English  |  正體中文  |  简体中文  |  Items with full text/Total items : 72887/72887 (100%)
Visitors : 23215749      Online Users : 585
RC Version 7.0 © Powered By DSPACE, MIT. Enhanced by NTU Library IR team.
Scope Tips:
  • please add "double quotation mark" for query phrases to get precise results
  • please goto advance search for comprehansive author search
  • Adv. Search
    HomeLoginUploadHelpAboutAdminister Goto mobile version

    Please use this identifier to cite or link to this item: http://ir.lib.ncu.edu.tw/handle/987654321/1044

    Title: 應用隨機規劃探討溫室氣體排放限制下之電力系統容量擴增計畫;A study of Power System Capacity Expansion and Location under Limitation of Greenhouse Gas Emission - Applying Stochastic Programming Approach
    Authors: 賴靜煜;Ching-Yu Lai
    Contributors: 土木工程研究所
    Keywords: 電力系統;區位選擇;分解法;情境分析;隨機規劃;穩健性規劃;decomposing method;power system;stochastic programming
    Date: 2006-09-15
    Issue Date: 2009-09-18 17:18:45 (UTC+8)
    Publisher: 國立中央大學圖書館
    Abstract: 能源是國家發展的基石,穩定的電力供給牽動國家的命脈,在滿足逐年成長的電力需求之虞,尋求最低的開發、營運成本是我們的目標。然而石化燃料價格上揚、電力供給與需求的不確定,及京都議定書限制各國二氧化碳的排放量,促使我們轉換能源型態,在面對許多隨機的外在因素下,本篇介紹Mulvey…等(Operation Research 43(2) (1995a) 264-281)提出的穩健規劃,構建電源開發穩健規劃雛型,以隨機規劃為基礎,分析不同情境與範疇下的能源決策。電源的開發計劃需考慮什麼時候(When)、在何處(Where)、什麼程度的規模(How many)以及何種種類(What kind of)的發電設備,在固定和變動成本的考量下,估算供電的最佳效益。電力系統規劃的研究相當多,如Malcolm (1994)、Albornoz (2004)、Nagurney (2004)…等,從不同的角度切入探討不確定的因素和均衡的機制。本研究以台灣地區為範疇,假設火力發電、風力發電及核能發電為未來裝置容量開發重點,決策者面臨了發電成本、再生能源電力供給及未來區域負載的不確定性,我們利用情境分析設定環境參數,找出新增發電機組較佳之區位選擇與配置,新增容量盡量達到區域負載平衡減少輸電損失。以二階段隨機規劃求出最小成本(固定成本、生產成本、輸電成本),並運用分解法及最佳切割(optimality cut)的概念作為求解演算法,藉由C語言和CPLEX運用撰寫程式,以範例測試驗證正確性,我們透過資料收集做實例測試與敏感度分析,探討關鍵議題做出結論。 Energy is the foundation of country development, and it is also important to supply electric power constantly. The goal is to satisfy the growing power demand of each year under lowest constructing cost and operation cost. There are lots of research in power planning, such as Malcolm (1994)、Albornoz (2004)、Nagurney (2004), they discuss it form different viewpoint in uncertainty approach or network equilibrium approach. In addition, facing the raising price of fossil fuels, the uncertainty of power demand and supply in future, and international limitation of Greenhouse Gas emission by Kyoto Protocol; it prompt us to transfer the structure of power system from high-polluted form to low-polluted form. In order to deal with so many external uncertainty factors, this thesis introduce robust optimization which was proposed by Mulvey in 1995, to propose the power expansion model. By simplified it, which became a two-staged stochastic programming model, based on it we analyze in different scenario and field to obtain a policy. While we perform a plan of development electric power plant, there are some factors need to be considered, such as when, where, how many, and what kind of electric generator. We assume that thermal power, wind power, and unclear power will still be installed to increase electric capacity in the future. Decision maker have to deal with the uncertainty of producing cost, green power supply, and regional electric load in future. We using scenario analysis to present environment parameters and obtain best strategic decision, finding out appropriate capacity and location to be installed, reaching regional load balance which will decrease the losing of power. The resultant model is solved numerically by the application of the L-shaped method, whose implementation and development were executed using the software AMPL, with CPLEX as a solver. The small example will verify model’s validity, at last the stuy will discuss key issue by design some examples, through data collecting and sensitivity analyzing; we make the conclusion according to the result.
    Appears in Collections:[土木工程研究所] 博碩士論文

    Files in This Item:

    File SizeFormat

    All items in NCUIR are protected by copyright, with all rights reserved.

    社群 sharing

    ::: Copyright National Central University. | 國立中央大學圖書館版權所有 | 收藏本站 | 設為首頁 | 最佳瀏覽畫面: 1024*768 | 建站日期:8-24-2009 :::
    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library IR team Copyright ©   - Feedback  - 隱私權政策聲明