Frequency regulation reserve allocation method for integrated thermal and energy storage systems considering the marginal substitution

doi:10.19799/j.cnki.2095-4239.2024.1090

Abstract

Abstract:

Energy storage systems and thermal power plants working together to handle frequency regulation in power systems are increasingly becoming standard practice in modern grid operations. Optimizing the coordinated use of thermal power and energy storage resources for frequency regulation is crucial for ensuring the safe and cost-effective operation of modern power systems. This paper proposes a method for allocating frequency regulation reserve capacities between thermal power plants and energy storage systems using marginal rate of substitution (MRS) analysis. First, a frequency response model is established a power system where thermal power and energy storage collaboratively perform frequency regulation. Using the root mean square error of the area control error (ACE) as an evaluation index for frequency regulation, an allocation method is developed based on MRS analysis. This method evaluates the frequency regulation reserves of thermal power and energy storage, leveraging the Gaussian process regression algorithm to reduce computational complexity during configuration. A multisegment fitting approach is used to generate the marginal substitution curve, capturing the effectiveness of thermal-storage frequency regulation. Furthermore, the method considers the different prices of frequency regulation reserves for thermal power and energy storage. It optimizes the allocation of these reserve capacities with the objective of minimizing overall costs. The proposed method is validated through a real-world case study examining daily load fluctuations.

Key words: frequency control, optimal operation, marginal substitution, automatic generation control (AGC)

CLC Number:

TM 76

Jiangzhe WEI, Maolong SHU, Yanqiao CHEN, Lulu ZHAO, Xinkai SU, Muyang LIU. Frequency regulation reserve allocation method for integrated thermal and energy storage systems considering the marginal substitution[J]. Energy Storage Science and Technology, 2025, 14(5): 2117-2129.

Figures/Tables 16

Fig. 1

Fig. 2

Fig. 3

Fig. 4

Fig. 5

Table 1

Parameters of simulation system model"

项目	模型仿真参数	数值
火电机组	有功下垂系数 $R G$	0.5
	发电机调速器时间常数 $T G$	0.08 s
	汽轮机时间常数 $T M$	0.3 s

储能系统	爬坡时间常数 $T b$	0.01 s

等效系统	等效惯性常数M	10 MVA.s/MW
等效系统	阻尼系数 $D$	1.0 N/m

控制系统	频率偏差系数 $β$	21.0 MW/Hz
	PI控制器比例控制参数 $K P$	0.822
	PI控制器积分控制参数 $K I$	0.16

Table 1

Fig. 6

Fig. 7

Fig. 8

Fig. 9

Fig. 10

Table 2

Fitting accuracy"

拟合方法		RMSE
指数拟合	$ω = 1$	3.38607
指数拟合	$ω = 2$	1.39663
二次多项式拟合		6.70638
三次多项式拟合		2.87712
分段多项式拟合		0.03250

Table 2

Fig. 11

Fig. 12

Fig. 13

Table 3

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场景	配置指标	火电/储能容量/MW	总成本占比
场景1	ACE_RMSE=74.84	125/0	100%
场景2	MRS_POWER=1	64.53/43.68	71.28%
场景3	ACE_RMSE=74.84	65.70/40.85	70.94%

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