@inproceedings{35461,
  keywords = {Demand response, Commissioning, M&V, Demand flexibility, Baseline Method},
  author = {Jingjing Liu and Lili Yu and Rongxin Yin and Mary Ann Piette and Marco Pritoni and Armando Casillas and Monica Neukomm and Amir Roth},
  title = {Benchmarking Demand Flexibility in Commercial Buildings and Flattening the Duck – Addressing Baseline and Commissioning Challenges},
  abstract = {<p>With the transition from our traditional electric grid to a cleaner grid with renewable power generation, there is a need to enable building loads to be flexible. Load shedding and shifting will be essential for flattening the “Duck” for decarbonization. This paper explored the trend in the timing of DR events as a reflection of the grid’s needs using recent four years of event data from 203 retail stores in 11 states. The events are becoming significantly shorter with 2-hour duration being the most popular; shifting to late afternoon and early evening is another trend beyond California.<br />Benchmarking will be essential for accounting DF as a reliable grid resource. This paper addresses a challenging aspect of benchmarking – inaccuracies in counterfactual baseline methods can introduce significant DF metrics variations in addition to weather and building characteristics related factors. The conventional “10/10” with adjustment baseline method has inherent limitation by design for load shifting applications. Therefore, it is imperative to identify alternative methods. This study compared three hourly regression baseline methods with “10/10” methods using two groups of commercial buildings that participated in DR programs: (1) 121 big-box retail stores, and (2) 11 office buildings in CA. The 14-day hourly outdoor temperature regression method was found to produce least error in the tested datasets and is promising for load shifting.<br />The paper also pointed out that commissioning issues can also be a significant barrier for achieving consistent DF performance, which building managers and utilities should be aware of.</p>},
  year = {2022},
  journal = {2022 Summer Study on Energy Efficiency in Buildings},
  month = {08/2022},
  publisher = {ACEEE},
  address = {Pacific Grove, CA},
  url = {https://escholarship.org/uc/item/2vf343pf},
  doi = {https://doi.org/10.20357/B7M89Q},
  language = {eng},
}