scholarly journals Wind Farm Cable Connection Layout Optimization with Several Substations

Energies ◽  
2021 ◽  
Vol 14 (12) ◽  
pp. 3615
Author(s):  
Adelaide Cerveira ◽  
Eduardo J. Solteiro Pires ◽  
José Baptista
Keyword(s):  
Energy Production ◽  
Wind Farm ◽  
Programming Model ◽  
Optimal Solution ◽  
Wind Farms ◽  
Green Energy ◽  
Fossil Energy ◽  
Proposed Model ◽  
Short Time ◽  
Cable Connection

Green energy has become a media issue due to climate changes, and consequently, the population has become more aware of pollution. Wind farms are an essential energy production alternative to fossil energy. The incentive to produce wind energy was a government policy some decades ago to decrease carbon emissions. In recent decades, wind farms were formed by a substation and a couple of turbines. Nowadays, wind farms are designed with hundreds of turbines requiring more than one substation. This paper formulates an integer linear programming model to design wind farms’ cable layout with several turbines. The proposed model obtains the optimal solution considering different cable types, infrastructure costs, and energy losses. An additional constraint was considered to limit the number of cables that cross a walkway, i.e., the number of connections between a set of wind turbines and the remaining wind farm. Furthermore, considering a discrete set of possible turbine locations, the model allows identifying those that should be present in the optimal solution, thereby addressing the optimal location of the substation(s) in the wind farm. The paper illustrates solutions and the associated costs of two wind farms, with up to 102 turbines and three substations in the optimal solution, selected among sixteen possible places. The optimal solutions are obtained in a short time.

scholarly journals Inter-annual variability of wind climates and wind turbine annual energy production

2018 ◽  
Author(s):  
Sara C. Pryor ◽  
Tristan J. Shepherd ◽  
Rebecca J. Barthelmie
Keyword(s):  
Standard Deviation ◽  
Wind Energy ◽  
Wind Turbine ◽  
Energy Production ◽  
Wind Farm ◽  
Wind Farms ◽  
Wind Speeds ◽  
Annual Variability ◽  
Eastern Usa

Abstract. Inter-annual variability (IAV) of expected annual energy production (AEP) from proposed wind farms plays a key role in dictating project financing. IAV in pre-construction projected AEP and the difference in 50th and 90th percentile (P50 and P90) AEP derives in part from variability in wind climates. However, the magnitude of IAV in wind speeds at/close to wind turbine hub-heights is poorly constrained and maybe overestimated by the 6 % standard deviation of annual mean wind speeds that is widely applied within the wind energy industry. Thus there is a need for improved understanding of the long-term wind resource and the inter-annual variability therein in order to generate more robust predictions of the financial value of a wind energy project. Long-term simulations of wind speeds near typical wind turbine hub-heights over the eastern USA indicate median gross capacity factors (computed using 10-minute wind speeds close to wind turbine hub-heights and the power curve of the most common wind turbine deployed in the region) that are in good agreement with values derived from operational wind farms. The IAV of annual mean wind speeds at/near to typical wind turbine hub-heights in these simulations is lower than is implied by assuming a standard deviation of 6 %. Indeed, rather than in 9 in 10 years exhibiting AEP within 0.9 and 1.1 times the long-term mean AEP, results presented herein indicate that over 90 % of the area in the eastern USA that currently has operating wind turbines simulated AEP lies within 0.94 and 1.06 of the long-term average. Further, IAV of estimated AEP is not substantially larger than IAV in mean wind speeds. These results indicate it may be appropriate to reduce the IAV applied to pre-construction AEP estimates to account for variability in wind climates, which would decrease the cost of capital for wind farm developments.

scholarly journals Assessing the effect of wind farms in fauna with a mathematical model

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Pablo Refoyo Román ◽  
Cristina Olmedo Salinas ◽  
Benito Muñoz Araújo
Keyword(s):  
Mathematical Model ◽  
Renewable Energy ◽  
Wind Turbines ◽  
Energy Production ◽  
Wind Farm ◽  
Considerable Increase ◽  
Wind Farms ◽  
Mathematical Algorithm ◽  
The World

Abstract Energy production by wind turbines has many advantages. The wind is a renewable energy that does not emit greenhouse gases and has caused a considerable increase in wind farms around the world. However, this type of energy is not completely free of impact. In particular, wind turbines displace and kill a wide variety of wild species what forces us to plan their location well. In any case, the determination of the effects of wind farms on fauna, especially the flying one, is difficult to determine and depends on several factors. In this work, we will try to establish a mathematical algorithm that allows us to combine all variables that affect the species with the idea of quantifying the effect that can cause the installation of a wind farm with certain characteristics in a given place. We have considered specific parameters of wind farms, the most relevant environmental characteristics related to the location of the wind farm, and morphological, ethological and legal characteristics in the species. Two types of assessment are established for the definitive valuation. Total Assessment and Weighted Assessment. Total Valuation is established based on a reference scale that will allow us to establish categories of affection for the different species while Weighted valuation allows us to establish which species are most affected.

scholarly journals DFIG use with combined strategy in case of failure of wind farm

2020 ◽  
Vol 10 (3) ◽  
pp. 2221
Author(s):  
Azeddine Loulijat ◽  
Najib Ababssi ◽  
Mohammed Makhad
Keyword(s):  
Wind Power ◽  
Wind Turbines ◽  
Wind Farm ◽  
Reactive Power ◽  
Low Voltage ◽  
Voltage Drop ◽  
Optimal Solution ◽  
Wind Farms ◽  
Electrical Networks ◽  
Constant Frequency

In the wind power area, Doubly Fed Induction Generator (DFIG) has many advantages due to its ability to provide power to voltage and constant frequency during rotor speed changes, which provides better wind capture as compared to fixed speed wind turbines (WTs). The high sensitivity of the DFIG towards electrical faults brings up many challenges in terms of compliance with requirements imposed by the operators of electrical networks. Indeed, in case of a fault in the network, wind power stations are switched off automatically to avoid damage in wind turbines, but now the network connection requirements impose stricter regulations on wind farms in particular in terms of Low Voltage Ride through (LVRT), and network support capabilities. In order to comply with these codes, it is crucial for wind turbines to redesign advanced control, for which wind turbines must, when detecting an abnormal voltage, stay connected to provide reactive power ensuring a safe and reliable operation of the network during and after the fault. The objective of this work is to offer solutions that enable wind turbines remain connected generators, after such a significant voltage drop. We managed to make an improvement of classical control, whose effectiveness has been verified for low voltage dips. For voltage descents, we proposed protection devices as the Stator Damping Resistance (SDR) and the CROWBAR. Finally, we developed a strategy of combining the solutions, and depending on the depth of the sag, the choice of the optimal solution is performed.

scholarly journals Wind Farm Layout Upgrade Optimization

Energies ◽  
2019 ◽  
Vol 12 (13) ◽  
pp. 2465 ◽  
Author(s):  
Mamdouh Abdulrahman ◽  
David Wood
Keyword(s):  
Energy Production ◽  
Wind Farm ◽  
Lower Cost ◽  
Wind Farms ◽  
Offshore Wind ◽  
General Representation ◽  
Thrust Coefficient ◽  
Wind Farm Layout ◽  
Cost Of Energy ◽  
Wide Range

The problem of optimally increasing the size of existing wind farms has not been investigated in the literature. In this paper, a proposed wind farm layout upgrade by adding different (in type and/or hub height) commercial turbines to an existing farm is introduced and optimized. Three proposed upgraded layouts are considered: internal grid, external grid, and external unstructured. The manufacturer’s power curve and a general representation for thrust coefficient are used in power and wake calculations, respectively. A simple field-based model is implemented and both offshore and onshore conditions are considered. A genetic algorithm is used for the optimization. The trade-off range between energy production and cost of energy is investigated by considering three objective functions, individually: (1) annual energy production; (2) cost of added energy; and (3) cost of total energy. The proposed upgraded layouts are determined for the Horns Rev 1 offshore wind farm. The results showed a wide range of suitable upgrade scenarios depending on the upgraded layout and the optimization objective. The farm energy production is increased by 190–336% with a corresponding increase in the total cost by 147–720%. The external upgrade offers more energy production but with much more cost. The unstructured layouts showed clear superiority over the grid ones by providing much lower cost of energy.

Analysis of Wind Turbine Capacity Factor Improvement by Correcting Yaw Error Using LIDAR

2017 ◽  
Author(s):  
Roozbeh Bakhshi ◽  
Peter Sandborn
Keyword(s):  
Energy Production ◽  
Wind Farm ◽  
Production Capacity ◽  
Wind Farms ◽  
Power Production ◽  
Capacity Factor ◽  
Offshore Wind ◽  
The Common ◽  
Turbine Capacity ◽  
The Cost

Yaw error is the angle between a turbine’s rotor central axis and the wind flow. The presence of yaw error results in lower power production from turbines. Yaw error also puts extra loads on turbine components, which in turn, lowers their reliability. In this study we develop a stochastic model to calculate the average capacity factor of a 50 turbine offshore wind farm and investigate the effects of minimizing the yaw error on the capacity factor. In this paper, we define the capacity factor in terms of energy production, which is consistent with the common practice of wind farms (rather than the power production capacity factor definition that is used in textbooks and research articles). The benefit of using the energy production is that it incorporates both the power production improvements and downtime decreases. For minimizing the yaw error, a nacelle mounted LIDAR is used. While the LIDAR is on a turbine, it collects wind speed and direction data for a period of time, which is used to calculate a correction bias for the yaw controller of the turbine, then it will be moved to another turbine in the farm to perform the same task. The results of our investigation shows that although the improvements of the capacity factor are less than the theoretical values, the extra income from the efficiency improvements is larger than the cost of the LIDAR.

Scheduling and Routing Optimization of Maintenance Fleet for Offshore Wind Farms Using Duo-ACO

2014 ◽  
Vol 1039 ◽  
pp. 294-301 ◽  
Author(s):  
Zhen You Zhang
Keyword(s):  
Wind Farm ◽  
Optimal Solution ◽  
Wind Farms ◽  
Daily Basis ◽  
Offshore Wind ◽  
Offshore Wind Farms ◽  
Routing Optimization ◽  
Renewable Power ◽  
Operation And Maintenance ◽  
The Cost

Wind energy is one of the fast growing sources of renewable power production currently and there is a great demand to reduce the cost of operation and maintenance to achieve competitive energy price in the market especially for offshore wind farms. An offshore wind farm usually comprises a large number of turbines and thus needs a number of service vessels for maintenance. It is already a complicated task to plan the schedule and route for each of the vessels on a daily basis, dealing with several constraints, such as weather window and maintenance demand, at the same time. Even more challenging is to find an optimal solution. This paper propose a method, i.e. Duo Ant Colony Optimization (Duo-ACO), to improve the utilization of the maintenance resources, specifically the efficient scheduling and routing of the maintenance fleet and thus reduce the operation and maintenance (O&M) cost. The proposed metaheuristic method can help operator to avoid a time-consuming process of manually planning the scheduling and routing.

scholarly journals MULTI-PERSON SELECTION OF THE BEST WIND TURBINE BASED ON THE MULTI-CRITERIA INTEGRATED ADDITIVE-MULTIPLICATIVE UTILITY FUNCTION

2014 ◽  
Vol 20 (4) ◽  
pp. 590-599 ◽  
Author(s):  
Vygantas Bagočius ◽  
Edmundas Kazimieras Zavadskas ◽  
Zenonas Turskis
Keyword(s):  
Wind Turbine ◽  
Wind Farm ◽  
Wind Farms ◽  
Green Energy ◽  
Offshore Wind ◽  
Modern World ◽  
Multiple Use ◽  
Flexible Tool ◽  
Major Purpose ◽  
Offshore Area

Energy generation and savings is a vital problem for the social and economic development of a modern world. The construction of wind farms is a challenge of crucial importance to Lithuania. Offshore wind farms are one of the possibilities of the multiple use of marine space. Wind energy industry has become the fastest growing renewable energy in the world. An offshore wind farm is considered one of the most promising sources of green energy towards meeting the EU targets for 2020 and 2050. They provide long-term green energy production. The major purpose of this study is the selection and ranking of the feasible location areas of wind farms and assessing the types of wind turbines in the Baltic Sea offshore area. Multi-criteria decision making methods represent a robust and flexible tool investigating and assessing possible discrete alternatives evaluated applying the aggregated WSM and WPM method namely WASPAS. The following criteria such as the nominal power of the wind turbine, max power generated in the area, the amount of energy per year generated in the area, investments and CO2 emissions have been taken into consideration.

scholarly journals Simulation Based Investigation of the Impact of Information Sharing on the Offshore Wind Farm Installation Process

2017 ◽  
Vol 2017 ◽  
pp. 1-11 ◽  
Author(s):  
Moritz Quandt ◽  
Thies Beinke ◽  
Abderrahim Ait-Alla ◽  
Michael Freitag
Keyword(s):  
Resource Availability ◽  
Information Acquisition ◽  
Wind Farm ◽  
Wind Farms ◽  
Limited Resource ◽  
Energy Generation ◽  
Green Energy ◽  
Offshore Wind ◽  
Offshore Wind Farms ◽  
The Impact

In the recent decades, the introduction of a sustainable and green energy infrastructure, and, by this, the reduction of emissions caused by fossil energy generation, has been focused on by industry-oriented nations worldwide. Among the technologies of renewable energy generation, wind energy has the highest deployment rate, due to the high wind resource availability and the high technology maturity reached mainly by the onshore installation of wind turbines. However, the planning and the installation of offshore wind farms are a challenging task, because of harsh weather conditions and limited resource availability. Due to the current practice of decentralised information acquisition by the supply chain partners, we investigate the impact of sharing information on the installation process of offshore wind farms by means of a simulation model. Therefore, relevant information items will be identified in order to improve the installation process.

scholarly journals Research on a Comprehensive Maintenance Optimization Strategy for an Offshore Wind Farm

Energies ◽  
2021 ◽  
Vol 14 (4) ◽  
pp. 965
Author(s):  
Yang Lu ◽  
Liping Sun ◽  
Yanzhuo Xue
Keyword(s):  
Wind Farm ◽  
Wind Farms ◽  
Weather Conditions ◽  
Offshore Wind ◽  
Monte Carlo Algorithm ◽  
Maintenance Cost ◽  
Offshore Wind Turbine ◽  
Offshore Wind Farm ◽  
Proposed Model ◽  
Maintenance Activities

Offshore wind is considered a crucial part in the future energy supply. However, influenced by weather conditions, the maintenance of offshore wind turbine system (OWTs) equipment is challenged by poor accessibility and serious failure consequences. It is necessary to study the optimized strategy of comprehensive maintenance for offshore wind farms, with consideration of the influences of incomplete equipment maintenance, weather accessibility and economic relevance. In this paper, a Monte Carlo algorithm-improved factor is presented to simulate the imperfect preventive maintenance activity, and waiting windows were created to study the accessibility of weather conditions. Based on a rolling horizon approach, an opportunity group maintenance model of an offshore wind farm was proposed. The maintenance correlations between systems and between equipment as well as breakdown losses, maintenance uncertainty, and weather conditions were taken into account in the model, thus realizing coordination of maintenance activities of different systems and different equipment. The proposed model was applied to calculate the maintenance cost of the Dafengtian Offshore Wind Farm in China. Results proved that the proposed model could realize long-term dynamic optimization of offshore wind farm maintenance activities, increase the total availability of the wind power system and reduce total maintenance costs.

scholarly journals Establishing Regional Power Sustainability and Feasibility Using Wind Farm Land-Use Optimization

Land ◽  
2021 ◽  
Vol 10 (5) ◽  
pp. 442
Author(s):  
Anne A. Gharaibeh ◽  
Deema A. Al-Shboul ◽  
Abdulla M. Al-Rawabdeh ◽  
Rasheed A. Jaradat
Keyword(s):  
Land Use ◽  
Wind Turbine ◽  
Wind Farm ◽  
Smart Cities ◽  
Optimal Solution ◽  
Wind Farms ◽  
Regional Power ◽  
Area Of Interest ◽  
Land Use Optimization ◽  
Planning Optimization

Wind-farm planning optimization is important for decision-making concerning regional energy planning in developing countries. This process is governed by restrictions on site selection based on land suitability metric variables, wind turbine technology variables, and land-use governing criteria. This study aims to create a framework for land appropriation strategies for locating optimum sites suitable for wind farms. It is using Jordan as an Area of Interest (AOI), where the scope is to illustrate how this framework will employ wind turbine energy to positively enhance the national Gross Domestic Product (GDP). The methodology employs thirteen GIS thematic layers with a 250-m spatial resolution to substantiate how site-specific criteria, turbine type, and turbine hub height variables are determining factors in the optimal solution. This method involves selecting relevant factors, database construction, data layer generation and preparation, numerical ranking and weighting of each factor, and computation of the potential wind farm locations map by overlaying all the thematic GIS layers. The results showed that the establishment of wind farms would not only meet the AOI’s growing energy needs, rather exceed them to generating income for the developing nation. The results of the feasibility study will boost the national GDP by 3.4%; where, for example, one governorate alone could produce 274.3% of the total required national consumption at a turbine hub height of 50 m. The study attests to a valuable framework that can be implemented elsewhere to establish regional power sustainability and feasibility for other nations. The results show that an added land-use layer indicating the potential value of land in terms of its suitability for establishing wind farms should be considered in future sustainable regional planning studies when considering networks for smart cities, industrial cities, smart agriculture, and new agglomerations.

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