Table of Contents
Fetching ...

Typical Scenarios Generation Method Considering System-level Characteristics of Power System

Tao Li, Chen Shen

Abstract

This paper proposes a method for generating typical scenarios based on system-level macroscopic characteristics of power system and considering its stability properties. First, considering uncertainties such as renewable energy generation in power-electronics-dominated power systems, multidimensional scaling is used to construct an electrical coordinate system. Based on this, system-level characteristics of the distribution of physical quantities, such as power generation and load, are characterized. Furthermore, a method for generating typical scenarios based on the system's system-level characteristics and stability properties is proposed. For the obtained joint probability distribution of system-level characteristics, weighted Mahalanobis distance can be used to predict the stability properties of random scenarios. Finally, the typicality and representativeness of the scenarios generated by the proposed method with respect to stability properties are verified on the CSEE benchmark case, and stability prediction for random scenarios is achieved using a probabilistic testing method.

Typical Scenarios Generation Method Considering System-level Characteristics of Power System

Abstract

This paper proposes a method for generating typical scenarios based on system-level macroscopic characteristics of power system and considering its stability properties. First, considering uncertainties such as renewable energy generation in power-electronics-dominated power systems, multidimensional scaling is used to construct an electrical coordinate system. Based on this, system-level characteristics of the distribution of physical quantities, such as power generation and load, are characterized. Furthermore, a method for generating typical scenarios based on the system's system-level characteristics and stability properties is proposed. For the obtained joint probability distribution of system-level characteristics, weighted Mahalanobis distance can be used to predict the stability properties of random scenarios. Finally, the typicality and representativeness of the scenarios generated by the proposed method with respect to stability properties are verified on the CSEE benchmark case, and stability prediction for random scenarios is achieved using a probabilistic testing method.

Paper Structure

This paper contains 21 sections, 16 equations, 10 figures, 3 tables.

Figures (10)

  • Figure 1: Eigenvalue spectrum of the benchmark case
  • Figure 2: Pearson correlation–spatial dimension relationship
  • Figure 3: Correlation between system-level characteristics and system stability
  • Figure 4: Flowchart of typical scenario generation
  • Figure 5: Topology of the CSEE benchmark
  • ...and 5 more figures

Theorems & Definitions (1)

  • Definition 1