Cost Of Wind Turbines Research Articles

Closed-loop supply chain network of end-of-life wind turbines mathematical model proposal considering environmental, employment, and cost reduction aspects

The worldwide climate issue makes wind energy an attractive renewable energy source. Wind energy reduces carbon emissions, energy prices, creates jobs, improves power access, and ensures energy security. The mass of employed materials in wind turbines indicates a lot of potential raw materials when the whole mass is evaluated. Additionally, a new wind turbine costs $2–$4 million. Remanufacturing or using recycled raw materials from end-of-life wind turbines is practical due to the decreased cost of new wind turbines. To ensure sustainability, CO2 emissions and social advantages like employment must be considered. Given the typical life expectancy of wind turbines at 20–25 years, this issue must be addressed globally in the mid-term. The objective of the conducted study is to provide a multi-objective mathematical framework that encompasses the environmental, social, and economic aspects of wind turbines at the end of their operational lifespan. Hence, this study presents a methodical framework for achieving sustainability in the wind energy sector through the implementation of a closed-loop supply chain. Furthermore, a lexicographic solution approach is offered for each objective of the mathematical model, with the aim of providing decision makers with a comprehensive overview of solutions. The methodology employed in this work involves the utilization of a mixed-integer linear programming (MILP) approach to address the closed-loop supply chain for end-of-life wind turbines. Additionally, a lexicographic solution approach is provided to effectively solve the problem at hand. The novelty of this article lies in its examination of the closed loop supply chain network for end-of-life wind turbines, encompassing the social, environmental, and economic dimensions. This study represents the first of its kind to explore these aspects comprehensively. The proposed mathematical model has three objectives which cover the remanufacturing and recycling and aims to minimize CO2 emissions, unemployment, and transportation cost. In order to evaluate the proposed model, Türkiye is utilized as case with real-life data and Gurobi 9.1.2 is utilized. The locations of wind turbines could not be collected individually, and Euclidian distance was used instead of road distance due to a lack of data. These are the main limitations of the proposed study. The study revealed that the TEC and TCE lexicographic approach has the best recycling and remanufacturing cost-to-manufacturing cost ratio, 52.54 %. The least desired result is 74.50 % from CTE.

Spatial and temporal evolution of cost-competitive offshore hydrogen in China: A techno-economic analysis

China's ascendancy as the premier offshore wind power developer and principal hydrogen consumer underscores the expanding demand for green hydrogen, which is vital to its decarbonization trajectory. Offshore wind power is recognized as a crucial pathway for the future supply of green hydrogen, and further exploration of its development potential and economic viability can provide important insights for optimizing resource allocation, reducing greenhouse gas emissions, and ensuring energy security. This study analyzed the potential and regional economic differences in offshore wind energy for hydrogen production in China's coastal regions by considering the temporal evolution of techno-economic parameters and the spatial and temporal characteristics of geospatial resources. The findings suggest a potential hydrogen production capacity of 434–493 Mt/year in Chinese waters, with the average levelized cost of hydrogen projected to decline from 7.13 $/kgH2 in 2025 to 3.77 $/kgH2 by 2050, which is attributed to advancements in wind turbine technology and cost reductions in components. By 2030, hydrogen production of 40 Mt/year is expected to be cost-competitive, especially in Liaoning and Hebei, with projections indicating an increase to 435 Mt/year by 2050. Notably, floating wind power, contributing to 54 % of China's total offshore hydrogen capacity, holds significant promise for provinces such as Guangdong, Hainan, and Zhejiang. The study conclude that China's offshore hydrogen production has significant potential, with cost-competitive production achievable by 2030 and broad economic viability anticipated by 2050.

Use of Dampers to Improve the Overspeed Control System with Movable Arms for Butterfly Wind Turbines

To reduce the cost of small wind turbines, a prototype of a butterfly wind turbine (6.92 m in diameter), a small vertical-axis type, was developed with many parts made of extruded aluminum suitable for mass production. An overspeed control system with movable arms that operated using centrifugal and aerodynamic forces was installed for further cost reduction. Introducing this mechanism eliminates the need for large active brakes and expands the operating wind speed range of the wind turbine. However, although the mechanism involving the use of only bearings is simple, the violent movement of the movable arms can be a challenge. To address this in the present study, dampers were introduced on the movable arm rotation axes to improve the movement of the movable arms. To predict the behavior of a movable arm and the performance of the wind turbine with the mechanism, a simulation method was developed based on the blade element momentum theory and the equation of motion of the movable arm system. A comparison of experiments and predictions with and without dampers demonstrated qualitative agreement. In the case with dampers, measurements confirmed the predicted increase in the rotor rotational speed when the shorter ailerons installed perpendicularly to the movable arms were used to achieve the inclination. Field experiments of the generated power at a wind speed of 6 m/s (10 min average) showed relative performance improvements of 11.4% by installing dampers, 91.3% by shortening the aileron length, and 57.6% by changing the control target data. The movable arm system with dampers is expected to be a useful device for vertical-axis wind turbines that are difficult to control.

Impact of Blade Pitch Actuation System on Wind Turbine Cost and Energy Production

To minimize the levelized cost of energy (LCOE) of wind turbines, advanced co-design strategies are required that also consider the contribution of active blade pitch control to overall energy production and wind turbine cost. Thereby, the demanded closed-loop performance drives the requirements on the blade pitch actuation system, which needs to be carefully balanced. To enable this, an extended LCOE measure is developed in this paper using stochastic estimates for quantifying pitch actuation cost in terms of pitch power and closed-loop performance in terms of net energy production. Additionally, the impact of blade pitch deflections on structural loads and hence cost is evaluated considering both collective and individual pitch control. The interdependencies between the different design objectives are revealed in a case study carried out on a 25MW wind turbine, demonstrating the guidance for engineers toward cost-effective and efficient wind turbine designs.

Wind speed prediction

With the help of wind farms, wind energy is a vital renewable energy source that contributes significantly to the worlds energy balance. The lifespan and maintenance costs of wind turbines will be reduced with an accurate wind speed prediction. On the other hand, wind speed is highly volatile and unpredictable. Thus, it is essential to do research into creating complex models and algorithms for precise wind speed prediction. So far, some of the most promising models include Support Vector Machine (SVM), Artificial Neural Networks (ANN), and Autoregressive Moving Average (ARMA). Python, as an advanced and versatile programming language, is exceptionally suited for scripting the algorithms of these sophisticated models. This paper will use the data from Austin Texas and apply a Support Vector Machine (SVM) for wind speed prediction involves several stages, including data collection, data preprocessing, model selection, model training, parameter optimization, model validation, and prediction. Wind energy resource optimisation, maintenance cost reduction, and total wind farm efficiency can all be significantly improved by incorporating these models into predictive analytics and continuously improving them against changing data.

An approach for cost and configuration optimization of horizontal axis wind turbine (HAWT)

In addition to the environmental advantage of wind turbines, the modern wind turbine design is aiming to become more competitive by minimizing the cost of energy (COE). When evaluating any change to the design of a wind turbine, it is critical that the designer evaluates the impact of the design change on the system cost and performance. A typical problem when start a wind turbine design project is to determine the optimum configuration and operation parameters to minimize COE. In this article an optimization approach is adopted using COE as objective function with the rotor size, power rating and rated rotational velocity (RPM) as design variable. The cost of energy model of the National Renewable Energy Laboratory (NREL) is adopted with modifications to include the main components load level effects on the COE. An aerodynamic blade design is developed and used as base for evaluating the rotor performance. The blade is scaled to present different rotor size and operating conditions for each power rating. Analysis tool is developed to consider coupled interactions between power rating and the rotor size. The Blade Element Momentum (BEM) technique is used to evaluate the effect of configuration and operational conditions on the wind turbine load levels and the expected annual energy production (AEP). These are used as inputs for the proposed COE model in addition to main parameters presenting the manufacturing technology and site conditions. The COE model is based on several elements such initial capital cost (ICC), balance of station (BOS), operations and maintenance (O&M), levelized replacement cost (LRC), AEP and design load levels. A pattern search technique is adopted for the optimization and the approach is illustrated by means of a principle test examples for two types of turbines platform one for low wind onshore site and another for high wind offshore site.

A bi-layer wind-CCUS-battery expansion stochastic planning framework considering a source-load bilateral carbon incentive mechanism based on the carbon emission flow theory

The rapid development of low-carbon energy technologies and energy storage technologies has provided an important and feasible path to decarbonizing the power system. In this context, there is an increasing number of studies on renewable energy, carbon capture, utilization and storage (CCUS) and energy storage expansion planning. However, most of the existing studies attribute the carbon responsibilities to the source side and a small number to the load side. Expansion planning studies that consider the overall carbon emissions of the system to be shared between the source and the load side are still relatively few. Therefore, it is necessary for the source and the load side to share the responsibility for the total system carbon emissions. To fill this research gap, this paper proposes a source-load bilateral carbon incentive mechanism for wind-CCUS-battery power systems based on the carbon emission flow theory. Besides, a bi-layer wind-CCUS-battery expansion stochastic planning framework considering wind and load uncertainties is constructed. The first layer takes the minimum expectation of power generation costs, fixed investment costs of wind turbines and CCUS units and carbon incentive costs as the objective function from a source-side perspective. The second layer takes the minimum battery investment cost and the expectation of electricity purchasing costs and load-side carbon incentive costs as the objective function from a load-side perspective. Finally, the proposed model is tested on the IEEE 24 bus power system for validity and advantage. The results show that the current high investment cost is not favorable to CCUS construction. At this time, the bilateral carbon incentive mechanism is more conducive to promoting system carbon reduction than the unilateral carbon incentive mechanism. In the future, as the cost of CCUS decreases, the source-side carbon incentive mechanism is more conducive to system carbon reduction than the bilateral carbon incentive mechanism. Due to the consideration of the stochastic uncertainty of wind turbines and loads, the research in this paper is closer to the reality, which can provide a reference for the future carbon emission reduction path of the power system, especially for the quantitative analysis of carbon emission reduction of CCUS, which is an important guiding significance for the promotion of the engineering practice of CCUS.

EFFICIENCY ANALYSIS OF ELECTROMECHANICAL CONVERSION SYSTEMS OF WIND TURBINES WITH AERODYNAMIC MULTIPLICATION

In this article, we have considered the state of development of high-power horizontal wind turbines. The most common wind turbines for operation with variable wind flow speed usually include a frequency converter to ensure the compatibility of generator with network. It leads to decrease in the efficiency of wind energy conversion system, while the use of direct connection of the generator to the axis of wind wheel leads to a significant increase in the weight and cost of the generator. The wind turbine with aerodynamic multiplication is an alternative to such systems. Its prototype with 750 kW power is manufactured and studied in Ukraine. This wind energy conversion system with the synchronous or induction generators offers the property to generate energy under optimal condition with invariable rotational speed of generator rotor within the wide range of variable speed of wind flow. In this case, it is not necessary to apply the frequency converter that contributes to increasing the efficiency and reducing the cost of wind turbine. As shown, the relative performances of mass, cost and efficiency of generators in proposed system comparatively to conventional one depend on the multiplication factor (i.e. ratio of the rotational speeds of wind turbine and generator). When the power of wind turbines is from 750 to 2500 kW, the multiplication factor is within the limits of 10.72 to 4.75. The theoretical and experimental study shows that the wind turbines with aerodynamic multiplication can be competitive as compared to conventional horizontal wind turbines. This article is aimed to comparative analysis of the quantitative and qualitative characteristics of the equipment used in high-power horizontal wind turbines with direct connection of generators to the axis of wind turbine and in wind turbines with aerodynamic multiplication. References 27, tables 1, figures 6.

Techno-economic evaluation and resource assessment of hydrogen production through offshore wind farms: A European perspective

The demand for hydrogen is expected to increase radically in the coming years, as it is an important lever for decarbonization and offshore wind is a credible option for running electrolyzers. A unified and detailed cost modeling is produced from the sparse literature that considers a variety of configurations (onshore, centralized offshore, and decentralized offshore electrolysis). A resource assessment at European scale is performed by combining the developed cost modeling with a geospatial analysis considering the levelized cost of hydrogen (LCOH). Geolocated power generation as well as technical and environmental constraints are considered to improve the assessment.The results reveal enormous resources in European seas, with LCOH falling from 4.5–7.5 €/kg in 2020 to 1.5–3.0 €/kg in 2050 as the costs of wind turbines and electrolyzers decrease. More than 1000 TWh of green hydrogen could be produced at a price of less than 3.0 €/kg in 2030 and 2.0 €/kg in 2050, making it competitive with gray hydrogen. A valuable resource of 200 TWh is identified in 2030 where offshore wind-to-hydrogen projects have a much lower LCOH than their wind-to-power counterparts. The results, provided at the country level, are valuable for energy modelers and local stakeholders. Finally, a detailed cost analysis shows that offshore electrolysis is becoming more relevant over time: In 2020, offshore electrolysis is preferred only for far-from-shore and deepwater seas while in 2030 it is closer to shore (over 100 km). In 2050, onshore electrolysis is only relevant for nearshore and shallow waters.

Assessment of energy production and costs associated with a massive exploitation of wind power in the North Sea

A study to assess the potential of a massive exploitation of offshore wind power in the North Sea has been performed. The study includes both a prediction of the available wind resources and the costs associated with such a large-scale exploitation of the wind power in the North Sea. The main parameters of the model are wind turbine size, average distance between the turbines (determined from area and number of turbines), as well as wind resources (i.e. mean wind speed Weibull distribution) and water depths conditioned on specific locations within the North Sea. The cost model includes expressions for the most essential wind farm cost elements, such as costs of wind turbines, support structures, cables and electrical substations, as well as costs of operation and maintenance - all as function of wind climate, rotor size, interspatial distance between the turbines and water depth. A main outcome of the study, is that exploiting an area of 180.000 km2, corresponding to about 1/3 of the North Sea, covered with 60.000 20 MW wind turbines, may in average produce electricity corresponding to the consumption of Europe at a price of 6.2 €cents/kWh (in 2020 prices). Furthermore, more energy could actually be captured by installing the wind turbines closer to each other. As an example, doubling the average power by installing more wind turbines on the same area will increase the levelized cost of energy from 6.2 €cent/kWh to 10.1 €cent/kWh. Still, this may be relevant in case of scarcity of suitable sites for a massive exploration.

Pattern mining based data fusion for wind turbine condition monitoring

The profitability of wind turbine energy production is for an important part determined by the operation and maintenance costs of wind turbines. An important driver of these costs is currently the premature failure of components due to excessive wear. If it would be possible to accurately predict these failures, preventive maintenance can be made more effective, which should result in less downtime and expensive unexpected failures. This in turn should lower the operational and maintenance costs. The research presented here is a contribution to the research on condition monitoring and failure prediction for wind turbines. To this end, a methodology for failure prediction is designed that combines (fuses) multiple information sources (i.e. SCADA and status log data). The novelty of this research lies in the fact that pattern mining techniques are used to identify relevant rules for a rule-based failure classifier. The methodology is validated on generator bearing failure cases from a real operational wind farm. The results show that the methodology is able to predict generator bearing failures accurately well in advance. The rules on which the predictions are based are interpretable and correspond in general to expert knowledge on the matter.

Semi-supervised multivariate time series anomaly detection for wind turbines using generator SCADA data

The maintenance cost and unplanned downtime caused by faults are an important part of the operation cost of wind turbines. Supervisory control and data acquisition (SCADA) data is a multivariate time series (MTS) for monitoring the status of wind turbines, in which anomaly patterns may indicate potential faults. The existing anomaly detection methods can neither extract and process pattern information in MTS stably, nor make reasonable use of a small amount of valuable labeled data. In this paper, we propose an end-to-end semi-supervised anomaly detection model including reconstruction model, prediction model and auxiliary discriminator, with a joint objective function. Combining reconstruction model and prediction model, the unsupervised model can effectively extract the inter-variable correlation and temporal dependence of MTS data. Further, using the semi-supervised auxiliary discriminator based on adversarial training, the proposed model can integrate expert knowledge to incrementally upgrade performance from unsupervised to supervised level. Our evaluation experiments are conducted on a public server dataset and a real-world wind turbine SCADA dataset. The results show that the F1-score of unsupervised model can exceed the several state-of-the-art baseline methods by 3.86% and 2.89%, and the F1-score can be increased to 98.60% and 98.30% after using the auxiliary discriminator.© 2016 Published by Elsevier Ltd. Selection and/or peer-review under responsibility of Global Science and Technology Forum Pte Ltd

Research on the Economic Dispatch of Power Systems with a High Proportion of Renewable Energy based on Improved PSO

The penetration rate of renewable energy sources represented by wind power and photovoltaics in the power grid is increasing, adding complexity to unit dispatch. In this paper, a multi-objective optimization model is established for power systems containing wind power and photovoltaic economic dispatch. Firstly, the power generation cost of traditional units, the emission cost of traditional units, the power generation costs of wind turbines and photovoltaics, and the output characteristics of wind power and photovoltaics are analyzed. Secondly, a multi-objective economic dispatch model with the lowest power generation cost, the smallest emission cost, and the smallest power generation cost of new energy units are established, and the power flow balance constraint, supply and demand balance constraint, unit output constraint, and node voltage constraint are considered. Then the improved particle swarm algorithm is proposed to solve the multi-objective function to obtain better convergence and optimal solution. Finally, the simulation is carried out in the IEEE-30 node system and the HRP-38 system, which compares and illustrates the similarities and differences of the solution results of various algorithms under multi-objective and verifies the effectiveness of the algorithm.

Monte Carlo modeling of tornado hazard to wind turbines in Germany.

Using a Monte Carlo hazard modeling approach, this study assesses the damage and losses to wind turbines caused by tornadoes over Germany. The model combines observed climatology of tornadoes, exposure map of wind turbines and their capacities, vulnerability curve (first developed in this study), and costs of wind turbines to estimate the likelihood of financial losses of different magnitudes. The losses are presented in terms of aggregated and highest annual losses as a function of the return period. Deterministic modeling of the vulnerability function produced larger variability of the most severe losses (rare, but high-intensity events) compared to the pseudorandom sampling of the damage from the vulnerability curve. Doubling the number of current wind turbines results in smaller expected losses than installing fewer but more powerful units (repowerment). Tornadoes are most frequent in the summer months when the capacity factors of wind farms are the lowest and the electricity consumption is also lower than in the winter months. By repeatedly placing a tornado track of a fixed size over the same wind farm, we further investigated the sensitivity of our model to different parameters. The probability of tornadoes of different intensities hitting a wind turbine over Germany is also calculated.

Techno-economic assessment of electrolytic hydrogen in China considering wind-solar-load characteristics

Hydrogen production by electrolysis is considered an essential means of consuming renewable energy in the future. However, the current assessment of the potential of renewable energy electrolysis for hydrogen production is relatively simple, and the perspective is not comprehensive. Here, we established a Combined Wind and Solar Electrolytic Hydrogen system, considering the influence of regional wind-solar-load characteristics and transmission costs to evaluate the hydrogen production potential of 31 provincial-level regions in China in 2050. The results show that in 2050, the levelized cost of hydrogen (LCOH) in China’s provincial regions will still be higher than 10 ¥/kg, which is not cost-competitive compared to the current hydrogen production from fossil fuels. It is more cost-effective to deploy wind turbines than photovoltaic in areas with similar wind and solar resources or rich in wind resources. Wind-solar differences impact LCOH, equipment capacity configuration, and transmission cost composition, while load fluctuation significantly impacts LCOH and electricity storage configuration. In addition, the sensitivity analysis of 11 technical and economic parameters showed differences in the response performance of LCOH changes to different parameters, and the electrolyzer conversion efficiency had the most severe impact. The analysis of subsidy policy shows that for most regions (except Chongqing and Xizang), subsidizing the unit investment cost of wind turbines can minimize LCOH. Nevertheless, from the perspective of comprehensive subsidy effect, subsidy cost, and hydrogen energy development, it is more cost-effective to take subsidies for electrolysis equipment with the popularization of hydrogen.

Comparison of aerodynamic models for horizontal axis wind turbine blades accounting for curved tip shapes

AbstractCurved tip extensions are among the rotor innovation concepts that can contribute to the higher performance and lower cost of horizontal axis wind turbines. One of the key drivers to exploit their advantages is the use of accurate and efficient computational aerodynamic models during the design stage. The present work gives an overview of the performance of different state‐of‐the‐art models. The following tools were employed, in descending order of complexity: (i) a blade‐resolved Navier Stokes solver, (ii) a lifting line model, (iii) a vortex‐based method coupling a near‐wake model with a far‐wake model, and (iv) two implementations of the widely used blade element momentum method (BEM), with and without radial induction. The predictions of the codes were compared when simulating the baseline geometry of a reference wind turbine and different tip extension designs with relatively large sweep angle and/or dihedral angle. Four load cases were selected for this comparison, to cover several aspects of the aerodynamic modeling: steady power curve, pitch step, extreme operating gust impact, and standstill in deep stall. The present study highlighted the limitations of the BEM‐based formulations to capture the trends attributed to the introduction of curvature at the tip. This was true even when using the radial induction submodel. The rest of the computational methods showed relatively good agreement in most of the studied load cases. An exception to this was the standstill configuration, as the blade‐resolved Navier‐Stokes solver was the only code able to capture the highly unsteady effects of deep stall.

Assessment of parapet effect on wind flow properties and wind energy potential over roofs of tall buildings

Wind energy harnessing in built environment contributes to the development of sustainable cities. In this study, flow features and wind energy over roofs with various parapet heights were investigated via computational fluid dynamics simulations. Effects of normalized parapet height (hp/H = 0, 1/320, 1/160, 3/320, and 1/80) and wind angle θ were examined. Moreover, flow features and associated aerodynamic mechanisms were investigated. Effect of hp/H on flow features and wind energy potential depended on roof locations and θ. Parapets had the greatest effect on velocity and turbulence intensity at θ = 45°. At θ = 45°, the largest u occurred at large heights as hp/H increased because parapets would lift up the roof flows. The largest amplification factor of wind energy decreased linearly as hp/H increased from 0 to 1/160, whereas no obvious variations for hp/H were observed from 1/160 to 1/80. The average hub height increased from 1.13 to 1.16 as hp/H increased from 0 to 1/80, indicating potential higher installation cost of wind turbines for larger hp/H. Analysis of parapet height is required to fully assess the wind energy potential and determine the layout of rooftop wind turbines.

Wind Turbine Energy Cost Optimisation Using Various Power Models

In modern times, the worldwide wind turbine installations have developed swiftly resulting in the decrease of green gas emissions. Though wind is a free gift of nature, it is expensive to harness this energy for useful applications like electricity generation. The cost of installation of the wind turbine at a particular station does not depend only on the wind resource, but also on the structure of the turbine and the energy conversion technology. The wind turbine Cost of Energy (CoE) is used to estimate the payback time for the return on the investment made by the wind farm owners for the turbine. Meticulous research is required to optimize the turbine CoE which will make wind a very competent source of energy. In this article, in order to minimize the wind turbine CoE, the wind speed is modelled using three different distributions namely, Dagum, Gamma and Weibull and the evaluation of the turbine Annual Energy Production (AEP) is carried out. Mathematical functions such as linear, quadratic and cubic have been used to model the wind power. For the cost analysis of the turbine, the price model which was established by United States, National Renewable Energy Laboratory (NREL) is employed. The comparative study of the proposed methodology have been done for six different stations. The turbine CoE model is an element of two factors, the rated power Pr of a turbine and the rated wind speed Vr of a turbine. Based on the results obtained, a broad recommendation to reduce the turbine CoE is presented. This study enables us to figure out the minimum turbine CoE among the three discussed mathematical distributions, the finest distribution for wind speed modelling and the optimum mathematical function for wind power modelling. The suitable size of the wind turbine also can be found by optimizing the rotor radius R of the turbine for each data.

Influence of Atmospheric Turbulence on Wind Turbine’s Rotor Teeter Dynamics

Wind energy is one of the fastest-growing sources of renewable energy. The mass and the cost of a wind turbine affect the cost of energy. A two-bladed wind turbine costs less than the most popular three-bladed wind turbine since it has one blade less. Although the less cost, the rotor dynamics of a two-bladed turbine limits its use. Due to the unbalanced loads of a two-bladed turbine, the rotor has an extra system for the rotor teeter. In this work, the rotor teeter dynamics are investigated under the influence of atmospheric turbulence. The AWT-27 two-bladed wind turbine is simulated for two different turbulence intensities of the values 10% and 50% turbulence at a mean wind speed of 12 m/s. The higher turbulence intensity indicates a 400% increase in the rotor mean teeter deflection. The rotor teeter mean velocity and acceleration increase as well by the ratios of 160% and 660% respectively. This massive increase in the teeter dynamics affects the fatigue loading of the rotor and hence reduces the lifetime of the wind turbine.

Optimal sizing of hybrid Systems for Power loss Reduction and Voltage improvement using PSO algorithm: Case study of Guissia Rural Grid

This work proposes a method for sizing and reducing power losses (MSRPL) of a hybrid photovoltaic and wind system (HPWS) in a radial distribution network (RDN) by developing an objective function, thanks to particles swarm optimization (PSO). The constraints defined on the objective function has permitted us to size the photovoltaic generator, wind turbine and total production cost. The proposed system configuration (PSC) improved the voltage level and minimized the power losses (PL) in the radial network. The proposed PSO algorithm was tested on Guissia (10°30’N, 15°18’E) rural electric grid (GREG) in the far north of Cameroon, which has a radial configuration. The integration of a battery bank allowed the system to have the power factor correction and production of active and reactive power. The test on IEEE 33-bus and IEEE 69 bus showed the robustness of the system and the reliability of the proposed method which also minimized the total cost of the system over 20 years.