Two-Level Planning of ESS in AC/DC Hybrid Distribution Network Considering Flexibility

doi:10.12204/j.issn.1000-7229.2022.07.005

Abstract

Abstract:

The AC/DC hybrid distribution network has the characteristics of high flexibility and high controllability, and will be widely used in the future distribution network. A two-level planning method for energy storage in AC/DC hybrid distribution network considering flexibility is proposed in this paper. Firstly, this paper analyzes the flexibility requirements in the AC/DC hybrid distribution network and the operating characteristics of the flexible resources considered, and then establishes a quantitative calculation index to measure the flexibility in the operation of the distribution network. Then, K-means clustering algorithm is used to establish the collection of typical operation scenarios for the output and daily load of distributed power generation in distribution network. Secondly, a two-level planning model for energy storage in AC/DC hybrid distribution network is established, which takes into account flexibility. The goal is to minimize the comprehensive operation cost of the distribution network and the optimal level of system flexibility, and the genetic algorithm is used to solve the optimal planning scheme. Finally, on the basis of the improved IEEE 33-node distribution network system, the rationality and effectiveness of the two-level planning model and the optimal configuration of energy storage are verified.

Key words: AC/DC hybrid distribution network, flexibility, two-level planning, genetic algorithm, non-linear principal component analysis

CLC Number:

TM731

GONG Jianfeng, ZHOU Zongchuan, JIN Panlong, ZHANG Bin, HAN Yiming, FENG Xue. Two-Level Planning of ESS in AC/DC Hybrid Distribution Network Considering Flexibility[J]. ELECTRIC POWER CONSTRUCTION, 2022, 43(7): 48-56.

Figures/Tables 14

Fig.1 Logical relationship of the two-level planning

Fig.2 Solution flow

Fig.3 IEEE 33-bus system

Table 1 Peak and valley period and TOU electricity price

Fig.4 Convergence characteristic curve of GA

Fig.5 Relationship between weighted average radius and the number of clusters

Fig.6 Typical scenes of distributed photovoltaic output

Fig.7 Typical scenes of the load

Table 2 Probability of typical scene about distributed generation

Table 3 Probability of typical scene about load

Table 4 Optimized configuration results of ESS

Table 5

Fig.8 Flexibility in three ways

Fig.9 Flexibility in two ways

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