Distributed energy resource exploitation through co-optimization of power system and data centers with uncertainties during demand response
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 IDC...
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sg-ntu-dr.10356-1710642023-10-13T15:41:00Z Distributed energy resource exploitation through co-optimization of power system and data centers with uncertainties during demand response Weng, Yu Liu, Yang Lim, Rachel Li Ting Nguyen, Hung D. School of Electrical and Electronic Engineering Engie Lab, Singapore Engineering::Electrical and electronic engineering Bilevel Optimization Demand Response 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. Energy Market Authority (EMA) Ministry of Education (MOE) Nanyang Technological University National Research Foundation (NRF) Published version This research is supported by NTU SUG, MOE AcRF TIER 1 RG60/22, EMA & NRF EMA-EP004-EKJGC-0003, NRF DERMS for Energy Grid 2.0, and Intra-CREATE Seed Fund NRF2022-ITS010-0005. 2023-10-11T02:04:59Z 2023-10-11T02:04:59Z 2023 Journal Article 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 2071-1050 https://hdl.handle.net/10356/171064 10.3390/su151410995 2-s2.0-85166217999 14 15 10995 en RG60/22 EMA-EP004-EKJGC-0003 NRF2022- ITS010-0005 Sustainability © 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/). application/pdf |
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Engineering::Electrical and electronic engineering Bilevel Optimization Demand Response Weng, Yu Liu, Yang Lim, Rachel Li Ting Nguyen, Hung D. Distributed energy resource exploitation through co-optimization of power system and data centers with uncertainties during demand response |
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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. |
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School of Electrical and Electronic Engineering |
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School of Electrical and Electronic Engineering Weng, Yu Liu, Yang Lim, Rachel Li Ting Nguyen, Hung D. |
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Article |
author |
Weng, Yu Liu, Yang Lim, Rachel Li Ting Nguyen, Hung D. |
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Weng, Yu |
title |
Distributed energy resource exploitation through co-optimization of power system and data centers with uncertainties during demand response |
title_short |
Distributed energy resource exploitation through co-optimization of power system and data centers with uncertainties during demand response |
title_full |
Distributed energy resource exploitation through co-optimization of power system and data centers with uncertainties during demand response |
title_fullStr |
Distributed energy resource exploitation through co-optimization of power system and data centers with uncertainties during demand response |
title_full_unstemmed |
Distributed energy resource exploitation through co-optimization of power system and data centers with uncertainties during demand response |
title_sort |
distributed energy resource exploitation through co-optimization of power system and data centers with uncertainties during demand response |
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2023 |
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https://hdl.handle.net/10356/171064 |
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1781793812654325760 |