Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | 홍승호 | - |
dc.date.accessioned | 2020-01-14T06:46:50Z | - |
dc.date.available | 2020-01-14T06:46:50Z | - |
dc.date.issued | 2019-04 | - |
dc.identifier.citation | APPLIED ENERGY, v. 239, Page. 549-559 | en_US |
dc.identifier.issn | 0306-2619 | - |
dc.identifier.issn | 1872-9118 | - |
dc.identifier.uri | https://www.sciencedirect.com/science/article/pii/S0306261919301850 | - |
dc.identifier.uri | https://repository.hanyang.ac.kr/handle/20.500.11754/121822 | - |
dc.description.abstract | Given the increasing prevalence of smart grids, the introduction of demand-side participation and distributed energy resources (DERs) has great potential for eliminating peak loads, if incorporated within a single framework such as a virtual power plant (VPP). In this paper, we develop a data mining-driven incentive-based demand response (DM-IDR) scheme to model electricity trading between a VPP and its participants, which induces load curtailment of consumers by offering them incentives and also makes maximum utilization of DERs. As different consumers exhibit different attitudes toward incentives, it is both essential and practical to provide flexible incentive rate strategies (IRSs) for consumers, thus respecting their unique requirements. To this end, our DM-IDR scheme first employs data mining techniques (e.g., clustering and classification) to divide consumers into different categories by their bid-offers. Next, from the perspective of VPP, the proposed scheme is formulated as an optimization problem to minimize VPP operation costs as well as guarantee consumer's interests. The experimental results demonstrate that through offering different IRSs to categorized consumers, the DM-IDR scheme induces more load reductions; this mitigates critical load, further decreases VPP operation costs and improves consumer profits. | en_US |
dc.description.sponsorship | This work was partially supported by the technology innovation program in establishment of infrastructure for microgrid international standardization, funded by the Ministry of Trade, Industry & Energy, Republic of Korea (No. 70300038), partly supported by the Human Resources Development of the Korea Institute of Energy Technology Evaluation and Planning (KETEP) grant funded by the Korea government Ministry of Knowledge Economy (No. 20174030201780), and partially supported under the framework of international cooperation program (Korea-China) managed by National Research Foundation of Korea (NRF-2018K1A3A1A61026320). | en_US |
dc.language.iso | en_US | en_US |
dc.publisher | ELSEVIER SCI LTD | en_US |
dc.subject | Virtual power plant | en_US |
dc.subject | Data mining | en_US |
dc.subject | Incentive-based demand response | en_US |
dc.subject | Incentive rate strategy | en_US |
dc.title | A data mining-driven incentive-based demand response scheme for a virtual power plant | en_US |
dc.type | Article | en_US |
dc.relation.volume | 239 | - |
dc.identifier.doi | 10.1016/j.apenergy.2019.01.142 | - |
dc.relation.page | 549-559 | - |
dc.relation.journal | APPLIED ENERGY | - |
dc.contributor.googleauthor | Luo, Zhe | - |
dc.contributor.googleauthor | Hong, SeungHo | - |
dc.contributor.googleauthor | Ding, YueMin | - |
dc.relation.code | 2019000806 | - |
dc.sector.campus | E | - |
dc.sector.daehak | COLLEGE OF ENGINEERING SCIENCES[E] | - |
dc.sector.department | DIVISION OF ELECTRICAL ENGINEERING | - |
dc.identifier.pid | shhong | - |
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.