A non-uniform grid approach for scheduling considering electricity load tracking and future load prediction. (4th October 2019)

• Record Type: Journal Article
• Authors: Dalle Ave, Giancarlo; Harjunkoski, Iiro; Engell, Sebastian
• Is Part Of: Computers & chemical engineering. Volume 129(2019)
• Publication Date: 2019-10-04
• Subjects: Resource-task network (RTN) -- Demand side management -- Intraday market -- Day-ahead market -- Discrete-time -- Non-uniform grid; Chemical engineering -- Data processing -- Periodicals; 660.0285
• DOI: 10.1016/j.compchemeng.2019.06.031
• Languages: English
• ISSNs: 0098-1354

Abstract

Highlights: Novel Demand Side Management scheduling formulation proposed that combines the concerns of the intraday and day-ahead markets into a single formulation based on the discrete-time Resource-Task Network formulation to maintain generality. Formulation is applied to an industrial stainless steelmaking case study. A generic non-uniform grid rolling-horizon-based solution algorithm is proposed for the solution of such scheduling models. Results show that that novel formulation more realistically models actual market conditions than current state-of-the-art models. Results show that the proposed solution algorithm greatly reduces computational complexity while still achieving a solution close to that of the full-space model. Abstract: Large consumers' electricity bills depend on many factors including: different electricity purchasing contracts and markets, deviation penalties, and grid fees. Two key markets are the intraday and the day-ahead markets. On the day-ahead market, the consumer commits to an amount of electricity that stacks upon their longer-term contract commitments. The next day, the consumer must follow this total demand profile to avoid paying deviation penalties. This total committed demand curve can be modified within the current day on the intraday market. In this work, a novel demand side management formulation is proposed that looks at a two-day scheduling horizon considering both the intraday and the day-ahead markets. As a result, instead of modeling a single-day load tracking problem a two-day problem is considered looking at both load following and future load prediction. Furthermore, the computational complexity of the problem is reduced with a non-uniform grid-based formulation. Results show that the novel formulation is able to effectively combine the intraday and day-ahead market concerns resulting in more realistic demand profiles than current formulations. Additionally, the non-uniform grid-based approach captures the key aspects of the formulation with a much lower computation time than the full-space approach.