Evaluate DC Meter Adoption for House-Level Storage Devices

Yang Weng, Shuman Luo, Qiushi Cui, Robert Trask, Hao Wang

Research output: Contribution to journalArticlepeer-review

Abstract

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.

Original languageEnglish (US)
Pages (from-to)1
Number of pages1
JournalIEEE Transactions on Smart Grid
DOIs
StateAccepted/In press - 2022

Keywords

  • Batteries
  • battery incentive
  • Behavioral sciences
  • bi-level optimization
  • Costs
  • data-driven constraint
  • DC meter
  • Load modeling
  • Meters
  • Optimization
  • social benefit
  • Tariffs

ASJC Scopus subject areas

  • Computer Science(all)

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