Power Generation Technology ›› 2024, Vol. 45 ›› Issue (4): 716-733.DOI: 10.12096/j.2096-4528.pgt.23083
• Smart Grid • Previous Articles Next Articles
Bai XIAO1, Xuechun ZHAO1, Guangde DONG2
Received:
2023-09-22
Revised:
2023-11-25
Published:
2024-08-31
Online:
2024-08-27
Supported by:
CLC Number:
Bai XIAO, Xuechun ZHAO, Guangde DONG. Summary and Prospect of Comprehensive Evaluation Methods of Power Quality[J]. Power Generation Technology, 2024, 45(4): 716-733.
赋权方法 | 优点 | 缺点 |
---|---|---|
主观赋权法 | 简洁实用、所需定量数据少、实用性强 | 主观随意性大、赋权结果不够客观 |
客观赋权法 | 有效减小主观因素对评估结果的影响 | 实用性和可参与性差,计算方法复杂 |
组合赋权法 | 同时反映主客观信息、信息损失最少 | 难以确定主客观的权重分配问题 |
Tab. 1 Comparison of three weighting methods
赋权方法 | 优点 | 缺点 |
---|---|---|
主观赋权法 | 简洁实用、所需定量数据少、实用性强 | 主观随意性大、赋权结果不够客观 |
客观赋权法 | 有效减小主观因素对评估结果的影响 | 实用性和可参与性差,计算方法复杂 |
组合赋权法 | 同时反映主客观信息、信息损失最少 | 难以确定主客观的权重分配问题 |
评估方法 | 优点 | 缺点 |
---|---|---|
基于数学理论 | 原理清晰、计算相对 简单 | 各种数学方法有其固有缺陷 |
基于决策理论 | 有效减小主观因素对评估结果的影响 | 计算过程相对复杂,计算量大 |
基于智能算法 | 模型更新速度快、自适应能力强 | 模型的物理意义不够明确,建模过程需要大量训练样本 |
动态评估建模方法 | 提供更全面的参考信息 | 方法和模型都较复杂 |
Tab. 2 Comparison of four assessment modeling methods
评估方法 | 优点 | 缺点 |
---|---|---|
基于数学理论 | 原理清晰、计算相对 简单 | 各种数学方法有其固有缺陷 |
基于决策理论 | 有效减小主观因素对评估结果的影响 | 计算过程相对复杂,计算量大 |
基于智能算法 | 模型更新速度快、自适应能力强 | 模型的物理意义不够明确,建模过程需要大量训练样本 |
动态评估建模方法 | 提供更全面的参考信息 | 方法和模型都较复杂 |
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