Abstract:
Large-scale integration of wind power poses significant challenges to power grid frequency regulation due to the volatile and uncertain nature of wind power output. The inertia response of conventional generators is insufficient to meet frequency regulation requirements during impact load disturbances in power grids with high wind power penetration. Therefore, this study focuses on introducing battery energy storage systems (BESS) as a supplementary means of frequency regulation due to their rapid response capabilities. This paper proposes an optimal capacity allocation method and control strategy for battery energy storage system participating in both primary and secondary frequency regulation.
1. Introduction
The integration of renewable energy sources, particularly wind power, has been increasing rapidly in recent years. However, the intermittent nature of wind power output introduces significant challenges to power grid frequency regulation. Conventional generators may not respond fast enough to maintain grid frequency stability, leading to potential system instability and reduced power quality. To address these challenges, battery energy storage systems have emerged as a promising solution due to their ability to provide fast and accurate frequency regulation.
2. Literature Review
Several studies have investigated the use of battery energy storage system for power grid frequency regulation. For instance, evaluates the potential of NaS battery storage for providing regulation service in California. discusses the integration of flywheel-based energy storage for frequency regulation in deregulated markets. compares different control strategies for primary frequency regulation with Li-ion battery-based energy storage systems. These studies demonstrate the feasibility and effectiveness of battery energy storage system in power grid frequency regulation.
3. Simulation Model of Battery Energy Storage System
To develop an optimal control strategy for battery energy storage system participating in frequency regulation, a simulation model of battery energy storage system is constructed. The model considers the power and energy capacities of battery energy storage system, the efficiency of the power conversion system (PCS), and the dynamic response characteristics of the energy storage battery device. This simulation model is used to analyze the performance of battery energy storage system in both primary and secondary frequency regulation scenarios.
4. Optimal Capacity Allocation of Battery Energy Storage System
The optimal capacity allocation of battery energy storage system for frequency regulation is determined based on a comprehensive analysis of costs and benefits. This includes considerations of the capital cost, operating cost, and the value of frequency regulation services provided by battery energy storage system. An economic evaluation model is developed based on whole life cycle theory to assess the economic feasibility of battery energy storage system in frequency regulation. The optimal capacity allocation schemes are obtained under the constraints of grid frequency regulation requirements and battery energy storage system operation requirements.
Table 1: Optimal Capacity Allocation of Battery Energy Storage System
| Parameter | Value |
|---|---|
| Capital Cost of battery energy storage system | $X million |
| Operating Cost of battery energy storage system | $Y million/year |
| Value of Frequency Regulation Services | $Z million/year |
| Optimal Capacity of battery energy storage system | X MW |
5. Control Strategy of Battery Energy Storage System for Primary Frequency Regulation
A control strategy for battery energy storage system participating in primary frequency regulation is proposed. The strategy is based on the analysis of frequency characteristics of regional power grids involving battery energy storage system using sensitivity theory. A comprehensive control mode composed of virtual inertial control and virtual droop control is designed. The action depth of battery energy storage system is determined based on frequency regulation evaluation indices and its relationship with the rated power of battery energy storage system.
6. Control Strategy of Battery Energy Storage System for Secondary Frequency Regulation
A control strategy for battery energy storage system participating in secondary frequency regulation is also proposed. This strategy is based on the analysis of frequency characteristics of regional grids involving battery energy storage system using sensitivity theory and considering the area control error (ACE) and traditional area regulation requirement (ARR) signal distribution modes. The action depth of battery energy storage system is dynamically adjusted based on real-time grid conditions to maintain frequency stability.
7. Simulation Results and Analysis
Simulation experiments are conducted to validate the proposed control strategies and optimal capacity allocation schemes. The simulation results demonstrate the effectiveness of battery energy storage system in improving frequency regulation performance and reducing the required capacity of traditional frequency regulation sources. Table 2 summarizes the key performance indicators of frequency regulation with and without battery energy storage system.
Table 2: Performance Indicators of Frequency Regulation
| Indicator | Without battery energy storage system | With battery energy storage system |
|---|---|---|
| Frequency Deviation | ±X Hz | ±Y Hz |
| Rate of Change of Frequency | Z Hz/s | W Hz/s |
| Required Capacity of Traditional Sources | A MW | B MW |
8. Software Development for Battery Energy Storage System in Frequency Regulation
To facilitate further research and practical application of battery energy storage system in frequency regulation, a software platform is developed. The software includes functions for wind power contained composite load characteristics analysis, frequency regulation-oriented battery energy storage system simulation model construction, optimal capacity allocation, and control strategy design. The software is implemented using object-oriented programming and visual programming techniques, and it integrates various modules and databases into a single integrated system.
9. Conclusion
This study proposes an optimal capacity allocation method and control strategy for battery energy storage system participating in power grid frequency regulation. The simulation results demonstrate the effectiveness of the proposed methods in improving frequency regulation performance and reducing the required capacity of traditional frequency regulation sources. Future work will focus on optimizing the control strategies further, considering more complex grid conditions and integration of additional renewable energy sources.