Najdenkoski, Krste
Preferred name
Najdenkoski, Krste
Official Name
Najdenkoski, Krste
Main Affiliation
Email
krste@feit.ukim.edu.mk
14 results
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Item type:Publication, Modeling the arrangement of turbines for onshore wind power plants under varying wind conditions(Wind Integration, 2018-10); ; ; ; Fickert, LotharWind field layout optimization concerning various parameters is a major point in planning and will influence the revenue for the whole life of the installation. Besides the obvious impact of wind distribution also other parameters like connection costs and levelized costs of energy influence the optimum layout and have to be included in a realistic optimization algorithm. In this paper the sophisticated optimization of wind field layout with of two fundamentally different heuristic algorithms is investigated. To do so, detailed real-world data from an existing wind field in Bogdanci, Macedonia is utilized by employing real wind field data we are able to calibrate model adequacy and ascertain a model that will serve as a referent guidance in the planning of future onshore wind fields. Different layouts were designed using sophisticated algorithms for handling the resulting high-dimensional, highly nonlinear optimization problem. In particular, a nondominated sorting genetic algorithm (NSGA) and a mixed discrete particle swarm optimization algorithm (MD-PSO) were applied. Both optimization algorithms established bi-objective fitness functions, in particular- minimizing the levelized cost of energy and maximizing the capacity factor. By comparing the results obtained with the existing layout, it is established that both optimization algorithms are adequate in determination of wind power plant layouts. It is proven that the implementation of sophisticated optimization methods can results in essential savings during the whole lifetime of the wind field. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Fault detection under operating wind turbine through yaw misalignment conditions(MAKO CIGRE, 2019-10); ; ; In the past few years, the interest in controlling the wind turbine yaw misalignment has re emerged. The reason for this interest is the desire for maximum exploitation of wind turbines and elimination of any omission in the production of electrical energy. The operation of wind generator systems in conditions of inadequate control and compliance with direct wind direction is reflected in the reduction of electricity produced, as well as in reducing the exploitation period of the wind turbine. Accurate yaw angle measurement is a fundamental for efficient operation of the non-compliance angle control system. In wind turbines, which lack such a modern metering system, the occurrence of fatigue working conditions is becoming more and more frequent, and thus the problems and defects that occur with all mechanisms for controlling and adapting nacelle face the upcoming wind. Of particular importance to maintenance an operating wind field, is the adequate and real time detection of such an error. Frequent changes on the direction of the nacelle, or a rare adaptation of the pitch angle to a particular wind turbine have been recorded during the operation mode of one wind turbine from the Bogdanci wind field. The analysis of its operating modes, as well as the proposed solution for optimal operation, in absence of a modern measuring system to control yaw misalignment of the nacelle and the wind direction, are presented in this paper. - Some of the metrics are blocked by yourconsent settings
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Item type:Publication, Wind regimes representation modeling by using multivariable distributions(MAKO CIGRE, 2019-10); ; ; The electricity produced from one wind turbine is almost entirely dependent on the intensity of the upcoming wind. On the other hand, while making analysis of electricity production of a single wind field, equal attention should be paid to wind direction, since it defines the overall wind flow in the wind field. Accordingly, when making estimations of the expected annual production of energy from one wind field, the correlations of wind speed and direction should be appropriately taken into account. The usual practice of using Weibull distributions by a number of sectors is not the most suitable for optimization processes for defining the layout of one wind filed. For this purpose, the paper proposes a method that is simple and easy to implement, which is based on a multivariable distribution function of the parameters of the wind. For the analysis of the proposed model the measured wind data used in this paper are from one existing wind field. In addition, three stage functional distributions are obtained, which satisfactorily match the measurement data. In order to determine the matching degree of the adapted multivariable distributions with the measurement data, the quantitative parameter for error estimation - R2 was used. Various sizes of data sampling intervals are also examined in order to reduce the generation time of multiple distributions, which will not affect the quality of matching between generated distributions and measured data. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Modeling an optimal wind turbine layout by application of evolutional algorithms(MAKO CIGRE, 2019-10); ; ; Optimization of wind farm layout concerning various parameters is a major point in planning and will influence the revenue for the whole life of the installation. Besides the obvious impact of wind distribution also other parameters like connection costs and levelized costs of energy influence the optimum layout and have to be included in a realistic optimization algorithm. In this disertation the sophisticated optimization of wind farm layout with of two fundamentally different heuristic algorithms is investigated. To do so, detailed real-world data from an existing wind farm in Bogdanci, Macedonia is utilized by employing real wind farm data we are able to calibrate model adequacy and ascertain a model that will serve as a referent guidance in the planning of future onshore wind farms. The major unique feature of the research is the simultaneous optimization taking into account all major technical influence and cost factors, including: (i) detailed and advanced models for power modeling due to bivariate distribution of wind speed and direction; (ii) accurate estimation of levelized cost of energy (LCOE); (iii) analysis of the shortest electrical interconnections among wind turbines and (iv) correction of hub height on each wind turbine in the wind farm with taking also the wake effect into consideration. Different layouts were designed using sophisticated algorithms for handling the resulting high-dimensional, highly non-linear optimization problem. In particular, a non dominated sorting genetic algorithm (NSGA) and a mixed-discrete particle swarm optimization algorithm (MDPSO) were applied. Both optimization algorithms established bi-objective fitness functions, in particular- minimizing the levelized cost of energy and maximizing the capacity factor. By comparing the results obtained with the existing layout, it is established that both optimization algorithms are adequate in determination of wind power plant layouts. Results show also a remarkable improvement of 2.05% and 5.59% for levelized costs and capacity factor, respectively, compared to the as built wind farm layout. - Some of the metrics are blocked by yourconsent settings
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Item type:Publication, Energy efficiency improvements in electric drives with centrifugal load(The Union of Electronics, Electrical Engineering and Telecommunications /CEEC/, BULGARIA, 2022-12); ;