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Power system security boundary visualization using intelligent techniques.

機譯：使用智能技術(shù)的電力系統(tǒng)安全邊界可視化。

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In the open access environment, one of the challenges for utilities is that typical operating conditions tend to be much closer to security boundaries. Consequently, security levels for the transmission network must be accurately assessed and easily identified on-line by system operators.;Security assessment through boundary visualization provides the operator with knowledge of system security levels in terms of easily monitorable pre-contingency operating parameters. The traditional boundary visualization approach results in a two-dimensional graph called a nomogram. However, an intensive labor involvement, inaccurate boundary representation, and little flexibility in integrating with the energy management system greatly restrict use of nomograms under competitive utility environment. Motivated by the new operating environment and based on the traditional nomogram development procedure, an automatic security boundary visualization methodology has been developed using neural networks with feature selection. This methodology provides a new security assessment tool for power system operations.;The main steps for this methodology include data generation, feature selection, neural network training, and boundary visualization. In data generation, a systematic approach to data generation has been developed to generate high quality data. Several data analysis techniques have been used to analyze the data before neural network training. In feature selection, genetic algorithm based methods have been used to select the most predicative precontingency operating parameters. Following neural network training, a confidence interval calculation method to measure the neural network output reliability has been derived. Sensitivity analysis of the neural network output with respect to input parameters has also been derived. In boundary visualization, a composite security boundary visualization algorithm has been proposed to present accurate boundaries in two dimensional diagrams to operators for any type of security problem.;This methodology has been applied to thermal overload, voltage instability problems for a sample system.
機譯：在開放訪問環(huán)境中，公用事業(yè)面臨的挑戰(zhàn)之一是典型的工作條件往往更接近于安全邊界。因此，傳輸網(wǎng)絡(luò)的安全級別必須由系統(tǒng)操作員進行準確的評估，并易于在線識別。通過邊界可視化進行的安全評估為操作員提供了系統(tǒng)安全級別方面的知識，包括易于監(jiān)控的應(yīng)急前操作參數(shù)。傳統(tǒng)的邊界可視化方法會產(chǎn)生一個稱為諾模圖的二維圖形。但是，勞動密集型，邊界表示不準確以及與能源管理系統(tǒng)集成的靈活性差，極大地限制了在競爭性公用事業(yè)環(huán)境下使用列線圖。受新的操作環(huán)境的啟發(fā)，并基于傳統(tǒng)的列線圖開發(fā)程序，使用具有特征選擇功能的神經(jīng)網(wǎng)絡(luò)開發(fā)了一種自動安全邊界可視化方法。該方法論為電力系統(tǒng)的運行提供了一種新的安全評估工具。該方法論的主要步驟包括數(shù)據(jù)生成，特征選擇，神經(jīng)網(wǎng)絡(luò)訓(xùn)練和邊界可視化。在數(shù)據(jù)生成中，已經(jīng)開發(fā)了一種系統(tǒng)的數(shù)據(jù)生成方法來生成高質(zhì)量數(shù)據(jù)。在神經(jīng)網(wǎng)絡(luò)訓(xùn)練之前，已經(jīng)使用了幾種數(shù)據(jù)分析技術(shù)來分析數(shù)據(jù)。在特征選擇中，基于遺傳算法的方法已被用于選擇最有預(yù)測力的預(yù)應(yīng)急操作參數(shù)。經(jīng)過神經(jīng)網(wǎng)絡(luò)訓(xùn)練，得出了一種測量神經(jīng)網(wǎng)絡(luò)輸出可靠性的置信區(qū)間計算方法。還得出了神經(jīng)網(wǎng)絡(luò)輸出相對于輸入?yún)?shù)的敏感性分析。在邊界可視化中，提出了一種復(fù)合安全邊界可視化算法，可針對任何類型的安全問題在二維圖中為操作員提供準確的邊界。該方法已應(yīng)用于示例系統(tǒng)的熱過載，電壓不穩(wěn)定問題。

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  • 作者

    Zhou, Guozhong.;

  • 作者單位

    Iowa State University.;

  • 授予單位 Iowa State University.;
  • 學(xué)科 Engineering Electronics and Electrical.;Artificial Intelligence.
  • 學(xué)位 Ph.D.
  • 年度 1998
  • 頁碼 132 p.
  • 總頁數(shù) 132
  • 原文格式 PDF
  • 正文語種 eng
  • 中圖分類
  • 關(guān)鍵詞

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