Pub Date : 2024-07-22DOI: 10.1109/TSTE.2024.3431616
Changhee Han;Ramesh R. Rao;Seokheon Cho
To achieve flexible operation of modern distribution networks with increasing renewable energy sources (RESs), this study proposes a stochastic operation method for a novel energy management platform that combines energy storage with a power flow controller, which is presented as a multi-terminal soft open point (MT-SOP). A Wasserstein metric-based distributionally robust chance-constrained optimization for the operation of the MT-SOP is proposed under the assumption that there is no prior knowledge about the distribution of forecast errors for both the load and RES outputs. The proposed method stochastically relaxes the reliability constraints on the bus voltage and branch power flow to maximize the cost-benefit of the distribution system operator (DSO). The proposed problem was reformulated into a tractable convex program using the concept of conditional value-at-risk. Based on case studies using modified IEEE-33 systems, the trade-offs between operational risks and cost–benefits were analyzed using parameters on the risk level and radius of the ambiguity set. Through numerical comparisons of the simulation results, we show that the DSO can achieve economic efficiency for imported electricity by relaxing conservativeness in distribution network reliability.
{"title":"Stochastic Operation of Multi-Terminal Soft Open Points in Distribution Networks With Distributionally Robust Chance-Constrained Optimization","authors":"Changhee Han;Ramesh R. Rao;Seokheon Cho","doi":"10.1109/TSTE.2024.3431616","DOIUrl":"10.1109/TSTE.2024.3431616","url":null,"abstract":"To achieve flexible operation of modern distribution networks with increasing renewable energy sources (RESs), this study proposes a stochastic operation method for a novel energy management platform that combines energy storage with a power flow controller, which is presented as a multi-terminal soft open point (MT-SOP). A Wasserstein metric-based distributionally robust chance-constrained optimization for the operation of the MT-SOP is proposed under the assumption that there is no prior knowledge about the distribution of forecast errors for both the load and RES outputs. The proposed method stochastically relaxes the reliability constraints on the bus voltage and branch power flow to maximize the cost-benefit of the distribution system operator (DSO). The proposed problem was reformulated into a tractable convex program using the concept of conditional value-at-risk. Based on case studies using modified IEEE-33 systems, the trade-offs between operational risks and cost–benefits were analyzed using parameters on the risk level and radius of the ambiguity set. Through numerical comparisons of the simulation results, we show that the DSO can achieve economic efficiency for imported electricity by relaxing conservativeness in distribution network reliability.","PeriodicalId":452,"journal":{"name":"IEEE Transactions on Sustainable Energy","volume":"16 1","pages":"81-94"},"PeriodicalIF":8.6,"publicationDate":"2024-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141780215","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-19DOI: 10.1109/TSTE.2024.3430844
Min Du;Jinning Zhang;Chenghong Gu;Xin Zhang
This paper aims to produce a practical and efficient decision for the system operator to harden critical components in power systems with high wind power penetration against uncertain attacks. Thus, an adjustable robust tri-level defender-attacker-defender (ART-DAD) model is proposed to improve the resilience of power systems by hardening critical transmission lines. The proposed ART-DAD model considers both uncertain attacks and uncertain wind power output, which provides meaningful insights into the resilience improvement of power systems that involve uncertainties. More specifically, the proposed defense model integrates dynamic N-K criterion for attack budgets and the polyhedral uncertainty set for wind power output to develop resilient line hardening strategies. The proposed defense model can be formulated as a mixed integer tri-level programming problem that is decoupled into a master and sub-problem. Then, a constraint-generation based solution algorithm is proposed to solve the overall ART-DAD model with a master and sub-problem scheme. Simulation results on IEEE RTS-79 and RTS-96 systems validate the effectiveness of the proposed resilience improving strategy.
{"title":"Resilience Improving Strategy for Power Systems With High Wind Power Penetration Against Uncertain Attacks","authors":"Min Du;Jinning Zhang;Chenghong Gu;Xin Zhang","doi":"10.1109/TSTE.2024.3430844","DOIUrl":"10.1109/TSTE.2024.3430844","url":null,"abstract":"This paper aims to produce a practical and efficient decision for the system operator to harden critical components in power systems with high wind power penetration against uncertain attacks. Thus, an adjustable robust tri-level defender-attacker-defender (ART-DAD) model is proposed to improve the resilience of power systems by hardening critical transmission lines. The proposed ART-DAD model considers both uncertain attacks and uncertain wind power output, which provides meaningful insights into the resilience improvement of power systems that involve uncertainties. More specifically, the proposed defense model integrates dynamic N-K criterion for attack budgets and the polyhedral uncertainty set for wind power output to develop resilient line hardening strategies. The proposed defense model can be formulated as a mixed integer tri-level programming problem that is decoupled into a master and sub-problem. Then, a constraint-generation based solution algorithm is proposed to solve the overall ART-DAD model with a master and sub-problem scheme. Simulation results on IEEE RTS-79 and RTS-96 systems validate the effectiveness of the proposed resilience improving strategy.","PeriodicalId":452,"journal":{"name":"IEEE Transactions on Sustainable Energy","volume":"15 4","pages":"2625-2637"},"PeriodicalIF":8.6,"publicationDate":"2024-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141740371","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-19DOI: 10.1109/TSTE.2024.3430972
Yubo Zhang;Songhao Yang;Zhiguo Hao;Baohui Zhang
The fast frequency support (FFS) towards frequency trajectory optimization provides a system view for the frequency regulation of wind farms (WFs). However, the existing frequency trajectory optimization-based FFS generally relies on the accurate governor dynamics model of synchronous generators (SGs), which aggrandizes the difficulty of controller implementation. In this paper, a proportional-integral (PI) based FFS of WFs is designed for tracking the optimal frequency trajectory, which gets rid of the dependence on the governor model. Firstly, the prototypical PI-based FFS of WFs is proposed and its feasibility for tracking the optimal frequency trajectory is analyzed and demonstrated. Then, based on the “frequency-RoCoF” form of the optimal frequency trajectory, a more practical PI controller is constructed, avoiding the time dependence of the prototypical PI controller. Besides, an adaptive gain associated with PI parameters is designed for multi-WF coordination. Finally, the validity of the proposed method is verified in both the single-WF system and the multi-WF system.
面向频率轨迹优化的快速频率支持（FFS）为风电场（WFs）的频率调节提供了系统视图。然而，现有的基于频率轨迹优化的 FFS 通常依赖于同步发电机 (SG) 的精确调速器动力学模型，这增加了控制器实现的难度。本文设计了一种基于比例积分（PI）的风力发电机 FFS，用于跟踪最优频率轨迹，摆脱了对调速器模型的依赖。首先，提出了基于 PI 的 WFs FFS 原型，并分析和论证了其跟踪最佳频率轨迹的可行性。然后，根据最佳频率轨迹的 "频率-RoCoF "形式，构建了一个更实用的 PI 控制器，避免了原型 PI 控制器的时间依赖性。此外，还为多 WF 协调设计了与 PI 参数相关的自适应增益。最后，在单 WF 系统和多 WF 系统中验证了所提方法的有效性。
{"title":"Model-Free Fast Frequency Support of Wind Farms for Tracking Optimal Frequency Trajectory","authors":"Yubo Zhang;Songhao Yang;Zhiguo Hao;Baohui Zhang","doi":"10.1109/TSTE.2024.3430972","DOIUrl":"10.1109/TSTE.2024.3430972","url":null,"abstract":"The fast frequency support (FFS) towards frequency trajectory optimization provides a system view for the frequency regulation of wind farms (WFs). However, the existing frequency trajectory optimization-based FFS generally relies on the accurate governor dynamics model of synchronous generators (SGs), which aggrandizes the difficulty of controller implementation. In this paper, a proportional-integral (PI) based FFS of WFs is designed for tracking the optimal frequency trajectory, which gets rid of the dependence on the governor model. Firstly, the prototypical PI-based FFS of WFs is proposed and its feasibility for tracking the optimal frequency trajectory is analyzed and demonstrated. Then, based on the “frequency-RoCoF” form of the optimal frequency trajectory, a more practical PI controller is constructed, avoiding the time dependence of the prototypical PI controller. Besides, an adaptive gain associated with PI parameters is designed for multi-WF coordination. Finally, the validity of the proposed method is verified in both the single-WF system and the multi-WF system.","PeriodicalId":452,"journal":{"name":"IEEE Transactions on Sustainable Energy","volume":"15 4","pages":"2638-2650"},"PeriodicalIF":8.6,"publicationDate":"2024-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141740370","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-18DOI: 10.1109/TSTE.2024.3430321
Douglas M. Logan;Fred Beasom;Murty P. Bhavaraju;Francis J. Bell;Lee Thaubald;Kai Jiang;Chris J. Dent
IEEE Standard Definitions for Use in Reporting Electric Generating Unit Reliability, Availability, and Productivity has recently been revised to extend the standard to variable energy resource (VER) generating facilities. The revision includes definitions of energy resource and resource unavailability, indexes that distinguish between equipment performance and the availability of a generator for system reliability analysis purposes, and generation-based reliability indexes for VER units corresponding to the traditional time-based indexes in previous versions of the standard. The revision also includes definition of critical period indexes, where the critical period is specified as hours of high system need. This paper describes the new terms and outlines issues with their definition.
{"title":"Reliability Indexes for Variable Energy Resource Generation in IEEE Standard 762-2023","authors":"Douglas M. Logan;Fred Beasom;Murty P. Bhavaraju;Francis J. Bell;Lee Thaubald;Kai Jiang;Chris J. Dent","doi":"10.1109/TSTE.2024.3430321","DOIUrl":"10.1109/TSTE.2024.3430321","url":null,"abstract":"<italic>IEEE Standard Definitions for Use in Reporting Electric Generating Unit Reliability, Availability, and Productivity</i>\u0000 has recently been revised to extend the standard to variable energy resource (VER) generating facilities. The revision includes definitions of energy resource and resource unavailability, indexes that distinguish between equipment performance and the availability of a generator for system reliability analysis purposes, and generation-based reliability indexes for VER units corresponding to the traditional time-based indexes in previous versions of the standard. The revision also includes definition of critical period indexes, where the critical period is specified as hours of high system need. This paper describes the new terms and outlines issues with their definition.","PeriodicalId":452,"journal":{"name":"IEEE Transactions on Sustainable Energy","volume":"15 4","pages":"2609-2624"},"PeriodicalIF":8.6,"publicationDate":"2024-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141740372","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-17DOI: 10.1109/TSTE.2024.3429781
Xueqian Fu;Chunyu Zhang;Xiurong Zhang;Hongbin Sun
The stochastic production simulation of photovoltaic (PV) power is crucial for the analysis of power balance in power planning, annual or monthly operational planning, and long-term transactions in the electricity market, especially in power systems with a high share of PVs. To model the uncertainty and temporal characteristics inherent in PV power, this letter introduces the style transfer and innovatively establishes bi-directional long short-term memory generative adversarial networks (GAN). Simulation results confirm the advantages of the proposed GAN over traditional convolutional neural network-based GANs in simulating the diversity and temporal characteristics of PV power.
光伏（PV）电力的随机生产模拟对于电力规划中的电力平衡分析、年度或月度运营规划以及电力市场中的长期交易至关重要，尤其是在光伏占比较高的电力系统中。为模拟光伏发电固有的不确定性和时间特性，本文引入了样式转移，并创新性地建立了双向长短期记忆生成式对抗网络（GAN）。仿真结果证实，与传统的基于卷积神经网络的 GAN 相比，所提出的 GAN 在模拟光伏发电的多样性和时间特性方面更具优势。
{"title":"A Novel GAN Architecture Reconstructed Using Bi-LSTM and Style Transfer for PV Temporal Dynamics Simulation","authors":"Xueqian Fu;Chunyu Zhang;Xiurong Zhang;Hongbin Sun","doi":"10.1109/TSTE.2024.3429781","DOIUrl":"10.1109/TSTE.2024.3429781","url":null,"abstract":"The stochastic production simulation of photovoltaic (PV) power is crucial for the analysis of power balance in power planning, annual or monthly operational planning, and long-term transactions in the electricity market, especially in power systems with a high share of PVs. To model the uncertainty and temporal characteristics inherent in PV power, this letter introduces the style transfer and innovatively establishes bi-directional long short-term memory generative adversarial networks (GAN). Simulation results confirm the advantages of the proposed GAN over traditional convolutional neural network-based GANs in simulating the diversity and temporal characteristics of PV power.","PeriodicalId":452,"journal":{"name":"IEEE Transactions on Sustainable Energy","volume":"15 4","pages":"2826-2829"},"PeriodicalIF":8.6,"publicationDate":"2024-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141740424","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Synchronous condensers (SynCons) are widely used in supporting the integration of renewable power plants (RPPs) in weak grids. However, recent research suggests that a SynCon co-located with RPPs may be prone to transient rotor angle instability due to the excessive active power injected by nearby RPPs during metallic faults. This paper further discovers that the transient stability of the SynCon may be lost even it generates electrical power during high-resistance faults. This novel mechanism of instability is investigated by deriving power-angle characteristics in different fault scenarios, and then the effect of the system parameters on the stability is analyzed via a proposed index based on the critical clearance time (CCT). It reveals that inappropriate parameters of SynCons, weak grid, and voltage support during fault ride-through (FRT) all contribute to such transient instability. To mitigate such instability, an adaptive FRT strategy is proposed. The electromagnetic transient (EMT) simulations based on the PSCAD are carried out to validate the effectiveness of the theoretical analysis and the proposed adaptive control strategy.
{"title":"Transient Stability of Synchronous Condenser Co-Located With Renewable Power Plants Under High-Resistance Faults and Risk Mitigation","authors":"Xinyu Liu;Huanhai Xin;Yongpeng Shan;Di Zheng;Dong Chen","doi":"10.1109/TSTE.2024.3429210","DOIUrl":"10.1109/TSTE.2024.3429210","url":null,"abstract":"Synchronous condensers (SynCons) are widely used in supporting the integration of renewable power plants (RPPs) in weak grids. However, recent research suggests that a SynCon co-located with RPPs may be prone to transient rotor angle instability due to the excessive active power injected by nearby RPPs during metallic faults. This paper further discovers that the transient stability of the SynCon may be lost even it generates electrical power during high-resistance faults. This novel mechanism of instability is investigated by deriving power-angle characteristics in different fault scenarios, and then the effect of the system parameters on the stability is analyzed via a proposed index based on the critical clearance time (CCT). It reveals that inappropriate parameters of SynCons, weak grid, and voltage support during fault ride-through (FRT) all contribute to such transient instability. To mitigate such instability, an adaptive FRT strategy is proposed. The electromagnetic transient (EMT) simulations based on the PSCAD are carried out to validate the effectiveness of the theoretical analysis and the proposed adaptive control strategy.","PeriodicalId":452,"journal":{"name":"IEEE Transactions on Sustainable Energy","volume":"15 4","pages":"2581-2593"},"PeriodicalIF":8.6,"publicationDate":"2024-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141718532","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-16DOI: 10.1109/TSTE.2024.3429152
Xuesong Gao;Zhihao Wang;Xianzhuo Sun;Lei Ding
Doubly-fed induction generator (DFIG)-based wind turbine generators (WTGs) are required to provide grid support during asymmetrical faults and the corresponding asymmetrical current control strategy (AsymCCS) is of great importance. However, the output capability of the rotor-side converter (RSC) under asymmetrical faults lacks a concise expression. This deficiency hinders the optimal allocation of current references in AsymCCSs and may further cause RSC overcurrent and over-modulation. To address these issues, a reduced-dimensional RSC asymmetrical controllable region (AsymCR) is firstly established in this paper, describing the characteristics of the RSC output capability. The AsymCR points out that the negative sequence current output should hold a higher priority to ensure the positive sequence current output capability. Based on an AsymCR-assisted optimal stator equivalent negative sequence reactance, a novel RSC AsymCCS is then proposed. The control strategy can offer sufficient negative sequence support to the grid while enlarging the positive sequence support capability, optimally allocating the positive and negnative sequence output and effectively avoiding overcurrent and over-modulation problems. Simulations are conducted in an electromagnetic transient test system to verify the effectiveness and improved performance of the proposed method.
{"title":"Reduced-Dimensional Controllable Region-Assisted Optimal Rotor Current Control Strategy of DFIG-Based WTGs During Asymmetrical Faults","authors":"Xuesong Gao;Zhihao Wang;Xianzhuo Sun;Lei Ding","doi":"10.1109/TSTE.2024.3429152","DOIUrl":"10.1109/TSTE.2024.3429152","url":null,"abstract":"Doubly-fed induction generator (DFIG)-based wind turbine generators (WTGs) are required to provide grid support during asymmetrical faults and the corresponding asymmetrical current control strategy (AsymCCS) is of great importance. However, the output capability of the rotor-side converter (RSC) under asymmetrical faults lacks a concise expression. This deficiency hinders the optimal allocation of current references in AsymCCSs and may further cause RSC overcurrent and over-modulation. To address these issues, a reduced-dimensional RSC asymmetrical controllable region (AsymCR) is firstly established in this paper, describing the characteristics of the RSC output capability. The AsymCR points out that the negative sequence current output should hold a higher priority to ensure the positive sequence current output capability. Based on an AsymCR-assisted optimal stator equivalent negative sequence reactance, a novel RSC AsymCCS is then proposed. The control strategy can offer sufficient negative sequence support to the grid while enlarging the positive sequence support capability, optimally allocating the positive and negnative sequence output and effectively avoiding overcurrent and over-modulation problems. Simulations are conducted in an electromagnetic transient test system to verify the effectiveness and improved performance of the proposed method.","PeriodicalId":452,"journal":{"name":"IEEE Transactions on Sustainable Energy","volume":"16 1","pages":"62-80"},"PeriodicalIF":8.6,"publicationDate":"2024-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141718612","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-16DOI: 10.1109/TSTE.2024.3429310
Zhuoxin Lu;Xiaoyuan Xu;Zheng Yan;Mohammad Shahidehpour;Weiqing Sun;Dong Han
This paper proposes a pricing and scheduling method for shared mobile energy storage systems (SMSs) in coupled power distribution and transportation networks. Different from existing shared energy storage studies, which mostly focus on stationary resources, the paper investigates the SMS operation considering the negotiation of rental prices as well as mobility and charging/discharging among SMS owners and different users. Specifically, the SMS pricing and scheduling with variable renewable energy are established as a bilevel mixed-integer chance-constrained distributionally robust optimization problem. In the upper-level problem, the SMS owner determines pricing and day-ahead mobility strategy to maximize its payoff. In the lower-level problem, the SMS users, i.e., distribution grid operators, determine the SMS charging/discharging power according to the SMS day-ahead pricing results and intra-day distribution grid operation strategies for accommodating variable renewable energy. The distributionally robust chance constraint is designed to cope with the intra-day operational risk caused by the variability of renewable power generation. To cope with the solution difficulty in the proposed bilevel optimization problem, the chance constraint is reformulated as second-order cone constraints, which are further transformed into a set of linear constraints, and then the reformulated bilevel mixed-integer linear programming problem is decomposed and iteratively solved to avoid enumerating lower-level integer variables. Simulation results show that the utilization rate of SMS batteries is increased and the excess renewable power is fully consumed when SMSs are shared among different distribution grids. The proposed distributionally robust optimization achieves higher revenue for the SMS owner and smaller operating costs of distribution grids than robust optimization under uncertain environments.
{"title":"Distributionally Robust Chance Constrained Optimization Method for Risk-Based Routing and Scheduling of Shared Mobile Energy Storage System With Variable Renewable Energy","authors":"Zhuoxin Lu;Xiaoyuan Xu;Zheng Yan;Mohammad Shahidehpour;Weiqing Sun;Dong Han","doi":"10.1109/TSTE.2024.3429310","DOIUrl":"10.1109/TSTE.2024.3429310","url":null,"abstract":"This paper proposes a pricing and scheduling method for shared mobile energy storage systems (SMSs) in coupled power distribution and transportation networks. Different from existing shared energy storage studies, which mostly focus on stationary resources, the paper investigates the SMS operation considering the negotiation of rental prices as well as mobility and charging/discharging among SMS owners and different users. Specifically, the SMS pricing and scheduling with variable renewable energy are established as a bilevel mixed-integer chance-constrained distributionally robust optimization problem. In the upper-level problem, the SMS owner determines pricing and day-ahead mobility strategy to maximize its payoff. In the lower-level problem, the SMS users, i.e., distribution grid operators, determine the SMS charging/discharging power according to the SMS day-ahead pricing results and intra-day distribution grid operation strategies for accommodating variable renewable energy. The distributionally robust chance constraint is designed to cope with the intra-day operational risk caused by the variability of renewable power generation. To cope with the solution difficulty in the proposed bilevel optimization problem, the chance constraint is reformulated as second-order cone constraints, which are further transformed into a set of linear constraints, and then the reformulated bilevel mixed-integer linear programming problem is decomposed and iteratively solved to avoid enumerating lower-level integer variables. Simulation results show that the utilization rate of SMS batteries is increased and the excess renewable power is fully consumed when SMSs are shared among different distribution grids. The proposed distributionally robust optimization achieves higher revenue for the SMS owner and smaller operating costs of distribution grids than robust optimization under uncertain environments.","PeriodicalId":452,"journal":{"name":"IEEE Transactions on Sustainable Energy","volume":"15 4","pages":"2594-2608"},"PeriodicalIF":8.6,"publicationDate":"2024-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141722228","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-12DOI: 10.1109/TSTE.2024.3426917
Pavlos G. Papageorgiou;Panagiotis T. Papafilippou;Konstantinos O. Oureilidis;Georgios C. Christoforidis
The volatility of grid-coupled photovoltaics can cause local voltage deviations, while the impact on frequency becomes obvious in isolated weak grids. Thus, a standalone battery is usually proposed for smoothing purposes. However, the frequent cycles and abrupt power variations shrink its life and impair control performance. To this end, this study introduces a controller for a hybrid system composed of a superconducting magnetic energy storage (SMES) and a battery. The proposed method establishes an idling zone for battery to eliminate its short-term activity, while SMES handles any power mismatch. The zone limits are dynamically adjusted in case of power balance detection, while an adaptive saturation is applied to them for maximal SMES utilization and minimal battery degradation. When SMES current deviates from this zone, battery operates with an adaptive ramp rate (i.e., di/dt) depending on the state of charge of SMES, to further optimize its life. Additionally, to prevent unnecessary power circulation among SMES and battery, supervisory control loops are implemented. Finally, to evaluate this scheme against preceding controllers regarding battery life extension, a real-time approach is followed using a dedicated simulator, while a hardware-in-the-loop verification is presented using an actual controller.
{"title":"An Adaptive Controller of a Hybrid Storage System for Power Smoothing With Enlarged Battery Lifetime","authors":"Pavlos G. Papageorgiou;Panagiotis T. Papafilippou;Konstantinos O. Oureilidis;Georgios C. Christoforidis","doi":"10.1109/TSTE.2024.3426917","DOIUrl":"10.1109/TSTE.2024.3426917","url":null,"abstract":"The volatility of grid-coupled photovoltaics can cause local voltage deviations, while the impact on frequency becomes obvious in isolated weak grids. Thus, a standalone battery is usually proposed for smoothing purposes. However, the frequent cycles and abrupt power variations shrink its life and impair control performance. To this end, this study introduces a controller for a hybrid system composed of a superconducting magnetic energy storage (SMES) and a battery. The proposed method establishes an idling zone for battery to eliminate its short-term activity, while SMES handles any power mismatch. The zone limits are dynamically adjusted in case of power balance detection, while an adaptive saturation is applied to them for maximal SMES utilization and minimal battery degradation. When SMES current deviates from this zone, battery operates with an adaptive ramp rate (i.e., di/dt) depending on the state of charge of SMES, to further optimize its life. Additionally, to prevent unnecessary power circulation among SMES and battery, supervisory control loops are implemented. Finally, to evaluate this scheme against preceding controllers regarding battery life extension, a real-time approach is followed using a dedicated simulator, while a hardware-in-the-loop verification is presented using an actual controller.","PeriodicalId":452,"journal":{"name":"IEEE Transactions on Sustainable Energy","volume":"15 4","pages":"2567-2580"},"PeriodicalIF":8.6,"publicationDate":"2024-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141614652","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-10DOI: 10.1109/TSTE.2024.3426337
Xianbang Chen;Yikui Liu;Lei Wu
Generally, day-ahead unit commitment (UC) is conducted in a predict-then-optimize process: it starts by predicting the renewable energy source (RES) availability and system reserve requirements; given the predictions, the UC model is then optimized to determine the economic operation plans. In fact, predictions within the process are raw . In other words, if the predictions are further tailored to assist UC in making the economic operation plans against realizations of the RES and reserve requirements, UC economics will benefit significantly. To this end, this paper presents a cost-oriented tailor of RES-and-reserve predictions for UC, deployed as an add-on to the predict-then-optimize process. The RES-and-reserve tailor is trained by solving a bi-level mixed-integer programming model: the upper level trains the tailor based on its induced operating cost; the lower level, given tailored predictions, mimics the system operation process and feeds the induced operating cost back to the upper level; finally, the upper level evaluates the training quality according to the fed-back cost. Through this training, the tailor learns to customize the raw predictions into cost-oriented predictions. Moreover, the tailor can be embedded into the existing predict-then-optimize process as an add-on, improving the UC economics. Lastly, the presented method is compared to traditional, binary-relaxing, neural network-based, stochastic, and robust methods.
{"title":"Towards Improving Unit Commitment Economics: An Add-On Tailor for Renewable Energy and Reserve Predictions","authors":"Xianbang Chen;Yikui Liu;Lei Wu","doi":"10.1109/TSTE.2024.3426337","DOIUrl":"10.1109/TSTE.2024.3426337","url":null,"abstract":"Generally, day-ahead unit commitment (UC) is conducted in a predict-then-optimize process: it starts by predicting the renewable energy source (RES) availability and system reserve requirements; given the predictions, the UC model is then optimized to determine the economic operation plans. In fact, predictions within the process are \u0000<italic>raw</i>\u0000. In other words, if the predictions are further tailored to assist UC in making the economic operation plans against realizations of the RES and reserve requirements, UC economics will benefit significantly. To this end, this paper presents a cost-oriented tailor of RES-and-reserve predictions for UC, deployed as an add-on to the predict-then-optimize process. The RES-and-reserve tailor is trained by solving a bi-level mixed-integer programming model: the upper level trains the tailor based on its induced operating cost; the lower level, given tailored predictions, mimics the system operation process and feeds the induced operating cost back to the upper level; finally, the upper level evaluates the training quality according to the fed-back cost. Through this training, the tailor learns to customize the raw predictions into cost-oriented predictions. Moreover, the tailor can be embedded into the existing predict-then-optimize process as an add-on, improving the UC economics. Lastly, the presented method is compared to traditional, binary-relaxing, neural network-based, stochastic, and robust methods.","PeriodicalId":452,"journal":{"name":"IEEE Transactions on Sustainable Energy","volume":"15 4","pages":"2547-2566"},"PeriodicalIF":8.6,"publicationDate":"2024-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141587066","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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