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Impact of Demand-Side Management on the Reliability of Generation Systems

Author

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  • Hussein Jumma Jabir

    (School of Electrical and Electronic Engineering, Universiti Sains Malaysia (USM), Nibong Tebal 14300, Penang, Malaysia
    Inspector General Office, Ministry of Water Resources, Filastin 10046, Baghdad, Iraq)

  • Jiashen Teh

    (School of Electrical and Electronic Engineering, Universiti Sains Malaysia (USM), Nibong Tebal 14300, Penang, Malaysia)

  • Dahaman Ishak

    (School of Electrical and Electronic Engineering, Universiti Sains Malaysia (USM), Nibong Tebal 14300, Penang, Malaysia)

  • Hamza Abunima

    (School of Electrical and Electronic Engineering, Universiti Sains Malaysia (USM), Nibong Tebal 14300, Penang, Malaysia)

Abstract

The load shifting strategy is a form of demand side management program suitable for increasing the reliability of power supply in an electrical network. It functions by clipping the load demand that is above an operator-defined level, at which time is known as peak period, and replaces it at off-peak periods. The load shifting strategy is conventionally performed using the preventive load shifting (PLS) program. In this paper, the corrective load shifting (CLS) program is proven as the better alternative. PLS is implemented when power systems experience contingencies that jeopardise the reliability of the power supply, whereas CLS is implemented only when the inadequacy of the power supply is encountered. The disadvantages of the PLS approach are twofold. First, the clipped energy cannot be totally recovered when it is more than the unused capacity of the off-peak period. The unused capacity is the maximum amount of extra load that can be filled before exceeding the operator-defined level. Second, the PLS approach performs load curtailment without discrimination. This means that load clipping is performed as long as the load is above the operator-defined level even if the power supply is adequate. The CLS program has none of these disadvantages because it is implemented only when there is power supply inadequacy, during which the amount of load clipping is mostly much smaller than the unused capacity of the off-peak period. The performance of the CLS was compared with the PLS by considering chronological load model, duty cycle and the probability of start-up failure for peaking and cycling generators, planned maintenance of the generators and load forecast uncertainty. A newly proposed expected-energy-not-recovered (EENR) index and the well-known expected-energy-not-supplied (EENS) were used to evaluate the performance of proposed CLS. Due to the chronological factor and huge combinations of power system states, the sequential Monte Carlo was employed in this study. The results from this paper show that the proposed CLS yields lower EENS and EENR than PLS and is, therefore, a more robust strategy to be implemented.

Suggested Citation

  • Hussein Jumma Jabir & Jiashen Teh & Dahaman Ishak & Hamza Abunima, 2018. "Impact of Demand-Side Management on the Reliability of Generation Systems," Energies, MDPI, vol. 11(8), pages 1-20, August.
    • Handle: RePEc:gam:jeners:v:11:y:2018:i:8:p:2155-:d:164336
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    References listed on IDEAS

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    1. Hussein Jumma Jabir & Jiashen Teh & Dahaman Ishak & Hamza Abunima, 2018. "Impacts of Demand-Side Management on Electrical Power Systems: A Review," Energies, MDPI, vol. 11(5), pages 1-19, April.
    2. Malik, Arif S, 1999. "Dynamic generating costs in DSM planning," Energy, Elsevier, vol. 24(1), pages 1-8.
    3. Karunanithi, K. & Saravanan, S. & Prabakar, B.R. & Kannan, S. & Thangaraj, C., 2017. "Integration of Demand and Supply Side Management strategies in Generation Expansion Planning," Renewable and Sustainable Energy Reviews, Elsevier, vol. 73(C), pages 966-982.
    4. Jiashen Teh & Chia Ai Ooi & Yu-Huei Cheng & Muhammad Ammirrul Atiqi Mohd Zainuri & Ching-Ming Lai, 2018. "Composite Reliability Evaluation of Load Demand Side Management and Dynamic Thermal Rating Systems," Energies, MDPI, vol. 11(2), pages 1-15, February.
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    2. Eunsung Oh, 2022. "Fair Virtual Energy Storage System Operation for Smart Energy Communities," Sustainability, MDPI, vol. 14(15), pages 1-16, August.
    3. Vasileios M. Laitsos & Dimitrios Bargiotas & Aspassia Daskalopulu & Athanasios Ioannis Arvanitidis & Lefteri H. Tsoukalas, 2021. "An Incentive-Based Implementation of Demand Side Management in Power Systems," Energies, MDPI, vol. 14(23), pages 1-24, November.
    4. Jiashen Teh, 2018. "Adequacy Assessment of Wind Integrated Generating Systems Incorporating Demand Response and Battery Energy Storage System," Energies, MDPI, vol. 11(10), pages 1-12, October.
    5. Mohamad, Farihan & Teh, Jiashen & Lai, Ching-Ming, 2021. "Optimum allocation of battery energy storage systems for power grid enhanced with solar energy," Energy, Elsevier, vol. 223(C).
    6. Yuriy Leonidovich Zhukovskiy & Margarita Sergeevna Kovalchuk & Daria Evgenievna Batueva & Nikita Dmitrievich Senchilo, 2021. "Development of an Algorithm for Regulating the Load Schedule of Educational Institutions Based on the Forecast of Electric Consumption within the Framework of Application of the Demand Response," Sustainability, MDPI, vol. 13(24), pages 1-26, December.
    7. Alessandro Niccolai & Gaia Gianna Taje & Davide Mosca & Fabrizio Trombello & Emanuele Ogliari, 2022. "Industrial Demand-Side Management by Means of Differential Evolution Considering Energy Price and Labour Cost," Mathematics, MDPI, vol. 10(19), pages 1-16, October.
    8. Tengfei Ma & Junyong Wu & Liangliang Hao & Huaguang Yan & Dezhi Li, 2018. "A Real-Time Pricing Scheme for Energy Management in Integrated Energy Systems: A Stackelberg Game Approach," Energies, MDPI, vol. 11(10), pages 1-19, October.
    9. Rajavelu Dharani & Madasamy Balasubramonian & Thanikanti Sudhakar Babu & Benedetto Nastasi, 2021. "Load Shifting and Peak Clipping for Reducing Energy Consumption in an Indian University Campus," Energies, MDPI, vol. 14(3), pages 1-16, January.
    10. Konstantinos Fiorentzis & Antonios Tsikalakis & Emmanuel Karapidakis & Yiannis Katsigiannis & George Stavrakakis, 2019. "Improving Reliability Indices of the Autonomous Power System of Crete Island Utilizing Extended Photovoltaic Installations," Energies, MDPI, vol. 13(1), pages 1-15, December.
    11. Hamza Abunima & Jiashen Teh & Ching-Ming Lai & Hussein Jumma Jabir, 2018. "A Systematic Review of Reliability Studies on Composite Power Systems: A Coherent Taxonomy Motivations, Open Challenges, Recommendations, and New Research Directions," Energies, MDPI, vol. 11(9), pages 1-37, September.

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