Parameter Design of a Photovoltaic Storage Battery Integrated System for Detached Houses Based on Nondominated Sorting Genetic Algorithm-II
Abstract
1. Introduction
2. Methodology
2.1. PV and Battery Integrated System and the Traditional Methods
2.2. The Optimization Process of the NSGA-II
3. Results
4. Discussion
5. Conclusions
- NSGA-II and the two single-objective GAs applied to the PV and battery integrated system produce consistent optimal solutions, even with fluctuating grid prices, demonstrating the accuracy of NSGA-II.
- All of the genetic algorithms converge quickly, achieving stable optimal solutions after approximately 2000 evaluations. NSGA-II completes the optimization in 726.1 s, saving 94% of the computation time compared to the traversal algorithms (12,216.1 s).
- The Pareto front solutions of NSGA-II reveal a clear trade-off between economic and environmental benefits. The experience method incurs a total electricity cost of CNY 7640 and uses 173.5 kWh of grid electricity, while the optimal NSGA-II solution costs CNY 2446.7 and uses 496.3 kWh, aligning better with typical household preferences.
- The traversal algorithm is inefficient and limited to integer solutions. NSGA-II intelligently bypasses unreasonable parameter ranges, aligning with the traversal algorithm’s solution space edges where total electricity cost and grid electricity usage are minimized.
Author Contributions
Funding
Data Availability Statement
Conflicts of Interest
References
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Specifications | Value |
---|---|
Discharge depth | 75% |
Capacity of the battery | 54 kWh |
Electricity charge capacity | 6 kW |
Electricity output capacity | 6 kW |
Electricity charge loss rate | 10% |
Electricity output loss rate | 10% |
Electricity time loss rate | 5%/month |
Parameters | Values |
---|---|
The area of PV (m2) | 19–62 |
The installation angle of PV (°) | 10–60 |
The capacity of storage battery (kWh) | 2–56 |
Unit price of PV (CNY/W) | 2.1 |
Unit price of storage battery (CNY/kWh) | 600 |
Price of grid electricity (CNY/kWh) | 0.5 |
Maximum power of the PV (W/m2) | 160 |
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Hou, Y.; Yuan, Q.; Wang, X.; Chang, H.; Wei, C.; Zhang, D.; Dong, Y.; Yang, Y.; Zhang, J. Parameter Design of a Photovoltaic Storage Battery Integrated System for Detached Houses Based on Nondominated Sorting Genetic Algorithm-II. Buildings 2024, 14, 1834. https://doi.org/10.3390/buildings14061834
Hou Y, Yuan Q, Wang X, Chang H, Wei C, Zhang D, Dong Y, Yang Y, Zhang J. Parameter Design of a Photovoltaic Storage Battery Integrated System for Detached Houses Based on Nondominated Sorting Genetic Algorithm-II. Buildings. 2024; 14(6):1834. https://doi.org/10.3390/buildings14061834
Chicago/Turabian StyleHou, Yaolong, Quan Yuan, Xueting Wang, Han Chang, Chenlin Wei, Di Zhang, Yanan Dong, Yijun Yang, and Jipeng Zhang. 2024. "Parameter Design of a Photovoltaic Storage Battery Integrated System for Detached Houses Based on Nondominated Sorting Genetic Algorithm-II" Buildings 14, no. 6: 1834. https://doi.org/10.3390/buildings14061834
APA StyleHou, Y., Yuan, Q., Wang, X., Chang, H., Wei, C., Zhang, D., Dong, Y., Yang, Y., & Zhang, J. (2024). Parameter Design of a Photovoltaic Storage Battery Integrated System for Detached Houses Based on Nondominated Sorting Genetic Algorithm-II. Buildings, 14(6), 1834. https://doi.org/10.3390/buildings14061834