Modeling Financial Feasibility Of Energy Storage

How are financial and economic models used in energy storage projects?

Financial and economic modeling are undertaken based on the data and assumptions presented in Table 1. Table 1. Project stakeholder interests in KPIs. To determine the economic feasibility of the energy storage project, the model outputs two types of KPIs: economic and financial KPIs.

How do you value energy storage projects?

The central tool for valuing an energy storage project is the project valuation model. Many still use simple Excel models to evaluate projects, but to capture the opportunities in the power market, it is increasing required to utilize something with far greater granularity in time and manage multiple aspects of the hardware.

How can a financial model improve energy storage system performance?

The model may integrate more data about energy storage system operation as they have an impact the system lifetime. This will have an influence on the financial outcomes. The existing financial model may be enhanced by adding new EES technical details. There are various valuation methods for energy storage.

What economic inputs are included in the energy storage model?

The economic inputs into the model will include both the revenue and costs for the project. Revenue for the energy storage project will either be expressed as a contracted revenue stream from a PPA (Power Purchase Agreement), derived from merchant activity by the facility, or some combination thereof.

How can the Department of energy improve the understanding of energy storage?

Valuation Models A critical role for the U.S. Department of Energy to improve the understanding of energy storage project and portfolio valuation is to continue to develop and make publicly available valuation models that serve the upcoming need of new and innovative roles in the energy storage market.

What are the valuation methods for energy storage?

There are various valuation methods for energy storage. Other valuation options may be utilized by the financial model to account for technical, economic, and financing uncertainty. To optimize income, an energy arbitrage algorithm can be used. 8. Conclusion