Adaptive cold-load pickup considerations in 2-stage microgrid unit commitment for enhancing microgrid resilience

Hu, Rongxing; Shirsat, Ashwin; Muthukaruppan, Valliappan; Li, Yiyan; Zhang, Si; Tang, Wenyuan; Baran, Mesut; Lu, Ning

doi:10.1016/j.apenergy.2023.122424

Adaptive cold-load pickup considerations in 2-stage microgrid unit commitment for enhancing microgrid resilience

Journal Article · Sat Dec 02 23:00:00 EST 2023 · Applied Energy

DOI:https://doi.org/10.1016/j.apenergy.2023.122424· OSTI ID:2329518

Hu, Rongxing ^[1]; Shirsat, Ashwin ^[2]; Muthukaruppan, Valliappan ^[2]; Li, Yiyan ^[2]; Zhang, Si ^[2]; Tang, Wenyuan ^[2]; Baran, Mesut ^[2]; Lu, Ning ^[2]

North Carolina State University, Raleigh, NC (United States); North Carolina State University
North Carolina State University, Raleigh, NC (United States)

In an extended main grid outage spanning multiple days, load shedding serves as a critical mechanism for islanded microgrids to maintain essential power and energy reserves that are indispensable for fulfilling reliability and resiliency mandates. However, using load shedding for such purposes leads to increasing occurrence of cold load pickup (CLPU) events. Here, this study presents an innovative adaptive CLPU model that introduces a method for determining and incorporating parameters related to CLPU power and energy requirements into a two-stage microgrid unit commitment (MGUC) algorithm. In contrast to the traditional fixed-CLPU-curve approach, this model calculates CLPU duration, power, and energy demands by considering outage durations and ambient temperature variations within the MGUC process. By integrating the adaptive CLPU model into the MGUC problem formulation, it allows for the optimal allocation of energy resources throughout the entire scheduling horizon to fulfill the CLPU requirements when scheduling multiple CLPU events. The performance of the enhanced MGUC algorithm considering CLPU needs is assessed using actual load and photovoltaic (PV) data. Simulation results demonstrate significant improvements in dispatch optimality evaluated by the amount of load served, customer comfort, energy storage operation, and adherence to energy schedules. These enhancements collectively contribute to reliable and resilient microgrid operation.

View Accepted Manuscript (DOE)

Research Organization:: North Carolina State University, Raleigh, NC (United States)

Sponsoring Organization:: USDOE Office of Energy Efficiency and Renewable Energy (EERE), Renewable Power Office. Solar Energy Technologies Office

Grant/Contract Number:: EE0008770

OSTI ID:: 2329518

Alternate ID(s):: OSTI ID: 2228779

Journal Information:: Applied Energy, Journal Name: Applied Energy Vol. 356; ISSN 0306-2619

Publisher:: ElsevierCopyright Statement

Country of Publication:: United States

Language:: English

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