The Experts below are selected from a list of 296799 Experts worldwide ranked by ideXlab platform
Kim A Stelson - One of the best experts on this subject based on the ideXlab platform.
-
a Mathematical Approach to minimizing the cost of energy for large utility wind turbines
Applied Energy, 2018Co-Authors: Jincheng Chen, Feng Wang, Kim A StelsonAbstract:With the aim of reducing green gas emission, wind turbine installations worldwide have grown rapidly in recent years. Wind energy itself is free, but has costs due to the wind turbine infrastructure and maintenance. The installation size of the wind turbine at a specific location is not only determined by the wind statistics at that location, but also by the turbine infrastructure and the maintenance cost. The payback time of the turbine is determined by the turbine cost of energy (COE). In this paper, a Mathematical Approach is proposed to minimize the turbine cost of energy based on wind statistics. Turbine annual energy production (AEP) is calculated based on turbine output power and annual wind speed distribution. A wind turbine cost model developed by U.S. National Renewable Energy Laboratory (NREL) is used for turbine cost analysis. The turbine cost of energy model includes the turbine rated power and the turbine rated wind speed. Finally a general guideline to minimize the turbine COE is presented. Three case studies are conducted to show the effectiveness of the proposed Approach.
Jincheng Chen - One of the best experts on this subject based on the ideXlab platform.
-
a Mathematical Approach to minimizing the cost of energy for large utility wind turbines
Applied Energy, 2018Co-Authors: Jincheng Chen, Feng Wang, Kim A StelsonAbstract:With the aim of reducing green gas emission, wind turbine installations worldwide have grown rapidly in recent years. Wind energy itself is free, but has costs due to the wind turbine infrastructure and maintenance. The installation size of the wind turbine at a specific location is not only determined by the wind statistics at that location, but also by the turbine infrastructure and the maintenance cost. The payback time of the turbine is determined by the turbine cost of energy (COE). In this paper, a Mathematical Approach is proposed to minimize the turbine cost of energy based on wind statistics. Turbine annual energy production (AEP) is calculated based on turbine output power and annual wind speed distribution. A wind turbine cost model developed by U.S. National Renewable Energy Laboratory (NREL) is used for turbine cost analysis. The turbine cost of energy model includes the turbine rated power and the turbine rated wind speed. Finally a general guideline to minimize the turbine COE is presented. Three case studies are conducted to show the effectiveness of the proposed Approach.
Madjid Fathi - One of the best experts on this subject based on the ideXlab platform.
-
Competence assessment as an expert system for human resource management: A Mathematical Approach
Expert Systems with Applications, 2017Co-Authors: Mahdi Bohlouli, George Kakarontzas, Theodosios Theodosiou, Nikolaos Mittas, Lefteris Angelis, Madjid FathiAbstract:Efficient human resource management needs accurate assessment and representation of available competences as well as effective mapping of required competences for specific jobs and positions. In this regard, appropriate definition and identification of competence gaps express differences between acquired and required competences. Using a detailed quantification scheme together with a Mathematical Approach is a way to support accurate competence analytics, which can be applied in a wide variety of sectors and fields. This article describes the combined use of software technologies and Mathematical and statistical methods for assessing and analyzing competences in human resource information systems. Based on a standard competence model, which is called a Professional, Innovative and Social competence tree, the proposed framework offers flexible tools to experts in real enterprise environments, either for evaluation of employees towards an optimal job assignment and vocational training or for recruitment processes. The system has been tested with real human resource data sets in the frame of the European project called ComProFITS.
Jnanjyoti Sarma - One of the best experts on this subject based on the ideXlab platform.
-
A new Mathematical Approach for shock-wave solution in a dusty plasma
Physics of Plasmas, 1997Co-Authors: Gopal Das, C. B. Dwivedi, Madhuri Talukdar, Jnanjyoti SarmaAbstract:The problem of nonlinear Burger equation in a plasma contaminated with heavy dust grains has been revisited. As discussed earlier [C. B. Dwivedi and B. P. Pandey, Phys. Plasmas 2, 9 (1995)], the Burger equation originates due to dust charge fluctuation dynamics. A new alternate Mathematical Approach based on a simple traveling wave formalism has been applied to find out the solution of the derived Burger equation, and the method recovers the known shock-wave solution. This technique, although having its own limitation, predicts successfully the salient features of the weak shock-wave structure in a dusty plasma with dust charge fluctuation dynamics. It is emphasized that this Approach of the traveling wave formalism is being applied for the first time to solve the nonlinear wave equation in plasmas.
Feng Wang - One of the best experts on this subject based on the ideXlab platform.
-
a Mathematical Approach to minimizing the cost of energy for large utility wind turbines
Applied Energy, 2018Co-Authors: Jincheng Chen, Feng Wang, Kim A StelsonAbstract:With the aim of reducing green gas emission, wind turbine installations worldwide have grown rapidly in recent years. Wind energy itself is free, but has costs due to the wind turbine infrastructure and maintenance. The installation size of the wind turbine at a specific location is not only determined by the wind statistics at that location, but also by the turbine infrastructure and the maintenance cost. The payback time of the turbine is determined by the turbine cost of energy (COE). In this paper, a Mathematical Approach is proposed to minimize the turbine cost of energy based on wind statistics. Turbine annual energy production (AEP) is calculated based on turbine output power and annual wind speed distribution. A wind turbine cost model developed by U.S. National Renewable Energy Laboratory (NREL) is used for turbine cost analysis. The turbine cost of energy model includes the turbine rated power and the turbine rated wind speed. Finally a general guideline to minimize the turbine COE is presented. Three case studies are conducted to show the effectiveness of the proposed Approach.