Pub Date : 2024-11-22DOI: 10.35833/MPCE.2024.000674
Yu-Qing Bao;Qing-Quan Yu;Yu Chen;Shu-Han Yu
Energy storage can smooth the fluctuations of wind power integrated into the grid. Due to the strong adaptability of the empirical mode decomposition (EMD) algorithm to non-stationary signals, it is widely used in wind power smoothing control strategies. However, traditional EMD algorithms cannot guarantee that the upper and lower areas of the calculated intrinsic mode functions (IMFs) are equal, which tends to result in imbalanced calculated energy storage power and thus exceeding the limit of energy storage capacity. Focusing on wind power smoothing control by energy storage, this paper proposes a strategy based on the area-equilibrium EMD, which modifies the upper and lower areas of the IMFs to achieve a more balanced distribution. As a result, the IMFs contain less energy, and consequently, the energy contained in the calculated smoothing power is also reduced. This makes the energy storage capacity less likely to exceed the limit, thereby achieving better wind power smoothing performance under given energy storage capacity. Case studies show that the proposed strategy results in more balanced upper and lower areas of the IMFs, reduces the fluctuating range of calculated energy storage, and improves the wind power smoothing effectiveness.
{"title":"Wind Power Smoothing Control by Energy Storage Based on Area-Equilibrium Empirical Mode Decomposition","authors":"Yu-Qing Bao;Qing-Quan Yu;Yu Chen;Shu-Han Yu","doi":"10.35833/MPCE.2024.000674","DOIUrl":"https://doi.org/10.35833/MPCE.2024.000674","url":null,"abstract":"Energy storage can smooth the fluctuations of wind power integrated into the grid. Due to the strong adaptability of the empirical mode decomposition (EMD) algorithm to non-stationary signals, it is widely used in wind power smoothing control strategies. However, traditional EMD algorithms cannot guarantee that the upper and lower areas of the calculated intrinsic mode functions (IMFs) are equal, which tends to result in imbalanced calculated energy storage power and thus exceeding the limit of energy storage capacity. Focusing on wind power smoothing control by energy storage, this paper proposes a strategy based on the area-equilibrium EMD, which modifies the upper and lower areas of the IMFs to achieve a more balanced distribution. As a result, the IMFs contain less energy, and consequently, the energy contained in the calculated smoothing power is also reduced. This makes the energy storage capacity less likely to exceed the limit, thereby achieving better wind power smoothing performance under given energy storage capacity. Case studies show that the proposed strategy results in more balanced upper and lower areas of the IMFs, reduces the fluctuating range of calculated energy storage, and improves the wind power smoothing effectiveness.","PeriodicalId":51326,"journal":{"name":"Journal of Modern Power Systems and Clean Energy","volume":"13 4","pages":"1238-1247"},"PeriodicalIF":5.7,"publicationDate":"2024-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10766354","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144716287","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 : 2024-11-22DOI: 10.35833/MPCE.2024.000859
Ali Alizadeh;Mahmoud A. Allam;Moein Esfahani;Innocent Kamwa
Advanced management algorithms are required in modern power systems to sustain energy supply with the highest availability and lowest cost. These algorithms need to be capable of not only maintaining scalability, tractability, and privacy, but also enabling the utilization of grid-edge aggregated flex-ibilities in transmission systems. This paper proposes a distributed hierarchical transactive energy management (TEM) scheme to manage peak load and line congestion problems using connected and aggregated flexibilities. In the scheme, resource owners can privately solve their respective preference problems and send their scheduled power to the corresponding node operator (NO). Afterward, NOs solve a coordination problem to harmonize the actions of resource owners at the same node. Meanwhile, the independent system operator (ISO) updates control signals to steer the scheduled power to a feasible and optimal point. To accomplish all these, a hybrid decomposition approach is further proposed based on consensus+exchange alternating direction method of multipliers (CE-ADMM) and dual decomposition (DD) (CE-ADMM + DD). Besides, a dynamically constrained cutting plane (DC-CP) update algorithm is evolved to control the feasibility condition and minimize sensitivity to initialization. The proposed hybrid decomposition approach is verified and its performance is compared with other reported approaches. Application to various networks verifies its scalability, enhanced accuracy, and convergence speed.
{"title":"Distributed Hierarchical Transactive Energy Management to Exploit Flexibilities in Transmission Systems","authors":"Ali Alizadeh;Mahmoud A. Allam;Moein Esfahani;Innocent Kamwa","doi":"10.35833/MPCE.2024.000859","DOIUrl":"https://doi.org/10.35833/MPCE.2024.000859","url":null,"abstract":"Advanced management algorithms are required in modern power systems to sustain energy supply with the highest availability and lowest cost. These algorithms need to be capable of not only maintaining scalability, tractability, and privacy, but also enabling the utilization of grid-edge aggregated flex-ibilities in transmission systems. This paper proposes a distributed hierarchical transactive energy management (TEM) scheme to manage peak load and line congestion problems using connected and aggregated flexibilities. In the scheme, resource owners can privately solve their respective preference problems and send their scheduled power to the corresponding node operator (NO). Afterward, NOs solve a coordination problem to harmonize the actions of resource owners at the same node. Meanwhile, the independent system operator (ISO) updates control signals to steer the scheduled power to a feasible and optimal point. To accomplish all these, a hybrid decomposition approach is further proposed based on consensus+exchange alternating direction method of multipliers (CE-ADMM) and dual decomposition (DD) (CE-ADMM + DD). Besides, a dynamically constrained cutting plane (DC-CP) update algorithm is evolved to control the feasibility condition and minimize sensitivity to initialization. The proposed hybrid decomposition approach is verified and its performance is compared with other reported approaches. Application to various networks verifies its scalability, enhanced accuracy, and convergence speed.","PeriodicalId":51326,"journal":{"name":"Journal of Modern Power Systems and Clean Energy","volume":"13 5","pages":"1520-1531"},"PeriodicalIF":6.1,"publicationDate":"2024-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10766353","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145090137","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 : 2024-11-19DOI: 10.35833/MPCE.2024.000529
Sufan Jiang;Fangxing Li;Xiaofei Wang;Chenchen Li
Energy equity refers to the condition in which access to the cleaner energy required by individuals is equally available to all. To relieve the energy expenditures - the key component in the concept of energy equity - of low-income communities, governments worldwide have imposed caps on soaring energy prices. However, the inherent mechanisms within the operational schedule remain undiscussed. This paper innovatively provides guidelines for operators to embed energy burden policies into the bulk power system model, by answering two critical questions. ① What is the impact on system price pattern when embedding the locational price constraints? ② How to reformulate the tie-line schedule to meet the equity thresholds? Consequently, a novel bi-level energy equity-constrained tie-line scheduling model is proposed. The conventional economic dispatch is solved at the upper level, and then a preliminary operational schedule is given to the lower level, where we propose an energy equity slackness component variable to evaluate the gap between preliminary and desired equity-satisfied operational schedules. The implicit constraints on the price are converted into explicit feasibility cuts with dual theory. Case studies on test systems demonstrate the reduced energy expenditure for underserved communities, and the optimal tie-line schedule is also validated.
{"title":"Energy Equity-Constrained Tie-Line Scheduling Model in Interconnected Systems","authors":"Sufan Jiang;Fangxing Li;Xiaofei Wang;Chenchen Li","doi":"10.35833/MPCE.2024.000529","DOIUrl":"https://doi.org/10.35833/MPCE.2024.000529","url":null,"abstract":"Energy equity refers to the condition in which access to the cleaner energy required by individuals is equally available to all. To relieve the energy expenditures - the key component in the concept of energy equity - of low-income communities, governments worldwide have imposed caps on soaring energy prices. However, the inherent mechanisms within the operational schedule remain undiscussed. This paper innovatively provides guidelines for operators to embed energy burden policies into the bulk power system model, by answering two critical questions. ① What is the impact on system price pattern when embedding the locational price constraints? ② How to reformulate the tie-line schedule to meet the equity thresholds? Consequently, a novel bi-level energy equity-constrained tie-line scheduling model is proposed. The conventional economic dispatch is solved at the upper level, and then a preliminary operational schedule is given to the lower level, where we propose an energy equity slackness component variable to evaluate the gap between preliminary and desired equity-satisfied operational schedules. The implicit constraints on the price are converted into explicit feasibility cuts with dual theory. Case studies on test systems demonstrate the reduced energy expenditure for underserved communities, and the optimal tie-line schedule is also validated.","PeriodicalId":51326,"journal":{"name":"Journal of Modern Power Systems and Clean Energy","volume":"13 2","pages":"391-402"},"PeriodicalIF":5.7,"publicationDate":"2024-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10758361","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143716389","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 this paper, a set of distributed secondary controllers is introduced that provide active regulation for both steady-state and transient-state performances of an islanded DC microgrid (MG). The secondary control for distributed converter interfaced generation (DCIG) not only guarantees that the system converges to the desired operating states in the steady state but also regulates the state variations to a prescribed transient-state performance. Compared with state-of-the-art techniques of distributed secondary control, this paper achieves accurate steady-state secondary regulations with prescribed transient-state performance in an islanded DC MG. Moreover, the applicability of the proposed control does not rely on any explicit knowledge of the system topology or physical parameters. Detailed controller designs are provided, and the system under control is proved to be Lyapunov stable using large-signal stability analysis. The steady-state and transient-state performances of the system are analyzed. The paper proves that as the perturbed system converges, the proposed control achieves accurate proportional power sharing and average voltage regulation among the DCIGs, and the transient variations of the operating voltages and power outputs at each DCIG are regulated to the prescribed transient-state performance. The effectiveness of the proposed control is validated via a four-DCIG MG system.
{"title":"Secondary Control for Distributed Converter Interfaced Generation with Prescribed Transient-State Performance in DC Microgrid","authors":"Aili Fan;Jiangong Yang;Yuhua Du;Zhipeng Li;Fei Gao;Yigeng Huangfu","doi":"10.35833/MPCE.2024.000267","DOIUrl":"https://doi.org/10.35833/MPCE.2024.000267","url":null,"abstract":"In this paper, a set of distributed secondary controllers is introduced that provide active regulation for both steady-state and transient-state performances of an islanded DC microgrid (MG). The secondary control for distributed converter interfaced generation (DCIG) not only guarantees that the system converges to the desired operating states in the steady state but also regulates the state variations to a prescribed transient-state performance. Compared with state-of-the-art techniques of distributed secondary control, this paper achieves accurate steady-state secondary regulations with prescribed transient-state performance in an islanded DC MG. Moreover, the applicability of the proposed control does not rely on any explicit knowledge of the system topology or physical parameters. Detailed controller designs are provided, and the system under control is proved to be Lyapunov stable using large-signal stability analysis. The steady-state and transient-state performances of the system are analyzed. The paper proves that as the perturbed system converges, the proposed control achieves accurate proportional power sharing and average voltage regulation among the DCIGs, and the transient variations of the operating voltages and power outputs at each DCIG are regulated to the prescribed transient-state performance. The effectiveness of the proposed control is validated via a four-DCIG MG system.","PeriodicalId":51326,"journal":{"name":"Journal of Modern Power Systems and Clean Energy","volume":"13 3","pages":"980-990"},"PeriodicalIF":5.7,"publicationDate":"2024-11-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10755057","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144139815","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 : 2024-11-15DOI: 10.35833/MPCE.2024.000409
Ziyang Yin;Shouxiang Wang;Qianyu Zhao
In the context of large-scale photovoltaic integration, flexibility scheduling is essential to ensure the secure and efficient operation of distribution networks (DNs). Recently, deep reinforcement learning (DRL) has been widely applied to scheduling problems. However, most methods neglect the vulnerability of DRL to state adversarial attacks such as load redistribution attacks, significantly undermining its security and reliability. To this end, a flexibility scheduling method is proposed based on robust graph DRL (RoGDRL). A flexibility gain improvement model considering temperature-dependent resistance is first proposed, which considers weather factors as additional variables to enhance the precision of flexibility analysis. Based on this, a state-adversarial two-player zero-sum Markov game (SA-TZMG) model is proposed, which converts the robust DRL scheduling problem into a Nash equilibrium problem. The proposed SA-TZMG model considers the physical constraints of state attacks that guarantee the maximal flexibility gain for the defender when confronted with the most sophisticated and stealthy attacker. A two-stage RoGDRL algorithm is proposed, which introduces the graph sample and aggregate (Graph-SAGE) driven soft actor-critic to capture the complex feature about the neighbors of nodes and their properties via inductive learning, thereby solving the Nash equilibrium policies more efficiently. Simulations based on the modified IEEE 123-bus system demonstrates the efficacy of the proposed method.
{"title":"A Flexibility Scheduling Method for Distribution Network Based on Robust Graph DRL Against State Adversarial Attacks","authors":"Ziyang Yin;Shouxiang Wang;Qianyu Zhao","doi":"10.35833/MPCE.2024.000409","DOIUrl":"https://doi.org/10.35833/MPCE.2024.000409","url":null,"abstract":"In the context of large-scale photovoltaic integration, flexibility scheduling is essential to ensure the secure and efficient operation of distribution networks (DNs). Recently, deep reinforcement learning (DRL) has been widely applied to scheduling problems. However, most methods neglect the vulnerability of DRL to state adversarial attacks such as load redistribution attacks, significantly undermining its security and reliability. To this end, a flexibility scheduling method is proposed based on robust graph DRL (RoGDRL). A flexibility gain improvement model considering temperature-dependent resistance is first proposed, which considers weather factors as additional variables to enhance the precision of flexibility analysis. Based on this, a state-adversarial two-player zero-sum Markov game (SA-TZMG) model is proposed, which converts the robust DRL scheduling problem into a Nash equilibrium problem. The proposed SA-TZMG model considers the physical constraints of state attacks that guarantee the maximal flexibility gain for the defender when confronted with the most sophisticated and stealthy attacker. A two-stage RoGDRL algorithm is proposed, which introduces the graph sample and aggregate (Graph-SAGE) driven soft actor-critic to capture the complex feature about the neighbors of nodes and their properties via inductive learning, thereby solving the Nash equilibrium policies more efficiently. Simulations based on the modified IEEE 123-bus system demonstrates the efficacy of the proposed method.","PeriodicalId":51326,"journal":{"name":"Journal of Modern Power Systems and Clean Energy","volume":"13 2","pages":"514-526"},"PeriodicalIF":5.7,"publicationDate":"2024-11-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10755058","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143716448","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 : 2024-11-15DOI: 10.35833/MPCE.2024.000534
Wei Zha;Haiwang Zhong;Yinyan Liu
The difficulty in capital recovery for distributed renewable energy operators (DREOs) and the high charging costs at electric vehicle charging stations (EVCSs) have long been significant challenges in power systems. Collaborative operation of DREOs and EVCSs can effectively address these challenges, yet few studies have approached incentivizing collaboration from the perspective of profit allocation. Therefore, this paper proposes a fair and efficient profit allocation method. Incorporating the Gauss-Legendre quadrature formula into the Aumann-Shapley value (GL-AS) method enables efficient calculation of the profit allocation of cooperative members. However, existing literature only discusses the profit allocation method of conventional power generation units, limiting its applicability. This paper addresses the problem of energy storage system (ESS) switching between charging and discharging in any time interval and the time-varying problem of renewable energy power output, thereby ensuring the efficiency of the solution process. Furthermore, a novel profit allocation adjustment model is provided through the adoption of triangular fuzzy comprehensive evaluation (TFCE). Finally, the effectiveness of the proposed profit allocation method is validated through numerical simulations in various scenarios.
{"title":"Fair and Efficient Profit Allocation for Collaborative Operation of Distributed Renewable Energy Operators and Electric Vehicle Charging Stations","authors":"Wei Zha;Haiwang Zhong;Yinyan Liu","doi":"10.35833/MPCE.2024.000534","DOIUrl":"https://doi.org/10.35833/MPCE.2024.000534","url":null,"abstract":"The difficulty in capital recovery for distributed renewable energy operators (DREOs) and the high charging costs at electric vehicle charging stations (EVCSs) have long been significant challenges in power systems. Collaborative operation of DREOs and EVCSs can effectively address these challenges, yet few studies have approached incentivizing collaboration from the perspective of profit allocation. Therefore, this paper proposes a fair and efficient profit allocation method. Incorporating the Gauss-Legendre quadrature formula into the Aumann-Shapley value (GL-AS) method enables efficient calculation of the profit allocation of cooperative members. However, existing literature only discusses the profit allocation method of conventional power generation units, limiting its applicability. This paper addresses the problem of energy storage system (ESS) switching between charging and discharging in any time interval and the time-varying problem of renewable energy power output, thereby ensuring the efficiency of the solution process. Furthermore, a novel profit allocation adjustment model is provided through the adoption of triangular fuzzy comprehensive evaluation (TFCE). Finally, the effectiveness of the proposed profit allocation method is validated through numerical simulations in various scenarios.","PeriodicalId":51326,"journal":{"name":"Journal of Modern Power Systems and Clean Energy","volume":"13 4","pages":"1395-1406"},"PeriodicalIF":5.7,"publicationDate":"2024-11-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10755053","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144716310","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 : 2024-11-12DOI: 10.35833/MPCE.2024.000469
Manijeh Alipour;Gevork B. Gharehpetian;Roya Ahmadiahangar;Argo Rosin
As the penetration of intermittent renewable energy resources in microgrids (MGs) continues to grow globally, optimal operation management becomes increasingly crucial due to the variability of these sources. One potential solution to this challenge is the use of demand response (DR) programs, which are practical and relatively low-cost options. However, ensuring the security of MG operation also requires evaluating its flexibility by determining the acceptable boundaries of uncertain variables. Additionally, in real-world operational decision-making problems, there is a simultaneous optimization of multiple objectives, including the maximization of system flexibility and the minimization of system cost. This paper presents a methodology for developing a cost-aware flexibility evaluation method for MGs connected to the upstream grid, which are subject to volatile market prices. The model is based on the feasibility analysis of the uncertain space of wind power generation and load, and it also investigates the level of inflexibility present in the system. The impact of the DR program on the flexibility of MGs is quantified through a case study. The case study confirms the success of the proposed method and underscores the significance of cost modeling in flexibility evaluation problems.
{"title":"Cost-Aware Flexibility Evaluation for Microgrids","authors":"Manijeh Alipour;Gevork B. Gharehpetian;Roya Ahmadiahangar;Argo Rosin","doi":"10.35833/MPCE.2024.000469","DOIUrl":"https://doi.org/10.35833/MPCE.2024.000469","url":null,"abstract":"As the penetration of intermittent renewable energy resources in microgrids (MGs) continues to grow globally, optimal operation management becomes increasingly crucial due to the variability of these sources. One potential solution to this challenge is the use of demand response (DR) programs, which are practical and relatively low-cost options. However, ensuring the security of MG operation also requires evaluating its flexibility by determining the acceptable boundaries of uncertain variables. Additionally, in real-world operational decision-making problems, there is a simultaneous optimization of multiple objectives, including the maximization of system flexibility and the minimization of system cost. This paper presents a methodology for developing a cost-aware flexibility evaluation method for MGs connected to the upstream grid, which are subject to volatile market prices. The model is based on the feasibility analysis of the uncertain space of wind power generation and load, and it also investigates the level of inflexibility present in the system. The impact of the DR program on the flexibility of MGs is quantified through a case study. The case study confirms the success of the proposed method and underscores the significance of cost modeling in flexibility evaluation problems.","PeriodicalId":51326,"journal":{"name":"Journal of Modern Power Systems and Clean Energy","volume":"13 3","pages":"1003-1013"},"PeriodicalIF":5.7,"publicationDate":"2024-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10751675","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144139850","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}
To improve the safety of the solid oxide fuel cell (SOFC) systems and avoid the generation of large amounts of pollutants during power switching, this paper designs a power switching strategy based on trajectory planning and sliding mode control (TP-SMC). The design elements of the power switching strategy are proposed through simulation analysis at first. Then, based on the gas transmission delay time and the change of gas flow obtained from testing, trajectory planning (TP) is implemented. Compared with other power switching strategies, it has been proven that the power switching strategy based on TP has significantly better control performance. Furthermore, considering the shortcomings and problems of TP in practical application, this paper introduces sliding mode control (SMC) on the basis of TP to improve the power switching strategy. The final simulation results also prove that the TP-SMC can effectively suppress the impact of uncertainty in gas flow and gas transmission delay time. Compared with TP, TP-SMC can ensure that under uncertain conditions, the SOFC system does not experience fuel starvation and temperature exceeding limit during power switching. Meanwhile, the NOx emissions are also within the normal and acceptable range. This paper can guide the power switching process of the actual SOFC systems to avoid safety issues and excessive generation of NOx, which is very helpful for improving the performance and service life of the SOFC systems.
{"title":"Power Switching Based on Trajectory Planning and Sliding Mode Control for Solid Oxide Fuel Cell Systems","authors":"Zhen Wang;Guoqiang Liu;Xingbo Liu;Jie Wang;Zhiyang Jin;Xiaowei Fu;Zhuo Wang;Bing Jin;Zhonghua Deng;Xi Li","doi":"10.35833/MPCE.2024.000284","DOIUrl":"https://doi.org/10.35833/MPCE.2024.000284","url":null,"abstract":"To improve the safety of the solid oxide fuel cell (SOFC) systems and avoid the generation of large amounts of pollutants during power switching, this paper designs a power switching strategy based on trajectory planning and sliding mode control (TP-SMC). The design elements of the power switching strategy are proposed through simulation analysis at first. Then, based on the gas transmission delay time and the change of gas flow obtained from testing, trajectory planning (TP) is implemented. Compared with other power switching strategies, it has been proven that the power switching strategy based on TP has significantly better control performance. Furthermore, considering the shortcomings and problems of TP in practical application, this paper introduces sliding mode control (SMC) on the basis of TP to improve the power switching strategy. The final simulation results also prove that the TP-SMC can effectively suppress the impact of uncertainty in gas flow and gas transmission delay time. Compared with TP, TP-SMC can ensure that under uncertain conditions, the SOFC system does not experience fuel starvation and temperature exceeding limit during power switching. Meanwhile, the NOx emissions are also within the normal and acceptable range. This paper can guide the power switching process of the actual SOFC systems to avoid safety issues and excessive generation of NOx, which is very helpful for improving the performance and service life of the SOFC systems.","PeriodicalId":51326,"journal":{"name":"Journal of Modern Power Systems and Clean Energy","volume":"12 6","pages":"1968-1979"},"PeriodicalIF":5.7,"publicationDate":"2024-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10747305","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142844558","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 power loss minimization and DC voltage stability of the multi-terminal direct current (MTDC) system with large-scale wind farm (WF) cluster affect the stability and power quality of the interconnected power grid. This paper proposes a distributed optimal voltage control (DOVC) strategy, which aims to optimize voltage distribution in MTDC and WF systems, reduce system power losses, and track power dispatch commands. The proposed DOVC strategy employs a bi-level distributed control architecture. At the upper level, the MTDC controller coordinates power flow, DC-side voltage of grid-side voltage source converters (GSVSCs), and WF-side voltage source converters (WFVSCs) for power loss minimization and DC voltage stabilization of the MTDC system. At the lower level, the WF controller coordinates the controlled bus voltage of WFVSC and the active and reactive power of wind turbines (WTs) to maintain WT terminal voltages within feasible range. Then, the WF controller minimizes the power loss of the WF system, while tracking the optimal command from the upper-level control strategy. Considering the computational tasks of multi-objective optimization with large-scale WF cluster, the proposed DOVC strategy is executed in a distributed manner based on the alternating direction method of multipliers (AD-MM). An MTDC system with large-scale WF cluster is established in MATLAB to validate the effectiveness of the proposed DOVC strategy.
{"title":"Distributed Optimal Voltage Control for Multi-Terminal Direct Current System with Large-Scale Wind Farm Cluster Based on ADMM","authors":"Xueping Li;Yinpeng Qu;Jianxin Deng;Sheng Huang;Derong Luo;Qiuwei Wu","doi":"10.35833/MPCE.2024.000298","DOIUrl":"https://doi.org/10.35833/MPCE.2024.000298","url":null,"abstract":"The power loss minimization and DC voltage stability of the multi-terminal direct current (MTDC) system with large-scale wind farm (WF) cluster affect the stability and power quality of the interconnected power grid. This paper proposes a distributed optimal voltage control (DOVC) strategy, which aims to optimize voltage distribution in MTDC and WF systems, reduce system power losses, and track power dispatch commands. The proposed DOVC strategy employs a bi-level distributed control architecture. At the upper level, the MTDC controller coordinates power flow, DC-side voltage of grid-side voltage source converters (GSVSCs), and WF-side voltage source converters (WFVSCs) for power loss minimization and DC voltage stabilization of the MTDC system. At the lower level, the WF controller coordinates the controlled bus voltage of WFVSC and the active and reactive power of wind turbines (WTs) to maintain WT terminal voltages within feasible range. Then, the WF controller minimizes the power loss of the WF system, while tracking the optimal command from the upper-level control strategy. Considering the computational tasks of multi-objective optimization with large-scale WF cluster, the proposed DOVC strategy is executed in a distributed manner based on the alternating direction method of multipliers (AD-MM). An MTDC system with large-scale WF cluster is established in MATLAB to validate the effectiveness of the proposed DOVC strategy.","PeriodicalId":51326,"journal":{"name":"Journal of Modern Power Systems and Clean Energy","volume":"13 3","pages":"1052-1063"},"PeriodicalIF":5.7,"publicationDate":"2024-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10746395","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144185811","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}
Traditional protection methods are not suitable for hybrid (cable and overhead) transmission lines in voltage source converter based high-voltage direct current (VSC-HVDC) systems. Accordingly, this paper presents the robust fault detection, classification, and location based on the empirical wavelet transform-Teager energy operator (EWT-TEO) and artificial neural network (ANN) for hybrid transmission lines in VSC-HVDC systems. The operational scheme of the proposed protection method consists of two loops: ①an EWT-TEO based feature extraction loop, ② and an ANN-based fault detection, classification, and location loop. Under the proposed protection method, the voltage and current signals are decomposed into several sub-passbands with low and high frequencies using the empirical wavelet transform (EWT) method. The energy content extracted by the EWT is fed into the ANN for fault detection, classification, and location. Various fault cases, including the high-impedance fault (HIF) as well as noises, are performed to train the ANN with two hidden layers. The test system and signal decomposition are conducted by PSCAD/EMT-DC and MATLAB, respectively. The performance of the proposed protection method is compared with that of the traditional non-pilot traveling wave (TW) based protection method. The results confirm the high accuracy of the proposed protection method for hybrid transmission lines in VSC-HVDC systems, where a mean percentage error of approximately 0.1% is achieved.
{"title":"Fault Detection, Classification, and Location Based on Empirical Wavelet Transform-Teager Energy Operator and ANN for Hybrid Transmission Lines in VSC-HVDC Systems","authors":"Jalal Sahebkar Farkhani;Özgür Çelik;Kaiqi Ma;Claus Leth Bak;Zhe Chen","doi":"10.35833/MPCE.2023.000925","DOIUrl":"https://doi.org/10.35833/MPCE.2023.000925","url":null,"abstract":"Traditional protection methods are not suitable for hybrid (cable and overhead) transmission lines in voltage source converter based high-voltage direct current (VSC-HVDC) systems. Accordingly, this paper presents the robust fault detection, classification, and location based on the empirical wavelet transform-Teager energy operator (EWT-TEO) and artificial neural network (ANN) for hybrid transmission lines in VSC-HVDC systems. The operational scheme of the proposed protection method consists of two loops: ①an EWT-TEO based feature extraction loop, ② and an ANN-based fault detection, classification, and location loop. Under the proposed protection method, the voltage and current signals are decomposed into several sub-passbands with low and high frequencies using the empirical wavelet transform (EWT) method. The energy content extracted by the EWT is fed into the ANN for fault detection, classification, and location. Various faul<sup>t</sup> cases, including the high-impedance fault (HIF) as well as noises, are performed to train the ANN with two hidden layers. The test system and signal decomposition are conducted by PSCAD/EMT-DC and MATLAB, respectively. The performance of the proposed protection method is compared with that of the traditional non-pilot traveling wave (TW) based protection method. The results confirm the high accuracy of the proposed protection method for hybrid transmission lines in VSC-HVDC systems, where a mean percentage error of approximately 0.1% is achieved.","PeriodicalId":51326,"journal":{"name":"Journal of Modern Power Systems and Clean Energy","volume":"13 3","pages":"840-851"},"PeriodicalIF":5.7,"publicationDate":"2024-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10747304","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144139847","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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