Optimal design for power system dynamic stabilizer by grey prediction PID control

[[abstract]]In this paper, we proposed an effective method to design the power system stabilizers (PSS). The design of a PSS can be formulated as an optimal linear regulator control problem; however, implementing this technique requires the design of estimators. This increases the implementation and reduces the reliability of control system. Therefore, favor a control scheme that uses only some desired state variables, such as torque angle and speed. To deal with this problem, we use the optimal reduced models to reduce the power system model into two state variables system by each generator and use grey prediction PID control to find control signal of each generator. Moreover, we will apply genetic algorithms (GAs) to find the appropriate parameter values for the desired system. Finally, the advantages of the proposed method are illustrated by numerical simulation of the two machines-infinite-bus power systems.[[conferencetype]]國際[[conferencedate]]20021211~20021214[[booktype]]紙本[[iscallforpapers]]Y[[conferencelocation]]Bangkok, Thailan

An optimal design for power system stabilizer by variable structure dynamic grey prediction controller

[[abstract]]This paper proposed a new approach to design the power system stablizers (PSS) by utilizing the fuzzy theory, genetic algorithms and grey system theory. The design of a PSS can be formulated as an optimal linear regulator control problem; however, implementing this technique requires the design of estimators. This increases the implementation and reduces the reliability of the control system. Therefore, a favor control scheme that uses only some desired state variables; such as torque angle and speed will be used. To deal with this problem, we use the optimal reduced models to reduce the power system model into two state variables system for each generator and use the variable structure dynamic grey prediction controller to find the control signal of each generator. The grey predictor is adopted to make the next-step prediction for the output states of the power system, the fuzzy system is built to produce an appropriate forecasting step and the GA is used to choose the appropriate parameters of the fuzzy system. Finally, the advantages of the proposed method are illustrated by numerical simulation of the two machines-infinite-bus power systems.[[sponsorship]]交通大學; 中國模糊學會; 國科會工程處工程科技推展中心[[notice]]補正完畢[[conferencetype]]國內[[conferencedate]]20021205~20021206[[conferencelocation]]新北市, 臺

[[alternative]]Variable Structure Dynamic Grey Predicition Controller Design

[[abstract]]灰色理論已經普遍的應用於各種工業領域上，然而對於預測步距的選取都是由嘗試錯誤法來獲得最佳的預測步距值。本文結合灰色理論以及模糊理論兩者的優點去設計一個可變結構動態灰預測控制器，可變結構動態灰預測控制器對預測步距做動態調整，可以改善傳統灰預測控制器的預測步距為固定值的缺點，使系統能達到良好的動態響應。在本文的最後，我們會將所提出的設計方式應用於雙機無限匯流排電力系統上，模擬此結果並舉出其優點。[[abstract]]Grey theorem has been applied to various industrial processes, however it is prediction step is usually obtained by trial and error. In this paper we combine the advantages of the grey prediction theory and fuzzy theory to design a variable structure dynamic grey prediction controller. The variable structure dynamic grey prediction controller can dynamically adjusting the prediction step and improve the drawback of the conventional grey prediction controller with the fixed prediction step size and the system exhibits good dynamic response. Finally, the advantages of the proposed method are illustrated by numerical simulation of the two machines-infinite-bus power systems.[[sponsorship]]遠東技術學院; 中華民國灰色系統學會[[notice]]補正完畢[[conferencetype]]國內[[conferencedate]]20021025~20021025[[booktype]]紙本[[iscallforpapers]]Y[[conferencelocation]]臺南縣, 臺

Power system dynamic stabilizer design using grey prediction fuzzy PID controller

[[abstract]]本文提出利用灰預測型模糊PID控制器來設計電力系統穩定器（PSS）。電力系統穩定器可利用最佳線性調整來設計，但利用此方法會造成設計上的耗費及減少可靠度。因此，我們提出只利用需要的狀態變數之控制設計，如角頻率及轉矩角。為了解決這些設計上的問題，我們使用最佳降階法將每部發電機降階成兩狀態變數矩陣，再利用模糊系統調整PID控制尋找得每部發電機的控制信號，其中，灰色預測器是採用系統的輸出當做下一時刻的輸入來進行預測。在本文的最後並會應用此方法於雙機無限匯流排，模擬此結果並舉出其優點。[[abstract]]This paper proposed a new approach to design the power system stabilizers (PSS) by utilizing the fuzzy PID with grey system theory. The design of a PSS can be formulated as an optimal linear regulator control problem; however, implementing this technique requires the design of estimators. This increases the implementation and reduces the reliability of the control system. Therefore, a favor control scheme that uses only some desired state variables; such as torque angle and speed will be used. To deal with this problem, we use the optimal reduced models to reduce the power system model into two state variables system for each generator and use the fuzzy PID control to find the control signal of each generator. The grey predictor is adopted to make the next-step prediction for the output states of the power system. Finally, the advantages of the proposed method are illustrated by numerical simulation of the two machines-infinite-bus power systems.[[sponsorship]]中原大學; 國科會; 成功大學[[notice]]補正完畢[[conferencetype]]國內[[conferencedate]]20021214~20021215[[booktype]]紙本[[conferencelocation]]桃園縣, 臺