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Quantification of Demand-Supply Balancing Capacity among Prosumers and Consumers: Community Self-Sufficiency Assessment for Energy Trading

Author

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  • Milad Afzalan

    (INFORM Lab, Department of Civil and Environmental Engineering, Virginia Tech, Blacksburg, VA 24061, USA
    ENGIE Impact, Boston, MA 02210, USA)

  • Farrokh Jazizadeh

    (INFORM Lab, Department of Civil and Environmental Engineering, Virginia Tech, Blacksburg, VA 24061, USA)

Abstract

With the increased adoption of distributed energy resources (DERs) and renewables, such as solar panels at the building level, consumers turn into prosumers with generation capability to supply their on-site demand. The temporal complementarity between supply and demand at the building level provides opportunities for energy exchange between prosumers and consumers towards community-level self-sufficiency. Investigating different aspects of community-level energy exchange in cyber and physical layers has received attention in recent years with the increase in renewables adoption. In this study, we have presented an in-depth investigation into the impact of energy exchange through the quantification of temporal energy deficit–surplus complementarity and its associated self-sufficiency capacities by considering the impact of variations in community infrastructure configurations, variations in household energy use patterns, and the potential for user adaptation for load flexibility. To this end, we have adopted a data-driven simulation using real-world data from a case-study neighborhood consisting of ~250 residential buildings in Austin, TX with a mix of prosumers and consumers and detailed data on decentralized DERs. By accounting for the uncertainties in energy consumption patterns across households, different levels of PV and energy storage integration, and different modalities of user adaptation, various scenarios of operations were simulated. The analysis showed that with PV integration of more than 75%, energy exchange could result in self-sufficiency for the entire community during peak generation hours from 11 a.m. to 3 p.m. However, there are limited opportunities for energy exchange during later times with PV-standalone systems. As a potential solution, leveraging building-level storage or user adaptation for load shedding/shifting during the 2-h low-generation timeframe (i.e., 5–7 p.m.) was shown to increase community self-sufficiency during generation hours by 17% and 5–10%, respectively, to 83% and 71–76%.

Suggested Citation

  • Milad Afzalan & Farrokh Jazizadeh, 2021. "Quantification of Demand-Supply Balancing Capacity among Prosumers and Consumers: Community Self-Sufficiency Assessment for Energy Trading," Energies, MDPI, vol. 14(14), pages 1-21, July.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:14:p:4318-:d:596339
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    References listed on IDEAS

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    Cited by:

    1. Seongwoo Lee & Joonho Seon & Chanuk Kyeong & Soohyun Kim & Youngghyu Sun & Jinyoung Kim, 2021. "Novel Energy Trading System Based on Deep-Reinforcement Learning in Microgrids," Energies, MDPI, vol. 14(17), pages 1-14, September.
    2. Huangjie Gong & Dan M. Ionel, 2021. "Improving the Power Outage Resilience of Buildings with Solar PV through the Use of Battery Systems and EV Energy Storage," Energies, MDPI, vol. 14(18), pages 1-16, September.

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