Two-Stage Robust Optimization for Large Logistics Parks to Participate in Grid Peak Shaving

Autor: Jiu Zhou, Jieni Zhang, Zhaoming Qiu, Zhiwen Yu, Qiong Cui, Xiangrui Tong
Jazyk: angličtina
Rok vydání: 2024
Předmět:
Zdroj: Symmetry, Vol 16, Iss 8, p 949 (2024)
Druh dokumentu: article
ISSN: 2073-8994
DOI: 10.3390/sym16080949
Popis: As new energy integration increases, power grid load curves become steeper. Large logistics parks, with their substantial cooling load, show great peak shaving potential. Leveraging this load while maintaining staff comfort, product quality, and operational costs is a major challenge. This paper proposes a two-stage robust optimization method for large logistics parks to participate in grid peak shaving. First, a Cooling Load’s Economic Contribution (CLEC) index is introduced, integrating the Predicted Mean Vote (PMV) and Sales Pressure Index (SPI). Then, an optimization model is established, accounting for renewable energy uncertainties and maximizing large logistics parks’ participation in peak shaving. Results illustrate that the proposed method leads to a reduction in the peak shaving pressure on the distribution network. Specifically, under the scenario tolerating the maximum potential uncertainty in renewable energy output, the absolute peak-to-valley difference and fluctuation variance of the park’s net load are decreased by 45.82% and 54.59%, respectively. Furthermore, the PMV and the SPI indexes are reduced by 39.12% and 26.36%, respectively. In comparison with the determined optimization method, despite a slight cost increase of 20.06%, the proposed method significantly reduces EDR load shedding by 98.1%.
Databáze: Directory of Open Access Journals
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