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A review on distributed generation allocation and planning in deregulated electricity market

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  • Singh, A.K.
  • Parida, S.K.

Abstract

Currently, distributed generation (DG) based on conventional energy sources and renewable energy sources (RESs) have played a vital role throughout the world. Energy policies are promoting distributed energy resources such as energy efficiency, increasing the number of DG installations and RESs planning. It can be observed that the load growth rates of countries are rapidly increasing. However, uncoordinated management of these alternative energy sources can put a severe stress on the power grid. To overcome from this problem, DGs are the best options for managing the need of energy. In this work, the robustness, sustainability and reliability of DG has been discussed with various aspects including different contingency scenario. Contingency analysis of a power system is a major action in power system planning and operation. This review covers the recent works done in the area of integration of DGs with various scenarios in electrical power systems. The main objective of this work is to study how to achieve a better integration of flexible demand as demand response, demand side management (DSM) with DGs and make the grid proficient. It then reviews the key results in this field and some of the interesting research challenges can be addressed are also acknowledged.

Suggested Citation

  • Singh, A.K. & Parida, S.K., 2018. "A review on distributed generation allocation and planning in deregulated electricity market," Renewable and Sustainable Energy Reviews, Elsevier, vol. 82(P3), pages 4132-4141.
    • Handle: RePEc:eee:rensus:v:82:y:2018:i:p3:p:4132-4141
    DOI: 10.1016/j.rser.2017.10.060
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    References listed on IDEAS

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    1. Muttaqi, K.M. & Le, An D.T. & Aghaei, J. & Mahboubi-Moghaddam, E. & Negnevitsky, M. & Ledwich, G., 2016. "Optimizing distributed generation parameters through economic feasibility assessment," Applied Energy, Elsevier, vol. 165(C), pages 893-903.
    2. Greene, Nathanael & Hammerschlag, Roel, 2000. "Small and Clean Is Beautiful: Exploring the Emissions of Distributed Generation and Pollution Prevention Policies," The Electricity Journal, Elsevier, vol. 13(5), pages 50-60, June.
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    6. Esmaeili, Mobin & Sedighizadeh, Mostafa & Esmaili, Masoud, 2016. "Multi-objective optimal reconfiguration and DG (Distributed Generation) power allocation in distribution networks using Big Bang-Big Crunch algorithm considering load uncertainty," Energy, Elsevier, vol. 103(C), pages 86-99.
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    Cited by:

    1. 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.
    2. Christos N. Dimitriadis & Evangelos G. Tsimopoulos & Michael C. Georgiadis, 2021. "A Review on the Complementarity Modelling in Competitive Electricity Markets," Energies, MDPI, vol. 14(21), pages 1-27, November.
    3. Zohaib Hussain Leghari & Mahesh Kumar & Pervez Hameed Shaikh & Laveet Kumar & Quynh T. Tran, 2022. "A Critical Review of Optimization Strategies for Simultaneous Integration of Distributed Generation and Capacitor Banks in Power Distribution Networks," Energies, MDPI, vol. 15(21), pages 1-40, November.
    4. Moreno, Blanca & Díaz, Guzmán, 2019. "The impact of virtual power plant technology composition on wholesale electricity prices: A comparative study of some European Union electricity markets," Renewable and Sustainable Energy Reviews, Elsevier, vol. 99(C), pages 100-108.
    5. Zengqiang Mi & Yulong Jia & Junjie Wang & Xiaoming Zheng, 2018. "Optimal Scheduling Strategies of Distributed Energy Storage Aggregator in Energy and Reserve Markets Considering Wind Power Uncertainties," Energies, MDPI, vol. 11(5), pages 1-17, May.

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