篇名 | 基於最小不安全性準位及彈性交流系統安裝費用之多目標最佳化輸電系統負載能力增強策略 |
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卷期 | 30 |
並列篇名 | Minimum Insecurity Levels and FACTS Installation Cost Based Multi-Objective Optimal Transmission System Loadability Enhancement Strategy |
作者 | 張亞清 |
頁次 | 019-038 |
關鍵字 | 彈性交流輸電系統 、 多目標最佳化 、 帕雷多前沿解 、 效能指標 、 系統安全性準位 、 系統 負載能力 、 FACTS 、 multi-objective optimization 、 pareto front set 、 system security level 、 system loadability |
出刊日期 | 201710 |
為使現存輸電網路在付出較低網路擴充費用下能容納更多的電力輸送量,在合適地點安裝 適當容量的靜態乏補償器 (Static VAR Compensator, SVC) 和閘控串連補償器 (Thyristor Controlled Series Compensator, TCSC) 已證實是最為可靠的選項之一。本論文所提的彈性交流輸 電系統 (Flexible AC Transmission System, FACTS) 安裝策略,首先於未安裝FACTS設備而輸電 系統運轉於其負載能力 (Loadability) 狀態下,分別使用切向量 (Tangent Vector) 及效能指標敏感 度因子,分析在哪些匯流排及線路最需安裝SVC 及TCSC,而在最小匯流排電壓安全準位、最 小線路潮流安全準位、最大輸電容量以及最小FACTS 設備安裝費用整合為一多目標函數下,此 最佳輸電負載能力增強問題即形成一多目標最佳化問題 (Multi-Objective Optimization Problem, MOP) ,並使用適應分享多目標粒子群優 (Fitness Sharing Multi-Objective Particle Swarm Optimization, MOPSO) 演算法求解一個帕雷多前沿解集合 (Pareto Front Set) ,最後,由此帕雷 多前沿解集合中,所推薦的解是其所安裝的SVC及TCSC能使電力系統維持相當的運轉安全性, 並且在最大效能指標值 (Performance Index Value) 下提供充分的系統負載能力。
In order for existing transmission networks to accommodate more power transfers with less network expansion cost, installation of static VAR compensator (SVC) and thyristor controlled series compensator (TCSC) at suitable locations with proper capacities is validated to be one of the most promising options. The FACTS installation strategy proposed in the project first applies the tangent vector and performance index (PI) sensitivity factor techniques to analyze which buses and lines are most necessary for SVC and TCSC installations respectively. And, with minimum bus voltage security level, line flow security level, maximum loadability and minimum installation cost of FACTS devices integrated as the multi-objective function, the problem to achieve the optimal transmission system loadability enhancement by determining the capacity for each SVC and TCSC installation is then formulated as a multi-objective optimization problem (MOP) and solved by using the fitness sharing multi-objective particle swarm optimization (MOPSO) method. Finally, in the Pareto front set obtained, the solution with the SVC and TCSC installations that can make the power system operate in a certain security level and provide sufficient system loadability with the biggest performance index value is recommended.