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Effect of demand response program of loads in cost optimization of microgrid considering uncertain parameters in PV/WT, market price and load demand

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  • Rajamand, Sahbasadat

Abstract

Using renewable distributed generators as photovoltaic cell and wind turbine in microgrid includes green and free energy exploitation. However, uncertainty of generated energy from these resources may underestimate energy planning for load demands. The uncertainty may be from market price and load demand in addition to the renewable distributed generators. To overcome the uncertainty challenge, energy storage system and demand response program with cooperation of users on demand side are applied as solutions to plan the energy flow in microgrid to guarantee the voltage stability and essential load supporting. In this paper, price-based demand response for industrial, commercial and house loads are considered in which the effect of demand response on the cost reduction is analyzed and discussed. Electrical and heat demand are considered in the microgrid while uncertainty of renewable distributed generators, market price and load demand are modeled and estimated by point estimation method. Simulation results with three scenarios are performed with and without price-based demand response program and results are compared. As shown in simulation results, demand response has highly reduced total cost (22–28% related to the case without that) where voltage dip (maximum 1.5%) and power deviation (maximum 1.33%) are also improved in the microgird.

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  • Rajamand, Sahbasadat, 2020. "Effect of demand response program of loads in cost optimization of microgrid considering uncertain parameters in PV/WT, market price and load demand," Energy, Elsevier, vol. 194(C).
    • Handle: RePEc:eee:energy:v:194:y:2020:i:c:s0360544220300244
    DOI: 10.1016/j.energy.2020.116917
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    8. Yang, Jun & Su, Changqi, 2021. "Robust optimization of microgrid based on renewable distributed power generation and load demand uncertainty," Energy, Elsevier, vol. 223(C).
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    10. Liu, Zhengguang & Guo, Zhiling & Chen, Qi & Song, Chenchen & Shang, Wenlong & Yuan, Meng & Zhang, Haoran, 2023. "A review of data-driven smart building-integrated photovoltaic systems: Challenges and objectives," Energy, Elsevier, vol. 263(PE).
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