A real options approach to evaluating investment in solar ready buildings

Sustainable building technologies such as Photovoltaics (PV) have promising features for energy saving and greenhouse gas (GHG) emissions reduction in the building sector. Nevertheless, adopting these technologies generally requires substantial initial investments. Moreover, the market for these technologies is often very vibrant from the technological and economic standpoints. Therefore, investors typically find it more attractive to delay investment on the PV panels. Nevertheless, they can prepare \u93Solar Ready Buildings\u94 that can easily adopt PV panels later in future at the optimal time; when their prices are lower, energy price are higher, or stricter environmental regulations are in place. The conventional valuation methods such as Net Present Value (NPV) are unable to identify the optimal timing for investing in the PV panels. Hence, in order to avoid over- and under-investment, the decision makers should be equipped with proper financial valuation models that help them identify the optimal investment timing. We apply Real Options Theory from finance/decision science to create an investment valuation framework for finding the optimal time for investing in PV technologies. Our proposed investment analysis model uses experience curve concept to model the changes in price and efficiency of the PV technologies over time. It also has an energy price modeling component that characterizes the uncertainty about future retail price of energy as a stochastic process. Finally, the model incorporates the information concerning specific policy and regulatory instruments that may affect the investment value. Using our mode, investors\u92 financial risk profiles of investment (i.e. Cumulative Distribution Function of the Investment Value) in the \u93fixed\u94 Solar Building and \u93flexible\u94 Solar Ready Buildings will be developed. This will determine the Financial Value (if any) of investing in the Solar ready building and identify the optimal time for installing the PV panels

Applying the shuffled frog-leaping algorithm to improve scheduling of construction projects with activity splitting allowed

In situation of contractors competing to finish a given project with the least duration and cost, acquiring the ability to improve the project quality properties seems essential for project managers. Evolutionary Algorithm (EAs) have been applied as suitable algorithms to develop the multi-objective Time-Cost trade-off Optimization (TCO) and Time-Cost-Resource Optimization (TCRO) in the past few decades ; however, by improving EAs, the Shuffled Frog Leaping Algorithm (SFLA) has been introduced as an algorithm capable of achieving a better solution with faster convergence. Furthermore, considering splitting in execution of activities can make models closer to approximating real projects. One example has been used to demonstrate the impact of SFLA and splitting on the results of the model and to compare with previous algorithms. Current research has elucidated that SFLA improves final results and splitting allows the model find suitable solutions

Multidisciplinary design optimization of large wind turbines: Technical, economic, and design challenges

Wind energy has experienced a continuous cost reduction in the last decades. A popular cost reduction technique is to increase the rated power of the wind turbine by making it larger. However, it is not clear whether further upscaling of the existing wind turbines beyond the 5–7MW range is technically feasible and economically attractive. To address this question, this study uses 5, 10, and 20MW wind turbines that are developed using multidisciplinary design optimization as upscaling data points. These wind turbines are upwind, 3-bladed, pitch-regulated, variable-speed machines with a tubular tower. Based on the design data and properties of these wind turbines, scaling trends such as loading, mass, and cost are developed. These trends are used to study the technical and economical aspects of upscaling and its impact on the design and cost. The results of this research show the technical feasibility of the existing wind turbines up to 20 MW, but the design of such an upscaled machine is cost prohibitive. Mass increase of the rotor is identified as a main design challenge to overcome. The results of this research support the development of alternative lightweight materials and design concepts such as a two-bladed downwind design for upscaling to remain a cost effective solution for future wind turbines.Wind Energ

A Non-Linear Upscaling Approach for Wind Turbines Blades Based on Stresses

The linear scaling laws for upscaling wind turbine blades show a linear increase of stresses due to the weight. However, the stresses should remain the same for a suitable design. Application of linear scaling laws may lead to an upscaled blade that may not be any more a feasible design. In this paper a non-linear upscaling approach is presented with the aim of keeping the stresses in the upscaled blade the same as the reference blade. The stresses due to the weight, aerodynamics and centrifugal forces are taken into account and the blade is modeled as a beam with equivalent structural properties. This new methodology is used to upscale the 5 MW NREL wind turbine blade to a 20 MW wind turbine blade. As a result, a 20 MW wind turbine blade is obtained in which the stresses are the same as the 5 MW blade. This provides initial blade design solution for optimization studies that is feasible and enables the designer to explore other interesting aspects of larger scale wind turbines.Aerodynamics, Wind Energy & PropulsionAerospace Engineerin