IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v165y2016icp583-591.html
   My bibliography  Save this article

Harmonic analysis in integrated energy system based on compressed sensing

Author

Listed:
  • Yang, Ting
  • Pen, Haibo
  • Wang, Dan
  • Wang, Zhaoxia

Abstract

The advent of Integrated Energy Systems enabled various distributed energy to access the system through different power electronic devices. The development of this has made the harmonic environment more complex. It needs low complexity and high precision of harmonic detection and analysis methods to improve power quality. To solve the shortages of large data storage capacities and high complexity of compression in sampling under the Nyquist sampling framework, this research paper presents a harmonic analysis scheme based on compressed sensing theory. The proposed scheme enables the performance of the functions of compressive sampling, signal reconstruction and harmonic detection simultaneously. In the proposed scheme, the sparsity of the harmonic signals in the base of the Discrete Fourier Transform (DFT) is numerically calculated first. This is followed by providing a proof of the matching satisfaction of the necessary conditions for compressed sensing. The binary sparse measurement is then leveraged to reduce the storage space in the sampling unit in the proposed scheme. In the recovery process, the scheme proposed a novel reconstruction algorithm called the Spectral Projected Gradient with Fundamental Filter (SPG-FF) algorithm to enhance the reconstruction precision. One of the actual microgrid systems is used as simulation example. The results of the experiment shows that the proposed scheme effectively enhances the precision of harmonic and inter-harmonic detection with low computing complexity, and has good capability of signal reconstruction. The maximum detection error reaches 0.0315%, and the reconstruction signals to noise ratio (SNR) is higher than 89dB.

Suggested Citation

  • Yang, Ting & Pen, Haibo & Wang, Dan & Wang, Zhaoxia, 2016. "Harmonic analysis in integrated energy system based on compressed sensing," Applied Energy, Elsevier, vol. 165(C), pages 583-591.
  • Handle: RePEc:eee:appene:v:165:y:2016:i:c:p:583-591
    DOI: 10.1016/j.apenergy.2015.12.058
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261915016311
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.apenergy.2015.12.058?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Arifujjaman, Md. & Iqbal, M.T. & Quaicoe, J.E., 2009. "Reliability analysis of grid connected small wind turbine power electronics," Applied Energy, Elsevier, vol. 86(9), pages 1617-1623, September.
    2. Boynuegri, A.R. & Uzunoglu, M. & Erdinc, O. & Gokalp, E., 2014. "A new perspective in grid connection of electric vehicles: Different operating modes for elimination of energy quality problems," Applied Energy, Elsevier, vol. 132(C), pages 435-451.
    3. Lv, Tianguang & Ai, Qian, 2016. "Interactive energy management of networked microgrids-based active distribution system considering large-scale integration of renewable energy resources," Applied Energy, Elsevier, vol. 163(C), pages 408-422.
    4. Drouineau, Mathilde & Maïzi, Nadia & Mazauric, Vincent, 2014. "Impacts of intermittent sources on the quality of power supply: The key role of reliability indicators," Applied Energy, Elsevier, vol. 116(C), pages 333-343.
    5. Carranza, O. & Figueres, E. & Garcerá, G. & Gonzalez, L.G., 2011. "Comparative study of speed estimators with highly noisy measurement signals for Wind Energy Generation Systems," Applied Energy, Elsevier, vol. 88(3), pages 805-813, March.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Wang, Xuewei & Wang, Jing & Wang, Lin & Yuan, Ruiming, 2019. "Non-overlapping moving compressive measurement algorithm for electrical energy estimation of distorted m-sequence dynamic test signal," Applied Energy, Elsevier, vol. 251(C), pages 1-1.
    2. Michal Kaczmarek & Piotr Kaczmarek & Ernest Stano, 2022. "The Effect of the Load Power Factor of the Inductive CT’s Secondary Winding on Its Distorted Current’s Harmonics Transformation Accuracy," Energies, MDPI, vol. 15(17), pages 1-11, August.
    3. Zhou, Wei & Wu, Yue & Huang, Xiang & Lu, Renzhi & Zhang, Hai-Tao, 2022. "A group sparse Bayesian learning algorithm for harmonic state estimation in power systems," Applied Energy, Elsevier, vol. 306(PB).
    4. Chen, Lei & Xie, Xiaorong & Li, Xiang & Yang, Lei & Cao, Xin, 2023. "Online SSO stability analysis-based oscillation parameter estimation in converter-tied grids," Applied Energy, Elsevier, vol. 351(C).
    5. Ernest Stano & Piotr Kaczmarek & Michal Kaczmarek, 2022. "Understanding the Frequency Characteristics of Current Error and Phase Displacement of the Corrected Inductive Current Transformer," Energies, MDPI, vol. 15(15), pages 1-16, July.
    6. Wang, Xuewei & Wang, Jing & Yuan, Ruiming & Jiang, Zhenyu, 2019. "Dynamic error testing method of electricity meters by a pseudo random distorted test signal," Applied Energy, Elsevier, vol. 249(C), pages 67-78.
    7. Michal Kaczmarek & Piotr Kaczmarek & Ernest Stano, 2022. "The Performance of the High-Current Transformer during Operation in the Wide Frequencies Range," Energies, MDPI, vol. 15(19), pages 1-15, September.
    8. Das, Laya & Garg, Dinesh & Srinivasan, Babji, 2020. "NeuralCompression: A machine learning approach to compress high frequency measurements in smart grid," Applied Energy, Elsevier, vol. 257(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Guido C. Guerrero-Liquet & Santiago Oviedo-Casado & J. M. Sánchez-Lozano & M. Socorro García-Cascales & Javier Prior & Antonio Urbina, 2018. "Determination of the Optimal Size of Photovoltaic Systems by Using Multi-Criteria Decision-Making Methods," Sustainability, MDPI, vol. 10(12), pages 1-18, December.
    2. Alimou, Yacine & Maïzi, Nadia & Bourmaud, Jean-Yves & Li, Marion, 2020. "Assessing the security of electricity supply through multi-scale modeling: The TIMES-ANTARES linking approach," Applied Energy, Elsevier, vol. 279(C).
    3. Fichter, Tobias & Soria, Rafael & Szklo, Alexandre & Schaeffer, Roberto & Lucena, Andre F.P., 2017. "Assessing the potential role of concentrated solar power (CSP) for the northeast power system of Brazil using a detailed power system model," Energy, Elsevier, vol. 121(C), pages 695-715.
    4. Rocha, P. A. Costa & Rocha, H. H. Barbosa & Carneiro, F. O. Moura & da Silva, M. E. Vieira & de Andrade, C. Freitas, 2016. "A case study on the calibration of the k–ω SST (shear stress transport) turbulence model for small scale wind turbines designed with cambered and symmetrical airfoils," Energy, Elsevier, vol. 97(C), pages 144-150.
    5. Audierne, Etienne & Elizondo, Jorge & Bergami, Leonardo & Ibarra, Humberto & Probst, Oliver, 2010. "Analysis of the furling behavior of small wind turbines," Applied Energy, Elsevier, vol. 87(7), pages 2278-2292, July.
    6. Hao, Ran & Lu, Tianguang & Ai, Qian & Wang, Zhe & Wang, Xiaolong, 2020. "Distributed online learning and dynamic robust standby dispatch for networked microgrids," Applied Energy, Elsevier, vol. 274(C).
    7. Yagcitekin, Bunyamin & Uzunoglu, Mehmet, 2016. "A double-layer smart charging strategy of electric vehicles taking routing and charge scheduling into account," Applied Energy, Elsevier, vol. 167(C), pages 407-419.
    8. Asaad Mohammad & Ramon Zamora & Tek Tjing Lie, 2020. "Integration of Electric Vehicles in the Distribution Network: A Review of PV Based Electric Vehicle Modelling," Energies, MDPI, vol. 13(17), pages 1-20, September.
    9. Kinnon, Michael Mac & Razeghi, Ghazal & Samuelsen, Scott, 2021. "The role of fuel cells in port microgrids to support sustainable goods movement," Renewable and Sustainable Energy Reviews, Elsevier, vol. 147(C).
    10. Jin, Xin & Ju, Wenbin & Zhang, Zhaolong & Guo, Lianxin & Yang, Xiangang, 2016. "System safety analysis of large wind turbines," Renewable and Sustainable Energy Reviews, Elsevier, vol. 56(C), pages 1293-1307.
    11. Rimkevicius, Sigitas & Kaliatka, Algirdas & Valincius, Mindaugas & Dundulis, Gintautas & Janulionis, Remigijus & Grybenas, Albertas & Zutautaite, Inga, 2012. "Development of approach for reliability assessment of pipeline network systems," Applied Energy, Elsevier, vol. 94(C), pages 22-33.
    12. Polleux, Louis & Guerassimoff, Gilles & Marmorat, Jean-Paul & Sandoval-Moreno, John & Schuhler, Thierry, 2022. "An overview of the challenges of solar power integration in isolated industrial microgrids with reliability constraints," Renewable and Sustainable Energy Reviews, Elsevier, vol. 155(C).
    13. Colmenar-Santos, Antonio & Linares-Mena, Ana-Rosa & Borge-Diez, David & Quinto-Alemany, Carlos-Domingo, 2017. "Impact assessment of electric vehicles on islands grids: A case study for Tenerife (Spain)," Energy, Elsevier, vol. 120(C), pages 385-396.
    14. Hu, Qian & Zhu, Ziqing & Bu, Siqi & Wing Chan, Ka & Li, Fangxing, 2021. "A multi-market nanogrid P2P energy and ancillary service trading paradigm: Mechanisms and implementations," Applied Energy, Elsevier, vol. 293(C).
    15. Wang, Shouxiang & Chen, Haiwen, 2019. "A novel deep learning method for the classification of power quality disturbances using deep convolutional neural network," Applied Energy, Elsevier, vol. 235(C), pages 1126-1140.
    16. Yong, Jia Ying & Ramachandaramurthy, Vigna K. & Tan, Kang Miao & Mithulananthan, N., 2015. "A review on the state-of-the-art technologies of electric vehicle, its impacts and prospects," Renewable and Sustainable Energy Reviews, Elsevier, vol. 49(C), pages 365-385.
    17. Maïzi, Nadia & Mazauric, Vincent & Assoumou, Edi & Bouckaert, Stéphanie & Krakowski, Vincent & Li, Xiang & Wang, Pengbo, 2018. "Maximizing intermittency in 100% renewable and reliable power systems: A holistic approach applied to Reunion Island in 2030," Applied Energy, Elsevier, vol. 227(C), pages 332-341.
    18. Umeozor, Evar Chinedu & Trifkovic, Milana, 2016. "Operational scheduling of microgrids via parametric programming," Applied Energy, Elsevier, vol. 180(C), pages 672-681.
    19. José Luis Ruiz Duarte & Neng Fan, 2022. "Operation of a Power Grid with Embedded Networked Microgrids and Onsite Renewable Technologies," Energies, MDPI, vol. 15(7), pages 1-24, March.
    20. Rezghi, Ali & Riasi, Alireza & Tazraei, Pedram, 2020. "Multi-objective optimization of hydraulic transient condition in a pump-turbine hydropower considering the wicket-gates closing law and the surge tank position," Renewable Energy, Elsevier, vol. 148(C), pages 478-491.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:appene:v:165:y:2016:i:c:p:583-591. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/405891/description#description .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.