A graphical approach to carbon-efficient spot market scheduling for Power-to-X applications. (15th November 2020)

• Record Type: Journal Article
• Authors: Bokde, Neeraj; Tranberg, Bo; Andresen, Gorm Bruun
• Is Part Of: Energy conversion and management. Volume 224(2020)
• Publication Date: 2020-11-15
• Subjects: CO2 emission -- Power-to-X -- Demand flexibility; Direct energy conversion -- Periodicals; Energy storage -- Periodicals; Energy transfer -- Periodicals; Énergie -- Conversion directe -- Périodiques; Direct energy conversion; Periodicals; 621.3105
• DOI: 10.1016/j.enconman.2020.113461
• Languages: English
• ISSNs: 0196-8904

Abstract

Abstract: In the Paris agreement of 2015, it was decided to reduce the CO 2 emissions of the energy sector to zero by 2050 and to restrict the global mean temperature increase to 1.5 °C above the pre-industrial level. Such commitments are possible only with practically CO 2 -free power generation based on variable renewable technologies. Historically, the main point of criticism regarding renewable power is the variability driven by weather dependence. Power-to-X systems, which convert excess power to other stores of energy for later use, can play an important role in offsetting the variability of renewable power production. In order to do so, however, these systems have to be scheduled properly to ensure they are being powered by low-carbon technologies. In this paper, a graphical approach is introduced for scheduling power-to-X plants in the day-ahead market by minimizing carbon emissions and electricity costs. This graphical approach is simple to implement and intuitively explain to stakeholders. In a simulation study using historical prices and CO 2 intensity for four different countries, it is observed that the price and CO 2 intensity tends to decrease with increasing scheduling horizon. However, the effect diminishes when requiring an increasing amount of full load hours per year. Specifically, for 6000 full load hours per year, the trade-off method leads to reductions of 28% CO 2 emissions and 8% costs for West Denmark, 50% and 4% for Norway, 7% and 1% for France, and −4% and −5% for Germany, when compared to the worst case for each of the two parameters. Additionally, investigating the trade-off between optimizing for price or CO 2 intensity shows that it is indeed a trade-off: it is not possible to obtain the lowest price and CO 2 intensity at the same time. Highlights: A graphical approach for scheduling power-to-X operations in the spot market. Scheduling power-to-X in the spot market to minimize costs and CO 2 emissions. 48-hour horizon forecast of the prices and CO 2 emissions of electricity. Trade-off between optimizing for electricity prices and CO 2 emissions.