As the world moves toward the ambitious “carbon peak and carbon neutrality” goals, the installed capacity of new energy power generation, especially wind power and photovoltaic (PV) power, has been increasing year by year. However, due to local climate conditions and the inherent intermittency of renewable resources, the output power of new energy power generation systems can experience rapid ramps or abrupt drops. These fluctuations pose significant challenges to the frequency regulation margin of the power system. Moreover, because of the unique output power characteristics and complex grid-connected impedance properties of renewable energy systems, large-scale centralized or distributed grid integration may induce frequency oscillations, leading to stability issues and threatening the security of power supply for loads. By integrating an energy storage battery system, the peak load and valley filling of the power system can be effectively realized, alleviating the peak-shaving pressure of thermal power units. Furthermore, using an energy storage battery as a primary frequency regulation resource can balance load fluctuations and keep the system frequency within an acceptable range.
Numerous studies have been conducted on energy storage systems across the globe. Some have introduced the prospects and advantages of energy storage systems, while others have analyzed the cost and benefit of generation-side and demand-side storage systems. Research has also focused on the control and management of storage systems to improve their stability. In addition, design studies have been carried out for supporting storage systems in PV-energy storage integrated projects and offshore wind projects, which relieve peak-shaving pressure and increase energy efficiency. Further studies have investigated the optimization and configuration of hybrid storage solutions, exploring complementary flexibility resources across different segments of the new power system. In order to better mitigate the impact of renewable energy integration on power system stability, this paper presents a first-person analysis of the application and functions of an energy storage battery in a grid-connected new energy power generation system. A case study of a PV-energy storage integrated microgrid project is also analyzed to evaluate the economic feasibility of the energy storage battery.
1. Role of the Energy Storage Battery in Grid-Connected New Energy Power Generation Systems
In this section, I focus on a new energy power generation system that includes both wind and PV power. I analyze the multiple roles that an energy storage battery can play in such a grid-connected system.
1.1 Peak Shaving and Valley Filling
Renewable energy generation often exhibits strong fluctuations over the course of a day and tends to be anti-peaking relative to the load curve. This means that when renewable energy is integrated into the grid, the demand for both upward and downward reserve capacity of the power system increases. In the evening peak period, typically from 19:00 to 22:00, PV generation produces no electrical power. Wind power, on the other hand, may generate full output at the time of the lowest daily load, often around midnight. As a result, a certain percentage of curtailed solar and wind energy occurs each year due to limited transmission capacity. In this context, an energy storage battery can store the excess electrical energy generated by wind power during the lowest load periods and release it during the evening peak hours. This effectively shifts electrical energy over time, maximizes the utilization of transmission lines to match the load consumption profile, and reduces the need for thermal power units to provide upward and downward regulation capacity. The energy storage battery thereby achieves the goal of peak shaving and valley filling.
By configuring an energy storage battery in a new energy power generation system, the equivalent load, defined as the sum of the daily load and the renewable generation output, can be effectively limited within the allowable maximum and minimum effective power boundaries of renewable energy grid integration. This avoids curtailment of renewable energy and shedding of load, improves the system’s ability to accommodate renewable energy, reduces the demand for reserve capacity, and enhances the overall operational efficiency of the power system.
1.2 Stabilizing the Power System
The short-term rate of change in the output power of a new energy power generation system must satisfy the stability requirements of the power system. Table 1 shows the current limits on active power variations for grid-connected new energy power generation systems in many grid codes.
| Installed capacity of new energy power generation system / MW | Maximum limit of active power variation in 10 min / MW | Maximum limit of active power variation in 1 min / MW |
|---|---|---|
| < 30 | 10 | 3 |
| 30 – 150 | 10 – 50 | 3 – 15 |
| > 150 | 50 | 15 |
Smoothing the fluctuation of renewable energy grid integration means using the energy storage battery to control the storage and release of renewable electrical energy, suppressing minute-level active power fluctuations. The total active power \(P\) is the sum of the energy storage battery output \(P_{\mathrm{BES}}\) and the new energy generation output \(P_{\mathrm{NE}}\). The fluctuation of \(P\) must satisfy the limits given in Table 1.
The active power control algorithms of the energy storage battery mainly include the point-by-point limit method and the low-pass filtering method.
When the point-by-point limit method is adopted, the output active power of the energy storage battery at time \(j\), denoted as \(P_{\mathrm{BES}}(j)\), must be constrained as follows:
$$
\max\left(\Delta P_{10}(j) – P_{y,10}, \; \Delta P_{1}(j) – P_{y,1}\right) < P_{\mathrm{BES}}(j) < \min\left(\Delta P_{10}(j) – P_{y,10}, \; \Delta P_{1}(j) – P_{y,1}\right)
$$
where \(\Delta P_{10}(j)\) is the change in the output active power of the energy storage battery between time \(j\) and the past 10 minutes; \(P_{y,10}\) is the maximum allowable fluctuating power of the energy storage battery within 10 minutes; \(\Delta P_{1}(j)\) is the change in the output active power between time \(j\) and the past 1 minute; and \(P_{y,1}\) is the maximum allowable fluctuating power within 1 minute.
The low-pass filtering method applies amplitude processing to the input signal through a low-pass filter, making the output signal smoother. With this method, the output active power of the energy storage battery at time \(j\) is expressed as:
$$
P_{\mathrm{BES}}(j) = \frac{\tau}{t} \left[ \sum P(j) – \sum P(j-1) \right]
$$
where \(\tau\) is the time constant, \(t\) is the control period, and \(\sum P(j)\) and \(\sum P(j-1)\) are the total active power outputs of the energy storage battery and the new energy generation system at times \(j\) and \(j-1\), respectively.
The time constant \(\tau\) is also related to the cutoff frequency \(f_c\) of the low-pass filter:
$$
\tau = \frac{1}{2\pi f_c}
$$
1.3 Primary Frequency Regulation
Primary frequency regulation is mainly intended to respond to short-term rapid load fluctuations in the power system. When the system frequency exceeds a certain limit, the generating units autonomously provide active power support or absorb active power from the grid. The primary frequency regulation requirements vary for different types of generation sources. For example, the dead band of primary frequency regulation for thermal power units is required to be 50 ± 0.033 Hz, for hydro power plants 50 ± 0.05 Hz, for PV generation 50 ± 0.06 Hz, and for wind power 50 ± 0.10 Hz.
Primary frequency regulation using an energy storage battery refers to the ability of the storage system to adjust its output or absorbed active power in real time according to the instantaneous frequency deviation of the power system. This allows rapid response to load fluctuations and maintains frequency stability. This frequency regulation method has the advantages of fast response speed and high regulation accuracy, making it an important means for ensuring stable power system operation. Compared with thermal power units, an energy storage battery can respond much faster to frequency changes. It can undertake primary frequency regulation either independently or together with new energy generation. According to relevant power system assessment rules, equipping a new energy power plant with an energy storage battery enables the plant to fulfill or improve its performance in peak shaving and primary frequency regulation. For a 300 MW thermal power unit, the primary frequency regulation limit is 8% of the rated capacity, i.e., 24 MW. The load adjustment of thermal power units for primary frequency regulation is 160 MW per Hz. A frequency deviation of 0.033 to 0.183 Hz corresponds to a regulation power of 0 to 24 MW. Each time the frequency exceeds the dead band, the output power of the thermal unit is adjusted by ±0.2% of rated power, which is ±600 kW. According to these technical requirements, if the primary frequency regulation task is independently handled by an energy storage battery, the single charge/discharge duration of the battery is only about 10 seconds. Since the probabilities of upper and lower frequency excursions are roughly equal, it is reasonable to configure an energy storage battery of 600 kW/0.5 h. If a reasonable state of charge (SOC) management strategy is also applied, the daily charge/discharge cycles may be relatively frequent, but the battery operates in a shallow charge/discharge manner around 50% SOC, ensuring a long service life.
In order to further reduce the required capacity of the energy storage battery and keep it within a suitable SOC range, a double-boundary improved smoothing control algorithm can be adopted. Through frequent but small adjustments, the SOC of the battery is optimized during operation, thus reducing the total capacity demand on the energy storage battery.
2. Application Case Study
2.1 Project Description and Main Equipment
I now present a concrete case study of a PV-energy storage integrated microgrid project. The project consists of a PV generation system with an installed capacity of 800 kW, a lithium iron phosphate (LiFePO4) energy storage battery system with a rated power of 250 kW and a storable energy of 500 kWh, and the user loads. The highest voltage level of the LiFePO4 energy storage battery system is 10 kV. When the PV power generated exceeds the local consumption, the surplus electric energy is stored in the LiFePO4 energy storage battery system and is later discharged to the grid during peak demand hours. The main equipment list of this project is given in Table 2.
| Equipment | Model / specification | Quantity |
|---|---|---|
| PV module | 550 W monocrystalline silicon | 1455 pieces |
| Inverter | Rated power 33 kW | 22 units |
| LiFePO4 battery cell | 3.2 V / 130 Ah | 1224 pieces |
| Power conversion system (PCS) | Rated power 250 kW | 1 unit |
| 10 kV step-up transformer | 10 kV / 0.4 kV, 800 kVA | 1 unit |
2.2 Main Operational Functions of the Microgrid
2.2.1 Black Start of the Energy Storage Battery
The microgrid stores the surplus PV electrical energy in the LiFePO4 energy storage battery system to prepare for emergencies. When the utility grid loses power, the point of common coupling is disconnected. The LiFePO4 energy storage battery system realizes a “black start”, meaning that the storage system and the PV system supply power to the loads without relying on the utility grid.
2.2.2 Voltage-Current Double Closed-Loop Operation Mode
The output of the LiFePO4 energy storage battery system uses two bus sections. When multiple battery strings under one bus section operate in the voltage-current double closed-loop mode, the other bus section operates under the microgrid grid-connected control strategy. In the voltage-current double closed-loop operation mode, the charge and discharge of the energy storage battery can be precisely controlled, ensuring both operational stability and charge/discharge efficiency, thereby maintaining the DC bus voltage balance.
2.2.3 Energy Management System (EMS)
The energy management system guarantees the efficient, stable, safe, and reliable operation of the microgrid and the optimal utilization of the PV generation system. Its functions include data and status monitoring, equipment management and system fault protection, information storage and recording, distribution network automation, intelligent metering, intelligent power consumption, video and environment monitoring, and comprehensive energy management.
2.3 Revenue Estimation of the Energy Storage Battery
The LiFePO4 energy storage battery system in this microgrid mainly operates in an economic mode to achieve peak shaving and valley filling. Specifically, the battery is charged from the grid during the valley load period and discharges to supply power to the grid during the daytime peak load period.
When the peak-valley electricity price difference at the project location is 0.7 yuan/kWh, and the depth of discharge of the LiFePO4 energy storage battery is 90%, the annual revenue of the energy storage battery can be calculated as:
$$
\text{Annual revenue} = 0.7 \times 500 \times 0.9 \times 365 \approx 11.5 \text{ ten thousand yuan}
$$
In addition, with the integration of the energy storage battery, the required power rating of the box-type transformer is reduced, thereby saving the purchase cost of the box transformer as well as saving electricity expenses. The annual revenue is summarized in Table 3.
| Parameter | Value |
|---|---|
| Peak-valley electricity price difference (yuan/kWh) | 0.7 |
| Rated capacity (kWh) | 500 |
| Depth of discharge (%) | 90 |
| Operating days per year | 365 |
| Annual revenue (ten thousand yuan) | ≈11.5 |
3. Discussion
Assisting grid-connected new energy power generation systems is one of the most important application fields of energy storage batteries. The functions of peak shaving and valley filling, together with primary frequency regulation, enable the existing power system to fully utilize its ability to accommodate renewable energy. This is of great significance for reducing the reserved capacity of thermal power units and mitigating renewable energy curtailment. With the improvement of minute-level prediction accuracy of renewable generation output and the application of energy storage batteries, the planning and dispatchability of renewable energy grid integration have also been strengthened. At the same time, the friendliness of renewable energy integration has increased, and the occupation of fast frequency regulation resources of the power system has been reduced.
However, under the current business model, applying these functions of the energy storage battery alone is generally not economically attractive. Moreover, the economic benefit of the energy storage battery may decrease seasonally because the electricity price difference and the load patterns vary throughout the year. Therefore, further exploring the roles of the energy storage battery in grid-connected new energy power generation systems, or improving the seasonal performance of the energy storage battery, will become new research directions.
4. Conclusion
In this work, I analyzed the application and functions of an energy storage battery in grid-connected new energy power generation systems. A PV-energy storage integrated microgrid project was selected as a case study to investigate the economic performance of the energy storage battery. The analysis results show that in a grid-connected new energy power generation system, the energy storage battery mainly plays three important roles: peak shaving and valley filling, power system stabilization, and primary frequency regulation. Based on the peak-valley electricity price difference at the project location, the energy storage battery operating in the economic peak-shaving mode can achieve an annual revenue of about 115,000 yuan. In addition to saving electricity costs, the integration of the energy storage battery can also save the purchase cost of the box-type transformer. It can be concluded that the application of the energy storage battery not only improves the operational reliability and stability of the power system, but also provides certain economic benefits.
From a personal perspective, I believe that the energy storage battery will play an increasingly central role in future power systems dominated by renewables. The rapid response capability of the energy storage battery makes it an ideal complement to the uncertain and variable output of wind and PV generation. As technology advances and costs decline, the economic viability of the energy storage battery will continue to improve. The primary frequency regulation function of the energy storage battery is particularly valuable because it can react within milliseconds, whereas conventional thermal units require seconds to minutes to respond. This characteristic makes the energy storage battery indispensable for maintaining frequency stability in grids with a high share of inverter-based resources.
The case study presented here demonstrates that even with a relatively modest storage capacity of 500 kWh, a meaningful annual revenue can be realized through peak-valley arbitrage. If the energy storage battery is also allowed to participate in the ancillary service market for frequency regulation, the revenue stream could be substantially higher. Many grid operators are now introducing fast frequency response market products that are specifically designed for energy storage batteries. In such markets, an energy storage battery can earn capacity payments as well as utilization payments, further improving project economics.
Nevertheless, there are still challenges to overcome. The degradation of the energy storage battery over time, the round-trip efficiency losses, and the thermal management requirements all affect the actual available capacity and lifespan. A proper battery management system is essential to monitor the state of charge, state of health, and temperature of each cell. Furthermore, the control algorithms discussed in this paper, such as the point-by-point limit method and low-pass filtering method, must be tuned carefully to balance smoothing performance and battery wear. An optimized SOC management strategy can prevent over-charge and over-discharge, thus extending cycle life while maintaining sufficient reserve for frequency regulation.
I also note that the integration of an energy storage battery in a microgrid requires coordinated control among the PV inverters, the power conversion system, and the EMS. The EMS should be able to forecast the PV output and load demand, and then schedule the energy storage battery accordingly. Real-time state estimation and fast communication are crucial for reliable operation. The black start capability of the energy storage battery, as described in the case study, is another valuable feature that enhances the resilience of the microgrid during grid outages.
In terms of future research, I expect that hybrid storage systems combining an energy storage battery with supercapacitors or flywheels will gain more attention. The energy storage battery provides long-duration energy shifing, while supercapacitors provide instantaneous high-power response. Such a hybrid configuration can reduce the stress on the energy storage battery during frequent frequency regulation events and extend its operational lifetime. Additionally, the use of artificial intelligence and machine learning for predictive control of the energy storage battery is a promising direction. By accurately predicting the renewable generation and load patterns, the energy storage battery can be dispatched more efficiently, maximizing economic benefits while maintaining system security.
Finally, it is essential to update the regulatory and market frameworks to fully unlock the value of the energy storage battery. Current market rules in many regions were designed for conventional generators and do not properly recognize the unique capabilities of storage, such as its fast ramping and bidirectional operation. New market products and remuneration mechanisms should be introduced to reward the flexibility and resilience services provided by the energy storage battery. With supportive policies and technological innovation, the energy storage battery will be a cornerstone of the clean, reliable, and affordable power system of the future.
To summarize, my analysis from the case study and the broader discussion leads to the following key points:
- An energy storage battery is essential for peak shaving and valley filling in grid-connected new energy power generation systems, as it shifts renewable energy from low-demand periods to high-demand periods.
- The energy storage battery effectively smooths the active power fluctuations of new energy generation, allowing the combined output to meet grid code limits.
- The energy storage battery provides fast and accurate primary frequency regulation, reducing the burden on thermal power units and improving frequency stability.
- In the presented microgrid project, a 250 kW/500 kWh LiFePO4 energy storage battery yields an annual revenue of approximately 115,000 yuan under a peak-valley price difference of 0.7 yuan/kWh, with a 90% depth of discharge.
- The integration of the energy storage battery also reduces the required transformer capacity, leading to additional capital cost savings.
- Despite current economic limitations, the energy storage battery offers multiple value streams that can be unlocked through appropriate market design and advanced control strategies.
In conclusion, the energy storage battery is not just a backup device but an active and intelligent component that enhances the reliability, stability, and economy of grid-connected new energy power generation systems. As the transition to renewable energy accelerates, the role of the energy storage battery will become even more critical. I am confident that with continuous improvements in battery chemistry, power electronics, and system-level optimization, the energy storage battery will enable a more sustainable and resilient energy future.