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Intelligent Resource Scheduling in Green Smart Grid Considering Uncertainties
https://ipsj.ixsq.nii.ac.jp/records/100824
https://ipsj.ixsq.nii.ac.jp/records/1008240bf85315-4deb-49bd-a27f-c4433627e9de
| 名前 / ファイル | ライセンス | アクション |
|---|---|---|
IPSJ-JNL5504007 (418.6 kB)
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Copyright (c) 2014 by the Information Processing Society of Japan
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| オープンアクセス | ||
| Item type | Journal(1) | |||||||||
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| 公開日 | 2014-04-15 | |||||||||
| タイトル | ||||||||||
| タイトル | Intelligent Resource Scheduling in Green Smart Grid Considering Uncertainties | |||||||||
| タイトル | ||||||||||
| 言語 | en | |||||||||
| タイトル | Intelligent Resource Scheduling in Green Smart Grid Considering Uncertainties | |||||||||
| 言語 | ||||||||||
| 言語 | eng | |||||||||
| キーワード | ||||||||||
| 主題Scheme | Other | |||||||||
| 主題 | [特集：Multiagent-based Societal Systems(特選論文)] smart grid, agent based system, quantum algorithm, unit commitment, renewables, PHEV | |||||||||
| 資源タイプ | ||||||||||
| 資源タイプ識別子 | http://purl.org/coar/resource_type/c_6501 | |||||||||
| 資源タイプ | journal article | |||||||||
| 著者所属 | ||||||||||
| Computer Science and Engineering, Nagoya Institute of Technology | ||||||||||
| 著者所属 | ||||||||||
| Computer Science and Engineering, Nagoya Institute of Technology | ||||||||||
| 著者所属(英) | ||||||||||
| en | ||||||||||
| Computer Science and Engineering, Nagoya Institute of Technology | ||||||||||
| 著者所属(英) | ||||||||||
| en | ||||||||||
| Computer Science and Engineering, Nagoya Institute of Technology | ||||||||||
| 著者名 |
Shantanu, Chakraborty
× Shantanu, Chakraborty
× Takayuki, Ito
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| 著者名(英) |
Shantanu, Chakraborty
× Shantanu, Chakraborty
× Takayuki, Ito
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| 論文抄録 | ||||||||||
| 内容記述タイプ | Other | |||||||||
| 内容記述 | This paper presents an intelligent economic operation on smart grid environment facilitating an advanced quantum evolutionary method. The proposed method models the wind generation (WG) and the photovoltaic generation (PV) as renewable power generation sources as measures of global warming effect. Thermal generators (TGs) are included in this model to provide the maximum amount of energy to meet consumers' demand. On the other hand, plug-in hybrid electric vehicles (PHEV) are capable of reducing CO2 and gradually becoming an integral part of a smart-grid infrastructure. Such an integration introduces uncertainties into the system that are addressed by a fuzzy agent (FA). The demanded load, the wind speed, the solar radiation and a number of involved PHEVs are taken as fuzzy parameters to resolve uncertainties. An optimizer agent (OA), based on intelligent quantum inspired evolutionary algorithm, is deployed to carry out the economic scheduling operation concerning scheduling and dispatching with the help of FA. OA features intelligent operators such as a sophisticated rotation operator, a differential operator, etc. The method is tested on a hypothetical power system with 10 thermal units, an equivalent number of PHEVs, an equivalent solar and wind farm. The simulation results will show the effectiveness of OA-FA that provides an excellent operational resource scheduling while reducing the production cost and emission. ------------------------------ This is a preprint of an article intended for publication Journal of Information Processing(JIP). This preprint should not be cited. This article should be cited as: Journal of Information Processing Vol.22(2014) No.2 (online) DOI http://dx.doi.org/10.2197/ipsjjip.22.219 ------------------------------ |
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| 論文抄録(英) | ||||||||||
| 内容記述タイプ | Other | |||||||||
| 内容記述 | This paper presents an intelligent economic operation on smart grid environment facilitating an advanced quantum evolutionary method. The proposed method models the wind generation (WG) and the photovoltaic generation (PV) as renewable power generation sources as measures of global warming effect. Thermal generators (TGs) are included in this model to provide the maximum amount of energy to meet consumers' demand. On the other hand, plug-in hybrid electric vehicles (PHEV) are capable of reducing CO2 and gradually becoming an integral part of a smart-grid infrastructure. Such an integration introduces uncertainties into the system that are addressed by a fuzzy agent (FA). The demanded load, the wind speed, the solar radiation and a number of involved PHEVs are taken as fuzzy parameters to resolve uncertainties. An optimizer agent (OA), based on intelligent quantum inspired evolutionary algorithm, is deployed to carry out the economic scheduling operation concerning scheduling and dispatching with the help of FA. OA features intelligent operators such as a sophisticated rotation operator, a differential operator, etc. The method is tested on a hypothetical power system with 10 thermal units, an equivalent number of PHEVs, an equivalent solar and wind farm. The simulation results will show the effectiveness of OA-FA that provides an excellent operational resource scheduling while reducing the production cost and emission. ------------------------------ This is a preprint of an article intended for publication Journal of Information Processing(JIP). This preprint should not be cited. This article should be cited as: Journal of Information Processing Vol.22(2014) No.2 (online) DOI http://dx.doi.org/10.2197/ipsjjip.22.219 ------------------------------ |
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| 書誌レコードID | ||||||||||
| 収録物識別子タイプ | NCID | |||||||||
| 収録物識別子 | AN00116647 | |||||||||
| 書誌情報 |
情報処理学会論文誌 巻 55, 号 4, 発行日 2014-04-15 |
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| ISSN | ||||||||||
| 収録物識別子タイプ | ISSN | |||||||||
| 収録物識別子 | 1882-7764 | |||||||||
