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This paper aims to propose a practical decision support model for the optimal design of future wind turbines based on available wind potential on the site of interest. A developed decision support model based a comprehensive wind turbine modeling and a constrained techno-economic optimization framework is presented. Optimization was subject to the Net Present Value (NPV) maximization of the net incomes from wind energy generation, under the constraints on wind turbine nominal power restriction and the maximum ratio permitted between the rotor diameter and tower hub height. Optimizations of rotor diameter and tower height sizing have direct impacts on energy and cost production, those parameters have been considered as the design variables. The optimal design selection considers: the nominal power, rotor diameter, and tower hub height, which led to the maximum NPV in a specific site. Furthermore, an analysis of the Levelized Cost of Energy production (LCOE) has been performed. The developed decision support model has been tested and applied to a case study to validate its application and performance. The developed model was verified and significant results were achieved using three different wind sites: Dakhla, Casablanca, and Tanger. Results showed that the optimal design of the wind turbine technologies is given by the limit conditions cited, conducting to the maximum NPV with low LCOE and more exploitation of available wind potential in Dakhla and Tanger; however Casablanca was found as no profitable site for wind projects presenting negative NPV.

This study presents a comprehensive decision support model formulated as a finite-horizon-constrained optimisation problem to optimally design the geometry variables that maximise the net present value (NPV) associated to the thermal energy storage (TES) investment over a given time horizon. This study faces one of the main problems in a TES, which is to react to the unpredictable production/demand processes, by determining a high-level optimal size of the TES maximising the NPV that captures the storage benefits as well as detailed fixed and variable costs over a chosen time horizon. The storage benefits are defined, so that they model the costs of the expected discharged thermal energy over a year. Moreover, the authors account for various costs model regarding the total costs of the heat transfer tube material, the storage material, and the insulation material. The proposed decision model can be considered as practical framework that can support engineers and decision makers in the process of design and planning of future. They investigate performance and efficiency of the proposed decision support system framework through representative case studies. Numerical studies demonstrate the usefulness and efficacy of the proposed decision model.

This study proposes a comprehensive decision support framework to optimally select the solid medium and heat transfer tubes material composing the thermal energy storage (TES). The proposed decision model aims to maximise the net present value (NPV) associated with the TES investment over a given time horizon. Compared with related works in the literature, the authors' design accounts for various practical investment costs and design parameters that are the number of heat transfer tubes, storage module length, and the storage unit diameter. The decision problem, which maximises the NPV is formulated as an optimisation problem to find out the optimal combination among a set of solid media and heat transfer tube materials considering their thermo-physical characteristics. The proposed design is evaluated through case studies to test its concrete practices and to evaluate the impacts of the design parameters on the TES investment costs.