In the deregulated electricity markets run by Independent System Operator (ISO), a two-settlement (day-ahead and real-time) process is typically used to determine the electricity price to the end-use customers at different buses. In the day-ahead settlement, the demand is predicted at each bus based on the previous consumption behavior of the consumers and thus, Locational Marginal Price (LMP) can be determined and shared to the consumers. A significant gap is usually observed between the planned and real-time demands due to the uncertainties of the weather (temperature, wind-speed etc.), the intensity of business, and everyday activities. Therefore, a large price variation may occur in the real-time market and the dispatching plan needs to be adjusted to respond to the variation. To reduce the gap between the day-ahead and real-time dispatching plans, a modified framework, i.e., a three-settlement process considering the integration of the manufacturing plants into the existing two-settlement process is proposed in this study. The manufacturing end-use customers report the flexibility of their loads to the ISO so that the ISO can update the day-ahead price through an updated dispatching plan that utilizes the feedback of the load flexibility from the manufacturers. A mathematical model is developed to identify the flexible and non-flexible loads of the manufacturers. Particle Swarm Optimization (PSO) is used to solve this mathematical model and a case study is conducted to illustrate the effectiveness of the model.

Meeting Name

25th International Conference on Production Research Manufacturing Innovation: Cyber Physical Manufacturing, ICPR 2019 (2019: Aug. 9-14, Chicago, IL)


Engineering Management and Systems Engineering

Second Department

Mathematics and Statistics

Keywords and Phrases

Flexibility; Independent System Operator; Manufacturing load; Three-settlement

International Standard Serial Number (ISSN)


Document Type

Article - Conference proceedings

Document Version

Final Version

File Type





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Creative Commons Licensing

Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.

Publication Date

01 Aug 2019