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http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/60978完整後設資料紀錄
| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 逄愛君 | |
| dc.contributor.author | Che-Wei Pai | en |
| dc.contributor.author | 白哲瑋 | zh_TW |
| dc.date.accessioned | 2021-06-16T10:39:32Z | - |
| dc.date.available | 2015-08-23 | |
| dc.date.copyright | 2013-08-23 | |
| dc.date.issued | 2013 | |
| dc.date.submitted | 2013-08-13 | |
| dc.identifier.citation | [1] U. D. of Energy, “”the smart grid: An introduction”,” 2009.
[2] A. Vojdani, “”smart integration”,” Power and Energy Magazine, IEEE, vol. 6, no. 6, pp. 71–79, 2008. [3] P. Samadi, A. Mohsenian-Rad, R. Schober, V. Wong, and J. Jatskevich, “”optimal real-time pricing algorithm based on utility maximization for smart grid”,” 2010 IEEE First International Conference on SmartGridComm, pp. 415– 420, 2010. [4] C. Joe-Wong, S. S., S. Ha, and M. Chiang, “”optimized day-ahead pricing for smart grids with device-specific scheduling flexibility”,” IEEE Journal on Selected Areas in Communications, vol. 30, no. 6, pp. 1075–1085, 2012. [5] I. E. A. D. S. M. Programme, “”integration of demand side management, distributed generation, renewable energy sources and energy storages”,” 2008. [6] A. Kossoy and P. Guigon, “”state and trends of the carbon market 2012”,” The World Bank, Washington, DC, 2012. [7] S. Boyd and L. Vandenberghe, “”convex optimization”,” Cambridge University Press, 2004. [8] A. Mohsenian-Rad, V. Wong, J. Jatskevich, R. Schober, and A. Leon-Garcia, “”autonomous demand-side management based on game-theoretic energy consumption scheduling for the future smart grid”,” IEEE Transactions on Smart Grid, pp. 320–331, 2010. [9] P. Samadi, H. Mohsenian-Rad, R. Schober, and V. Wong, “”advanced demand side management for the future smart grid using mechanism design”,” IEEE Transactions on Smart Grid, pp. 1170–1180, 2012. [10] N. Li, L. Chen, and S. Low, “”optimal demand response based on utility maximization in power networks”,” in IEEE Power and Energy Society General Meeting, 2011. [11] Y. Yamamoto, “”pricing electricity from residential photovoltaic systems: A comparison of feed-in tariffs, net metering, and net purchase and sale”,” Solar Energy, pp. 2678 – 2685, 2012. [12] P. Yang, P. Chavali, and A. Nehorai, “”parallel autonomous optimization of demand response with renewable distributed generators”,” in 2012 IEEE Third International Conference on SmartGridComm, 2012, pp. 55–60. [13] I. Atzeni, L. Ordonez, G. Scutari, D. Palomar, and J. Fonollosa, “”demandside management via distributed energy generation and storage optimization”,” IEEE Transactions on Smart Grid, pp. 866–876, 2013. [14] T. Couture and Y. Gagnon, “An analysis of feed-in tariff remuneration models: Implications for renewable energy investment,” Energy Policy, pp. 955 – 965, 2010. [15] M. Fahrioglu and F. Alvarado, “”using utility information to calibrate customer demand management behavior models”,” IEEE Transactions on Power Systems, vol. 16, no. 2, pp. 317–322, 2001. [16] X. L. B. Stephen and M. Almir, “”subgradient methods”,” Stanford University, Autumn, 2003. [17] A. de Miguel and J. Bilbao, “”test reference year generation from meteorological and simulated solar radiation data ”,” Solar Energy, pp. 695 – 703, 2005. [18] R. Huang, T. Huang, R. Gadh, and N. Li, “”solar generation prediction using the arma model in a laboratory-level micro-grid”,” in 2012 IEEE Third International Conference on SmartGridComm, 2012. [19] I. Ontario, “”market data”,” http://www.ieso.ca/imoweb/marketdata/ marketData.asp, Sep. 2011. [20] H. Nguyen, J. song, and Z. Han, “”demand side management to reduce peakto- average ratio using game theory in smart grid”,” in 2012 IEEE Conference on INFOCOM WKSHPS, 2012, pp. 91–96. | |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/60978 | - |
| dc.description.abstract | 基於最近先進的電力系統技術以及無線通訊技術的發展, 智慧電網的概念開始
逐漸蓬勃發展, 到了現在使用者已經有能力可以在家中裝設再生能源發電的裝置 和儲存電力的設備。另一方面, 由於環境的考量, 電力公司也積極利用再生能源發 電來替代傳統發電的能源。其中一種有效的方法就是電力公司提供一個有吸引力 的買電價來激勵使用者生產更多的再生能源並將自己的再生能源賣回去給電力公 司。跟之前的研究不同的是, 我們考慮一種結合再生能源的買回價格的動態電價方 法。我們將整個電價問題利用凹性最佳化數學模型來解決, 並且提出一個日前動態 計價方法並利用分散式演算法來處理我們的問題, 這樣一來我們可以同時兼顧使 用者的隱私以及整體系統的彈性。我們的目標就是希望可以將整體利益最大化並 且同時對使用者和電力公司都可以帶來利益。同時以我們有限的知識所知,我們 是最早考慮到結合環境利益的研究。實驗的結果也顯示我們的方法確實可以有效 的降低尖峰時刻電力的負擔和平衡整體電力系統的供電曲線。 | zh_TW |
| dc.description.abstract | Thanks to the recent advance on power engineering and wireless communications,
the smart grid technology has emerged and users are now capable of deploying renewable energy generators and storage devices at their homes. On the other side, due to the rise of environmental consciousness, electric companies are eager to replace traditional generators with renewable energy. One of the most efficient ways is to provide an electricity buyback scheme for electric companies to encourage users to generate more renewable energy at their homes. Different from the previous works, we consider dynamic pricing with renewable energy buyback as our target scenario. We formulate the dynamic pricing problem as a convex optimization dual problem and propose a day-ahead time-dependent pricing scheme in a distributed manner which provides more privacy to users. The goal of our developed framework is to achieve the maximum benefits for both users and electric companies. To the best of our knowledge, this is one of the very first works to tackle the timedependent problem with taking the environmental benefit of renewable energy into consideration for smart grid. The numerical results show that our framework can significantly reduce the peak time loading and efficiently balance the system energy provision. | en |
| dc.description.provenance | Made available in DSpace on 2021-06-16T10:39:32Z (GMT). No. of bitstreams: 1 ntu-102-R00944006-1.pdf: 2058093 bytes, checksum: 95284207a69b127f2e7d8c950fdc9aac (MD5) Previous issue date: 2013 | en |
| dc.description.tableofcontents | 口試委員會審定書i
誌謝ii 摘要iii Abstract iv Contents vi List of Figures vii List of Tables viii 1 Introduction 1 2 Related Work 4 3 System Model 6 3.1 Customers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 3.1.1 Utility function . . . . . . . . . . . . . . . . . . . . . . . . . . 8 3.1.2 Energy storage cost function . . . . . . . . . . . . . . . . . . . 8 3.1.3 Renewable energy cost function . . . . . . . . . . . . . . . . . 9 3.2 Electric company . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 3.2.1 Cost function . . . . . . . . . . . . . . . . . . . . . . . . . . . 10 3.2.2 Carbon emission trading function . . . . . . . . . . . . . . . . 10 4 Day-Ahead Pricing Framework 12 4.1 Optimization Problem Formulation . . . . . . . . . . . . . . . . . . . 12 4.2 Lagrangian Dual Decomposition . . . . . . . . . . . . . . . . . . . . . 14 4.3 Distributed Day-Ahead Pricing Algorithms . . . . . . . . . . . . . . . 18 5 Performance Evaluation 22 5.1 Simulation Setup . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22 5.2 Comparison of different scenarios . . . . . . . . . . . . . . . . . . . . 24 5.3 Comparison of different pricing schemes . . . . . . . . . . . . . . . . 26 5.3.1 Flat Selling with Flat Buyback pricing (FSFB) . . . . . . . . 26 5.3.2 Dynamic Selling with Flat Buyback pricing (DSFB) . . . . . . 26 5.3.3 Our approach, Dynamic Selling with Dynamic Buyback pricing (DSDB) . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26 v 6 Conclusion 29 Bibliography 32 | |
| dc.language.iso | en | |
| dc.subject | 智慧電網 | zh_TW |
| dc.subject | 動態計價 | zh_TW |
| dc.subject | 再生能源 | zh_TW |
| dc.subject | 凹性最佳化 | zh_TW |
| dc.subject | 碳交易 | zh_TW |
| dc.subject | renewable energy | en |
| dc.subject | convex optimization | en |
| dc.subject | carbon emission trading | en |
| dc.subject | day-ahead pricing | en |
| dc.subject | Smart grid | en |
| dc.title | 智慧電網結合再生能源之動態計價方法 | zh_TW |
| dc.title | Optimal Day-Ahead Pricing with Renewable Energy in Smart Grid | en |
| dc.type | Thesis | |
| dc.date.schoolyear | 101-2 | |
| dc.description.degree | 碩士 | |
| dc.contributor.oralexamcommittee | 馮輝文,蔡孟勳,楊舜仁 | |
| dc.subject.keyword | 智慧電網,動態計價,再生能源,凹性最佳化,碳交易, | zh_TW |
| dc.subject.keyword | Smart grid,day-ahead pricing,renewable energy,convex optimization,carbon emission trading, | en |
| dc.relation.page | 32 | |
| dc.rights.note | 有償授權 | |
| dc.date.accepted | 2013-08-13 | |
| dc.contributor.author-college | 電機資訊學院 | zh_TW |
| dc.contributor.author-dept | 資訊網路與多媒體研究所 | zh_TW |
| 顯示於系所單位: | 資訊網路與多媒體研究所 | |
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