Pub Date : 2025-09-29DOI: 10.35833/MPCE.2025.000456
Bo Wang;Zhehan Jia;Xingying Chen;Lei Gan;Haochen Hua;Kun Yu;Jun Shen
Liquefied natural gas (LNG), recognized as the primary form for natural gas transportation, can release substantial cold energy during gasification. To make efficient use of this cold energy, this paper proposes a data-driven stochastic robust (DDSR) energy management method for the multi-stage cascade utilization of LNG cold energy in a multi-energy microgrid (MEMG) of an LNG receiving terminal. Firstly, a general scheduling model considering the flexible coupling between adjacent stages, energy losses, and electric power consumption for the cascade utilization of LNG cold energy is introduced. This model is applied to carbon capture, cryogenic power generation, and direct cooling, which are sequentially associated with the deep, medium, and shallow cooling zones of LNG cold energy, respectively. Moreover, a two-stage energy management framework is proposed to coordinate the cascade utilization of LNG cold energy with other energy resources in the MEMG. To tackle the uncertainties of renewable energy generation and various loads, a DDSR-based solution method is developed, aiming to achieve both economic benefits and solution robustness by identifying the worst-case scenarios and the corresponding worst-case probability. Accordingly, a Benders decomposition-based solution algorithm is proposed to divide the original problem into a master problem and a slave problem, which are solved iteratively. The simulation results verify the effectiveness and high efficiency of the proposed DDSR energy management method for multi-stage cascade utilization of LNG cold energy.
{"title":"Data-Driven Stochastic Robust Energy Management for Multi-Stage Cascade Utilization of Liquefied Natural Gas Cold Energy in Multi-Energy Microgrid","authors":"Bo Wang;Zhehan Jia;Xingying Chen;Lei Gan;Haochen Hua;Kun Yu;Jun Shen","doi":"10.35833/MPCE.2025.000456","DOIUrl":"https://doi.org/10.35833/MPCE.2025.000456","url":null,"abstract":"Liquefied natural gas (LNG), recognized as the primary form for natural gas transportation, can release substantial cold energy during gasification. To make efficient use of this cold energy, this paper proposes a data-driven stochastic robust (DDSR) energy management method for the multi-stage cascade utilization of LNG cold energy in a multi-energy microgrid (MEMG) of an LNG receiving terminal. Firstly, a general scheduling model considering the flexible coupling between adjacent stages, energy losses, and electric power consumption for the cascade utilization of LNG cold energy is introduced. This model is applied to carbon capture, cryogenic power generation, and direct cooling, which are sequentially associated with the deep, medium, and shallow cooling zones of LNG cold energy, respectively. Moreover, a two-stage energy management framework is proposed to coordinate the cascade utilization of LNG cold energy with other energy resources in the MEMG. To tackle the uncertainties of renewable energy generation and various loads, a DDSR-based solution method is developed, aiming to achieve both economic benefits and solution robustness by identifying the worst-case scenarios and the corresponding worst-case probability. Accordingly, a Benders decomposition-based solution algorithm is proposed to divide the original problem into a master problem and a slave problem, which are solved iteratively. The simulation results verify the effectiveness and high efficiency of the proposed DDSR energy management method for multi-stage cascade utilization of LNG cold energy.","PeriodicalId":51326,"journal":{"name":"Journal of Modern Power Systems and Clean Energy","volume":"14 1","pages":"310-321"},"PeriodicalIF":6.1,"publicationDate":"2025-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11184716","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146102986","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 : 2025-08-12DOI: 10.35833/MPCE.2024.001154
Marzio Barresi;Davide del Giudice;Davide de Simone;Samuele Grillo
Modular multilevel converters (MMCs) have emerged as a promising solution for integrating renewables. In case of photovoltaic (PV) systems, PV arrays can be integrated at the submodule (SM) level, and the distributed maximum power point tracking (DMPPT) can be achieved through AC and DC circulating current control and perturb and observe (P&O) methods. However, this implementation is hindered by the need for numerous measurements, since the voltage and current of all PV arrays in each SM must be known. To address this issue, we propose a three-phase reduced-sensor MMC with distributed MPPT for PV integration based on an extended Kalman filter (EKF). For each MMC arm, the EKF estimates the voltage and irradiance of each SM by exploiting their gate signals and duty cycles as well as the arm current and voltage. This solution is compatible with uniform and non-uniform irradiance conditions both under the steady-state and transient conditions and uses significantly fewer sensors than other strategies employed in similar-purpose MMCs, while achieving comparable efficiency. Moreover, by exploiting the PV array characteristics, it allows performing DMPPT more directly, without using P&O methods. These features are confirmed by simulations of an MMC-based PV system with 12 SMs per arm.
{"title":"Three-Phase Reduced-Sensor Modular Multilevel Converter with Distributed MPPT for PV Integration Based on Extended Kalman Filter","authors":"Marzio Barresi;Davide del Giudice;Davide de Simone;Samuele Grillo","doi":"10.35833/MPCE.2024.001154","DOIUrl":"https://doi.org/10.35833/MPCE.2024.001154","url":null,"abstract":"Modular multilevel converters (MMCs) have emerged as a promising solution for integrating renewables. In case of photovoltaic (PV) systems, PV arrays can be integrated at the submodule (SM) level, and the distributed maximum power point tracking (DMPPT) can be achieved through AC and DC circulating current control and perturb and observe (P&O) methods. However, this implementation is hindered by the need for numerous measurements, since the voltage and current of all PV arrays in each SM must be known. To address this issue, we propose a three-phase reduced-sensor MMC with distributed MPPT for PV integration based on an extended Kalman filter (EKF). For each MMC arm, the EKF estimates the voltage and irradiance of each SM by exploiting their gate signals and duty cycles as well as the arm current and voltage. This solution is compatible with uniform and non-uniform irradiance conditions both under the steady-state and transient conditions and uses significantly fewer sensors than other strategies employed in similar-purpose MMCs, while achieving comparable efficiency. Moreover, by exploiting the PV array characteristics, it allows performing DMPPT more directly, without using P&O methods. These features are confirmed by simulations of an MMC-based PV system with 12 SMs per arm.","PeriodicalId":51326,"journal":{"name":"Journal of Modern Power Systems and Clean Energy","volume":"14 1","pages":"368-382"},"PeriodicalIF":6.1,"publicationDate":"2025-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11123591","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146102988","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 : 2025-08-01DOI: 10.35833/MPCE.2024.000949
Hao Lin;Liang Liang;Haiqiong Yi;Xiangjun Kong
Sending-end multi-terminal high-voltage direct current (MT-HVDC) systems are well-suited for large-scale renewable energy collection and transmission. However, the capacity planning for converter stations (CSs), which is directly correlated with their ability to convert renewable energy, remains a critical issue. In this paper, an optimal capacity planning method for CSs is proposed to maximize the converted energy (CE). The proposed method considers the uncertainties of photovoltaic (PV) generation and derives analytical formulas for stochastic CEs. The equal incremental rate (EIR) principle is employed to calculate the optimal capacity planning scheme, and then a general guideline for the capacity planning in stochastic scenarios is presented. Case studies are conducted to validate the effectiveness of the proposed method and the proposed guideline. The results demonstrate that the proposed method converts more renewable energy than the deterministic method.
{"title":"Optimal Capacity Planning for Converter Stations in Sending-End MT-HVDC Systems Considering Uncertainties of PV Generation","authors":"Hao Lin;Liang Liang;Haiqiong Yi;Xiangjun Kong","doi":"10.35833/MPCE.2024.000949","DOIUrl":"https://doi.org/10.35833/MPCE.2024.000949","url":null,"abstract":"Sending-end multi-terminal high-voltage direct current (MT-HVDC) systems are well-suited for large-scale renewable energy collection and transmission. However, the capacity planning for converter stations (CSs), which is directly correlated with their ability to convert renewable energy, remains a critical issue. In this paper, an optimal capacity planning method for CSs is proposed to maximize the converted energy (CE). The proposed method considers the uncertainties of photovoltaic (PV) generation and derives analytical formulas for stochastic CEs. The equal incremental rate (EIR) principle is employed to calculate the optimal capacity planning scheme, and then a general guideline for the capacity planning in stochastic scenarios is presented. Case studies are conducted to validate the effectiveness of the proposed method and the proposed guideline. The results demonstrate that the proposed method converts more renewable energy than the deterministic method.","PeriodicalId":51326,"journal":{"name":"Journal of Modern Power Systems and Clean Energy","volume":"13 6","pages":"2180-2191"},"PeriodicalIF":6.1,"publicationDate":"2025-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11107279","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145610637","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}
Accurate load profile data are essential for optimizing energy systems. However, real-world datasets often suffer from low resolution and significant missing values. To address these challenges, this paper introduces physics-informed loss generative adversarial network (PIL-GAN), a model that combines generative adversarial networks (GANs) with physics-informed losses (PILs) derived from physics-informed neural networks (PINNs) that are integrated directly into the generator. High-resolution load profiles are generated that not only fill in missing data but also ensure that the generated profiles adhere to physical laws governing the energy systems, such as energy conservation and load fluctuations. By embedding domain-specific physics into the generation process, the proposed model significantly enhances data quality and resolution for low-quality datasets. The experimental results demonstrate notable gains in data accuracy, resolution, and consistency, making PIL-GAN an effective tool for energy management systems. The PIL-GAN also has broader applicability in other fields such as generating and inpainting high-resolution datasets for energy systems, industrial processes, and any domain in which data must comply with real-world physical laws or operational requirements.
{"title":"Generative Adversarial Networks with Physics-Informed Losses for High-Resolution Load Profile Generation and Inpainting","authors":"Swodesh Sharma;Apeksha Ghimire;Shashwot Shrestha;Rachana Subedi;Sushil Phuyal","doi":"10.35833/MPCE.2024.001153","DOIUrl":"https://doi.org/10.35833/MPCE.2024.001153","url":null,"abstract":"Accurate load profile data are essential for optimizing energy systems. However, real-world datasets often suffer from low resolution and significant missing values. To address these challenges, this paper introduces physics-informed loss generative adversarial network (PIL-GAN), a model that combines generative adversarial networks (GANs) with physics-informed losses (PILs) derived from physics-informed neural networks (PINNs) that are integrated directly into the generator. High-resolution load profiles are generated that not only fill in missing data but also ensure that the generated profiles adhere to physical laws governing the energy systems, such as energy conservation and load fluctuations. By embedding domain-specific physics into the generation process, the proposed model significantly enhances data quality and resolution for low-quality datasets. The experimental results demonstrate notable gains in data accuracy, resolution, and consistency, making PIL-GAN an effective tool for energy management systems. The PIL-GAN also has broader applicability in other fields such as generating and inpainting high-resolution datasets for energy systems, industrial processes, and any domain in which data must comply with real-world physical laws or operational requirements.","PeriodicalId":51326,"journal":{"name":"Journal of Modern Power Systems and Clean Energy","volume":"14 1","pages":"334-346"},"PeriodicalIF":6.1,"publicationDate":"2025-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11107276","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146102973","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}
The growing electricity demand, combined with the increasing integration of photovoltaic (PV) generation into the distribution system, requires higher flexibility from the demand side. This paper proposes a customized scheduling approach for demand response (DR) of customers with dispatchable inverters in distribution-level PV facilities. Based on the Chilean context, the proposed approach enables these energy resources to provide flexibility in the technical and economic management of the distribution system operator (DSO). Specifically, a bi-level optimization model is introduced. At the upper level, the DSO minimizes distribution system costs by determining daily price signals for customers based on their response profile classes (RPCs) and active and reactive power set points for PV facilities. At the lower level, customers aim to reduce their electricity bills. In addition, the proposed approach ensures the reliable operation of the distribution system with high probability by ad-dressing uncertainty through chance constraints (CCs). Incorporated CCs in the distribution system modeling include the squared magnitude of nodal voltage, complex power flow in lines, and apparent power of inverters. Finally, two case studies are presented, involving 420 residential and commercial Chilean customers with two distribution-level PV facilities using real-world market prices and daily consumption profiles on the IEEE 37-node test feeder. Results demonstrate how the proposed model enables the customized scheduling of customers and PV facilities, highlighting its effectiveness over the uniform price scheme.
{"title":"Customized Scheduling of Demand Response of Customers with Dispatchable Inverters in Distribution-Level Photovoltaic Facilities","authors":"Lester Marrero;Daniel Sbárbaro;Luis García-Santander","doi":"10.35833/MPCE.2024.001304","DOIUrl":"https://doi.org/10.35833/MPCE.2024.001304","url":null,"abstract":"The growing electricity demand, combined with the increasing integration of photovoltaic (PV) generation into the distribution system, requires higher flexibility from the demand side. This paper proposes a customized scheduling approach for demand response (DR) of customers with dispatchable inverters in distribution-level PV facilities. Based on the Chilean context, the proposed approach enables these energy resources to provide flexibility in the technical and economic management of the distribution system operator (DSO). Specifically, a bi-level optimization model is introduced. At the upper level, the DSO minimizes distribution system costs by determining daily price signals for customers based on their response profile classes (RPCs) and active and reactive power set points for PV facilities. At the lower level, customers aim to reduce their electricity bills. In addition, the proposed approach ensures the reliable operation of the distribution system with high probability by ad-dressing uncertainty through chance constraints (CCs). Incorporated CCs in the distribution system modeling include the squared magnitude of nodal voltage, complex power flow in lines, and apparent power of inverters. Finally, two case studies are presented, involving 420 residential and commercial Chilean customers with two distribution-level PV facilities using real-world market prices and daily consumption profiles on the IEEE 37-node test feeder. Results demonstrate how the proposed model enables the customized scheduling of customers and PV facilities, highlighting its effectiveness over the uniform price scheme.","PeriodicalId":51326,"journal":{"name":"Journal of Modern Power Systems and Clean Energy","volume":"14 1","pages":"322-333"},"PeriodicalIF":6.1,"publicationDate":"2025-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11031136","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146102991","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 : 2025-06-06DOI: 10.35833/MPCE.2024.001191
Qiangang Jia;Wenshu Jiao;Sijie Chen;Jian Ping;Zheng Yan;Haitao Sun
Distributed photovoltaic (PV) entities can be coordinated to provide reactive power for voltage regulation in distribution networks. However, integrating large-scale distributed PV entities into reactive power optimization makes it difficult to balance the individual benefit of each PV entity with the overall economic efficiency of the system. To address this challenge, we propose a market-oriented two-stage reactive power regulation method. At the first stage, a long-term multi-layer reactive power capacity market is created to incentivize each PV entity to provide reactive power capacity, while ensuring their financial interests are guaranteed. At the second stage, a real-time multi-layer reactive power dispatch mechanism is introduced to manage the reactive power generation of distributed PV entities, prioritizing the dispatch of lower-cost PV entities to maximize system-wide economic efficiency. Simulation results based on a real Finnish radial distribution network demonstrate the effectiveness of the proposed method in optimizing reactive power for large-scale distributed PV entities.
{"title":"Market-Oriented Two-Stage Reactive Power Regulation for Large-Scale Distributed Photovoltaic Entities","authors":"Qiangang Jia;Wenshu Jiao;Sijie Chen;Jian Ping;Zheng Yan;Haitao Sun","doi":"10.35833/MPCE.2024.001191","DOIUrl":"https://doi.org/10.35833/MPCE.2024.001191","url":null,"abstract":"Distributed photovoltaic (PV) entities can be coordinated to provide reactive power for voltage regulation in distribution networks. However, integrating large-scale distributed PV entities into reactive power optimization makes it difficult to balance the individual benefit of each PV entity with the overall economic efficiency of the system. To address this challenge, we propose a market-oriented two-stage reactive power regulation method. At the first stage, a long-term multi-layer reactive power capacity market is created to incentivize each PV entity to provide reactive power capacity, while ensuring their financial interests are guaranteed. At the second stage, a real-time multi-layer reactive power dispatch mechanism is introduced to manage the reactive power generation of distributed PV entities, prioritizing the dispatch of lower-cost PV entities to maximize system-wide economic efficiency. Simulation results based on a real Finnish radial distribution network demonstrate the effectiveness of the proposed method in optimizing reactive power for large-scale distributed PV entities.","PeriodicalId":51326,"journal":{"name":"Journal of Modern Power Systems and Clean Energy","volume":"14 1","pages":"347-356"},"PeriodicalIF":6.1,"publicationDate":"2025-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11026871","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146102970","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 : 2025-04-30DOI: 10.35833/MPCE.2024.000650
Weiye Diao;Ao Liu;Jun Mei;Linyuan Wang;Guanghua Wang;Fujin Deng
Under weak grid conditions, grid impedance is coupled with a control system for voltage source converter based high-voltage direct current (VSC-HVDC) systems, resulting in decreased synchronization stability. Unfortunately, most studies are based on the assumption that impedance ratio $(R/X)$ is sufficiently small to ignore the effects of grid impedance. In this study, we establish a dynamic coupling model that includes grid impedance and control loops, revealing the influence mechanism of $R/X$ on synchronization stability from a physical perspective. We also quantify the stability range of $R/X$ in the static analysis model and introduce a sensitivity factor to measure its effect on voltage stability. Additionally, we utilize a dynamic analysis model to evaluate power angle convergence, proposing a corresponding stability criterion. We then present a method of synchronous voltage reconstruction aimed at enhancing the grid strength. Theoretical analysis shows that this method can effectively mitigate the effects of coupling between grid impedance and the controller under weak grid conditions, ensuring stable operation even under extremely weak grid conditions. Experiments validate the accuracy and effectiveness of the analysis and method.
{"title":"Synchronous Voltage Reconstruction of VSC-HVDC Systems Under Weak Grid Conditions","authors":"Weiye Diao;Ao Liu;Jun Mei;Linyuan Wang;Guanghua Wang;Fujin Deng","doi":"10.35833/MPCE.2024.000650","DOIUrl":"https://doi.org/10.35833/MPCE.2024.000650","url":null,"abstract":"Under weak grid conditions, grid impedance is coupled with a control system for voltage source converter based high-voltage direct current (VSC-HVDC) systems, resulting in decreased synchronization stability. Unfortunately, most studies are based on the assumption that impedance ratio <tex>$(R/X)$</tex> is sufficiently small to ignore the effects of grid impedance. In this study, we establish a dynamic coupling model that includes grid impedance and control loops, revealing the influence mechanism of <tex>$R/X$</tex> on synchronization stability from a physical perspective. We also quantify the stability range of <tex>$R/X$</tex> in the static analysis model and introduce a sensitivity factor to measure its effect on voltage stability. Additionally, we utilize a dynamic analysis model to evaluate power angle convergence, proposing a corresponding stability criterion. We then present a method of synchronous voltage reconstruction aimed at enhancing the grid strength. Theoretical analysis shows that this method can effectively mitigate the effects of coupling between grid impedance and the controller under weak grid conditions, ensuring stable operation even under extremely weak grid conditions. Experiments validate the accuracy and effectiveness of the analysis and method.","PeriodicalId":51326,"journal":{"name":"Journal of Modern Power Systems and Clean Energy","volume":"13 3","pages":"1040-1051"},"PeriodicalIF":5.7,"publicationDate":"2025-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10981584","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144185827","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}
High proportion of renewable energies and the installation of power electronic devices (PEDs) pose tough challenges to the operation of power systems. In this paper, the remote coordination adjustment (RCA) of PEDs in stochastic scenarios is studied. The steady-state model for the AC/DC system with PEDs is first established, and the alternate iteration method based on linearization (AIML) is adopted, especially for efficient deterministic power flow calculation. Then, the RCA is proposed using a modular local sensitivity method combined with AIML, which can adjust the electrical variables by diverse PEDs with high efficiency. Additionally, the probabilistic power flow calculation using the quasi-Monte Carlo method with the adaptive sampling number (ASN-QMC) is introduced to keep the balance between the computational efficiency and accuracy, as well as demonstrating the positive impact of RCA by the PEDs in stochastic scenarios. The effectiveness of the proposed RCA is validated by a series of modified IEEE test systems.
{"title":"Remote Coordination Adjustment of Power Electronic Devices in AC/DC Systems by Power Flow Calculation with Linearization and Sensitivity","authors":"Junzhou Wang;Xingyu Lin;Junjie Tang;Yuzhi Wang;Guodong Huang;Dan Xu","doi":"10.35833/MPCE.2024.000784","DOIUrl":"https://doi.org/10.35833/MPCE.2024.000784","url":null,"abstract":"High proportion of renewable energies and the installation of power electronic devices (PEDs) pose tough challenges to the operation of power systems. In this paper, the remote coordination adjustment (RCA) of PEDs in stochastic scenarios is studied. The steady-state model for the AC/DC system with PEDs is first established, and the alternate iteration method based on linearization (AIML) is adopted, especially for efficient deterministic power flow calculation. Then, the RCA is proposed using a modular local sensitivity method combined with AIML, which can adjust the electrical variables by diverse PEDs with high efficiency. Additionally, the probabilistic power flow calculation using the quasi-Monte Carlo method with the adaptive sampling number (ASN-QMC) is introduced to keep the balance between the computational efficiency and accuracy, as well as demonstrating the positive impact of RCA by the PEDs in stochastic scenarios. The effectiveness of the proposed RCA is validated by a series of modified IEEE test systems.","PeriodicalId":51326,"journal":{"name":"Journal of Modern Power Systems and Clean Energy","volume":"13 6","pages":"2168-2179"},"PeriodicalIF":6.1,"publicationDate":"2025-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10977786","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145610639","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 : 2025-04-25DOI: 10.35833/MPCE.2024.000853
Heling Yuan;Yan Xu
The widespread penetration of wind power has introduced challenges in managing the rotor angle stability characteristics of the power system, affecting both small- and large-disturbance rotor angle stabilities due to its uncertain steady-state power output and inverter-based grid interfacing. Traditionally, the two stability criteria are separately analyzed and improved via preventive control, e.g., generation rescheduling. However, they may have conflicting relationship during the preventive control optimization. Therefore, this paper firstly integrates both small- and large-disturbance rotor angle stabilities and proposes an optimization model for preventive generation rescheduling to simultaneously improve them while considering wind power uncertainty. The stability constraints are linearized using trajectory sensitivity analysis, while the wind power fluctuation is represented by employing a scenario-based Taguchi's orthogonal array testing (TOAT) method. An iterative solution method is proposed to efficiently solve the optimization model. The proposed optimization model is established on the New England 10-machine 39-bus system and a large Nordic system, demonstrating its robustness and effectiveness in addressing wind power fluctuations.
{"title":"Optimal Preventive Generation Rescheduling for Improving Small- and Large-Disturbance Rotor Angle Stabilities of Power Systems Considering Wind Power Uncertainty","authors":"Heling Yuan;Yan Xu","doi":"10.35833/MPCE.2024.000853","DOIUrl":"https://doi.org/10.35833/MPCE.2024.000853","url":null,"abstract":"The widespread penetration of wind power has introduced challenges in managing the rotor angle stability characteristics of the power system, affecting both small- and large-disturbance rotor angle stabilities due to its uncertain steady-state power output and inverter-based grid interfacing. Traditionally, the two stability criteria are separately analyzed and improved via preventive control, e.g., generation rescheduling. However, they may have conflicting relationship during the preventive control optimization. Therefore, this paper firstly integrates both small- and large-disturbance rotor angle stabilities and proposes an optimization model for preventive generation rescheduling to simultaneously improve them while considering wind power uncertainty. The stability constraints are linearized using trajectory sensitivity analysis, while the wind power fluctuation is represented by employing a scenario-based Taguchi's orthogonal array testing (TOAT) method. An iterative solution method is proposed to efficiently solve the optimization model. The proposed optimization model is established on the New England 10-machine 39-bus system and a large Nordic system, demonstrating its robustness and effectiveness in addressing wind power fluctuations.","PeriodicalId":51326,"journal":{"name":"Journal of Modern Power Systems and Clean Energy","volume":"13 5","pages":"1568-1579"},"PeriodicalIF":6.1,"publicationDate":"2025-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10977789","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145090132","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 : 2025-04-25DOI: 10.35833/MPCE.2024.001021
Jing Ma;Yawen Deng;Honglu Xu;Yufeng Zhao
Existing sub-/super-synchronous oscillation stability control methods are primarily focused on specific operating conditions at discrete frequencies, limiting their adaptation to varying oscillation scenarios in the power system connected with direct-drive permanent magnet synchronous generator (PMSG)-based wind farms. Based on supplementary dissipation compensation, this paper proposes an oscillation stability control method incorporating equipment-level and farm-level cooperative optimization to enhance the system-level stability. First, the effects of dynamic self-dissipation and dynamic coupled dissipation on system stability are analyzed, establishing the foundational principle of supplementary dissipation compensation. Subsequently, the optimal locations for supplementary dissipation compensation are identified based on critical control designed to enhance the dynamic self-dissipation effect and suppress the dynamic coupled dissipation effect. Furthermore, by considering energy requirements under the combined wind farm-grid interaction and inter-PMSG interactions and balancing the wind farm-grid interaction dissipation energy with inter-PMSG interaction dissipation energy distribution, an equipment-level control parameter optimization algorithm and a farm-level power cooperative optimization algorithm are established. Finally, the simulation results demonstrate that dynamic coupled dissipation constitutes the root cause of oscillation inception and progression. Through equipment-level and farm-level cooperative optimization, the proposed method can reliably compensate dynamic dissipation energy, while adapting to the variation of oscillation frequency and the oscillation scenario. It can maximize the energy dissipation effect of the interconnected system, achieving rapid suppression of sub-/super-synchronous oscillations.
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