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New laws offer nuclear industry incentives for existing power plant uprates
This year, the U.S. nuclear industry received a much-needed economic boost that could help preserve operating nuclear power plants and incentivize upgrades that extend their lifespan and power output.
Signed into law in 2022, the Inflation Reduction Act offers production tax credits (PTCs) for existing nuclear power plants and either PTCs or investment tax credits (ITCs) for new carbon-free generation. These credits could make power uprates—increasing the maximum power level at which a commercial plant may operate—a much more appealing option for utilities.
Ser Gi Hong, Kang-Seog Kim, Jae Seung Song
Nuclear Science and Engineering | Volume 164 | Number 1 | January 2010 | Pages 33-52
Technical Paper | doi.org/10.13182/NSE09-18
Articles are hosted by Taylor and Francis Online.
This paper analyzes the convergence of the rebalance iteration methods for accelerating the power iteration method of the discrete ordinates transport equation in the eigenvalue problem. The rebalance iteration methods include the coarse mesh rebalance (CMR), the coarse mesh finite difference (CMFD), and the partial current-based CMFD methods. The convergence analysis is performed with the well-known Fourier analysis through linearization. In the linearized form, these rebalance methods are formulated in a unified way where the rebalance methods are different only in a parameter. The analyses are applied for both one- and two-group problems in a homogeneous infinite medium and a finite medium having periodic boundary conditions. The theoretical analysis shows that the convergences of the rebalance methods for the eigenvalue problems are closely related with the ones for the fixed source problems and that the convergences for the eigenvalue problems can be analyzed with the formula for the fixed source problem after transforming the scattering cross sections into a different cross-section set. The numerical tests show that the Fourier convergence analysis provides a reasonable estimate for the numerical spectral radii for the model problems.