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Demand Response Economic Assessment with the Integration of Renewable Energy for Developing Electricity Markets

Author

Listed:
  • Abdul Conteh

    (Department of Electrical and Electronics Engineering, University of the Ryukyus, Okinawa 903-0213, Japan
    Electricity Distribution and Supply Authority (EDSA), Freetown 00232, Sierra Leone)

  • Mohammed Elsayed Lotfy

    (Department of Electrical and Electronics Engineering, University of the Ryukyus, Okinawa 903-0213, Japan
    Department of Electrical Power and Machines, Zagazig University, Zagazig 44519, Egypt)

  • Oludamilare Bode Adewuyi

    (Department of Electrical and Electronics Engineering, University of the Ryukyus, Okinawa 903-0213, Japan)

  • Paras Mandal

    (Department of Electrical and Computer Engineering, University of Texas, El Paso, TX 79968, USA)

  • Hiroshi Takahashi

    (Fuji Elctric Co., Ltd., Tokyo 141-0032, Japan)

  • Tomonobu Senjyu

    (Department of Electrical and Electronics Engineering, University of the Ryukyus, Okinawa 903-0213, Japan)

Abstract

Electricity disparity in sub-Saharan Africa is a multi-dimensional challenge that has significant implications on the current socio-economic predicament of the region. Strategic implementation of demand response (DR) programs and renewable energy (RE) integration can provide efficient solutions with several benefits such as peak load reduction, grid congestion mitigation, load profile modification, and greenhouse gas emissions reduction. In this research, an incentive and price-based DR programs model using the price elasticity concepts is proposed. Economic analysis of the customer benefit, utility revenue, load factor, and load profile modification are optimally carried out using Freetown (Sierra Leone) peak load demand. The strategic selection index is employed to prioritize relevant DR programs that are techno-economically beneficial for the independent power producers (IPPs) and participating customers. Moreover, optimally designed hybridized grid-connected RE was incorporated using the Genetic Algorithm (GA) to meet the deficit after DR implementation. GA is used to get the optimal solution in terms of the required PV area and the number of BESS to match the net load demand after implementing the DR schemes. The results show credible enhancement in the load profile in terms of peak period reduction as measured using the effective load factor. Moreover, customer benefit and utility revenues are significantly improved using the proposed approach. Furthermore, the inclusion of the hybrid RE supply proves to be an efficient approach to meet the load demand during low peak and valley periods and can also mitigate greenhouse gas emissions.

Suggested Citation

  • Abdul Conteh & Mohammed Elsayed Lotfy & Oludamilare Bode Adewuyi & Paras Mandal & Hiroshi Takahashi & Tomonobu Senjyu, 2020. "Demand Response Economic Assessment with the Integration of Renewable Energy for Developing Electricity Markets," Sustainability, MDPI, vol. 12(7), pages 1-20, March.
    • Handle: RePEc:gam:jsusta:v:12:y:2020:i:7:p:2653-:d:337880
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    References listed on IDEAS

    as
    1. Alcázar-Ortega, Manuel & Calpe, Carmen & Theisen, Thomas & Carbonell-Carretero, José Francisco, 2015. "Methodology for the identification, evaluation and prioritization of market handicaps which prevent the implementation of Demand Response: Application to European electricity markets," Energy Policy, Elsevier, vol. 86(C), pages 529-543.
    2. David Abdul Konneh & Harun Or Rashid Howlader & Ryuto Shigenobu & Tomonobu Senjyu & Shantanu Chakraborty & Narayanan Krishna, 2019. "A Multi-Criteria Decision Maker for Grid-Connected Hybrid Renewable Energy Systems Selection Using Multi-Objective Particle Swarm Optimization," Sustainability, MDPI, vol. 11(4), pages 1-36, February.
    3. Shen, Bo & Ghatikar, Girish & Lei, Zeng & Li, Jinkai & Wikler, Greg & Martin, Phil, 2014. "The role of regulatory reforms, market changes, and technology development to make demand response a viable resource in meeting energy challenges," Applied Energy, Elsevier, vol. 130(C), pages 814-823.
    4. Adom, Philip Kofi, 2017. "The long-run price sensitivity dynamics of industrial and residential electricity demand: The impact of deregulating electricity prices," Energy Economics, Elsevier, vol. 62(C), pages 43-60.
    5. Adeoye, Omotola & Spataru, Catalina, 2019. "Modelling and forecasting hourly electricity demand in West African countries," Applied Energy, Elsevier, vol. 242(C), pages 311-333.
    6. Abdul Conteh & Mohammed Elsayed Lotfy & Kiptoo Mark Kipngetich & Tomonobu Senjyu & Paras Mandal & Shantanu Chakraborty, 2019. "An Economic Analysis of Demand Side Management Considering Interruptible Load and Renewable Energy Integration: A Case Study of Freetown Sierra Leone," Sustainability, MDPI, vol. 11(10), pages 1-19, May.
    7. Jong-Chan Kim & Jun-Ho Huh & Jae-Sub Ko, 2019. "Improvement of MPPT Control Performance Using Fuzzy Control and VGPI in the PV System for Micro Grid," Sustainability, MDPI, vol. 11(21), pages 1-27, October.
    8. Aghaei, Jamshid & Alizadeh, Mohammad-Iman, 2013. "Demand response in smart electricity grids equipped with renewable energy sources: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 18(C), pages 64-72.
    9. Torriti, Jacopo & Hassan, Mohamed G. & Leach, Matthew, 2010. "Demand response experience in Europe: Policies, programmes and implementation," Energy, Elsevier, vol. 35(4), pages 1575-1583.
    10. Ogunjuyigbe, A.S.O. & Ayodele, T.R. & Akinola, O.A., 2017. "User satisfaction-induced demand side load management in residential buildings with user budget constraint," Applied Energy, Elsevier, vol. 187(C), pages 352-366.
    11. Montuori, Lina & Alcázar-Ortega, Manuel & Álvarez-Bel, Carlos & Domijan, Alex, 2014. "Integration of renewable energy in microgrids coordinated with demand response resources: Economic evaluation of a biomass gasification plant by Homer Simulator," Applied Energy, Elsevier, vol. 132(C), pages 15-22.
    12. Seong-Kyu Kim & Jun-Ho Huh, 2018. "A Study on the Improvement of Smart Grid Security Performance and Blockchain Smart Grid Perspective," Energies, MDPI, vol. 11(8), pages 1-22, July.
    13. Zhe Xiao & Tinghua Li & Ming Huang & Jihong Shi & Jingjing Yang & Jiang Yu & Wei Wu, 2010. "Hierarchical MAS Based Control Strategy for Microgrid," Energies, MDPI, vol. 3(9), pages 1-17, September.
    14. Aalami, H.A. & Moghaddam, M. Parsa & Yousefi, G.R., 2010. "Demand response modeling considering Interruptible/Curtailable loads and capacity market programs," Applied Energy, Elsevier, vol. 87(1), pages 243-250, January.
    15. Ikpe, Eka & Torriti, Jacopo, 2018. "A means to an industrialisation end? Demand Side Management in Nigeria," Energy Policy, Elsevier, vol. 115(C), pages 207-215.
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    Cited by:

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    2. Mahmoud M. Gamil & Makoto Sugimura & Akito Nakadomari & Tomonobu Senjyu & Harun Or Rashid Howlader & Hiroshi Takahashi & Ashraf M. Hemeida, 2020. "Optimal Sizing of a Real Remote Japanese Microgrid with Sea Water Electrolysis Plant Under Time-Based Demand Response Programs," Energies, MDPI, vol. 13(14), pages 1-22, July.
    3. Keifa Vamba Konneh & Hasan Masrur & Mohammad Lutfi Othman & Hiroshi Takahashi & Narayanan Krishna & Tomonobu Senjyu, 2021. "Multi-Attribute Decision-Making Approach for a Cost-Effective and Sustainable Energy System Considering Weight Assignment Analysis," Sustainability, MDPI, vol. 13(10), pages 1-22, May.
    4. Larry Erickson & Stephanie Ma, 2021. "Solar-Powered Charging Networks for Electric Vehicles," Energies, MDPI, vol. 14(4), pages 1-10, February.
    5. Mark Kipngetich Kiptoo & Oludamilare Bode Adewuyi & Masahiro Furukakoi & Paras Mandal & Tomonobu Senjyu, 2023. "Integrated Multi-Criteria Planning for Resilient Renewable Energy-Based Microgrid Considering Advanced Demand Response and Uncertainty," Energies, MDPI, vol. 16(19), pages 1-25, September.
    6. Mahmoud M. Gamil & Soichirou Ueda & Akito Nakadomari & Keifa Vamba Konneh & Tomonobu Senjyu & Ashraf M. Hemeida & Mohammed Elsayed Lotfy, 2022. "Optimal Multi-Objective Power Scheduling of a Residential Microgrid Considering Renewable Sources and Demand Response Technique," Sustainability, MDPI, vol. 14(21), pages 1-20, October.

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