計及風險系數的含風電場電力系統多目標動態優化調度

文獻標志碼：A

計及風險系數的含風電場電力系統多目標動態優化調度

李晨1，胡志堅1，董驥2，仉夢林1

(1.武漢大學電氣工程學院，湖北武漢430072；2.宜昌供電公司，湖北宜昌443000)

Multi-objective Dynamic Dispatching of Power Grid with Wind Farms by Considering Risk Index LI Chen1, HU Zhijian1, DONG Ji2, ZHANG Menglin1

(1.School of Electrical Engineering, Wuhan University, Wuhan 430072,China;

2.Yichang Power Supply Company, Yichang 443000, China)

摘要：隨著風電并網容量的不斷增加，傳統的確定性優化調度方法已難以滿足電力系統安全運行要求。本文建立了計及風險系數的含風電場電力系統多目標動態優化調度模型，模型包括風險系數、燃料成本及污染排放量最小3個目標，將風電場出力及負荷的不確定性納入模型綜合考慮。為了對模型中的隨機變量進行處理，引入概率性序列理論，并對其運算空間進行擴展,然后提出了一種改進的多目標教與學優化算法對模型進行求解。含風電場的10機系統算例驗證了本文模型及算法的可行性和有效性。

關鍵詞：多目標動態優化調度；風險系數；概率性序列理論；教與學算法；帕累托最優解

文章編號：1007-2322(2015)05-0056-10

中圖分類號：TM731

基金項目：高等學校博士學科點專項科研

收稿日期：2014-08-28

作者簡介：

Abstract：With the increasing of wind capacity integrated into grid, the traditional deterministic optimization method can hardly meet the requirements for the safe operation of the power system. A multi-objective dynamic dispatch model for power grid with wind farms is presented by considering risk index, which includes such three objectives as minimum fuel cost, minimum emissions and minimum risk index, and also takes the uncertainty of load and the power output of wind farms into consideration. To deal with random variables in this model, probabilistic sequence theory is introduced and its operational space is extended. Then, an improved multi-objective teaching-learning-based optimization (IMOTLBO) algorithm is proposed to solve the model. In the end, the validity and effectiveness of proposed model and algorithm are verified through a 10-gnerators test system with wind farms.

Keywords：multi-objective dynamic dispatch; risk index; probabilistic sequence theory; teaching-learning based optimization; pareto optimal solution

0引言

隨著能源危機和環境污染的日益嚴重，風能的開發和利用已受到各國的高度重視。然而風能的隨機性和波動性使得大規模風電場并網下的電力系統運行中不確定因素增多[1]。國內外對于含風電場電力系統調度模型方面做了大量研究。

確定性建模方法[2-6]通過將風電出力預測值的一定百分比作為附加的旋轉備用需求，來達到保障系統安全可靠運行的目的。但確定性分析方法所得結果容易造成旋轉備用不足或浪費，無法使電力系統的經濟性最優。……