Wind Power Research Articles

Research on short-term optimization and scheduling of multi-energy complementary systems based on forecast scenario dynamic correction

The inherent unpredictability and instability of renewable energy sources, such as wind and solar power, hinder the precise execution of power generation plans in complementary systems, posing significant challenges to their integration into power grids. Therefore, this study proposes a dynamic correction method for wind and solar output forecast scenarios in the short-term scheduling of wind-solar-hydro complementary systems. The method utilizes statistical analysis of forecast errors in wind and solar power outputs to characterize uncertainty patterns across different forecast levels and constructs a typical forecast scenario set based on single-day forecasts. This approach probabilistically models each scenario according to the temporal migration patterns of wind and solar power outputs and develops a neural network-based dynamic correction fusion model to refine the forecasts. Application of this method in a case study of the Yalong River Basin demonstrated that, after applying dynamic correction to the forecast scenarios, the mean absolute error in total wind and solar output predictions during the wet and dry seasons was reduced by 50.73 % and 47.95 %, respectively. Additionally, the dynamic correction reduced the maximum residual load on typical wet and dry days by 82.70 % and 62.37 %, respectively, and decreased the total intraday residual electricity by 91.17 % and 73.24 %, compared to single-day forecasts. The study concludes that the proposed dynamic correction method enhances power system stability and improves power generation efficiency and reliability.

Assessing the Techno-enviro-economic viability of wind farms to address electricity shortages and Foster sustainability in Palestine

This study critically examines the feasibility of wind turbines in addressing electricity shortages in the coastal region of Palestine. Assessing technical, economic, and environmental aspects offers vital insights for sustainable energy solutions. Hence, 10 turbines with different rated powers were selected to determine the optimal and economically viable solution. Wind velocities were assessed at altitudes of 10, 65, and 80 m. Various performance indicators such as wind power density, capacity factor (Cf), anticipated energy yield, cost of wind-generated electricity, benefit-cost ratio (BCR), and simple payback period were examined. The findings indicate that the Siemens SWT-2.3-93 turbine yields an annual energy production of 3910.3 MWh. The Lagerwey-LW58/750 turbine boasts the highest capacity factor at 20.5 % making it the most cost-effective option with generation costs of $0.0604/kWh to $0.0825/kWh. It exhibited the highest benefit-cost ratio, ranging from 1.287 to 1.758, and payback period of 6.33 years. Consequently, the Lagerwey-LW58/750 turbine emerges as the optimal choice for implementing the wind power plant project in Palestine's coastal region. The use of wind turbines to generate electricity leads to 3323.75 ton/year of emissions reduction. This research provides crucial insights for decision-makers aiming to tackle electricity shortages and enhance environmental sustainability in Palestine's energy sector.

Solar Energy Resource and Power Generation in Morocco: Current Situation, Potential, and Future Perspective

The world’s attention is currently focused on the energy transition to sustainable energy. The drive to reduce greenhouse gas emissions in order to limit global warming, energy security, and the generalization of access to energy have contributed to the adoption of the Moroccan Energy Strategy, with a strong focus on renewable energy (RE). Morocco is notoriously poor in conventional primary fossil energy resources, with energy dependence on the order of 90%. In addition, the energy crisis that resulted from the COVID-19 pandemic and geopolitical conflicts, compounded with steady increase in demand, has heavily affected the security and stability of the country’s energy situation. The transition to RE by strongly engaging in the implementation of several solar, wind, and hydro energy projects has made the country the leader in RE in Africa. These projects benefit from the country’s excellent solar and wind energy potential. As a consequence, by 2030, the share of RE in the installed capacity is expected to reach 52%. An overview of the current situation of RE (particularly solar energy) in Morocco is provided, including the potentials, obstacles, challenges, and future perspectives. Thanks to its high solar potential, it is predictable that Morocco’s effort will be focused on this field: the Erasmus plus INNOMED project is a virtuous example of international cooperation, aiming at promoting solar energy through capacity building and the creation of solar energy networks, in synergy with EU Partners.

Harvesting multidirectional wind energy based on flow-induced vibration triboelectric nanogenerator with directional tuning mechanism

Wind-induced vibration (WIV), as low-velocity wind energy utilization technology in agricultural environment, has significant advantages. Nevertheless, there is a mismatch between the variability of wind direction and the work mode of triboelectric nanogenerator (TENG), which leads to a sharp decline in the performance of triboelectric power generation. This work proposes a TENG based on multidirectional WIV (TENG-WIV), which mainly contains triboelectric power generation unit, guide-wing and triboelectric direction sensor. By introducing the directional tuning mechanism based on guide-wing, the TENG-WIV aims to break the constraints of single wind direction response and effectively respond to the wind direction within 360° range, thereby realizing multidirectional wind energy harvesting and sensor power supply. The empirical findings indicate that the output voltage and current of triboelectric power generation unit are in the ranges of 62–241 V and 0.25–1.21 μA, respectively, at the wind velocities of 1.23–5.13 m/s. At a wind velocity of 3.18 m/s, the unit achieves an out-power peak of 0.09 mW. Furthermore, the triboelectric direction sensor can respond to changes in 8 directions and has wind direction monitoring potentiality. The directional tuning mechanism endows flow-induced vibration energy harvesters with an all-around multidirectional sensitivity.

A Multi-Decadal Hourly Coincident Wind and Solar Power Production Dataset for the Contiguous United States

As renewable energy continues its rapid expansion in the Unites States, multi-decadal hourly datasets of electricity production are needed to asses reliability and resource adequacy of power grids. Recent years have seen the release of grid-cell-level simulated meteorological variables, however these are not extended to the power domain, are not developed from a dynamically consistent numerical weather model, and only cover a historical baseline of less than a decade. To fill this gap, this work provides a dataset of 43 years of coincident plant-level wind and solar power production data. The dataset is designed to be aggregated to appropriate scales of interest for bulk system studies such as Balancing Authorities (BAs), states, and nodes of a production cost model. The dataset covers every plant in the contiguous U.S. that is reported in the U.S. Energy Information Administration (EIA) Form 860 as of 2020. When compared with the EIA-923 monthly generation, we find minimal bias (less than 5%). When compared with BA-reported hourly generation, we find low bias in solar (less than 7%), and slight underdispersion in wind. This coincident multi-decadal historical dataset provides a documented and evaluated multi-resource baseline for studies on reliability, resource adequacy, climate change impacts, and characterization of emergent climate threats on renewable resources.

Protection of rotor side converter of doubly fed induction generator based wind energy conversion system under symmetrical grid voltage fluctuations

This paper presents the protection of the rotor side converter in a grid-connected doubly fed induction generator (DFIG)-based wind energy conversion system (WECS) during a symmetrical voltage dip. In order to manage rotor current and regulate DC link voltage, an efficient active crowbar protection circuit is implemented in the rotor side converter (RSC). To improve the low-voltage ride-through capability for grid-connected wind turbine systems, an integrated DFIG-based WECS role is crucial because wind turbines must remain connected to the utility grid during faults to ensure continuity and reliability of power supply. This paper aims to design and implement an efficient active crowbar protection technique to protect the RSC and avoid excessive rotor current during a symmetrical voltage dip. Therefore, the efficient active crowbar protection circuit is designed using MATLAB-Simulink software, and its performance is validated using a real-time (RT) simulator. Finally, the existing methods are compared with the proposed work outcomes, and a conclusion is made.

Addressing VAWT Aerodynamic Challenges as the Key to Unlocking Their Potential in the Wind Energy Sector

While the wind turbine industry has been primarily dominated by horizontal-axis wind turbines, the forefront of knowledge of these turbines has revealed significant challenges in various aspects, including manufacturing, structural design, cost, and maintenance. On the other hand, the advantages associated with Darrieus vertical-axis wind turbines (VAWTs) demonstrate significant potential that can address the existing challenges of the wind turbine industry. Current work aims to investigate the practicality of this potential for the wind energy sector. To this end, the benefits of employing Darrieus turbines for domestic and industrial applications, isolated operation, and on/offshore windfarm applications have been explored. It is apparent that Darrieus VAWTs are better suited to a wide range of environments, whether they are deployed in isolation or integrated systems, and whether they are utilized on a small or large scale. Darrieus VAWTs are adaptable to urban unsteady variable wind, are less expensive on large scales, provide higher power density at the windfarm level, and provide stability for offshore platforms. Nevertheless, challenges remain in fully harnessing VAWT potential rooted in their complex aerodynamics. This serves as a primary challenge for VAWTs to address the challenges of the wind turbine industry in line with the 2050 roadmap.

Optimization of offshore wind farm cluster transmission system topology based on Stackelberg game

Offshore wind energy is pivotal in the global energy transition, with a global installed capacity reaching 64.3 GW by 2022 and an expected annual increase of 60.2 GW over the next decade. This study aims to optimize the topology of transmission systems (TS) for offshore wind farm (OWF) clusters using Stackelberg game theory. The OWF investor (OWFI) acts as the leader, optimizing investment returns while considering wake effects, and the offshore TS operator (OTSO) follows by adjusting transmission strategies to reduce costs. The analysis includes the wake effects within OWF clusters and their impact on power generation efficiency. Simulation results demonstrate that the proposed model can balance stakeholder interests and enhance the economic viability of OWF clusters, showing a potential increase in net present value (NPV) by up to 30 %. This study validates the practical application of the Stackelberg game model in optimizing OWF cluster TS topology, contributing to more efficient and cost-effective renewable energy integration.

Power generation mix in Colombia including wind power: Markowitz portfolio efficient frontier analysis with machine learning

The Colombian power market is hydro-dominated since 67 % of the power produced comes from hydro-power sources. In addition, it has thermal power from natural gas and coal, and in the last years, alternative energy sources such as wind and solar have been introduced, although so far their share is not significant. Due to this condition, the Colombian power market is very volatile and depends on weather conditions. Usually, in rainy seasons prices are low and power is available, while in dry seasons, prices are high and power can be scarce. One of the main advantages of the new energy sources is that they are complementary to hydro-power, in the case of wind regimes, they are higher during dry seasons and lower during rainy seasons. We propose a complementarity analysis in the energy mix using Markowitz Portfolio analysis to determine if the efficient frontier is improved by introducing wind power to the system and the traditional port-folio analysis is improved by introducing Machine Learning (ML) into calculations. Results show that wind power improves the return while minimizing risk. Therefore, wind power would significantly reduce prices in Colombia's power mix while reducing volatility. This work follows the Open Innovation (OI) paradigm, the intersection of Machine Learning, portfolio optimization, and renewable energy presents a promising landscape for research and practical applications. Continued interdisciplinary collaboration and innovation are essential for harnessing the full potential of these technologies for a sustainable energy future.

GERICS supporting climate-resilient wind energy sites

GERICS supporting climate-resilient wind energy sites Dr. Irem Isik Cetin and Dr Elke Keup-Thiel offer expert insights on how GERICS supports the climate-resilient development of wind energy sites. Since the oil crisis in 1973, the use of modern wind turbines has clearly grown. By 2023, the installed capacity of wind energy globally surpassed 1 terawatt (TW). (1) With low costs and high emission reduction potential (2), wind energy has emerged as one of the most promising options for moving towards a low-carbon energy transition. For this reason, after COP28, more than 200 countries aimed to triple renewable energy capacity.

Method for Wind–Solar–Load Extreme Scenario Generation Based on an Improved InfoGAN

In recent years, extreme events have frequently occurred, and the extreme uncertainty of the source-demand side of high-ratio renewable energy systems poses a great challenge to the safe operation of power systems. Accurately generating extreme scenarios related to the source-demand side under a high percentage of new power systems is vital for the safe operation of power systems and the assessment of their reliability. However, at this stage, methods for extreme scenario generation that fully consider the correlation between wind power, solar power, and load are lacking. To address these problems, this paper proposes a method for extreme scenario generation based on information-maximizing generative adversarial networks (InfoGANs) for high-proportion renewable power systems. The example analysis shows that the method for extreme scenario generation proposed in this paper can fully explore the correlation between historical wind–solar–load data, greatly improve the accuracy with which extreme scenarios are generated, and provide effective theories and methodologies for the safe operation of a new type of power system.

Sustainable mega-seaports with integrated multi-energy systems: Life-cycle environmental and economic evaluation

Ports play a critical role in modern society by acting as crucial links between water and land transportation, and integrating transportation with energy systems. This integration results in a high demand for various types of energy uses, with polluting emissions produced by the diverse energy sources. Integrated renewable energy systems represent promising solutions to achieving high levels of energy supply while lowering carbon footprints. In this research, a framework is proposed for a port multi-energy system that encompasses solar energy, wind energy, a hydrogen system and a number of energy storage systems. The proposed framework is tailored for implementation at Ningbo Zhoushan Port, the largest port globally. Different system design schemes are compared based on the number and rated power of wind turbines. Then, a comprehensive life-cycle economic and environmental assessment of the system is conducted through simulation. The economic and environmental metrics such as LCOE, REF and CO2 emissions are considered. The outcomes demonstrate that the design scheme incorporating two wind turbines with high rated power outperforms others in both environmental and economic metrics. Over the life-cycle, the renewable energy fraction exceeds 72%, and the levelized cost of energy plummets to 0.46 yuan/kWh. The implementation of the proposed port integrated multi-energy system yields substantial environmental and economic benefits. Specifically, it allows for a reduction of 66.68% in CO2 emissions and a cost reduction of 70.94%. These outcomes highlight the potential that the proposed system holds for enhancing environmental sustainability and economic efficiency within the port context.

ENERGY MANAGEMENT IN HYBRID PV-WIND-BATTERY STORAGE-BASED MICROGRID USING DROOP CONTROL TECHNIQUE

The paper presents an efficient energy management system designed for a small-scale hybrid microgrid incorporating wind, solar, and battery-based energy generation systems using the droop control technique. The heart of the proposed system is the energy management system, which is responsible for maintaining power balance within the microgrid. The EMS continuously monitors variations in renewable energy generation and load demand and adjusts the operation of the energy conversion systems and battery storage to ensure optimal performance and reliability. The primary objective of the energy management system is to maintain power balance within the microgrid, even in the face of fluctuations in renewable energy generation and load demand. This involves dynamically adjusting the operation of the renewable energy sources and battery storage system to match the instantaneous power requirements of the microgrid. Overall, the paper presents a comprehensive approach to designing and implementing an efficient energy management system for a small-scale hybrid wind-solar-battery-based microgrid to extract maximum profit from electricity generation. By integrating renewable energy sources with energy storage and advanced control algorithms, the proposed system aims to enhance the reliability, stability, and sustainability of the microgrid's power supply.

Research on Electric Hydrogen Hybrid Storage Operation Strategy for Wind Power Fluctuation Suppression

Research on Electric Hydrogen Hybrid Storage Operation Strategy for Wind Power Fluctuation Suppression

Corrosivity Control Inside Offshore Wind Power Turbines by Combined Dehumidification and Overpressure

Corrosivity Control Inside Offshore Wind Power Turbines by Combined Dehumidification and Overpressure

Superconducting cable with energy storage function and its potential for next-generation power system compatible with large-scale renewable energy installation

Abstract The mass introduction of renewable energy is essential to realize a sustainable society. On the other hand, when photovoltaic (PV) and wind power generation are used as main power sources in a power system, it is indispensable to compensate for their severe output fluctuations up to the rating of the power system; however, this is difficult to achieve with conventional energy storage devices alone. To solve this problem, we have proposed a superconducting cable with energy storage function and its use in a DC power system. This cable provides large inertia to the power system without the need for additional energy storage equipment; as a result, the power system itself become capable of high-speed and high-power compensating operations for output fluctuations from renewable energy sources. This paper summarizes our recent works on this research topic: an overview of the proposal, conceptual design of the cable, experimental verification of the principle, and positive effects on the energy use efficiency of renewable energy. For example, an experiment with the use of a small model cable showed the capability of high-speed charge–discharge operations at a high power up to the rating of the microgrid. It was also showed that such a function was indispensable for real-time use of electric power from PV power generation resulting in significant enhancement of energy use efficiency of renewable energy. These results suggest that this concept hold the key to next-generation power systems enabling massive use of renewable energy in the future society.

Ultra-Short-Term Wind Farm Power Prediction Considering Correlation of Wind Power Fluctuation

Accurate ultra-short-term power prediction for wind farms is challenging under rapid wind speed fluctuations, complicating production planning and power balancing. This paper proposes a new method considering spatial and temporal correlations of wind fluctuations among adjacent wind farms. The method first calculates the time difference between power fluctuations based on wind speed, direction, and relative positions, determining the prior information period. The variational Bayesian model is then used to extract implicit relationships between power fluctuations of adjacent wind farms, enabling power prediction during the prior information period. Finally, the non-prior information period is predicted to complete the ultra-short-term power prediction. Using measured data from three wind farms in Fujian Province, compared to other models, the method demonstrates improved accuracy by effectively leveraging the power fluctuation characteristics of adjacent wind farms, and it has a certain amount of generalizability.

Enhanced control of grid-connected multi-machine wind power generation systems using fuzzy backstepping approaches

This research paper presents an approach for enhancing the performance of a multi-machine wind power generation system (WPGS) through the combination of nonlinear and intelligent control techniques. The suggested approach focuses on optimizing the WPGS, which utilizes permanent magnet synchronous generators (PMSGs) interconnected with the grid. To enable grid connection, a back-to-back configuration is employed for both the rectifier and inverter in a fifteen-switch configuration, with control achieved through pulse width modulation. The designed control algorithm is designed to effectively regulate the system and reduce the active and reactive power ripples. Initially, the WPGS model is provided. Subsequently, the fuzzy backstepping control (FBC) law is detailed, incorporating the Lyapunov stability technique. Fuzzy logic is used to adapt the gains in the backstepping approach, ensuring the control system can accommodate disturbances and system variations. As a result, this adaptive control approach enables optimal effusiveness of the entire system in both static and dynamic operational regimes. Experimental tests were conducted using MATLAB to compare the efficacy of the designed strategy against the traditional backstepping control approach. The obtained results demonstrated the robustness and effective reference tracking capabilities of the designed FBC approach, along with the complete elimination of speed overshoot across diverse wind conditions. These findings validate the designed control approach's effectiveness and superiority over the BC approach under varying conditions.

Wind Rose Analysis of Temperature Variation with Sensor Implantation Technique for Wind Turbine

This study focuses on analysing the impact of seasonal variations in heat on different parts of a "wind energy system," serving as a representative mechanical system. The proposed methodology utilizes wind rose analysis, offering a straightforward means to assess heat transfer effects, applicable to any mechanical system comprising numerous small heat-dissipating components. Furthermore, this work elucidates the correlation between mechanical component performance and heat dissipation impact, providing breakdown alerts for various wind turbine components. Additionally, it analyses the influence of mechanical part temperatures on energy generation, highlighting how high temperatures can indicate component deterioration, such as bearing damage. Notably, the study focuses on wind speeds ranging from 10 to 15 m/s, a typical operational range for wind turbines. By employing wind rose charts and real-time readings, the graded heat dissipating potential of mechanical parts under various wind velocities and weather conditions is determined. Moreover, the study emphasizes the significance of heat transfer analysis in optimizing wind turbine performance, demonstrating how temperature differentials between mechanical components and the environment, along with increased surface area, affect heat transfer. The proposed analysis underscores the importance of considering heat's impact on each mechanical component in tandem with seasonal environmental temperature fluctuations. The wind rose methodology, integrated with sensor implantation, emerges as a cost-effective tool for studying -level heat variances in mechanical systems, enabling the development of heat profiles for future turbine designs and computational fluid dynamics (CFD) analyses. As heat transfer coefficient increases the wind turbine performance decrease. The heat transfer coefficient decreases 14.28% from rainy to winter season and 42.85% from winter to summer season. The wind rose analysis provides valuable insights into wind patterns and characteristics at a specific location, which can inform decision-making in various fields such as energy, construction, environmental management, and safety planning. As the turbine temperature increases the wind velocity decreases. Here it decreases 28 % from rainy to winter season.

Can combined wind and solar power meet the increased electricity load on heatwave days in China after the carbon emission peak? A case study in southern Hebei

Wind and photovoltaic (PV) power are the fastest-growing renewable energy sources; however, they are vulnerable to weather extremes. In the context of global warming, the frequency of extreme weather events, particularly heatwaves (HW), is anticipated to increase. Compared to normal summer days, HW days not only cause a rise in electricity demand but also exhibit a complementary growth in wind/PV generation. Therefore, determining whether the increase in wind/PV generation on HW days can meet the corresponding surge in electricity load is pivotal for replacing fossil fuel-based electricity. To address this question, this study conducts a case study for southern Hebei Province, which has the highest combined wind/PV installations in China, for the period 2031–2040 under the scenario that China will achieve its carbon peak (2030) and carbon neutrality goals as planned. We use recently developed load and wind power models and calibrate a boosting ensemble learning model to simulate PV generation. The results reveal that the total increase in wind/PV generation on HW days can fully meet the total increase in electricity consumption starting in 2039. However, due to the uneven distribution of wind/PV generation and load changes throughout the HW days, 9 GWh of energy storage capacity is required to ensure electricity supply in the early morning hours. Under China's climate change adaptation strategy, Hebei Province can harness wind/PV energy to address peak load demands during HW conditions and initiate climate-resilient urban development pilot projects.