What is it about?
In an effort to run integrated energy systems (IES) in a way that's both economical and low in carbon emissions, this research introduces small, miniaturized nuclear power (NP) units and carbon trading into the energy mix. We present a new scheduling model that brings two primary strategies into play: firstly, we conduct a heating renovation on the NP units, transforming them into cogeneration units (producing both electricity and useful heat) to enhance their operating flexibility. Secondly, we introduce auxiliary equipment like electricity and heat storage systems, as well as units that convert power to gas, aiming to further boost the system’s flexibility by enabling energy to be stored, time-shifted, or converted into different forms. Amidst the uncertainties of renewable energy outputs, our scheduling model uses chance-constrained programming and is validated by testing on a real North China IES, showcasing notable economic and low-carbon benefits.
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Why is it important?
This research is crucial as it provides a novel pathway towards achieving low-carbon operation in integrated energy systems by leveraging small nuclear power units and carbon trading. The integration of NP units offers a steadfast and low-carbon energy source, while the incorporation of a carbon trading mechanism aligns the financial and environmental interests of the IES. By converting nuclear power units into cogeneration systems and introducing auxiliary units that add a layer of operational flexibility, the IES can dynamically respond to varying energy demands and renewable energy fluctuations. Moreover, the model provides a practical and economically viable approach to maintaining a stable, low-carbon energy supply, offering a blueprint that could be extrapolated to various IESs worldwide, thus making a significant contribution towards global carbon emission reduction goals.
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Read the Original
This page is a summary of: Optimal dispatch of low-carbon integrated energy system considering nuclear heating and carbon trading, Journal of Cleaner Production, December 2022, Elsevier,
DOI: 10.1016/j.jclepro.2022.134540.
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