IDEAS home Printed from https://ideas.repec.org/a/eee/rensus/v73y2017icp125-134.html
   My bibliography  Save this article

Challenges with renewable energy sources and storage in practical distribution systems

Author

Listed:
  • Muruganantham, B.
  • Gnanadass, R.
  • Padhy, N.P.

Abstract

The intuition of the power distribution system is to supply good quality of power to the customers with cost-effectively and environment friendly. Renewable energy resources (RES) are integrated in the distribution system to meet out the variable load demand with the decarbonizing effect. With the inclusion of RES, the operation of Distribution Network (DN) has become more complex. This paper describes the state of art in various load flow methods used to analyze the parameters in DN. This paper emphasizes upon the various challenges of DN with the integration of RES. It reviews the various pricing methodologies for the delivered power in DN elaborately. The importance of Demand Side Management (DSM) and energy storage in DN are explored in this paper. The analysis of nodal voltages in the DN with Solar PV, Storage, PHEV and Diesel sources is demonstrated on IEEE four node test feeder.

Suggested Citation

  • Muruganantham, B. & Gnanadass, R. & Padhy, N.P., 2017. "Challenges with renewable energy sources and storage in practical distribution systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 73(C), pages 125-134.
  • Handle: RePEc:eee:rensus:v:73:y:2017:i:c:p:125-134
    DOI: 10.1016/j.rser.2017.01.089
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1364032117301004
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.rser.2017.01.089?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. Ghasemi, A. & Shayeghi, H. & Moradzadeh, M. & Nooshyar, M., 2016. "A novel hybrid algorithm for electricity price and load forecasting in smart grids with demand-side management," Applied Energy, Elsevier, vol. 177(C), pages 40-59.
    2. Alham, M.H. & Elshahed, M. & Ibrahim, Doaa Khalil & Abo El Zahab, Essam El Din, 2016. "A dynamic economic emission dispatch considering wind power uncertainty incorporating energy storage system and demand side management," Renewable Energy, Elsevier, vol. 96(PA), pages 800-811.
    3. Torriti, Jacopo, 2012. "Price-based demand side management: Assessing the impacts of time-of-use tariffs on residential electricity demand and peak shifting in Northern Italy," Energy, Elsevier, vol. 44(1), pages 576-583.
    4. Muthamizh Selvam, M. & Gnanadass, R. & Padhy, N.P., 2016. "Initiatives and technical challenges in smart distribution grid," Renewable and Sustainable Energy Reviews, Elsevier, vol. 58(C), pages 911-917.
    5. Aleksandr Rudkevich & Max Duckworth & Richard Rosen, 1998. "Modeling Electricity Pricing in a Deregulated Generation Industry: The Potential for Oligopoly Pricing in a Poolco," The Energy Journal, International Association for Energy Economics, vol. 0(Number 3), pages 19-48.
    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. Feng, Wenxiu, 2023. "Risk Management of Energy Communities with Hydrogen Production and Storage Technologies," DES - Working Papers. Statistics and Econometrics. WS 36274, Universidad Carlos III de Madrid. Departamento de Estadística.
    2. Mahmoud G. Hemeida & Salem Alkhalaf & Al-Attar A. Mohamed & Abdalla Ahmed Ibrahim & Tomonobu Senjyu, 2020. "Distributed Generators Optimization Based on Multi-Objective Functions Using Manta Rays Foraging Optimization Algorithm (MRFO)," Energies, MDPI, vol. 13(15), pages 1-37, July.
    3. Ayman B. Attya & Adam Vickers, 2021. "Operation and Control of a Hybrid Power Plant with the Capability of Grid Services Provision," Energies, MDPI, vol. 14(13), pages 1-15, June.
    4. Gul, Eid & Baldinelli, Giorgio & Bartocci, Pietro & Bianchi, Francesco & Domenghini, Piergiovanni & Cotana, Franco & Wang, Jinwen, 2022. "A techno-economic analysis of a solar PV and DC battery storage system for a community energy sharing," Energy, Elsevier, vol. 244(PB).
    5. Rong-Ceng Leou & Jen-Hao Teng & Yun-Fang Li & Wei-Min Lin & Yu-Hung Lin, 2020. "System Unbalance Analyses and Improvement for Rooftop Photovoltaic Generation Systems in Distribution Networks," Energies, MDPI, vol. 13(8), pages 1-18, April.
    6. Logeswaran, T. & Senthil Raja, M. & Beevi Sahul Hameed, Jennathu & Abdulrahim, Mahabuba, 2022. "Power flow management of hybrid system in smart grid requirements using ITSA-MOAT approach," Applied Energy, Elsevier, vol. 319(C).
    7. Samuel Godfrey, 2023. "Redesigning a Solar PV Kiosk in High-Temperature Environments of Burundi, Africa," Sustainability, MDPI, vol. 15(6), pages 1-13, March.
    8. Vu, Ba Hau & Chung, Il-Yop, 2022. "Optimal generation scheduling and operating reserve management for PV generation using RNN-based forecasting models for stand-alone microgrids," Renewable Energy, Elsevier, vol. 195(C), pages 1137-1154.
    9. Mendoza-Vizcaino, Javier & Raza, Muhammad & Sumper, Andreas & Díaz-González, Francisco & Galceran-Arellano, Samuel, 2019. "Integral approach to energy planning and electric grid assessment in a renewable energy technology integration for a 50/50 target applied to a small island," Applied Energy, Elsevier, vol. 233, pages 524-543.
    10. Lucas Roth & Jens Lowitzsch & Özgür Yildiz, 2021. "An Empirical Study of How Household Energy Consumption Is Affected by Co-Owning Different Technological Means to Produce Renewable Energy and the Production Purpose," Energies, MDPI, vol. 14(13), pages 1-38, July.
    11. Salvatore Favuzza & Mariano Giuseppe Ippolito & Fabio Massaro & Rossano Musca & Eleonora Riva Sanseverino & Giuseppe Schillaci & Gaetano Zizzo, 2018. "Building Automation and Control Systems and Electrical Distribution Grids: A Study on the Effects of Loads Control Logics on Power Losses and Peaks," Energies, MDPI, vol. 11(3), pages 1-15, March.
    12. Hassan Elahi & Marco Eugeni & Paolo Gaudenzi, 2018. "A Review on Mechanisms for Piezoelectric-Based Energy Harvesters," Energies, MDPI, vol. 11(7), pages 1-35, July.
    13. Cruz, Marco R.M. & Fitiwi, Desta Z. & Santos, Sérgio F. & Catalão, João P.S., 2018. "A comprehensive survey of flexibility options for supporting the low-carbon energy future," Renewable and Sustainable Energy Reviews, Elsevier, vol. 97(C), pages 338-353.
    14. Jingpeng Yue & Zhijian Hu & Amjad Anvari-Moghaddam & Josep M. Guerrero, 2019. "A Multi-Market-Driven Approach to Energy Scheduling of Smart Microgrids in Distribution Networks," Sustainability, MDPI, vol. 11(2), pages 1-16, January.
    15. Deevela, Niranjan Rao & Singh, Bhim & Kandpal, Tara C., 2023. "Optimization and economic analysis of solar PV based hybrid system for powering Base Transceiver Stations in India," Energy, Elsevier, vol. 283(C).
    16. Stavros Lazarou & Vasiliki Vita & Lambros Ekonomou, 2018. "Protection Schemes of Meshed Distribution Networks for Smart Grids and Electric Vehicles," Energies, MDPI, vol. 11(11), pages 1-17, November.
    17. Feng, Wenxiu & Ruiz, Carlos, 2023. "Risk management of energy communities with hydrogen production and storage technologies," Applied Energy, Elsevier, vol. 348(C).
    18. Das, Choton K. & Bass, Octavian & Kothapalli, Ganesh & Mahmoud, Thair S. & Habibi, Daryoush, 2018. "Overview of energy storage systems in distribution networks: Placement, sizing, operation, and power quality," Renewable and Sustainable Energy Reviews, Elsevier, vol. 91(C), pages 1205-1230.
    19. Yi, Ji Hyun & Cherkaoui, Rachid & Paolone, Mario & Shchetinin, Dmitry & Knezovic, Katarina, 2022. "Expansion planning of active distribution networks achieving their dispatchability via energy storage systems," Applied Energy, Elsevier, vol. 326(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. Jordehi, A. Rezaee, 2019. "Optimisation of demand response in electric power systems, a review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 103(C), pages 308-319.
    2. Wiser, R. H., 2000. "The role of public policy in emerging green power markets: an analysis of marketer preferences," Renewable and Sustainable Energy Reviews, Elsevier, vol. 4(2), pages 177-212, June.
    3. Liu, Che & Sun, Bo & Zhang, Chenghui & Li, Fan, 2020. "A hybrid prediction model for residential electricity consumption using holt-winters and extreme learning machine," Applied Energy, Elsevier, vol. 275(C).
    4. Zheng, Yingying & Jenkins, Bryan M. & Kornbluth, Kurt & Kendall, Alissa & Træholt, Chresten, 2018. "Optimization of a biomass-integrated renewable energy microgrid with demand side management under uncertainty," Applied Energy, Elsevier, vol. 230(C), pages 836-844.
    5. Kovacic, Zora & Giampietro, Mario, 2015. "Empty promises or promising futures? The case of smart grids," Energy, Elsevier, vol. 93(P1), pages 67-74.
    6. Holmberg, Pär & Newbery, David & Ralph, Daniel, 2013. "Supply function equilibria: Step functions and continuous representations," Journal of Economic Theory, Elsevier, vol. 148(4), pages 1509-1551.
    7. Y, Kiguchi & Y, Heo & M, Weeks & R, Choudhary, 2019. "Predicting intra-day load profiles under time-of-use tariffs using smart meter data," Energy, Elsevier, vol. 173(C), pages 959-970.
    8. Abolmassov Aleksandr & Kolodin Denis, 2003. "Structural changes in Russian electricity market," EERC Working Paper Series 01-016e, EERC Research Network, Russia and CIS.
    9. Kim, Kyungah & Choi, Jihye & Lee, Jihee & Lee, Jongsu & Kim, Junghun, 2023. "Public preferences and increasing acceptance of time-varying electricity pricing for demand side management in South Korea," Energy Economics, Elsevier, vol. 119(C).
    10. Pär Holmberg, 2017. "Pro‐competitive Rationing in Multi‐unit Auctions," Economic Journal, Royal Economic Society, vol. 127(605), pages 372-395, October.
    11. Pär Holmberg & Andy Philpott, 2014. "Supply function equilibria in transportation networks," Cambridge Working Papers in Economics 1421, Faculty of Economics, University of Cambridge.
    12. Yunusov, Timur & Torriti, Jacopo, 2021. "Distributional effects of Time of Use tariffs based on electricity demand and time use," Energy Policy, Elsevier, vol. 156(C).
    13. Anjo, João & Neves, Diana & Silva, Carlos & Shivakumar, Abhishek & Howells, Mark, 2018. "Modeling the long-term impact of demand response in energy planning: The Portuguese electric system case study," Energy, Elsevier, vol. 165(PA), pages 456-468.
    14. Sourav Khanna & Victor Becerra & Adib Allahham & Damian Giaouris & Jamie M. Foster & Keiron Roberts & David Hutchinson & Jim Fawcett, 2020. "Demand Response Model Development for Smart Households Using Time of Use Tariffs and Optimal Control—The Isle of Wight Energy Autonomous Community Case Study," Energies, MDPI, vol. 13(3), pages 1-27, January.
    15. D'Ecclesia, Rita Laura & Gallo, Crescenzio, 2002. "Price-caps and Efficient Pricing for the Electricity Italian Market," MPRA Paper 10048, University Library of Munich, Germany.
    16. John Morris, 2000. "Finding Market Power in Electric Power Markets," International Journal of the Economics of Business, Taylor & Francis Journals, vol. 7(2), pages 167-178.
    17. Liu, Zhi-Feng & Li, Ling-Ling & Liu, Yu-Wei & Liu, Jia-Qi & Li, Heng-Yi & Shen, Qiang, 2021. "Dynamic economic emission dispatch considering renewable energy generation: A novel multi-objective optimization approach," Energy, Elsevier, vol. 235(C).
    18. Ventosa, Mariano & Baillo, Alvaro & Ramos, Andres & Rivier, Michel, 2005. "Electricity market modeling trends," Energy Policy, Elsevier, vol. 33(7), pages 897-913, May.
    19. Osaru Agbonaye & Patrick Keatley & Ye Huang & Motasem Bani Mustafa & Neil Hewitt, 2020. "Design, Valuation and Comparison of Demand Response Strategies for Congestion Management," Energies, MDPI, vol. 13(22), pages 1-29, November.
    20. Kiguchi, Y. & Weeks, M. & Arakawa, R., 2021. "Predicting winners and losers under time-of-use tariffs using smart meter data," Energy, Elsevier, vol. 236(C).

    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:rensus:v:73:y:2017:i:c:p:125-134. 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/600126/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.