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Article: Operating Cost Reduction of DC Microgrids Under Real-Time Pricing Using Adaptive Differential Evolution Algorithm
Title | Operating Cost Reduction of DC Microgrids Under Real-Time Pricing Using Adaptive Differential Evolution Algorithm |
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Authors | |
Keywords | Microgrids Fuel cells Load flow Real-time systems Voltage control |
Issue Date | 2020 |
Publisher | Institute of Electrical and Electronics Engineers: Open Access Journals. The Journal's web site is located at http://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=6287639 |
Citation | IEEE Access, 2020, v. 8, p. 169247-169258 How to Cite? |
Abstract | Virtual resistance-based droop control is widely adopted as secondary-layer control for grid-connected converters in DC microgrids. This paper presents an alternative usage of the virtual resistances to minimize the total operating cost of DC microgrids under real-time pricing. The total operating cost covers the running cost of utility grids, renewable energy sources (RES), energy storage systems (ESS), fuel cells, and power loss on the distribution lines. An adaptive Differential Evolution (ADE) algorithm is adopted in this paper to optimize the virtual resistances of the droop control for the grid-connected converters of dispatchable units, such that the power flow can be regulated. The performances of the proposed strategy are evaluated by the case studies of a 12-bus 380 V DC microgrid using Matlab and a 32-bus 380 V DC microgrid using a Real-Time Digital Simulator (RTDS). Both results validate that the ADE can significantly reduce the operating cost of DC microgrids and outperform the conventional Genetic Algorithm (GA) in terms of cost saving. Comparisons among the microgrids with different numbers of dispatchable units reveal that the cost saving is more prominent when the expansion of dispatchable units. |
Persistent Identifier | http://hdl.handle.net/10722/288074 |
ISSN | 2021 Impact Factor: 3.476 2020 SCImago Journal Rankings: 0.587 |
ISI Accession Number ID |
DC Field | Value | Language |
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dc.contributor.author | Qian, X | - |
dc.contributor.author | Yang, Y | - |
dc.contributor.author | Li, C | - |
dc.contributor.author | Tan, SC | - |
dc.date.accessioned | 2020-10-05T12:07:29Z | - |
dc.date.available | 2020-10-05T12:07:29Z | - |
dc.date.issued | 2020 | - |
dc.identifier.citation | IEEE Access, 2020, v. 8, p. 169247-169258 | - |
dc.identifier.issn | 2169-3536 | - |
dc.identifier.uri | http://hdl.handle.net/10722/288074 | - |
dc.description.abstract | Virtual resistance-based droop control is widely adopted as secondary-layer control for grid-connected converters in DC microgrids. This paper presents an alternative usage of the virtual resistances to minimize the total operating cost of DC microgrids under real-time pricing. The total operating cost covers the running cost of utility grids, renewable energy sources (RES), energy storage systems (ESS), fuel cells, and power loss on the distribution lines. An adaptive Differential Evolution (ADE) algorithm is adopted in this paper to optimize the virtual resistances of the droop control for the grid-connected converters of dispatchable units, such that the power flow can be regulated. The performances of the proposed strategy are evaluated by the case studies of a 12-bus 380 V DC microgrid using Matlab and a 32-bus 380 V DC microgrid using a Real-Time Digital Simulator (RTDS). Both results validate that the ADE can significantly reduce the operating cost of DC microgrids and outperform the conventional Genetic Algorithm (GA) in terms of cost saving. Comparisons among the microgrids with different numbers of dispatchable units reveal that the cost saving is more prominent when the expansion of dispatchable units. | - |
dc.language | eng | - |
dc.publisher | Institute of Electrical and Electronics Engineers: Open Access Journals. The Journal's web site is located at http://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=6287639 | - |
dc.relation.ispartof | IEEE Access | - |
dc.rights | IEEE Access. Copyright © Institute of Electrical and Electronics Engineers (IEEE): OAJ. | - |
dc.rights | This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License. | - |
dc.subject | Microgrids | - |
dc.subject | Fuel cells | - |
dc.subject | Load flow | - |
dc.subject | Real-time systems | - |
dc.subject | Voltage control | - |
dc.title | Operating Cost Reduction of DC Microgrids Under Real-Time Pricing Using Adaptive Differential Evolution Algorithm | - |
dc.type | Article | - |
dc.identifier.email | Qian, X: qianxy@hku.hk | - |
dc.identifier.email | Yang, Y: cacaloto@HKUCC-COM.hku.hk | - |
dc.identifier.email | Tan, SC: sctan@eee.hku.hk | - |
dc.identifier.authority | Tan, SC=rp01606 | - |
dc.description.nature | published_or_final_version | - |
dc.identifier.doi | 10.1109/ACCESS.2020.3024112 | - |
dc.identifier.scopus | eid_2-s2.0-85101350502 | - |
dc.identifier.hkuros | 315128 | - |
dc.identifier.volume | 8 | - |
dc.identifier.spage | 169247 | - |
dc.identifier.epage | 169258 | - |
dc.identifier.isi | WOS:000572979000001 | - |
dc.publisher.place | United States | - |
dc.identifier.issnl | 2169-3536 | - |