Analysis method of independent energy storage power plant usage

What is the research progress of energy storage in IES?

At present, the research progress of energy storage in IES primarily focuses on reducing operational and investment costs. This includes studying the integration of single-type energy storage systems [3, 4] and multi-energy storage systems . The benefits of achieving power balance in IES between power generation and load sides are immense.

Is there a planning methodology for multi-energy storage systems in IES?

However, according to our investigation, there is still a lack of mature theoretical research on the planning methodology for multi-energy storage systems in IES. At present, the research progress of energy storage in IES primarily focuses on reducing operational and investment costs.

How can energy storage configuration models be improved?

On the other hand, refining the energy storage configuration model by incorporating renewable energy uncertainty management or integrating multiple market transaction systems (such as spot and ancillary service markets) would improve the model’s practical applicability.

Are self-built and leased energy storage modes a benefit evaluation method?

This paper proposes a benefit evaluation method for self-built, leased, and shared energy storage modes in renewable energy power plants. First, energy storage configuration models for each mode are developed, and the actual benefits are calculated from technical, economic, environmental, and social perspectives.

Which energy storage mode is best for new energy plants?

Despite the extensive research on energy storage configuration models, most studies focus on a single mode (such as self-built, leased, or shared storage), without conducting a comprehensive analysis of all three modes to determine which provides the best benefits for new energy plants.

How to improve the economic viability and renewable generation rate of IES?

To enhance the economic viability and renewable generation rate of IES, Wang Y et al. developed a planning optimization model for Multi-Energy Storage Systems (MESS). They employed wavelet packet and frequency decomposition methods to distribute the power of energy storage devices according to their response speed .