The deployment of new technologies, the importance of accurately modeling the dynamics of the generating units and the introduction of new policies are making the solution of the Unit Commitment/Economic Dispatch problem more and more complicated.In the present scenario, traditionally followed scheduling criteria might not lead to the optimal fleet configuration any more. In addition, most of the widely used techniques have limited capabilities at modeling the nonlinear dynamics of committed power plants. When realistic power systems comprising of several tens of generating units are modeled, the resulting optimization problem turns to be computationally intensive for the current computing capabilities. In this paper, an improved version of a GA-based optimization algorithm is presented. A detailed methodology aimed at obtaining a more efficient version of the GA, and a more detailed and accurate description of the flexible operation flexibility of the power plants is described.

The variations in the nuclear waste management performance have been assessed for 40 fuel-cycle examples with the calculation of the mass, activity, toxicity and decay heat of spent nuclear fuel and high-level waste at 10, 100 and 100,000 years after reactor discharge. The variation in the 10 years activity is primarily due to the variation in the specific activity of the fission products, which is higher for thorium fuel cycles, and is reduced when the fuel residence time is long. The variation in the 100,000 years activity is primarily explained by the quantity of U-233 and Pu-239 sent to nuclear waste, which is linked to the type of fuel and of reprocessing scheme employed. The difference between the inhalation toxicity and the activity is explained by the variations in the effective dose coefficients since heavy actinides such as Pu, Am and Cm have a predominant effect on the inhalation toxicity. Materials for disposal such as fission products and transuranics are responsible for most of the mass, and radiotoxicity of high-level waste, but the reprocessing/separation losses also have a potentially significant impact on the results.

Modeling and simulation in many science and engineering domains often involves the execution and/or iteration of a sequence of applications, with data transfer between applications typically required. These applications often do not have a formal application programming interface (API). Instead, executing an application requires first writing a text-based input file, the format of which is typically defined in a user's manual. While text-based input files are suitable for simple one-off calculations, they can become cumbersome if a user wants to execute the applications multiple times and systematically vary input parameters, especially when a complex workflow is involved. In this case, they must resort to either manually making changes in the input file or developing their own script that modifies the input file and executes the application. Depending on the format of the input file, writing such a script can be a non-trivial and error-prone task.

The Holos-Quad micro-reactor concept is proposed by HolosGen LLC to generate 22 MWt with a lifetime of approximately 8 effective full power years (EFPYs) for civilian applications. The design is based on a very innovative high-temperature gas-cooled reactor concept using four Subcritical Power Modules (SPMs) that fit into one commercial 40-foot transport ISO container. A rigorous design approach was employed in order to ensure that all input parameters were fully investigated and the best solutions possible were considered. The first step of this approach consisted of properly defining the Holos-Quad design problem by identifying the design objectives, the operational constraints, and the input parameters. In the second step, a sensitivity analysis was performed to enable a preliminary investigation of the input parameters to identify the correlations among input and output variables. Finally, the design optimization was performed in the third step, employing a genetic algorithm to effectively explore the highly constrained input parameters and find global optimal solutions. The multi-objective optimization identified various core solutions that would be optimum solutions for different types of applications. For applications where economics matters less and the ease of transportation matters more, a core weight of ~15 tons could achieve a lifetime of ~3.5 EFPYs. For applications where economics matters more and the ease of transportation matters less, a lifetime of 8.3 EFPYs could be achieved with a total core weight of ~26.7 tons.