Evaluate DC Meter Adoption for House-Level Storage Devices

Although batteries are increasingly adopted in individual households, utilities typically do not know the real behaviors of the customer-owned batteries. Therefore, it is hard for the utilities to evaluate the necessity of adding a DC meter on the DC side of the battery. Meanwhile, the customers do not know the benefits they can get, so they cannot make an adoption decision of DC meters. To solve these practical problems, this paper aims to provide a DC meter evaluation tool for utilities and customers to calculate their costs and revenues. Specifically, we formulate a bi-level optimization framework that considers the battery incentive design and physical law simultaneously. To reflect the reality, the optimization is also based on data-driven constraints based on big utility data and accurate performance. While the optimization problem is complex, we enforce convexity via various designs to provide the optimal solution for incentive planning. Through simulation, the battery incentive design model is tested to be valid under different market rates and case studies. The proposed optimization model provides a promising tool for utilities and customers to evaluate DC meter adoption decisions.

Automated summary

Although batteries are increasingly used in households, utilities lack knowledge of customer-owned batteries, making it difficult to determine the necessity of adding a DC meter. To address this issue, this paper proposes a bi-level optimization framework that considers battery incentive design and physical law to enable utilities and customers to evaluate the costs and benefits of adopting DC meters.