Distributionally Robust Hydrogen Optimization with Ensured Security and Multi-Energy Couplings
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Article de revue
Este ítem está publicado en
IEEE Transactions on Power Systems. 2021-01-01, vol. 36, n° 1, p. 504 - 513
Resumen en inglés
Power-to-gas (P2G) can convert excessive renewable energy into hydrogen via electrolysis, which can then be transported by natural gas systems to bypass constrained electricity systems. However, the injection of hydrogen ...Leer más >
Power-to-gas (P2G) can convert excessive renewable energy into hydrogen via electrolysis, which can then be transported by natural gas systems to bypass constrained electricity systems. However, the injection of hydrogen could impact gas quality since gas composition fundamentally changes, adversely effecting the combustion, safety and lifespan of appliances. This paper develops a new gas quality management scheme for hydrogen injection into natural gas systems produced from excessive wind power. It introduces four gas quality indices for the integrated electricity and gas system (IEGS) measuring gas quality, considering the coordinated operation of tightly coupled infrastructures. To maintain gas quality under an acceptable range, the gas mixture of nitrogen and liquid petroleum gas with hydrogen is adopted to address the gas quality violation caused by hydrogen injection. A distributionally robust optimization (DRO) modelled by Kullback-Leibler (KL) divergence-based ambiguity set is applied to flexibly control the robustness to capture wind uncertainty. Case studies demonstrate that wind power is maximally utilized and gas mixture is effectively managed, thus improving both gas quality and performance of IEGS. The work can benefit system operators with i) ensured gas quality under hydrogen injection ii) low system operation cost and iii) high renewable energy penetration< Leer menos
Palabras clave en inglés
Distributionally robust optimization
gas security management
integrated electricity and gas system
integrated energy system
power-to-gas
renewable uncertainty
Centros de investigación