Travis Hagan;Dilan Senaratne;Rich Meier;Eduardo Cotilla-Sanchez;Jinsub Kim
{"title":"Implementing Power System Protection Algorithms in a Digital Hardware-in-the-Loop Substation","authors":"Travis Hagan;Dilan Senaratne;Rich Meier;Eduardo Cotilla-Sanchez;Jinsub Kim","doi":"10.1109/OAJPE.2022.3229413","DOIUrl":"https://doi.org/10.1109/OAJPE.2022.3229413","url":null,"abstract":"Real-time power system algorithms are necessary for grid advancement, but few practical applications have been demonstrated in a research usability context. The work in this paper consists of implementing a data correction algorithm, its deployment within realistic substation equipment, and the design of a testbed to demonstrate the overall framework and its usability. A digital simulator is used to generate Phasor Measurement Unit (PMU) data for the algorithm. The algorithm corrects data that has been perturbed by GPS spoofing attacks. Finally, the entire system is visualized on power-utility software, SEL Synchrowave Operations. Considerations and potential issues are discussed and are applicable to digital Hardware-in-the-Loop (HIL) systems as well as to field-deployed systems. The system is demonstrated with 11 simultaneously GPS-spoofing attacked PMUs in a 21 PMU system. The HIL testbed developed in this paper provides a valuable tool for easily testing a variety of real-time power system algorithms and the communications and control necessary for them operate successfully.","PeriodicalId":56187,"journal":{"name":"IEEE Open Access Journal of Power and Energy","volume":"10 ","pages":"270-282"},"PeriodicalIF":3.8,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/8784343/9999142/09987543.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49985058","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Paolo Castello;Carlo Muscas;Paolo Attilio Pegoraro;Sara Sulis;Johan Rens;Jacobus Van Zyl
{"title":"A Practical Solution for Locating the Source of Voltage Dips in HV/MV Interconnected Grids","authors":"Paolo Castello;Carlo Muscas;Paolo Attilio Pegoraro;Sara Sulis;Johan Rens;Jacobus Van Zyl","doi":"10.1109/OAJPE.2023.3268499","DOIUrl":"https://doi.org/10.1109/OAJPE.2023.3268499","url":null,"abstract":"Monitoring the technical performance of a power system is significantly enhanced when distributed instrumentation produces coherent field data, i.e., synchronized by GPS timestamping. In this paper a practical methodology is presented to improve the localization of the source of a voltage dip on power grids. The proposed solution makes use of synchronized dip data provided by power quality meters. Field data reporting events occurred in an HV/MV interconnected system in South Africa are used to validate the results obtained by the improved method and compare with results of two alternative methods.","PeriodicalId":56187,"journal":{"name":"IEEE Open Access Journal of Power and Energy","volume":"10 ","pages":"406-414"},"PeriodicalIF":3.8,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/8784343/9999142/10105653.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49985071","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Very Short-Term Solar Power Forecasting Using a Frequency Incorporated Deep Learning Model","authors":"Hossein Panamtash;Shahrzad Mahdavi;Qun Zhou Sun;Guo-Jun Qi;Hongrui Liu;Aleksandar Dimitrovski","doi":"10.1109/OAJPE.2023.3294457","DOIUrl":"https://doi.org/10.1109/OAJPE.2023.3294457","url":null,"abstract":"This paper aims to forecast solar power in very short horizons to assist in real-time distribution system operations. Popular machine learning methods for time series forecasting are studied, including recurrent neural networks with Long Short-Term Memory (LSTM). Although LSTM networks perform well in different applications by accounting for long-term dependencies, they do not consider the frequency domain patterns, especially the low frequencies in the solar power data compared to the sampling frequency. The State Frequency Memory (SFM) model in this paper extends LSTM and adds multi-frequency components into memory states to reveal a variety of frequency patterns from the data streams. To further improve the forecasting performance, the idea of Fourier Transform is integrated for optimal selection of the frequency bands by identifying the most dominant frequencies in solar power output. The results show that although the SFM model with uniform frequency selection does not significantly improve upon the LSTM model, the proper selection of frequencies yields overall better performances than the LSTM and 27% better than the persistent forecasts for forecast horizons up to one minute. Furthermore, a predictive voltage control based on solar forecasts is implemented to demonstrate the superior performance of the proposed model.","PeriodicalId":56187,"journal":{"name":"IEEE Open Access Journal of Power and Energy","volume":"10 ","pages":"517-527"},"PeriodicalIF":3.8,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/8784343/9999142/10179133.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49945653","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"PowerSAS.m—An Open-Source Power System Simulation Toolbox Based on Semi-Analytical Solution Technologies","authors":"Jianzhe Liu;Rui Yao;Feng Qiu;Yang Liu;Kai Sun","doi":"10.1109/OAJPE.2023.3245040","DOIUrl":"https://doi.org/10.1109/OAJPE.2023.3245040","url":null,"abstract":"In handling complex power system simulation tasks, semi-analytical solution (SAS) methods have proven to be numerically robust and computationally efficient. They provide a competitive alternative to traditional numerical approaches. Still, there is inadequate power system simulation software, especially the open-source tools, that implements this technology. This paper introduces PowerSAS.m, an open-source toolbox that closes this gap by providing SAS baseline simulation options for power system steady-state and dynamic simulations. At its core, it implements a novel SAS method and encloses various heuristics and simulation techniques to ensure enhanced computational performance. In case studies, we verify PowerSAS.m in benchmarking comparisons and demonstrate its functionalities in grid analysis scenarios.","PeriodicalId":56187,"journal":{"name":"IEEE Open Access Journal of Power and Energy","volume":"10 ","pages":"222-232"},"PeriodicalIF":3.8,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/8784343/9999142/10049254.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49992155","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Analysis of Targeted Coordinated Attacks on Decomposition-Based Robust State Estimation","authors":"Naime Ahmadi;Yacine Chakhchoukh;Hideaki Ishii","doi":"10.1109/OAJPE.2022.3230905","DOIUrl":"https://doi.org/10.1109/OAJPE.2022.3230905","url":null,"abstract":"The impact of false data injection (FDI) attacks on static state estimation of power systems has been actively studied in the past decade. In this paper, we consider an estimation method that first decomposes the system into islands and then implements robust regression estimators at the island level as well as the system level. We carry out an analysis to establish its advantages in terms of state estimation accuracy and attack detections. In particular, we focus on highly adversarial cases where the attacker can attack both the measurement vector and the regressor matrix and attempts to manipulate the states to targeted values. Our estimation approach employs a system decomposition method capable to generate islands small in their sizes and applies the robust estimation method of least trimmed squares. We make comparisons with methods using other decompositions and other robust estimators. To this end, we analyze the structure of the system topology and measurements and perform extensive simulations using the IEEE 14- and 118-bus systems. Furthermore, we investigate robustness improvement when phasor measurement units (PMUs) are available and hybrid state estimation can be employed.","PeriodicalId":56187,"journal":{"name":"IEEE Open Access Journal of Power and Energy","volume":"10 ","pages":"116-127"},"PeriodicalIF":3.8,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/8784343/9999142/09992206.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49977687","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Coordinated Planning of Electric Vehicle Charging Infrastructure and Renewables in Power Grids","authors":"Bo Wang;Payman Dehghanian;Dongbo Zhao","doi":"10.1109/OAJPE.2023.3245993","DOIUrl":"https://doi.org/10.1109/OAJPE.2023.3245993","url":null,"abstract":"This paper proposes a new planning model to coordinate the expansion of electric vehicle charging infrastructure (EVCI) and renewables in power grids. Firstly, individual electric vehicle (EV) charging behaviours are modeled considering EV customers adopting smart charging services as the main charging method and those using fast charging, super fast charging and battery swapping services as a complementary charging approach. Next, EV aggregation and the associated system economic dispatch model are built. A novel model predictive control (MPC) learning approach is then proposed to iteratively learn the correlation between different types of EV charging loads and the EV interactions with renewables and other generating units in modern power grids of the future. The simulation results demonstrate that the proposed approach can be used to quantify the ratio of different types of charging loads in a region and strategically guide on the integration of EVs and renewables to achieve the clean energy transition goals. The proposed framework can also be used to decide charging capacity needs in a charging demand zone.","PeriodicalId":56187,"journal":{"name":"IEEE Open Access Journal of Power and Energy","volume":"10 ","pages":"233-244"},"PeriodicalIF":3.8,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/8784343/9999142/10045673.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49992156","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Chen-Ching Liu;Akshay Kumar Jain;Dushan Boroyevich;Igor Cvetkovic;Nitasha Sahani;Lung-An Lee;Jennifer Appiah-Kubi;Kevin P. Schneider;Francis K. Tuffner;Dan Ton
{"title":"Microgrid Building Blocks: Concept and Feasibility","authors":"Chen-Ching Liu;Akshay Kumar Jain;Dushan Boroyevich;Igor Cvetkovic;Nitasha Sahani;Lung-An Lee;Jennifer Appiah-Kubi;Kevin P. Schneider;Francis K. Tuffner;Dan Ton","doi":"10.1109/OAJPE.2023.3282188","DOIUrl":"https://doi.org/10.1109/OAJPE.2023.3282188","url":null,"abstract":"For power grids with high penetration of distributed energy resources (DERs), microgrids can provide operation and control capabilities for clusters of DERs and load. Furthermore, microgrids enhance resilience of the hosting bulk power grid if they are enabled to serve critical load beyond the jurisdiction of the microgrids. For widespread deployment of microgrids, a modular and standardized Microgrid Building Block (MBB) is essential to help reduce the cost and increase reliability. This paper proposes the conceptual design of an MBB with integrated features of power conversion, control, and communications, resulting in a systemwide controller for the entire microgrid. The results of a feasibility study indicate that, in a utility-connected mode, MBB-based microgrids can exchange power with the hosting power grid while serving regulation and optimal dispatch functions. In a resiliency (islanded) mode when the microgrid is disconnected from the utility system, the MBB control system acts to stabilize the system frequency and voltage under small or large disturbances. The microgrid controller is supported by a communication system that meets the latency requirements imposed by the microgrid dynamics as well as data acquisition time. The extended IEEE 13-node system is used as a microgrid model to validate the proposed MBB design and functionality.","PeriodicalId":56187,"journal":{"name":"IEEE Open Access Journal of Power and Energy","volume":"10 ","pages":"463-476"},"PeriodicalIF":3.8,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/8784343/9999142/10142006.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49945713","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Operational Challenges of Solar PV Plus Storage Power Plants and Modeling Recommendations","authors":"Lingling Fan;Zhixin Miao;Deepak Ramasubramanian;Huazhao Ding","doi":"10.1109/OAJPE.2023.3284375","DOIUrl":"https://doi.org/10.1109/OAJPE.2023.3284375","url":null,"abstract":"This paper reviews potential operational challenges facing hybrid power plants, particularly solar photovoltaic (PV) plus battery energy storage systems (BESS). Real-world operation has witnessed many challenges, e.g., overvoltage at fault recovery, oscillations during solar PV ramping up, large phase angle change during faults, etc. This paper reviews potential operational challenges while focusing on those caused by plant-level control and inverter-level control coordination. To this end, detailed plant-level frequency-power droop control and voltage control are presented. Effect of the communication delay from the plant level to the inverter level is examined. This paper also presents recommendations on how to test hybrid power plants to detect those potential operational challenges in the planning stage. The contribution of the paper is two-fold: 1) A list of operational challenges has been reviewed with several analyzed in detail and demonstrated in case studies. Modeling and testing recommendations to capture those challenges in the planning stage have been presented. 2) The paper presents the details of IBR controls at both the plant level and the inverter level, elucidating the connection between control parameters and operational challenges. Mitigation plans, e.g., control parameter tuning, can be derived based on the insights revealed from this research.","PeriodicalId":56187,"journal":{"name":"IEEE Open Access Journal of Power and Energy","volume":"10 ","pages":"477-489"},"PeriodicalIF":3.8,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/8784343/9999142/10146308.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49945714","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Roshan L. Kini;David Raker;Roan Martin-Hayden;Robert G. Lutes;Srinivas Katipamula;Randy Ellingson;Michael J. Heben;Raghav Khanna
{"title":"Control-Centric Living Laboratory for Management of Distributed Energy Resources","authors":"Roshan L. Kini;David Raker;Roan Martin-Hayden;Robert G. Lutes;Srinivas Katipamula;Randy Ellingson;Michael J. Heben;Raghav Khanna","doi":"10.1109/OAJPE.2022.3223656","DOIUrl":"https://doi.org/10.1109/OAJPE.2022.3223656","url":null,"abstract":"Variability and uncertainty of renewable distributed generation increase power grid complexity, necessitating the development of advanced control strategies. demonstrates a real-world testbed and the implementation of control strategies on it to mitigate the challenges associated with variability and uncertainty of renewable distributed generation. This control-centric testbed includes 4.6 MW of controllable building loads, a 1 MW solar array, and a 125 kW / 130 kWh battery energy storage system (BESS). The capabilities of the testbed are illustrated by highlighting the implementation of three specific scenarios relevant to future smart grid infrastructures. In the first scenario, photovoltaic output variability is mitigated with the BESS using adaptive moving average and adaptive state of charge control methods. The second and third scenarios demonstrate peak load management and load following control to manage uncertainty using the Intelligent Load Control (ILC) algorithm. The ILC modifies controllable loads using a prioritization matrix and an analytical hierarchy process. The three scenarios all operate at a different time-constant, and are each effectively addressed, demonstrating the versatility and flexibility of the presented testbed. This demonstrated ability to rapidly test the efficacy of alternate control algorithms on a real system is crucial to the maturation of future smart-grid.","PeriodicalId":56187,"journal":{"name":"IEEE Open Access Journal of Power and Energy","volume":"10 ","pages":"48-60"},"PeriodicalIF":3.8,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/8784343/9999142/09956809.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49945802","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Comparing Electric Water Heaters and Batteries as Energy-Storage Resources for Energy Shifting and Frequency Regulation","authors":"Mahan A. Mansouri;Ramteen Sioshansi","doi":"10.1109/OAJPE.2022.3231834","DOIUrl":"https://doi.org/10.1109/OAJPE.2022.3231834","url":null,"abstract":"Recent technical, market, and policy developments in the electricity industry are increasing interest in and need for energy storage. We examine the potential for using the flexibility of an aggregation of tank electric water heaters as a source of virtual energy storage. Specifically, we examine the operational performance of and operating profit that is earned by a fleet of water heaters that provide energy shifting and frequency regulation. We contrast this performance and operating profit to that of a lithium-ion battery. We find that water heaters do not achieve the same level of performance or operating profit that a battery does. However, when accounting for the capital costs of the two technologies, water heaters are superior, insomuch as they have a better cost-to-profit ratio. We find that both water heaters and batteries earn significant operating profits from frequency regulation as opposed to energy shifting. Water heaters have a stronger bias towards frequency regulation, due to temporal constraints on load shifting. Relaxing these constraints improve water-heater performance slightly.","PeriodicalId":56187,"journal":{"name":"IEEE Open Access Journal of Power and Energy","volume":"10 ","pages":"164-175"},"PeriodicalIF":3.8,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/iel7/8784343/9999142/10006357.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49977690","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}