Please use this identifier to cite or link to this item:
https://hdl.handle.net/10356/171064
Title: | Distributed energy resource exploitation through co-optimization of power system and data centers with uncertainties during demand response | Authors: | Weng, Yu Liu, Yang Lim, Rachel Li Ting Nguyen, Hung D. |
Keywords: | Engineering::Electrical and electronic engineering | Issue Date: | 2023 | Source: | Weng, Y., Liu, Y., Lim, R. L. T. & Nguyen, H. D. (2023). Distributed energy resource exploitation through co-optimization of power system and data centers with uncertainties during demand response. Sustainability, 15(14), 10995-. https://dx.doi.org/10.3390/su151410995 | Project: | RG60/22 EMA-EP004-EKJGC-0003 NRF2022- ITS010-0005 |
Journal: | Sustainability | Abstract: | This paper presents a robust bi-level co-optimization model that promotes the active participation of Internet Data Centers (IDCs) in demand response (DR) programs, thereby enhancing the flexibility of power systems. Our approach involves leveraging virtual power lines to migrate workloads among IDCs, optimizing resource allocations, and benefiting both domains. The model incorporates a Gaussian Process Regression (GPR)-constructed DR price–amount curve, which largely contributes to the simplification of the optimization problem with high accuracy and computational efficiency. It also respects the information barriers between the two domains of power systems and IDCs, and thus safeguards the privacy and flexibility of IDCs. The uncertainty in IDC operations is considered by incorporating the variance in GPR into the demand response curve. By integrating IDCs as DR resources, the framework of this research enhances the flexibility of power systems and the efficiency of cross-domain co-optimization. The model and algorithm are validated using modified IEEE test systems. | URI: | https://hdl.handle.net/10356/171064 | ISSN: | 2071-1050 | DOI: | 10.3390/su151410995 | Schools: | School of Electrical and Electronic Engineering | Organisations: | Engie Lab, Singapore | Rights: | © 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/). | Fulltext Permission: | open | Fulltext Availability: | With Fulltext |
Appears in Collections: | EEE Journal Articles |
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sustainability-15-10995-v2.pdf | 2.93 MB | Adobe PDF | ![]() View/Open |
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