With the escalating global demand for clean energy and the pressing need for environmental protection, solar energy, as a renewable and clean resource, has garnered significant attention. Silicon tandem photovoltaic (PV) modules, known for their high photoelectric conversion efficiency, represent a pivotal technological direction in solar energy utilization. Concurrently, the battery energy storage system (BESS), particularly lithium-based systems, plays a crucial role in electrical energy storage due to its high energy density and long cycle life. The integration of these two technologies into a cooperative energy system effectively addresses the intermittency and volatility issues associated with PV power generation, enabling stable energy supply and efficient utilization. However, current research on the cooperative working characteristics between silicon tandem PV modules and the battery energy storage system remains insufficient, with challenges such as system configuration optimization and stable operation under complex conditions requiring urgent resolution. Therefore, conducting experimental studies on the cooperative characteristics of silicon tandem PV modules and the battery energy storage system is of great theoretical and practical significance for enhancing system performance and advancing new energy technologies.
In this study, we focus on the cooperative operation of silicon tandem PV modules and a lithium-based battery energy storage system. We establish power and energy balance models, design four distinct configuration schemes involving different PV module bandgaps and lithium battery pack setups, and perform tests under combined conditions of stepwise variations in light intensity and load power, as well as simulated full-day sunlight environments from 6:00 to 18:00. Our findings demonstrate that the optimal performance is achieved with a PV module featuring an upper bandgap of 2.0 eV and a lower bandgap of 1.0 eV, paired with a series-connected lithium battery pack comprising 25 cells of 25 Ah and 3.8 V each. Under complex operating conditions, the power balance deviation rate is controlled within 1.3%, providing robust data support and theoretical basis for system optimization.
Fundamental Principles of Silicon Tandem PV Modules and Battery Energy Storage System
The silicon tandem PV module consists of multiple crystalline silicon sub-cells with different bandgaps connected in series, with its operation centered on the semiconductor photoelectric effect. When sunlight irradiates the module, photons of varying energies are absorbed by the corresponding bandgap sub-cells: high-energy photons are captured by wide-bandgap sub-cells, while low-energy photons are received by narrow-bandgap sub-cells. The photon energy enables electrons in the semiconductor material to gain sufficient kinetic energy for transition, thereby generating electron-hole pairs. Under the influence of the built-in electric field formed by the p-n junction, electrons and holes move in opposite directions and are effectively separated—electrons flow toward the negative electrode, and holes toward the positive electrode—creating an electric current external to the module. This mechanism allows the silicon tandem PV module to achieve layered utilization of the solar spectrum, reducing thermal losses from high-energy photons and significantly enhancing photoelectric conversion efficiency compared to traditional monocrystalline PV modules.
The battery energy storage system (BESS) primarily comprises a lithium battery pack, a battery management system (BMS), and power conversion equipment. Lithium batteries utilize lithium metal oxide as the positive electrode and graphite as the negative electrode, separated by an electrolyte and a diaphragm. During charging, an external power source causes lithium atoms to lose outer electrons; electrons flow to the negative electrode via external conductors, while lithium ions migrate through the electrolyte and embed into the layered structure of the negative graphite. In the discharge process, lithium ions de-intercalate from the negative electrode, return to the positive electrode through the electrolyte, and electrons are attracted by the positive charge of the positive electrode, forming a current through the external circuit to power the load. The BMS monitors parameters such as battery voltage, current, and temperature in real-time, precisely controlling the charging and discharging processes to prevent overcharging, over-discharging, and other abnormal conditions. Through balanced management of the battery pack, the BMS ensures consistent performance across all battery units, effectively extending battery life and guaranteeing the safe and stable operation of the battery energy storage system, thereby enabling efficient reversible conversion between electrical and chemical energy.
The cooperative operation between the silicon tandem PV modules and the battery energy storage system is essential for maintaining energy stability. The power balance in the system can be expressed by the following equation:
$$P_{pv} = P_{load} + P_{battery}$$
where \(P_{pv}\) is the output power of the silicon tandem PV module in watts (W), \(P_{load}\) is the power consumed by the load in watts (W), and \(P_{battery}\) is the charging or discharging power of the lithium battery in watts (W), with positive values indicating charging and negative values discharging. By real-time monitoring of \(P_{pv}\) and \(P_{load}\), and calculating the target value of \(P_{battery}\) based on the power balance equation, the system dynamically adjusts the charging and discharging states of the battery energy storage system. When \(P_{pv} > P_{load}\), excess electrical energy is stored through positive \(P_{battery}\) charging; when \(P_{pv} < P_{load}\), the battery energy storage system supplements the power deficit through negative \(P_{battery}\) discharging, ensuring stable operation under varying conditions such as fluctuating light intensity and load changes, and achieving efficient synergistic conversion of light energy, electrical energy, and chemical energy.
Furthermore, the core of cooperative work lies in achieving dynamic balance among PV power generation, battery energy storage system storage, and load power consumption. When PV power is abundant, excess energy must be stored through the energy storage link, and the energy balance equation is given by:
$$E_{in} = \int (P’_{pv} \cdot \eta_{dc} \cdot \eta_{inv} – P’_{load}) dt$$
where \(P’_{pv}\) is the output power of the PV module in watts (W), \(\eta_{dc}\) is the efficiency of the bidirectional DC-DC converter (dimensionless), \(\eta_{inv}\) is the inverter efficiency (dimensionless), \(P’_{load}\) is the load power consumption in watts (W), \(E_{in}\) is the charging energy of the lithium battery in watt-hours (Wh), and \(t\) is time in hours (h). After accounting for efficiency losses in the converter and inverter, a portion of the PV output power directly supplies the load, and the remainder is stored in the battery energy storage system as charging energy.
Experimental Methodology and System Configuration
In this experimental study, we aim to investigate the cooperative working characteristics of silicon tandem PV modules and the battery energy storage system. We employ a controlled variable approach to design multiple comparative schemes. By adjusting the bandgap combinations of the PV modules (upper 1.8 eV/2.0 eV, lower 1.0 eV/1.1 eV) and the parameters of the lithium battery pack (capacity 20 Ah/25 Ah, voltage 3.7 V/3.8 V, series connection of 25/30 cells), we systematically analyze the impact of different configurations on power balance and energy conversion efficiency. The battery energy storage system is central to these tests, as it manages energy flow and storage.
The experimental setup involves a professional testing platform equipped with an AAA-grade solar simulator to simulate gradient light intensities from 1000 W/m² to 600 W/m², with irradiation uniformity error < 2% and spectral matching meeting Class A standards. A programmable electronic load simulates step changes in load power from 50 W to 110 W, with power adjustment accuracy of 0.1 W. High-precision Hall current sensors (accuracy ±0.5%) and voltage acquisition modules (resolution 0.01 V) are used for real-time monitoring of system parameters, with a data acquisition frequency of 10 Hz. Prior to testing, all equipment is calibrated, and each scheme is tested three times with average values taken. Environmental temperature is stabilized at 25 ± 1°C using a temperature and humidity control chamber to minimize external interference. Data is processed using Matlab for filtering, and trend curves are plotted with Origin to ensure reliability and accuracy. The battery energy storage system parameters are carefully configured to match the PV outputs.
The specific experimental schemes are detailed in the table below, which outlines the configurations of the PV modules and the battery energy storage system for each case.
| Scheme | PV Module Bandgap (eV) | Battery Energy Storage System Configuration |
|---|---|---|
| Control Group | Upper 1.8, Lower 1.1 | 30 cells of 20 Ah, 3.7 V each in series |
| Scheme 1 | Upper 2.0, Lower 1.0 | 30 cells of 20 Ah, 3.7 V each in series |
| Scheme 2 | Upper 1.8, Lower 1.1 | 25 cells of 25 Ah, 3.8 V each in series |
| Scheme 3 | Upper 1.8, Lower 1.1 | 30 cells of 20 Ah, 3.7 V each in series |
| Scheme 4 | Upper 2.0, Lower 1.0 | 25 cells of 25 Ah, 3.8 V each in series |
These configurations allow us to evaluate how variations in the battery energy storage system setup affect overall performance. For instance, the battery energy storage system in Scheme 4 is optimized for higher capacity and voltage, which may enhance energy retention and discharge capabilities under fluctuating conditions.
Analysis of Power Balance Under Complex Conditions
To deeply explore the power balance characteristics of each scheme under complex conditions, we designed combined tests involving stepwise changes in light intensity (1000 W/m² → 800 W/m² → 600 W/m²) and step changes in load power (50 W → 80 W → 110 W). The power balance rates for the control group, Scheme 1, Scheme 2, Scheme 3, and Scheme 4 were recorded, with results summarized in the table below. The battery energy storage system plays a critical role in maintaining this balance by compensating for power discrepancies.
| Test Condition | Control Group | Scheme 1 | Scheme 2 | Scheme 3 | Scheme 4 |
|---|---|---|---|---|---|
| Light 1000 W/m², Load 50 W | 0% | 0% | 0% | 0% | 0% |
| Light 800 W/m², Load 80 W | 1.20% | 0.80% | 1.00% | 0.90% | 0.7% |
| Light 600 W/m², Load 110 W | 2.10% | 1.50% | 1.80% | 1.70% | 1.3% |
Under the condition of 1000 W/m² light intensity and 50 W load, the power balance deviation rates for all schemes are 0%. This is because the PV module output power far exceeds the load power, and the battery energy storage system has sufficient capacity to store the excess energy, allowing the system to easily maintain power balance. When light intensity decreases to 800 W/m² and load increases to 80 W, the control group shows a deviation rate of 1.20%, higher than Scheme 1, Scheme 2, and Scheme 3. Scheme 1, with its upper bandgap of 2.0 eV and lower bandgap of 1.0 eV, achieves better layered utilization of the spectrum, resulting in more stable output power. Schemes 2 and 3, through adjustments in battery capacity and voltage, optimize the energy storage capability of the battery energy storage system, leading to superior power balance. As light intensity further drops to 600 W/m² and load rises to 110 W, the deviation rates for all schemes increase, with the control group reaching 2.10%. At this point, PV module output power significantly decreases, demanding higher compensation capability from the battery energy storage system during discharge. Scheme 4, with its optimized PV module bandgaps and battery energy storage system configuration, maintains the lowest deviation rate within 1.3%. Its wide-bandgap PV module fully absorbs high-energy photons, and the matched battery energy storage system precisely discharges when power is insufficient, ensuring system power balance.
Overall, Scheme 4 demonstrates the best power balance performance under varying conditions, validating that rational optimization of PV module bandgaps and the battery energy storage system configuration is crucial for enhancing the system’s power balance capability in complex operating scenarios. The battery energy storage system efficiency is key to this performance, as it directly influences how well energy imbalances are managed.
System Overall Efficiency Under Simulated Full-Day Conditions
We further simulated a full-day sunlight environment from 6:00 to 18:00, collecting data hourly to calculate the overall system energy conversion efficiency (\(\eta\)) for the control group, Scheme 1, Scheme 2, Scheme 3, and Scheme 4. The results are presented in the table below. The battery energy storage system contributes significantly to this efficiency by enabling optimal energy storage and retrieval.
| Time (h) | Control Group (%) | Scheme 1 (%) | Scheme 2 (%) | Scheme 3 (%) | Scheme 4 (%) |
|---|---|---|---|---|---|
| 6:00–7:00 | 18 | 20 | 19 | 19 | 21 |
| 11:00–12:00 | 22 | 25 | 23 | 24 | 26 |
| 17:00–18:00 | 16 | 19 | 18 | 18 | 20 |
| Full-Day Average | 20 | 23 | 21 | 22 | 24 |
From the table, during the early morning hours with weak light (6:00–7:00), Scheme 4 achieves an energy conversion efficiency of 21%, which is 3% higher than the control group and 1%, 2%, and 2% higher than Scheme 1, Scheme 2, and Scheme 3, respectively, demonstrating its stronger capability to capture low-energy photons. At noon, under the strongest light (11:00–12:00), the efficiency advantage of Scheme 4 further expands to 26%, exceeding the control group by 4% and Scheme 1, Scheme 2, and Scheme 3 by 1%, 3%, and 2%, respectively, fully leveraging the efficacy of spectral layered utilization. In the evening as light diminishes (17:00–18:00), Scheme 4 still maintains a high efficiency of 20%. In terms of full-day averages, Scheme 4 has the highest overall efficiency at 24%, representing a 4% improvement over the control group and 1%, 3%, and 2% higher than Scheme 1, Scheme 2, and Scheme 3, respectively. While Scheme 1, Scheme 2, and Scheme 3 show good efficiency in some periods, their overall stability is weaker compared to Scheme 4. This indicates that the optimized configuration of Scheme 4 enables efficient and stable operation throughout the day under varying light conditions, achieving superior conversion of light energy to electrical energy and chemical energy, and providing a better reference for the selection and configuration of silicon tandem PV module-based battery energy storage systems.
The energy conversion efficiency can be mathematically represented by integrating the power outputs and inputs over time, considering the role of the battery energy storage system. For instance, the overall efficiency \(\eta\) is calculated as:
$$\eta = \frac{\int P_{load} dt}{\int P_{pv} dt} \times 100\%$$
where the numerator represents the total energy delivered to the load, and the denominator is the total energy generated by the PV modules. The battery energy storage system aids in maximizing this ratio by storing excess energy and releasing it when needed, thus reducing losses and improving overall system performance.
Conclusion and Implications for Battery Energy Storage System Integration
This experimental study demonstrates that the cooperative performance of silicon tandem PV modules and the battery energy storage system is significantly influenced by the PV module bandgaps and the configuration of the battery energy storage system. By comparing different experimental schemes, we find that rational optimization of system configuration can effectively enhance power balance capability and overall energy conversion efficiency under complex conditions. Specifically, Scheme 4—featuring a PV module with an upper bandgap of 2.0 eV and a lower bandgap of 1.0 eV, paired with a battery energy storage system comprising 25 series-connected cells of 25 Ah and 3.8 V each—exhibits the best performance. Under varying light and load conditions, the power balance deviation rate is controlled within 1.3%, and the full-day average energy conversion efficiency reaches 24%.
The findings underscore the importance of tailored configurations in real-world applications of battery energy storage systems. For example, in distributed energy scenarios, the battery energy storage system must be sized and specified to match the PV output characteristics and load demands. The layered absorption of the solar spectrum by tandem PV modules, combined with the efficient energy management of the battery energy storage system, enables reduced thermal losses and higher utilization rates. Future work could explore additional factors such as temperature effects, aging of battery energy storage system components, and economic considerations to further optimize these cooperative systems. Ultimately, this research provides valuable insights for advancing the integration of silicon tandem PV technology with battery energy storage systems, contributing to the development of reliable and efficient renewable energy solutions.
In summary, the synergy between silicon tandem PV modules and the battery energy storage system is pivotal for achieving sustainable energy goals. The battery energy storage system not only mitigates the intermittency of solar power but also enhances overall system resilience. As technologies evolve, continued refinement of these integrations will play a key role in global energy transitions, making the battery energy storage system an indispensable component in modern power networks.