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Distribution Grid Optimal Power Flow Integrating Volt-Var Droop of Smart Inverters 智能型逆变器集成电压-无下垂的配电网最优潮流
2021 IEEE Green Technologies Conference (GreenTech) Pub Date : 2021-04-01 DOI: 10.1109/GreenTech48523.2021.00020
Alper Savasci, Adedoyin Inaolaji, S. Paudyal
{"title":"Distribution Grid Optimal Power Flow Integrating Volt-Var Droop of Smart Inverters","authors":"Alper Savasci, Adedoyin Inaolaji, S. Paudyal","doi":"10.1109/GreenTech48523.2021.00020","DOIUrl":"https://doi.org/10.1109/GreenTech48523.2021.00020","url":null,"abstract":"Smart inverters (SIs) with local volt-var droop functions are effective in maintaining voltage and reactive power on the distribution feeders. Volt-var optimization (VVO) is generally carried out using distribution grid optimal power flow (DOPF)-based model that provides set point for the inverters and/or legacy grid devices. However, the existing works do not consider volt-var droop settings in the VVO framework, making the inverter dispatch solutions unsuitable at the local inverter controller level. Therefore, in this work, we propose the inclusion of SIs' local volt-var droop functions (as per the IEEE-1547) as constraints in the VVO formulation. We adopt a well-known second-order cone programming (SOCP) version of DOPF and with the inclusion of SIs' droop functions, the resulting VVO renders an efficient mixed-integer SOCP (MISOCP) problem. The efficacy of the proposed model is shown on a 33-node distribution feeder with 4 SIs having volt-var droop functions set as per the IEEE-1547.","PeriodicalId":146759,"journal":{"name":"2021 IEEE Green Technologies Conference (GreenTech)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134090865","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 8
Synthetic High Impedance Fault Data through Deep Convolutional Generated Adversarial Network 基于深度卷积生成对抗网络的高阻抗故障数据合成
2021 IEEE Green Technologies Conference (GreenTech) Pub Date : 2021-04-01 DOI: 10.1109/GreenTech48523.2021.00061
Kun Yang, Wei Gao, Rui Fan, Tianzhixi Yin, Jianming Lian
{"title":"Synthetic High Impedance Fault Data through Deep Convolutional Generated Adversarial Network","authors":"Kun Yang, Wei Gao, Rui Fan, Tianzhixi Yin, Jianming Lian","doi":"10.1109/GreenTech48523.2021.00061","DOIUrl":"https://doi.org/10.1109/GreenTech48523.2021.00061","url":null,"abstract":"High impedance faults (HIFs) have always been significant challenges in the power grids. Researchers have developed some advanced protective methods to detect the HIFs. To test and validate these methods, large amounts of HIF data are required. This paper presents a synthetic HIF data generating method using the deep convolutional generated adversarial network (DCGAN). The DCGAN includes a generator module to create synthetic HIF waveform from random noises; and a discriminator module to identify the flaws of those synthetic data, which ultimately helps improve the quality of the synthetic data created by the generator. To test the fidelity of the generated synthetic HIF data, two different HIF-detection methods have been applied. Extensive simulation results have validated the effectiveness of using the DCGAN to create synthetic HIF data.","PeriodicalId":146759,"journal":{"name":"2021 IEEE Green Technologies Conference (GreenTech)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134150806","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 4
High Voltage AC (HVAC) and High Voltage DC (HVDC) Transmission Topologies of Offshore Wind Power and Reliability Analysis 海上风电的高压交流(HVAC)和高压直流(HVDC)传输拓扑结构及其可靠性分析
2021 IEEE Green Technologies Conference (GreenTech) Pub Date : 2021-04-01 DOI: 10.1109/GreenTech48523.2021.00051
A. Biswas, Sina Ibne Ahmed, Shravan Kumar Akula, H. Salehfar
{"title":"High Voltage AC (HVAC) and High Voltage DC (HVDC) Transmission Topologies of Offshore Wind Power and Reliability Analysis","authors":"A. Biswas, Sina Ibne Ahmed, Shravan Kumar Akula, H. Salehfar","doi":"10.1109/GreenTech48523.2021.00051","DOIUrl":"https://doi.org/10.1109/GreenTech48523.2021.00051","url":null,"abstract":"High Voltage AC (HVAC) is the standard transmission system for short distances, while High Voltage DC (HVDC) is a popular solution for the long-distance transmission of offshore wind power generation. An HVDC transmission system has an increased commercial cost due to the addition of power converter stations; therefore, the efficient design of offshore wind power transmission systems and their reliability are critical for the smooth operation of the transmission grid and improved cost-effectiveness. In this paper, the simplified topologies of offshore HVAC and HVDC transmission systems have been studied and compared based on their reliability using fault tree analysis (FTA).","PeriodicalId":146759,"journal":{"name":"2021 IEEE Green Technologies Conference (GreenTech)","volume":"78 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114863873","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 6
On-line Coherency Analysis based on Sliding-Window Koopman Mode Decomposition 基于滑动窗口Koopman模态分解的在线相干分析
2021 IEEE Green Technologies Conference (GreenTech) Pub Date : 2021-04-01 DOI: 10.1109/GreenTech48523.2021.00081
H. Chamorro, A. Guel-Cortez, C. A. Ordonez, M. Paternina, M. Budišić
{"title":"On-line Coherency Analysis based on Sliding-Window Koopman Mode Decomposition","authors":"H. Chamorro, A. Guel-Cortez, C. A. Ordonez, M. Paternina, M. Budišić","doi":"10.1109/GreenTech48523.2021.00081","DOIUrl":"https://doi.org/10.1109/GreenTech48523.2021.00081","url":null,"abstract":"Nowadays, power systems complexity requires of innovative methods to monitor and provide an adequate online assessment. Coherency identification (based on data-driven methods) is a potential tool that can be integrated into the system infrastructure for the protection and resilience of the power grid. This work presents a modification of the Koopman Mode Decomposition (KMD) by adding a sliding-window to emulate the processed system's signals and to visualise the data concentration as a Transmission System Operator (TSO). Finally, we present a study of a data-set of rotor angle observables from the Nordic 32 test system after a disturbance to observe the rapid coherency at specific time-shots. This study provides evidence that the proposed modified KMD is a fast and robust approach to analyze large time-domain simulation data.","PeriodicalId":146759,"journal":{"name":"2021 IEEE Green Technologies Conference (GreenTech)","volume":"433 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115715981","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 2
Active Learning Approaches for Sustainable Energy Engineering Education 可持续能源工程教育的主动学习方法
2021 IEEE Green Technologies Conference (GreenTech) Pub Date : 2021-04-01 DOI: 10.1109/GreenTech48523.2021.00048
P. Caratozzolo, S. Rosas-Meléndez, Carlos Ortiz-Alvarado
{"title":"Active Learning Approaches for Sustainable Energy Engineering Education","authors":"P. Caratozzolo, S. Rosas-Meléndez, Carlos Ortiz-Alvarado","doi":"10.1109/GreenTech48523.2021.00048","DOIUrl":"https://doi.org/10.1109/GreenTech48523.2021.00048","url":null,"abstract":"International groups of stakeholders are currently involved in the redefinition of the objectives of sustainable engineering education. They are releasing different reports where clearly raise the need that the acquisition of cognitive skills must be carried out complying with the knowledge, attitudes and values of the complex demands of the Fourth Industrial Revolution framework. Inherited from the past, the stiffness of the academic structures in some higher education institutions, may prove today an insurmountable barrier to the new adaptable learning approaches required by Generation Z students. During this study, engineering students received critical and creative thinking instruction to comply with the enhancement of: (i) their ability of design Net Zero Carbon 2050 strategies; (ii) their capacity to cope with uncertainty, ambiguity and volatility in sustainable energy fields; and (iii) their handling of non-routine interpersonal and analytical skills for digital transformation. The obtained results indicate that Active Learning and Challenge-based Learning approaches are highly effective for the development of sustainability thinking skills in engineering students.","PeriodicalId":146759,"journal":{"name":"2021 IEEE Green Technologies Conference (GreenTech)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121442392","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Voltage Stabilization of DC-Link in EVs using DAB Converter based on Higher-Order SMC approach 基于高阶SMC方法的DAB变换器在电动汽车直流链路中的稳压研究
2021 IEEE Green Technologies Conference (GreenTech) Pub Date : 2021-04-01 DOI: 10.1109/GreenTech48523.2021.00044
T. Zaman, I. Khan, N. Ullah
{"title":"Voltage Stabilization of DC-Link in EVs using DAB Converter based on Higher-Order SMC approach","authors":"T. Zaman, I. Khan, N. Ullah","doi":"10.1109/GreenTech48523.2021.00044","DOIUrl":"https://doi.org/10.1109/GreenTech48523.2021.00044","url":null,"abstract":"The bidirectional dual active bridge (DAB) converters play a vital role in the emerging smart-grid and Electric Vehicles (EVs) applications. The bidirectional converter plays the role of an intermediate converter between the main DC link of EV and the energy storing elements. In this work, a higher order sliding mode controller is derived based on the nonlinear Fourier switching harmonics of the DAB converter. The controller aims to regulate the converter's output voltage at the main DC link irrespective of the external disturbance as a load and variations in the voltage. The derived controller is validated by experimental results using hardware in the loop (HIL) and TI C2000 F28379D Launchpad.","PeriodicalId":146759,"journal":{"name":"2021 IEEE Green Technologies Conference (GreenTech)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124906071","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Detection of False Data Injection of PV Production 光伏生产假数据注入检测
2021 IEEE Green Technologies Conference (GreenTech) Pub Date : 2021-04-01 DOI: 10.1109/GreenTech48523.2021.00012
H. Riggs, S. Tufail, Mohammad Khan, I. Parvez, A. Sarwat
{"title":"Detection of False Data Injection of PV Production","authors":"H. Riggs, S. Tufail, Mohammad Khan, I. Parvez, A. Sarwat","doi":"10.1109/GreenTech48523.2021.00012","DOIUrl":"https://doi.org/10.1109/GreenTech48523.2021.00012","url":null,"abstract":"Due to cyber attack threats to the cyber physical systems which compose modern smart grids additional layers of security could be valuable. The potential of data tampering in the smart grid spurs the research of data integrity attacks and additional security means to detect such tampering. This paper conducts a study of photovoltaic based production data tampering as a detection problem and shows a set of machine learning models and highlights the best performing of the set at the detection task. The signal is observed daily and data tampering by increasing to 110%-150% of original signal is detected with over 80% accuracy and under 10% false alarm. This paper finds that the artificial neural network (ANN) slightly out performs the support vector machine (SVM) at the detection task, however the SVM is a much faster algorithm to fit the data with.","PeriodicalId":146759,"journal":{"name":"2021 IEEE Green Technologies Conference (GreenTech)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115205191","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 6
Efficiency Assessment of a Residential DC Nanogrid with Low and High Distribution Voltages Using Realistic Data 基于实际数据的低、高配电电压住宅直流纳米电网效率评估
2021 IEEE Green Technologies Conference (GreenTech) Pub Date : 2021-04-01 DOI: 10.1109/GreenTech48523.2021.00096
Saeed Habibi, Ramin Rahimi, P. Shamsi, M. Ferdowsi
{"title":"Efficiency Assessment of a Residential DC Nanogrid with Low and High Distribution Voltages Using Realistic Data","authors":"Saeed Habibi, Ramin Rahimi, P. Shamsi, M. Ferdowsi","doi":"10.1109/GreenTech48523.2021.00096","DOIUrl":"https://doi.org/10.1109/GreenTech48523.2021.00096","url":null,"abstract":"Direct Current (DC) power distribution has gained attention in the Residential Nanogrids (RNGs) due to the substantial increase in the number of roof-top Photovoltaic (PV) systems and internally DC appliances used in buildings. Using DC distribution improves the efficiency of the RNGs compared to AC distribution. This paper investigated the efficiency of a DC RNG for low and high distribution voltage levels by exploring reasons for power losses. The studied DC RNG consisted of various types of local loads, on-site PV generation, and battery storage systems. The realistic load, PV profiles, and converter efficiency curves were used to make the analysis more accurate. In addition, three load profiles with low, medium, and high power consumptions were considered to study the load impacts on the overall system efficiency.","PeriodicalId":146759,"journal":{"name":"2021 IEEE Green Technologies Conference (GreenTech)","volume":"50 3","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114038005","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 5
Optimal Power Flow Considering Time of Use and Real-Time Pricing Demand Response Programs 考虑使用时间和实时定价需求响应方案的最优潮流
2021 IEEE Green Technologies Conference (GreenTech) Pub Date : 2021-02-15 DOI: 10.1109/GreenTech48523.2021.00021
Sayyad Nojavan, Vafa Ajoulabadi, T. Khalili, A. Bidram
{"title":"Optimal Power Flow Considering Time of Use and Real-Time Pricing Demand Response Programs","authors":"Sayyad Nojavan, Vafa Ajoulabadi, T. Khalili, A. Bidram","doi":"10.1109/GreenTech48523.2021.00021","DOIUrl":"https://doi.org/10.1109/GreenTech48523.2021.00021","url":null,"abstract":"In recent years, the implementation of the demand response (DR) programs in the power system's scheduling and operation is increased. DR is used to improve the consumers' and power providers' economic condition. That said, optimal power flow is a fundamental concept in the power system operation and control. The impact of exploiting DR programs in the power management of the systems is of significant importance. In this paper, the effect of time-based DR programs on the cost of 24-hour operation of a power system is presented. The effect of the time of use and real-time pricing programs with different participation factors are investigated. In addition, the system's operation cost is studied to analyze the DR programs' role in the current power grids. For this aim, the 14-bus IEEE test system is used to properly implement and simulate the proposed approach.","PeriodicalId":146759,"journal":{"name":"2021 IEEE Green Technologies Conference (GreenTech)","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115297748","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 2
Adaptive Day-Ahead Prediction of Resilient Power Distribution Network Partitions 弹性配电网分区的自适应日前预测
2021 IEEE Green Technologies Conference (GreenTech) Pub Date : 2021-01-07 DOI: 10.1109/GreenTech48523.2021.00080
Chinmay Shah, R. Wies
{"title":"Adaptive Day-Ahead Prediction of Resilient Power Distribution Network Partitions","authors":"Chinmay Shah, R. Wies","doi":"10.1109/GreenTech48523.2021.00080","DOIUrl":"https://doi.org/10.1109/GreenTech48523.2021.00080","url":null,"abstract":"The conventional power distribution network is being transformed drastically due to high penetration of renewable energy sources (RES) and energy storage. The optimal scheduling and dispatch is important to better harness the energy from intermittent RES. Traditional centralized optimization techniques limit the size of the problem and hence distributed techniques are adopted. The distributed optimization technique partitions the power distribution network into sub-networks which solves the local sub problem and exchanges information with the neighboring sub-networks for the global update. This paper presents an adaptive spectral graph partitioning algorithm based on vertex migration while maintaining computational load balanced for synchronization, active power balance and sub-network resiliency. The parameters that define the resiliency metrics of power distribution networks are discussed and leveraged for better operation of sub-networks in grid connected mode as well as islanded mode. The adaptive partition of the IEEE 123-bus network into resilient sub-networks is demonstrated in this paper.","PeriodicalId":146759,"journal":{"name":"2021 IEEE Green Technologies Conference (GreenTech)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116775535","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 5
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