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研究生: 孫德宇
Sun, Stephen Deyu
論文名稱: 論智慧電網裡為了最佳發電成本問題設計的在優先順序條件約束下的排程演算法
Scheduling with Precedence Constraints for Electricity Cost in Smart Grid
指導教授: 韓永楷
Hon, Wing-Kai
劉向瑄
Liu, Hsiang-Hsuan
口試委員: 李哲榮
學位類別: 碩士
Master
系所名稱: 電機資訊學院 - 資訊系統與應用研究所
Institute of Information Systems and Applications
論文出版年: 2022
畢業學年度: 110
語文別: 英文
論文頁數: 41
中文關鍵詞: 智慧電網排程問題需量反應
外文關鍵詞: Smart Grid, Scheduling Problem, Demand response
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  • 我們研究了在智慧電網裡關於需量反應問題離線排程問題。我們假設在智慧
    電網裡,時間線被平分成等長的時段,並且有許多等長的電力請求;有一些電
    力請求有先後關係,而它們各自需要在特定時段中的某一個時段中被執行。我
    們假設一個時段的發電成本是基於那個時段的電力請求數量的某種凸函數,這
    個排程問題的目標便是試圖分配所有電力請求來實現總體發電成本最小化。
    為了解決這個排程問題,我們提出了一個演算法;此演算法可以在時間複雜
    度O(n^2*τ) 下對於這些有著先後順序的電力請求找到最佳分配方法,其中n為電
    力請求的總數量,τ為時段的總數量。


    We study an offline scheduling problem that arises in demand response management
    in smart grid. We assume in the smart grid, the time horizon is partitioned
    into unit-size time sessions, there are many unit-size power requests, some of them
    are in precedence relationship, and each of them need to be done in one time session
    in a set of specific time sessions. We assume the general electricity cost for
    each time session is a convex function of the amount of power requests assigned
    to that time session. The objective of the problem is to assign all requests with
    the minimum total electricity cost. For this problem, we introduce an algorithm
    to find the optimal assignment for these unit-size power requests with precedence
    constraints in O(n^2*τ) time, where n = the amount of the power requests, τ = the
    amount of timeslots.

    Abstract (Chinese) I Abstract II Acknowledgements (Chinese) III Contents IV List of Algorithms VI 1 Introduction 1 2 Preliminaries 3 2.1 Objective . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 2.2 Definition Of Alternative Assignment Graph . . . . . . . . . . . . . 4 2.3 Legal Path Of The Alternative Assignment Graph . . . . . . . . . . 5 2.4 A Shift Along The Legal Path Of The Alternative Assignment Graph 5 3 Our Algorithm 6 4 Correctness 8 4.1 Proof Of Invariant (I1) . . . . . . . . . . . . . . . . . . . . . . . . . 8 4.1.1 Agreement Graph . . . . . . . . . . . . . . . . . . . . . . . . 8 4.1.2 Proof of Invariant (I1) . . . . . . . . . . . . . . . . . . . . . 12 IV 4.1.2.1 Proof Of Lemma 1 . . . . . . . . . . . . . . . . . . 13 4.1.2.2 Proof Of Lemma 2 . . . . . . . . . . . . . . . . . . 13 4.1.2.3 Proof Of Lemma 3 . . . . . . . . . . . . . . . . . . 14 4.1.2.4 Proof Of Lemma 4 . . . . . . . . . . . . . . . . . . 15 4.2 Proof Of Lemma 9 and Lemma 10 . . . . . . . . . . . . . . . . . . . 16 4.2.1 Additional Notations. . . . . . . . . . . . . . . . . . . . . . . 16 4.2.2 Proof Of Lemma 5 . . . . . . . . . . . . . . . . . . . . . . . 16 4.2.3 Proof Of Lemma 6 . . . . . . . . . . . . . . . . . . . . . . . 28 4.2.4 Proof Of Lemma 7 . . . . . . . . . . . . . . . . . . . . . . . 30 4.2.5 Proof Of Lemma 8 . . . . . . . . . . . . . . . . . . . . . . . 31 4.2.6 Proof Of Lemma 9 . . . . . . . . . . . . . . . . . . . . . . . 35 4.2.7 Proof Of Lemma 10 . . . . . . . . . . . . . . . . . . . . . . . 36 4.3 Proof Of The Correctness . . . . . . . . . . . . . . . . . . . . . . . 36 5 Time Complexity 37 6 Conclusion 39 Bibliography 40

    [1] Mihai Burcea, Wing-Kai Hon, Hsiang-Hsuan Liu, Prudence W. H. Wong, and
    David K. Y. Yau. Scheduling for electricity cost in a smart grid. J. Scheduling,
    19(6):687–699, 2016.
    [2] Osama Majeed Butt, Muhammad Zulqarnain, and Tallal Majeed Butt. Recent
    advancement in smart grid technology: Future prospects in the electrical
    power network. Ain Shams Engineering Journal, 12(1):687–695, 2021.
    [3] Vincent Chau, Shengzhong Feng, and Nguyen Kim Thang. Competitive algorithms
    for demand response management in smart grid. In LATIN, pages
    303–316, 2018.
    [4] Chen Chen, K. G. Nagananda, Gang Xiong, Shalinee Kishore, and
    Lawrence V. Snyder. A communication-based appliance scheduling scheme
    for consumer-premise energy management systems. IEEE Trans. Smart Grid,
    4(1):56–65, 2013.
    [5] Xin Feng, Yinfeng Xu, and Feifeng Zheng. Online scheduling for electricity
    cost in smart grid. In COCOA, pages 783–793. Springer, 2015.
    [6] Iordanis Koutsopoulos and Leandros Tassiulas. Control and optimization
    meet the smart power grid: Scheduling of power demands for optimal energy
    management. In e-Energy, pages 41–50. ACM, 2011.
    [7] R. Krishnan. Meters of tomorrow [in my view]. IEEE Power and Energy
    Mag., 6(2):96–94, 2008.
    [8] Fu-Hong Liu, Hsiang-Hsuan Liu, and Prudence W. H. Wong. Non-preemptive
    scheduling in a smart grid model and its implications on machine minimization.
    Algorithmica, 82(12):3415–3457, 2020.
    [9] Fu-Hong Liu, Hsiang-Hsuan Liu, and Prudence W. H. Wong. Greedy is optimal
    for online restricted assignment and smart grid scheduling for unit size
    jobs. Theory Comput. Syst., 65(6):1009–1032, 2021.
    [10] Thillainathan Logenthiran, Dipti Srinivasan, and Tan Zong Shun. Demand
    side management in smart grid using heuristic optimization. IEEE Trans.
    Smart Grid, 3(3):1244–1252, 2012.
    [11] Sabita Maharjan, Quanyan Zhu, Yan Zhang, Stein Gjessing, and Tamer
    Basar. Dependable demand response management in the smart grid: A stackelberg
    game approach. IEEE Trans. Smart Grid, 4(1):120–132, 2013.
    [12] Shuva Paul, Md Sajed Rabbani, Ripon Kumar Kundu, and Sikdar Mohammad
    Raihan Zaman. A review of smart technology (smart grid) and its features.
    In 2014 1st International Conference on Non Conventional Energy
    (ICONCE 2014), pages 200–203, 2014.
    [13] Sergio Salinas, Ming Li, and Pan Li. Multi-objective optimal energy consumption
    scheduling in smart grids. IEEE Trans. Smart Grid, 4(1):341–348,
    2013.

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