmenting the European power grid with HVDC lines is economically viable, particularly for segmenting the Iberian Peninsula, due to its favorable cost-risk reduction ratio.
{"title":"Reducing Blackout Risk by Segmenting European Power Grid with HVDC Lines","authors":"Damià Gomila;Benjamín A. Carreras;José-Miguel Reynolds-Barredo;María Martínez-Barbeito;Pere Colet;Oriol Gomis-Bellmunt","doi":"10.35833/MPCE.2024.000768","DOIUrl":"https://doi.org/10.35833/MPCE.2024.000768","url":null,"abstract":"The utilization of high-voltage direct current (HVDC) lines for the segmentation of the European power grid has been demonstrated to be a highly effective strategy for the mitigation of the risk of cascading blackouts. In this study, an accurate and efficient method for determining the optimal power flow through HVDC lines is presented, with the objective of minimizing load shedding. The proposed method is applied to two distinct scenarios: first, the segmentation of the power grid along the Pyrenees, with the objective of segmenting the Iberian Peninsula from the rest of Europe; and second, the segmentation of the power grid into Eastern and Western Europe, approximately in half. In both scenarios, the method effectively reduces the size of blackouts impacting both sides of the HVDC lines, resulting in a 46% and 67% reduction in total blackout risk, respectively. Furthermore, we have estimated the cost savings from risk reduction and the expenses associated with converting conventional lines to HVDC lines. Our findings indicate that segmenting the European power grid with HVDC lines is economically viable, particularly for segmenting the Iberian Peninsula, due to its favorable cost-risk reduction ratio.","PeriodicalId":51326,"journal":{"name":"Journal of Modern Power Systems and Clean Energy","volume":"13 5","pages":"1556-1567"},"PeriodicalIF":6.1,"publicationDate":"2025-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10944521","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145090136","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-03-25DOI: 10.35833/MPCE.2024.000521
Songmei Wu;Hui Guo;Fei Wang;Yuxin Zhu
Peer-to-peer (P2P) energy trading provides a promising solution for integrating distributed microgrids (MGs). However, most existing research works on P2P energy trading among MGs ignore the influence of the dynamic network usage fees imposed by the distribution system operator (DSO). Therefore, a method of P2P energy trading among MGs based on the optimal dynamic network usage fees is proposed in this paper to balance the benefits of DSO. The interaction between DSO and MG is formulated as a Stackelberg game, in which the existence and uniqueness of optimal dynamic network usage fees are proven. Additionally, the optimal dynamic network usage fees are obtained by transforming the bi-level problem into single-level mixed-integer quadratic programming using Karush-Kuhn-Tucker conditions. Furthermore, the underlying relationship among optimal dynamic network usage fees, electrical distance, and power flow is revealed, and the mechanism of the optimal dynamic network usage fee can further enhance P2P energy trading among MGs. Finally, simulation results on an enhanced IEEE 33-bus system demonstrate that the proposed mechanism achieves a 17.08% reduction in operation costs for MG while increasing DSO revenue by 15.36%.
{"title":"Balancing Benefits of Distribution System Operator in Peer-to-Peer Energy Trading Among Microgrids Based on Optimal Dynamic Network Usage Fees","authors":"Songmei Wu;Hui Guo;Fei Wang;Yuxin Zhu","doi":"10.35833/MPCE.2024.000521","DOIUrl":"https://doi.org/10.35833/MPCE.2024.000521","url":null,"abstract":"Peer-to-peer (P2P) energy trading provides a promising solution for integrating distributed microgrids (MGs). However, most existing research works on P2P energy trading among MGs ignore the influence of the dynamic network usage fees imposed by the distribution system operator (DSO). Therefore, a method of P2P energy trading among MGs based on the optimal dynamic network usage fees is proposed in this paper to balance the benefits of DSO. The interaction between DSO and MG is formulated as a Stackelberg game, in which the existence and uniqueness of optimal dynamic network usage fees are proven. Additionally, the optimal dynamic network usage fees are obtained by transforming the bi-level problem into single-level mixed-integer quadratic programming using Karush-Kuhn-Tucker conditions. Furthermore, the underlying relationship among optimal dynamic network usage fees, electrical distance, and power flow is revealed, and the mechanism of the optimal dynamic network usage fee can further enhance P2P energy trading among MGs. Finally, simulation results on an enhanced IEEE 33-bus system demonstrate that the proposed mechanism achieves a 17.08% reduction in operation costs for MG while increasing DSO revenue by 15.36%.","PeriodicalId":51326,"journal":{"name":"Journal of Modern Power Systems and Clean Energy","volume":"13 2","pages":"663-674"},"PeriodicalIF":5.7,"publicationDate":"2025-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10938862","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143716550","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
A novel planning tool for optimizing the placement of electric springs (ESs) in unbalanced distribution networks is introduced in this study. The total voltage deviation is used as the optimization criterion and is calculated when the ESs operate at their maximum reactive power either in the inductive or capacitive modes. The power rating of the ES is adjusted on the basis of the available active power at the bus. And in the optimization problem, it is expressed as the power ratio of the non-critical load (NCL) and critical load (CL). The implemented ES model is flexible, which can be used on any bus and any phase. The model determines the output voltage from the parameters and operating conditions at the point of common coupling (PCC). These conditions are integrated using the backward/forward sweep method (BFSM) and are updated during power flow calculations. The problem is described as a mixed-integer nonlinear problem and solved efficiently using an improved BF-SM-based genetic algorithm, which computes power flow and ES placement simultaneously. The effectiveness of this method is evaluated through testing in IEEE 13-bus and 34-bus systems.
{"title":"Optimal Placement of Electric Springs in Unbalanced Distribution Networks Using Improved Backward/Forward Sweep Method Based Genetic Algorithm","authors":"Guillermo Tapia-Tinoco;Gerardo Humberto Valencia-Rivera;Martin Valtierra-Rodriguez;Arturo Garcia-Perez;David Granados-Lieberman","doi":"10.35833/MPCE.2024.000649","DOIUrl":"https://doi.org/10.35833/MPCE.2024.000649","url":null,"abstract":"A novel planning tool for optimizing the placement of electric springs (ESs) in unbalanced distribution networks is introduced in this study. The total voltage deviation is used as the optimization criterion and is calculated when the ESs operate at their maximum reactive power either in the inductive or capacitive modes. The power rating of the ES is adjusted on the basis of the available active power at the bus. And in the optimization problem, it is expressed as the power ratio of the non-critical load (NCL) and critical load (CL). The implemented ES model is flexible, which can be used on any bus and any phase. The model determines the output voltage from the parameters and operating conditions at the point of common coupling (PCC). These conditions are integrated using the backward/forward sweep method (BFSM) and are updated during power flow calculations. The problem is described as a mixed-integer nonlinear problem and solved efficiently using an improved BF-SM-based genetic algorithm, which computes power flow and ES placement simultaneously. The effectiveness of this method is evaluated through testing in IEEE 13-bus and 34-bus systems.","PeriodicalId":51326,"journal":{"name":"Journal of Modern Power Systems and Clean Energy","volume":"13 3","pages":"940-952"},"PeriodicalIF":5.7,"publicationDate":"2025-03-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10937285","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144139856","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Demand response (DR) is a practical solution to overcoming the challenges posed by the volatility and intermittency of the renewable generation in power systems. Industrial electricity demand is growing rapidly, which makes the DR potential estimation of industrial user critical for the DR implementation. In this paper, a unified model for estimating DR potential in the production processes of aluminum, cement, and steel is proposed on the basis of their unique operational characteristics. Firstly, considering the typical characteristic constraints of different industrial users, a DR potential estimation model is developed to capture typical industrial user response behavior under various operational and economic factors. The proposed estimation model is further refined to account for the uncertain and subjective factors present in the actual estimation environment. Secondly, a virtual data acquisition method is introduced to obtain the private virtual parameters required in the estimation process. Then, an industrial user participation threshold is presented to determine whether industrial users may participate in DR at a given time with consideration of their response characteristics. The industrial users may not always act with perfect rationality, and the response environment remains uncertain. In addition, the subjective factor in this paper includes the proposed threshold and the bounded rationality. Finally, an improved DR potential estimation model is proposed to reduce the difficulties in the actual estimation process. The simulation results validate the effectiveness of the proposed estimation model and the improved DR potential estimation model across multiple cases.
{"title":"Demand Response Potential Estimation Model for Typical Industrial Users Considering Uncertain and Subjective Factors","authors":"Tingyu Jiang;Chuan Qin;Yuzhong Gong;Ke Wang;Ping Ju;Chi Yung Chung","doi":"10.35833/MPCE.2024.000764","DOIUrl":"https://doi.org/10.35833/MPCE.2024.000764","url":null,"abstract":"Demand response (DR) is a practical solution to overcoming the challenges posed by the volatility and intermittency of the renewable generation in power systems. Industrial electricity demand is growing rapidly, which makes the DR potential estimation of industrial user critical for the DR implementation. In this paper, a unified model for estimating DR potential in the production processes of aluminum, cement, and steel is proposed on the basis of their unique operational characteristics. Firstly, considering the typical characteristic constraints of different industrial users, a DR potential estimation model is developed to capture typical industrial user response behavior under various operational and economic factors. The proposed estimation model is further refined to account for the uncertain and subjective factors present in the actual estimation environment. Secondly, a virtual data acquisition method is introduced to obtain the private virtual parameters required in the estimation process. Then, an industrial user participation threshold is presented to determine whether industrial users may participate in DR at a given time with consideration of their response characteristics. The industrial users may not always act with perfect rationality, and the response environment remains uncertain. In addition, the subjective factor in this paper includes the proposed threshold and the bounded rationality. Finally, an improved DR potential estimation model is proposed to reduce the difficulties in the actual estimation process. The simulation results validate the effectiveness of the proposed estimation model and the improved DR potential estimation model across multiple cases.","PeriodicalId":51326,"journal":{"name":"Journal of Modern Power Systems and Clean Energy","volume":"13 4","pages":"1360-1372"},"PeriodicalIF":5.7,"publicationDate":"2025-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10925540","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144716305","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-03-13DOI: 10.35833/MPCE.2024.0001027
Haoxiang Zong;Chen Zhang;Marta Molinas
The dynamics of diverse synchronization control, such as grid-following (GFL) and grid-forming (GFM) control, are complicating the oscillatory behaviors in multi-converter systems. In this context, the impedance network (IN) based frequency-domain modal analysis (FMA) method is useful for diag-nosing oscillations. However, since the conventional impedance model retains only electric nodes, the FMA primarily reflects the circuit-related information, e. g., node participation factor, making it less intuitive for probing the synchronous dynamics. To address this issue, this paper proposes an augmented impedance network (AIN) modeling method by explicitly characterizing synchronous control loops for stability assessment. First, a four-port augmented impedance model (AIM) with an additional synchronization port is proposed for a generic AC/DC converter, and the corresponding AIN model of a generic AC/DC multi-converter system is formulated in a scalable approach. Then, the FMA method is generalized by simultaneously incorporating the electric nodes (including AC and DC nodes) and synchronous nodes. Finally, the AIN model and its associated FMA method are comprehensively validated in a typical point-to-point high-voltage direct current (HVDC) system and a modified IEEE 9-bus system, both with GFM and GFL converters.
{"title":"An Augmented Impedance Network Modeling Method with Explicit Synchronization Port for Stability Assessment of Multi-Converter System","authors":"Haoxiang Zong;Chen Zhang;Marta Molinas","doi":"10.35833/MPCE.2024.0001027","DOIUrl":"https://doi.org/10.35833/MPCE.2024.0001027","url":null,"abstract":"The dynamics of diverse synchronization control, such as grid-following (GFL) and grid-forming (GFM) control, are complicating the oscillatory behaviors in multi-converter systems. In this context, the impedance network (IN) based frequency-domain modal analysis (FMA) method is useful for diag-nosing oscillations. However, since the conventional impedance model retains only electric nodes, the FMA primarily reflects the circuit-related information, e. g., node participation factor, making it less intuitive for probing the synchronous dynamics. To address this issue, this paper proposes an augmented impedance network (AIN) modeling method by explicitly characterizing synchronous control loops for stability assessment. First, a four-port augmented impedance model (AIM) with an additional synchronization port is proposed for a generic AC/DC converter, and the corresponding AIN model of a generic AC/DC multi-converter system is formulated in a scalable approach. Then, the FMA method is generalized by simultaneously incorporating the electric nodes (including AC and DC nodes) and synchronous nodes. Finally, the AIN model and its associated FMA method are comprehensively validated in a typical point-to-point high-voltage direct current (HVDC) system and a modified IEEE 9-bus system, both with GFM and GFL converters.","PeriodicalId":51326,"journal":{"name":"Journal of Modern Power Systems and Clean Energy","volume":"13 6","pages":"2192-2202"},"PeriodicalIF":6.1,"publicationDate":"2025-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10925541","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145610641","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-03-11DOI: 10.35833/MPCE.2024.000057
Njegos Jankovic;Javier Roldán-Pérez;Milan Prodanovic;Jon Are Suul;Salvatore D’Arco;Luis Rouco
In recent years, transmission system operators have started requesting converter-interfaced generators (CIGs) to participate in grid services such as power oscillation damping (POD). As power systems are prone to topology changes because of connection and disconnection of generators and lines, one of the most important requirements in the design of POD controller is to account for these changes. This can be done by either adjusting the controller structure during the operation or applying a fixed structure designed to address changes in the system. The fixed structure is usually preferred by transmission system operators since it is easier to determine its impact on the system. In this paper, a design procedure is proposed for network-reconfiguration-aware POD controller with fixed structure for CIG-based power plants that considers network configurations with any one line disconnected. The design procedure is based on frequency-response techniques, so it is suitable for application in CIG-based power plants, even in cases when a detailed small-signal model of the system is not available. Designs of a POD controller for the damping of critical system modes can be obtained by using active power, reactive power, or both power components simultaneously. The application to the design of a POD controller for a CIG-based power plant connected to the IEEE 39-bus system is presented as an example. Simulations performed in MATLAB and SimPowerSystems are used to validate the proposed design procedure. The validation includes an analysis of system performance with changes considered in the proposed designed procedure. Also, the system performance under unconsidered changes is examined, covering variations in load and inertia values, as well as disconnection of synchronous generators.
{"title":"Network-Reconfiguration-Aware Power Oscillation Damping Controller for Converter-Interfaced Generator Based Power Plants","authors":"Njegos Jankovic;Javier Roldán-Pérez;Milan Prodanovic;Jon Are Suul;Salvatore D’Arco;Luis Rouco","doi":"10.35833/MPCE.2024.000057","DOIUrl":"https://doi.org/10.35833/MPCE.2024.000057","url":null,"abstract":"In recent years, transmission system operators have started requesting converter-interfaced generators (CIGs) to participate in grid services such as power oscillation damping (POD). As power systems are prone to topology changes because of connection and disconnection of generators and lines, one of the most important requirements in the design of POD controller is to account for these changes. This can be done by either adjusting the controller structure during the operation or applying a fixed structure designed to address changes in the system. The fixed structure is usually preferred by transmission system operators since it is easier to determine its impact on the system. In this paper, a design procedure is proposed for network-reconfiguration-aware POD controller with fixed structure for CIG-based power plants that considers network configurations with any one line disconnected. The design procedure is based on frequency-response techniques, so it is suitable for application in CIG-based power plants, even in cases when a detailed small-signal model of the system is not available. Designs of a POD controller for the damping of critical system modes can be obtained by using active power, reactive power, or both power components simultaneously. The application to the design of a POD controller for a CIG-based power plant connected to the IEEE 39-bus system is presented as an example. Simulations performed in MATLAB and SimPowerSystems are used to validate the proposed design procedure. The validation includes an analysis of system performance with changes considered in the proposed designed procedure. Also, the system performance under unconsidered changes is examined, covering variations in load and inertia values, as well as disconnection of synchronous generators.","PeriodicalId":51326,"journal":{"name":"Journal of Modern Power Systems and Clean Energy","volume":"13 4","pages":"1420-1431"},"PeriodicalIF":5.7,"publicationDate":"2025-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10923627","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144716257","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-03-11DOI: 10.35833/MPCE.2024.000772
Antonio Bracale;Pierluigi Caramia;Guido Carpinelli;Pasquale De Falco;Paola Verde
The probabilistic short circuit analysis provides relevant information for power system planning and power quality assessment tasks. Traditional Monte Carlo methods (TMCMs) are usually applied to consider the randomness affecting short circuit operating conditions, but they require numerous iterations to properly characterize the network conditions. This paper proposes a mixed Taguchi-based method (MTBM) as a new alternative tool to account for the uncertainties affecting the inputs of probabilistic short circuit analysis. The MTBM significantly reduces the number of iterations required to properly address the randomness of inputs (environmental conditions, pre-fault conditions, fault characteristics), and allows diversifying the representation of inputs through a quantile-based selection of their levels. The proposed method is applied to unbalanced three-phase four-wire low-voltage (LV) distribution systems with photovoltaic systems (PVSs) operating in low voltage ride-through (LVRT) during the fault. Numerical applications related to a test system are presented, and the proposed MTBM is compared with the TMCM, the unmixed Taguchi-based method (UTBM), and the point estimate method (PEM). The proposed MTBM returns values very close to those of the TMCM (with average deviations ranging from 0.01% to 3.12%) and enables a fast and accurate analysis of faulted LV distribution systems with PVSs operating in LVRT.
{"title":"Mixed Taguchi-Based Method for Probabilistic Short Circuit Analysis of Low-Voltage Distribution Systems with Photovoltaic Systems","authors":"Antonio Bracale;Pierluigi Caramia;Guido Carpinelli;Pasquale De Falco;Paola Verde","doi":"10.35833/MPCE.2024.000772","DOIUrl":"https://doi.org/10.35833/MPCE.2024.000772","url":null,"abstract":"The probabilistic short circuit analysis provides relevant information for power system planning and power quality assessment tasks. Traditional Monte Carlo methods (TMCMs) are usually applied to consider the randomness affecting short circuit operating conditions, but they require numerous iterations to properly characterize the network conditions. This paper proposes a mixed Taguchi-based method (MTBM) as a new alternative tool to account for the uncertainties affecting the inputs of probabilistic short circuit analysis. The MTBM significantly reduces the number of iterations required to properly address the randomness of inputs (environmental conditions, pre-fault conditions, fault characteristics), and allows diversifying the representation of inputs through a quantile-based selection of their levels. The proposed method is applied to unbalanced three-phase four-wire low-voltage (LV) distribution systems with photovoltaic systems (PVSs) operating in low voltage ride-through (LVRT) during the fault. Numerical applications related to a test system are presented, and the proposed MTBM is compared with the TMCM, the unmixed Taguchi-based method (UTBM), and the point estimate method (PEM). The proposed MTBM returns values very close to those of the TMCM (with average deviations ranging from 0.01% to 3.12%) and enables a fast and accurate analysis of faulted LV distribution systems with PVSs operating in LVRT.","PeriodicalId":51326,"journal":{"name":"Journal of Modern Power Systems and Clean Energy","volume":"13 5","pages":"1738-1751"},"PeriodicalIF":6.1,"publicationDate":"2025-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10923628","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145089995","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In modern microgrids (MGs) with high penetration of distributed energy resources (DERs), system reconfiguration occurs more frequently and becomes a significant issue. Fixed-parameter controllers may not handle these tasks effectively, as they lack the ability to adapt to the dynamic conditions in such environments. This paper proposes an intelligence-driven grid-forming (GFM) converter control method for islanding MGs using a robustness-guided neural network (RNN). To enhance the adaptability of the proposed method, traditional proportional-integral controllers in the GFM primary control loops are entirely replaced by the RNN. The RNN is trained by a robustness-guided strategy to replicate their robust behaviors. All the training stages are purely data-driven methods, which means that no system parameters are required for the controller design. Consequently, the proposed method is an intelligence-driven modelless GFM converter control. Compared with traditional methods, the simulation results in all testing scenarios show the clear benefits of the proposed method. The proposed method reduces overshoots by more than 71.24%, which keeps all damping ratios within the stable region and provides faster stabilization. In comparison to traditional methods, at the highest probability, the proposed method improves damping by over 14.7% and reduces the rates of change of frequency and voltage by over 59.97%. Additionally, the proposed method effectively suppresses the interactions between state variables caused by inverter-based resources, with frequencies ranging from 1.0 Hz to 1.422 Hz. Consequently, these frequencies contribute less than 19.79% To the observed transient responses.
{"title":"Intelligence-Driven Grid-Forming Converter Control for Islanding Microgrids","authors":"Issarachai Ngamroo;Tossaporn Surinkaew;Yasunori Mitani","doi":"10.35833/MPCE.2024.001157","DOIUrl":"https://doi.org/10.35833/MPCE.2024.001157","url":null,"abstract":"In modern microgrids (MGs) with high penetration of distributed energy resources (DERs), system reconfiguration occurs more frequently and becomes a significant issue. Fixed-parameter controllers may not handle these tasks effectively, as they lack the ability to adapt to the dynamic conditions in such environments. This paper proposes an intelligence-driven grid-forming (GFM) converter control method for islanding MGs using a robustness-guided neural network (RNN). To enhance the adaptability of the proposed method, traditional proportional-integral controllers in the GFM primary control loops are entirely replaced by the RNN. The RNN is trained by a robustness-guided strategy to replicate their robust behaviors. All the training stages are purely data-driven methods, which means that no system parameters are required for the controller design. Consequently, the proposed method is an intelligence-driven modelless GFM converter control. Compared with traditional methods, the simulation results in all testing scenarios show the clear benefits of the proposed method. The proposed method reduces overshoots by more than 71.24%, which keeps all damping ratios within the stable region and provides faster stabilization. In comparison to traditional methods, at the highest probability, the proposed method improves damping by over 14.7% and reduces the rates of change of frequency and voltage by over 59.97%. Additionally, the proposed method effectively suppresses the interactions between state variables caused by inverter-based resources, with frequencies ranging from 1.0 Hz to 1.422 Hz. Consequently, these frequencies contribute less than 19.79% To the observed transient responses.","PeriodicalId":51326,"journal":{"name":"Journal of Modern Power Systems and Clean Energy","volume":"13 4","pages":"1310-1322"},"PeriodicalIF":5.7,"publicationDate":"2025-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10916672","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144716309","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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