Blending green hydrogen from renewable generations into the natural gas infrastructure can effectively mitigate carbon emissions of energy consumers. However, distributed hydrogen blending could lead to heterogeneous gas compositions across the network. The traditional nodal energy price scheme is designed for uniform gas composition, which cannot reflect the impacts of heterogeneous nodal gas composition and carbon emission mitigation. This paper proposes a novel nodal energy price scheme in hydrogen-blended integrated electricity and gas systems (H-IEGS). First, we propose a joint market-clearing model for H-IEGS, where the nonlinear physical properties of gas mixtures caused by heterogeneous gas compositions are characterized. The impacts of hydrogen blending on the carbon emission cost are also quantified. To retrieve the nodal energy price from this highly nonlinear and nonconvex optimization problem, a successive second-order cone programming (SSOCP) method is tailored to get the dual variables tractably. Considering the continuous market clearing process, a warm-start technique is proposed to provide initial reference points for the SSOCP to improve computation efficiency. Finally, an H-IEGS test case in Belgium and a large-scale practical case in Northwest China are used to validate the effectiveness of the proposed method.

Carbon-Embedded Nodal Energy Price in Hydrogen-Blended Integrated Electricity and Gas Systems with Heterogeneous Gas Compositions

Siano P.
2024-01-01

Abstract

Blending green hydrogen from renewable generations into the natural gas infrastructure can effectively mitigate carbon emissions of energy consumers. However, distributed hydrogen blending could lead to heterogeneous gas compositions across the network. The traditional nodal energy price scheme is designed for uniform gas composition, which cannot reflect the impacts of heterogeneous nodal gas composition and carbon emission mitigation. This paper proposes a novel nodal energy price scheme in hydrogen-blended integrated electricity and gas systems (H-IEGS). First, we propose a joint market-clearing model for H-IEGS, where the nonlinear physical properties of gas mixtures caused by heterogeneous gas compositions are characterized. The impacts of hydrogen blending on the carbon emission cost are also quantified. To retrieve the nodal energy price from this highly nonlinear and nonconvex optimization problem, a successive second-order cone programming (SSOCP) method is tailored to get the dual variables tractably. Considering the continuous market clearing process, a warm-start technique is proposed to provide initial reference points for the SSOCP to improve computation efficiency. Finally, an H-IEGS test case in Belgium and a large-scale practical case in Northwest China are used to validate the effectiveness of the proposed method.
2024
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11386/4888768
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