What the study found
The study found that a multi-objective optimization method using an improved sparrow search algorithm can be used to configure photovoltaic (solar power) and energy storage capacity. In the case study, the proposed approach improved economic benefit and power supply reliability.
Why the authors say this matters
The authors say this matters because enterprise parks face high electricity costs, large peak-valley price differences, and weak use of renewable energy. The study suggests that including price-based demand response and cycle life constraints may help address these issues.
What the researchers tested
The researchers built a multi-objective function to minimize equivalent annualized comprehensive cost and energy imbalance rate. They then improved the standard sparrow search algorithm by adding chaotic mapping, adaptive inertia weight, Harris Hawks encircling, and predation strategies, and tested it with real load data from an enterprise park in Zhuzhou City.
What worked and what didn't
The proposed algorithm reportedly improved convergence speed and accuracy on high-dimensional problems compared with the traditional sparrow search algorithm. In the case study, it achieved a maximum economic benefit improvement of 7.32% over conventional intelligent algorithms and further enhanced power supply reliability.
What to keep in mind
The abstract does not provide detailed numerical comparisons beyond the 7.32% figure, and it does not describe specific limitations of the study. The results are based on a case study using real load data from one enterprise park.
Key points
- The study proposes a multi-objective method for sizing photovoltaic and energy storage systems.
- The method includes price-based demand response and cycle life constraints.
- An improved sparrow search algorithm was created using chaotic mapping and other added strategies.
- The case study used real load data from an enterprise park in Zhuzhou City.
- The proposed approach achieved a maximum economic benefit improvement of 7.32% over conventional intelligent algorithms.
Disclosure
- Research title:
- Improved algorithm optimizes photovoltaic-storage capacity
- Authors:
- Luting Zhang, Wei Zhao, Jinhui Zeng, Jie Liu
- Institutions:
- Hunan University of Technology, Hunan University of Technology, Hunan University of Technology, Hunan University of Technology
- Publication date:
- 2026-02-02
- OpenAlex record:
- View
- Image credit:
- Asurnipal, Wikimedia Commons, CC BY-SA 4.0
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