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Real-Time Pricing and Energy Storage for Voltage Improvement in a Distribution Feeder

Received: 13 September 2016    Accepted: 10 January 2017    Published: 24 February 2017
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Abstract

Increasing demand on electrical energy coupled with lack of new distribution facilities create a potential threat that can eventually sprawl to jeopardize the distribution system reliability. The variability characteristics of wind energy sources present a fundamental problem to its smooth integration in the distribution feeders, in a large proportion. Energy storage (ES) systems and demand response (DR) technique have the potential to improve the flexibility of distribution network, by allowing two ways of freedom for the distribution network operator (DNO), to support mitigation of demand-supply balance issues, and thereby the share of renewable energy sources (RESs) or improve penetration levels of renewables. By shifting electricity supply and customer demand patterns, this paper applies real time pricing and energy storage not only to significantly increase the penetration of wind energy, but also to offer other important value to shifts demand to times of relatively high renewable energy resources and low load; and by storing energy during off-peak, with less line losses, and redispatching this energy when needed. The results show that real time pricing and energy storage can effectively provide demand-supply benefits to the distribution network and customers.

Published in International Journal of Mechanical Engineering and Applications (Volume 5, Issue 1)
DOI 10.11648/j.ijmea.20170501.15
Page(s) 41-46
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2024. Published by Science Publishing Group

Keywords

Energy Storage, Real Time Pricing, Peak-Valley Levelling, PSOGSA, Wind Energy

References
[1] Alharbi, W. and K. Bhattacharya. Demand response and energy storage in MV islanded microgrids for high penetration of renewables. Electrical Power & Energy Conference (EPEC), 2013.
[2] Roberts, B. P. and C. Sandberg. "The role of energy storage in development of smart grids." Proceedings of the IEEE, 2011, 99 (6): 1139-1144.
[3] Petinrin, J. O. and M. Shaaban. "Implementation of Energy Storage in a Future Smart Grid." Australian Journal of Basic and Applied Sciences,2013, 7 (4): 273-279.
[4] Venkatesan, N., J. Solanki and S. K. Solanki). "Residential Demand Response model and impact on voltage profile and losses of an electric distribution network." Applied energy, 2012 96: 84-91.
[5] Chen C.-R and M.-J. Lan. "Optimal Demand Response of Smart Home with PV Generators." International Journal of Photoenergy, 2014, pp. 1-9.
[6] Petinrin, J. O. and M. Shaaban. Voltage control in a smart distribution network using demand response. IEEE International Conference on Power and Energy (PECon), Sarawak, Malaysia, 1-3 December, 2014.
[7] Siano, P. "Demand response and smart grids—A survey." Renewable and Sustainable Energy Reviews 2014, 30: 461-478.
[8] Zhao, Z. Lee, W. C. Shin Y. and Song, K_B. An Optimal Power Scheduling Method for Demand Response in Home Energy Management System. IEEE Transactions on Smart Grid, 2013. 4 (3): 1391-1400.
[9] Zakariazadeh, A., Homaee, O. Jadid S. and Siano, P. A new approach for real time voltage control using demand response in an automated distribution system. Applied Energy, 2014. 117: 157-166.
[10] Monitoring Analytics. "State of the Market Report for PJM: January through September. Technical report," PJM Interconnection: 2014, 102.
[11] Ibrahim H., Llinca A. and Perron, J. Energy storage systems—characteristics and comparisons. Renewable and Sustainable Energy Reviews, 2008. 12 (5): 1221-1250.
[12] Fioravanti, R. Distributed bulk storage!: Independent Testing of Complete (CES) systems. Power and Energy Society General Meeting, 2011. 1-2.
[13] Marra F., Fawzy, Y. T. Bulo, T. and Blazic, B. Energy storage options for voltage support in low-voltage grids with high penetration of photovoltaic. IEEE PES International Conference and Exhibition on Innovative Smart Grid Technologies (ISGT Europe), 2012. 1-7.
[14] Kamdar K. and Karady, G. G. Optimal capacity and location assessment of natural gas fired distributed generation in residential areas. Power Systems Conference (PSC), Clemson University, 2014. 1-5.
[15] Khan, N., Ghosh, S. and Ghoshal, S. Binary Gravitational Search based Algorithm for Optimum Siting and Sizing of DG and Shunt Capacitors in Radial Distribution Systems. Energy and Power Engineering, 2013. 5: 1005.
[16] Tan W. S., Hassan, M. Y. Rahman, H. A. Abdullah, M. P. and Hussin, F. Multi-distributed generation planning using hybrid particle swarm optimisation-gravitational search algorithm including voltage rise issue. IET Generation, Transmission & Distribution, 2013. 7 (9): 929-942.
[17] Atwa Y. M. and El-Saadany, E. Optimal allocation of ESS in distribution systems with a high penetration of wind energy. IEEE Transactions on Power Systems, 2010. 25 (4): 1815-1822.
[18] Liu, A. Aichhorn, Liu, L. and Li, H. Coordinated control of distributed energy storage system with tap changer transformers for voltage rise mitigation under high photovoltaic penetration. IEEE Transactions on Smart Grid, 2012. 3 (2): 897-906.
Cite This Article
  • APA Style

    J. O. Petinrin, M. A. Sanusi, M. A. Tijani, A. K. Adebayo, M. O. Abolarin. (2017). Real-Time Pricing and Energy Storage for Voltage Improvement in a Distribution Feeder. International Journal of Mechanical Engineering and Applications, 5(1), 41-46. https://doi.org/10.11648/j.ijmea.20170501.15

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    ACS Style

    J. O. Petinrin; M. A. Sanusi; M. A. Tijani; A. K. Adebayo; M. O. Abolarin. Real-Time Pricing and Energy Storage for Voltage Improvement in a Distribution Feeder. Int. J. Mech. Eng. Appl. 2017, 5(1), 41-46. doi: 10.11648/j.ijmea.20170501.15

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    AMA Style

    J. O. Petinrin, M. A. Sanusi, M. A. Tijani, A. K. Adebayo, M. O. Abolarin. Real-Time Pricing and Energy Storage for Voltage Improvement in a Distribution Feeder. Int J Mech Eng Appl. 2017;5(1):41-46. doi: 10.11648/j.ijmea.20170501.15

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  • @article{10.11648/j.ijmea.20170501.15,
      author = {J. O. Petinrin and M. A. Sanusi and M. A. Tijani and A. K. Adebayo and M. O. Abolarin},
      title = {Real-Time Pricing and Energy Storage for Voltage Improvement in a Distribution Feeder},
      journal = {International Journal of Mechanical Engineering and Applications},
      volume = {5},
      number = {1},
      pages = {41-46},
      doi = {10.11648/j.ijmea.20170501.15},
      url = {https://doi.org/10.11648/j.ijmea.20170501.15},
      eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijmea.20170501.15},
      abstract = {Increasing demand on electrical energy coupled with lack of new distribution facilities create a potential threat that can eventually sprawl to jeopardize the distribution system reliability. The variability characteristics of wind energy sources present a fundamental problem to its smooth integration in the distribution feeders, in a large proportion. Energy storage (ES) systems and demand response (DR) technique have the potential to improve the flexibility of distribution network, by allowing two ways of freedom for the distribution network operator (DNO), to support mitigation of demand-supply balance issues, and thereby the share of renewable energy sources (RESs) or improve penetration levels of renewables. By shifting electricity supply and customer demand patterns, this paper applies real time pricing and energy storage not only to significantly increase the penetration of wind energy, but also to offer other important value to shifts demand to times of relatively high renewable energy resources and low load; and by storing energy during off-peak, with less line losses, and redispatching this energy when needed. The results show that real time pricing and energy storage can effectively provide demand-supply benefits to the distribution network and customers.},
     year = {2017}
    }
    

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  • TY  - JOUR
    T1  - Real-Time Pricing and Energy Storage for Voltage Improvement in a Distribution Feeder
    AU  - J. O. Petinrin
    AU  - M. A. Sanusi
    AU  - M. A. Tijani
    AU  - A. K. Adebayo
    AU  - M. O. Abolarin
    Y1  - 2017/02/24
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    N1  - https://doi.org/10.11648/j.ijmea.20170501.15
    DO  - 10.11648/j.ijmea.20170501.15
    T2  - International Journal of Mechanical Engineering and Applications
    JF  - International Journal of Mechanical Engineering and Applications
    JO  - International Journal of Mechanical Engineering and Applications
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    PB  - Science Publishing Group
    SN  - 2330-0248
    UR  - https://doi.org/10.11648/j.ijmea.20170501.15
    AB  - Increasing demand on electrical energy coupled with lack of new distribution facilities create a potential threat that can eventually sprawl to jeopardize the distribution system reliability. The variability characteristics of wind energy sources present a fundamental problem to its smooth integration in the distribution feeders, in a large proportion. Energy storage (ES) systems and demand response (DR) technique have the potential to improve the flexibility of distribution network, by allowing two ways of freedom for the distribution network operator (DNO), to support mitigation of demand-supply balance issues, and thereby the share of renewable energy sources (RESs) or improve penetration levels of renewables. By shifting electricity supply and customer demand patterns, this paper applies real time pricing and energy storage not only to significantly increase the penetration of wind energy, but also to offer other important value to shifts demand to times of relatively high renewable energy resources and low load; and by storing energy during off-peak, with less line losses, and redispatching this energy when needed. The results show that real time pricing and energy storage can effectively provide demand-supply benefits to the distribution network and customers.
    VL  - 5
    IS  - 1
    ER  - 

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Author Information
  • Department of Electrical and Electronic Engineering, School of Engineering, Federal Polytechnic Ede, Ede, Nigeria

  • Department of Electrical and Electronic Engineering, School of Engineering, Federal Polytechnic Ede, Ede, Nigeria

  • Department of Electrical and Electronic Engineering, School of Engineering, Federal Polytechnic Ede, Ede, Nigeria

  • Department of Electrical and Electronic Engineering, School of Engineering, Federal Polytechnic Ede, Ede, Nigeria

  • Department of Electrical and Electronic Engineering, School of Engineering, Federal Polytechnic Ede, Ede, Nigeria

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