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Combined hybrid energy storage system and transmission grid model for peak shaving based on time series operation simulation

2023-06-02

【论文推荐】西南交通大学廖凯等：基于时序运行模拟的混合储能和输电网联合调峰模型

摘要

本研究提出了混合储能系统（HESS）和输电网（TG）的联合模型，并建立了相应的时序运行模拟（TSOS）模型，以缓解可再生能源接入下的电力系统的调峰压力。首先，建立了线性的HESS运行模型，模型考虑了抽水蓄能系统、电化学储能系统和新型液体压缩空气储能系统的不同功率-效率特性。其次，建立了用于调峰的TSOS模型，以最大化从风电场和HESS进入电网的能量。基于所提模型，本研究考虑了TG的传输能力，通过添加TG的潮流约束，建立了基于TSOS的HESS和TG联合调峰模型。最后，以改进后的IEEE-39和IEEE-118节点系统为算例，验证了模型的有效性和可行性。

Combined hybrid energy storage system and transmission grid model for peak shaving based on time series operation simulation

基于时序运行模拟的混合储能和输电网联合调峰模型

Mingkui Wei¹, Yiyu Wen¹, Qiu Meng², Shunwei Zheng², Yuyang Luo², Kai Liao²

(1.Southwest Branch of State Grid Corporation of China, No. 299 Shuxiu West Road, Chengdu 610000, P. R. China

2.School of Electrical Engineering, Southwest Jiaotong University, No. 999 Xi’an Road, Chengdu 610000, P. R. China)

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Combined hybrid energy storage system and transmission grid model for peak shaving based on time series operation simulation

Abstract

This study proposes a combined hybrid energy storage system (HESS) and transmission grid (TG) model, and a corresponding time series operation simulation (TSOS) model is established to relieve the peak-shaving pressure of power systems under the integration of renewable energy. First, a linear model for the optimal operation of the HESS is established, which considers the different power-efficiency characteristics of the pumped storage system, electrochemical storage system, and a new type of liquid compressed air energy storage. Second, a TSOS simulation model for peak shaving is built to maximize the power entering the grid from the wind farms and HESS. Based on the proposed model, this study considers the transmission capacity of a TG. By adding the power-flow constraints of the TG, a TSOS-based HESS and TG combination model for peak shaving is established. Finally, the improved IEEE-39 and IEEE-118 bus systems were considered as examples to verify the effectiveness and feasibility of the proposed model.

Keywords

Peak shaving; Hybrid energy storage system; Combined energy storage and transmission grid model; Time series operation simulation.

Fig.1 Piecewise linearization of P-E curve of LCAES

Fig.2 Linearization process of P-E curve

Fig.3 Piecewise linearization of P-E curve of PSS

Fig.4 Piecewise linearization of P-E curve of ESS

Fig.5 Schematic diagram of peak shaving of HESS

Fig.6 Flow chart of the TSOS model

Fig.7 IEEE 39 bus system

Fig.8 Net load curve of scenarios 1‒4

Fig.9 MPV,MPVR,APRV,APRVR for scenarios 1‒4

Fig.10 Output of HESS in 24 h

Fig.11 System net load after peak shaving in Scenario 1 and Scenario 5

Fig.12 Node voltage and branch active power in scenario 1 and scenario 5

Fig.13 System power balance

Fig.14 Voltage amplitude of nodes and active power of branches within 24 h

本文引文信息

Wei MK, Wen YY, Qiu M, et al (2023) Combined hybrid energy storage system and transmission grid model for peak shaving based on time series operation simulation. Global Energy Interconnection, 6(2): 154-165

魏明奎，文一宇，孟秋等 (2023) 基于时序运行模拟的混合储能和输电网联合调峰模型. 全球能源互联网（英文）, 6(2): 154-165

Biographies

Mingkui Wei

Mingkui Wei received the B.S. degree at North China Electric Power University, Beijing, China. He is currently working in State Grid Corporation of China. His research interests include power system planning and power system operation analysis.

Yiyu Wen

Yiyu Wen received the master degree at Chongqing University, Chongqing, China. He is currently working in State Grid Corporation of China. His research interests include power system planning and power system operation analysis.

Qiu Meng

Qiu Meng is currently working towards the master degree in Southwest Jiaotong University, Chengdu, China. His research interests include renewable energy power system planning and operation.

Shunwei Zheng

Shunwei Zheng is currently working towards the Ph.D. degree in Southwest Jiaotong University, Chengdu, China. His current research interests include renewable energy integration, and power system operation optimization.

Yuyang Luo

Yuyang Luo is currently working towards the master degree in Southwest Jiaotong University, Chengdu, China. His research interests include renewable energy power system planning and scheduling, and power system operation optimization.

Kai Liao

Kai Liao received the Ph.D degree at Southwest Jiaotong University in 2016, Chengdu, China. He is currently an Associate Professor in the School of Electrical Engineering with Southwest Jiaotong University, Chengdu, China. His research interests include wind power system control, and power system stability.

编辑：刘通明

审核：王伟

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