Wind Generation Research Articles

A synthesis of the REE-Fe-polymetallic mineral system of the REE-line, Bergslagen, Sweden: New mineralogical and textural-paragenetic constraints

Rare earth elements (REE) have gained increasing significance for numerous technologies, particularly in today’s rapidly expanding “green transition” applications such as wind generators and electric vehicle traction engines. Among the more well-known REE mineralisation types in Sweden, together with alkaline intrusions and apatite-iron oxide ores, is the classic yet enigmatic REE-Fe-polymetallic mineral system of Bastnäs-type. The mineralisation type is regional in context and occurs in a discontinuous SW-NE-striking belt (the REE-line) in the west-central part of the Palaeoproterozoic Bergslagen ore province, Sweden. This contribution is aimed at integrating and synthesising existing geological mineralogical, and textural features with new observations from both well-known and several lesser-known, underexplored or previously unrecognised REE-enriched occurrences within this belt, and to discuss key features within the context of mineral systems modelling. A considerable diversity in both the style and abundance of REE mineralisation as well as in discrete REE mineralogy is evident both regionally across the entire REE-line and locally within different ore districts or mine fields. These variations also extend laterally within or across different stratigraphic levels, and within different host rocks, primarily skarn-altered metacarbonates but also variably altered felsic metavolcanic rocks. Many of the mineralisations share similar textural features, which record a protracted evolution with multiple stages of formation or replacement of REE-minerals. The earliest recognised REE assemblages feature fine-grained cerite-(CeCa) with minor bastnäsite-(Ce) – bastnäsite-(La) or fluorbritholite-(Ce) – fluorbritholite-(Y) or locally britholite-(Ce) – britholite-(Y) minerals. Such assemblages typically display anhedral-granoblastic textures appearing in folded assemblages, all suggesting recrystallisation and ductile deformation during regional metamorphism of REE-minerals that had formed during an early stage of the Svecokarelian orogeny. Overprinting overgrowths and cross-cutting vein-like features of allanite-group minerals likely represent different stage(s) of REE mineralisation and (re)-mobilisation during this orogenic evolution. Several of the REE-enriched occurrences contain variably abundant and diverse polymetallic Cu-Mo-Bi-(Co) sulphide mineralisation that typically occur in late paragenetic positions and show a prevalence to REE-rich assemblages, often dominated by different allanite-group minerals. Sulphide and REE mineralisation are locally strongly associated with metamorphic minerals formed during metamorphism of variably Mg-(Fe)-altered metavolcanic rocks. The diversity in style and intensity of the REE mineralisations, along with variations in textures and specific mineralogy, suggest slight differences in the ore-forming conditions or environment at the time of mineralisation. Additionally, these differences may also reflect variations in the preservation or modification processes that operated later in the evolution of the Svecokarelian orogeny, also featuring remobilisation of REEs and sulphidic minerals. The insights gained from all available evidence synthesised herein, from micro-scale to province-scale, help define key proxies for prospectivity mapping. The combined evidence supports that the primary ore-forming stages in the mineral system coincided with felsic volcanism and associated sub-volcanic to plutonic processes at around 1.9 Ga.

The monster mechanical delusion: nineteenth-century controversies concerning perpetual motion

Abstract The history of attempts to make a perpetual motion machine is not (just) the saga of irrational efforts to defy the laws of thermodynamics. In the eighteenth-century Enlightenment there were good reasons to believe in perpetual growth both in Nature and the economy, just as the planets and Sun appeared to move perpetually in the heavens. Why not machines also? In nineteenth-century Britain numerous purported perpetual motion devices were patented and promoted as potential investments in unbounded energy sources. While such frauds were finally prevented by a change in law in 1932 that rendered patents for perpetual motion devices impermissible the lessons learned from six centuries of failed attempts to deliver practical forms of perpetual motion gave some of the strongest evidence to support the First and Second Laws of Thermodynamics. In the twenty-first century the energy industry’s solar, wind, geothermal and tidal power generation can now secure effectively free energy to move our machinery for the indefinite future.

Joint intelligent optimizing economic dispatch and electric vehicles charging in 5G vehicular networks

In recent years, with the rapid development of 5G networks, the road traffic network composed of vehicles with different energy sources has become more and more complex, and the problems of environmental pollution and road congestion have also become increasingly serious. Electric vehicles are favored by people due to their environmental protection and energy-saving characteristics. However, improper charging dispatching will cause excess energy in charging stations, affecting the power grid and road traffic, such as energy shortages and lower traffic throughput. Therefore, how to design a reasonable charging strategy that can maximize the user’s charging satisfaction and consume the energy of the charging station as much as possible becomes a challenge. Meanwhile, this strategy should consider power economic dispatch to reduce power generation costs and polluting gas emissions. With the support of 5G’s high-bandwidth and low-latency characteristics, this paper designs an intelligent charging model which indirectly reflects the charging satisfaction through the time cost, energy consumption cost, charging cost, and the user’s range anxiety, while consuming the remaining energy of the charging station as much as possible. Due to the uncertainty of wind and photovoltaic power generation, this paper proposes a two-stage economic dispatch model to improve the accuracy of power dispatch and reduce power generation costs and carbon emissions. Due to the highly variable traffic environment and energy demand, we employ proximal policy optimization-based deep reinforcement learning algorithms to realize electric vehicle charging dispatching and charging station power dispatching. Numerical results show the efficiency of our proposed strategy for electric vehicle charging in terms of the convergence speed.

Optimal solution of multiobjective stable environmental economic power dispatch problem considering probabilistic wind and solar PV generation

The Environmental Economic Power Dispatch (EEPD) problem, a widely studied bi-objective nonlinear optimization challenge in power systems, traditionally focuses on the economic dispatch of thermal generators without considering network security constraints. However, environmental sustainability necessitates reducing emissions and increasing the penetration of renewable energy sources (RES) into the electrical grid. The integration of high levels of RES, such as wind and solar PV, introduces stability issues due to their uncertain and intermittent nature. This paper addresses these concerns by formulating and solving the Stable Environmental Economic Power Dispatch (SEEPD) problem, which includes fixed zonal reserve capacity from conventional thermal generators and uncertain reserves from RES. Uncertainties in RES and load demand are modeled using random variable generation techniques, applying Gaussian, Weibull, and log-normal probability density functions (PDFs) for load demand, wind velocity, and solar irradiance, respectively. The stochastic SEEPD problem extends to multiple periods by replicating the single-period problem for each interval in the planning horizon, linking periods through intertemporal ramping costs, physical ramp rate, and fixed zonal reserve constraints on dispatch variables. Multi-Objective Evolutionary Algorithms (MOEAs) have gained importance for solving complex nonlinear problems involving multi-objective functions. This paper applies the latest MOEAs to tackle the proposed SEEPD problem, incorporating stochastic wind and solar PV power sources. Network security constraints, such as transmission line capacities and bus voltage limits, are considered along with constraints on generator capabilities and intertemporal spinning reserves, ramp-up and ramp-down constraints for thermal generators. A bidirectional coevolutionary-based multi-objective evolutionary algorithm is employed, integrating an advanced constraint-handling technique to ensure compliance with system constraints. The simulation results show that the proposed formulation achieves a better trade-off between various conflicting objective functions compared to other state-of-the-art MOEAs.

Electromagnetic plasma micro actuator for active airflow control

This study presents a novel electromagnetic plasma micro actuator capable of generating ionic wind at an extremely low voltage. Ionic and electron movements, driven by the Lorentz force, introduce a lateral injection of initiation carriers, resulting in a significant reduction in discharge onset voltage. Straight ionic wind was demonstrated using a tapered gap electrode, which allowed continuous movement of plasma filament along the electrode at the speed of 4m/s when a DC pulse of 900V was applied. The results suggest that the proposed device may address key challenges faced by current ionic wind generators, such as high voltage requirements and limited device lifespans. In addition, a notable change in the airflow was observed when the direction of ionic wind was altered, indicating the feasibility of active airflow control with stable plasma formation and fast response times.

Fluid flow and heat transfer of a novel passive cooling system for gearless wind turbines with a power range of 3–12 MW

Today, the gearless horizontal axis wind turbines are mainstream in wind energy industry. High demands of electric power led to bigger systems and active cooling reduces the overall efficiency of the turbines. Passive cooling systems have been examined for the first time for a gearless wind energy generator with power range of 3–12 MW. With further developed heat conductors, it is possible to operate a wind generator in a larger power class with passive cooling components. This is accompanied by enormous cost savings due to elimination of costs for active cooling elements such as the use of fans, pumps, and heat exchangers. An additional factor is the significant reduction in necessary maintenance due to the minimized incidence of corrosion and wear. Design of the cooling fins and an ideal position of the generator within the housing of the wind turbine has been objectives. Mandatory is that maximum temperatures of the generator fins should stay under 155 °C, which could be reached with several designs for different heat exchanger geometries.

Reducing Overall Active Power Loss by Placing Solar and Wind Generators in a Distribution Power System using Wild Horse Optimizer Algorithm

This study optimized the locations and sizes of wind-based distributed generators (WDGs) and solar photovoltaic-based distributed generators (PVDGs) to reduce the overall active power loss (OAPL) of an IEEE 85-bus distribution power system (DPS). Three meta-heuristic algorithms, including the Wild Horse Optimizer Algorithm (WHOA), the Archimedes Optimization Algorithm (AOA), and the Transient Search Optimization (TSO) algorithm, were applied and compared to each other to identify the most effective method for finding the best value of OAPL. Based on the analysis, WHOA outperformed the other methods in achieving the best value of OAPL according to different criteria. Additionally, the effectiveness of WHOA was compared with previous studies, while WHOA also proved its strength in reducing overall losses, decreasing grid power, and improving voltage profiles. Moreover, the effectiveness of WHOA was tested for a 24-hour period with varying loads and the addition of PVDGs and WDGs. The results indicated that WHOA could successfully determine the optimal positions of both PVDGs and WDGs in Case 3, Case 4.1, and Case 4.2, achieving the optimal value of OAPL in the selected DPS, decreasing grid power utilization, and improving the voltage profile. In conclusion, WHOA proved itself to be an effective optimization tool for dealing with large-scale optimization problems

Optimal Coordination of Hybrid AC/DC Microgrids based on IEEE-12 Bus System: An Analytical Approach

Recently, the microgrid's design and implementation techniques have placed a significant emphasis on alternating current (AC) systems. Due to their many benefits, DC microgrids are becoming more and more popular than AC microgrids. The benefits include the elimination of frequency modulation and the requirement for synchronization. DC microgrids are better suited for distributed energy resources (DERs) and DC loads. When it comes to hybrid microgrids, the options are practical and reasonably priced. Graphical depictions of the voltage profiles, wind generation, and total PV generation show how the system operates and performs. The removal of power converters between AC, DC systems is the cause of this. This article suggests an analytical approach for the best possible coordination between AC, DC microgrids using the IEEE 12 bus system.

Implementation Joule Thief Buck-Boost Converter in A Neodymium Wind Power Plant

Wind power generation is gaining popularity as an environmentally friendly renewable energy source. However, the output voltage of a wind generator usually varies according to the wind speed, requiring a power converter to produce a stable DC voltage. The author of this research aims to implement a Joule Thief Buck-Boost Converter on a neodymium wind power generation system. Joule Thief is a DC-DC converter that has the ability to convert a low input voltage into a higher output voltage, and can maintain a relatively stable output voltage despite changes in the input voltage. In this study, a Joule Thief buck-boost converter is used to regulate the output DC voltage of the neodymium wind generator to remain stable despite the changing wind speed. System testing is done by measuring the output voltage of the neodymium wind power plant. The test results show that the Joule Thief Buck-Boost Converter can maintain the output DC voltage at a stable value of 14V at input voltages above 3V, so the implementation of this converter in neodymium wind power plants is proven effective in producing a stable DC voltage. This research is expected to contribute to the development of a more efficient and reliable wind power generation system.

Short-Term Hydro-Wind-PV peak shaving scheduling using approximate hydropower output characters

With the massive construction of wind and photovoltaic (PV) power plants, the uncertainty of their output poses challenges for grid peak regulation. Hydropower, characterized by convenient regulation, fast response speed, and low cost, is an ideal choice for compensating for wind and PV energy generation. Mixed-Integer Linear Programming (MILP) is employed to work out short-term scheduling of hydro-wind-PV power. However, considering hydropower scheduling alone is already highly complex, and incorporating the deviations in wind and PV energy further reduces the solution efficiency. In practical scheduling, operators often rely on empirical scheduling methods that can yield satisfactory results. To enhance solution quality and improve the scalability and efficiency of the MILP method, a short-term optimization scheduling model for hydropower plants has been proposed and applied to the Hongshui River cascade system. The case study shows that the model can perform calculations in just 2 s, demonstrating extremely high computational efficiency. This can significantly enhance decision-making in cascaded hydropower scheduling. At the same time, the model leaves sufficient reserve capacity to address the uncertainty of wind and solar power output while reducing the residual load by 0.8 %, which is beneficial for the stable operation of the grid.

Ocean wave and wind power harnessed by hybrid nanogenerator

Charge self-shuttling improves power density for combined wind and water wave energy generators.

Tracking performance and power quality enhancement of DFIG based wind turbine using robust integral terminal sliding mode control

The aim of this work is to develop a robust Integral Terminal Sliding Mode Control (ITSMC) strategy for a Doubly Fed Induction Generator (DFIG) wind turbine (WT) operating in challenging conditions. This controller is designed to manage the system's rotor side converter (RSC) and grid side converter (GSC), ensuring maximum power production, improved power quality, and accurate tracking of system state variables, even in the face of fluctuating wind conditions, parameter uncertainties, and external disturbances. The stability of the proposed controller is assured using the Lyapunov theory. The performance of ITSMC is compared with that of the conventional sliding mode controller (SMC) and backstepping controller through simulation tests, using the integral absolute error (IAE) as a performance metric. The results highlight the superiority of ITSMC, demonstrating its ability to precisely track reference values, eliminate static errors, and minimize chattering. ITSMC consistently achieves the lowest IAE for all tracked state variables and across all test scenarios. A comparative study analyzing the Total Harmonic Distortion (THD) of the proposed controller versus SMC, the backstepping controller, and other similar works in the literature shows a marked improvement in the THD of stator and filter currents by at least 24.53 % and 7.96 %, respectively. These findings underscore the controller's capability to enhance the power quality delivered to the grid.

A comprehensive review on crack detection schemes and modelling techniques in high-speed rotor systems

ABSTRACT The combination of a rotor and bearings plays a pivotal role in various industrial applications, including gas turbines, compressors, turbochargers, aircraft engines, and wind generators. Ensuring the structural integrity of the rotor-bearing assembly during static and dynamic conditions is most important, as any failure could lead to unpredictable losses. Due to their continuous operation, high-speed rotors are more susceptible to faults such as misalignment, bow, eccentricity, and cracks. Among these faults, cracks are the most predominant fault that affects the system’s reliability. Despite significant advancements in rotor dynamics, cracks still threaten the integrity and performance of the rotor-bearing assembly. This review paper aims to thoroughly review the challenges and issues associated with crack formation in high-speed rotor systems. Various crack detection methods are also explored using vibration signals obtained from the rotor-bearing unit and their associated processing techniques. This study also gives an extensive overview of different crack modelling and analysis techniques. Furthermore, a novel rotor-bearing model is modelled using the finite element method, and the numerical results obtained from this model are validated with the existing literature model. This review paper will serve as a valuable resource for researchers that offers insights into the latest advancements and emphasises the importance of crack detection for ensuring the reliability of high-speed rotor systems.

Hybrid local energy markets: Incorporating utility function-based peer risk attributes, renewable energy integration, and grid constraints analysis

This study proposes a novel hybrid Local Energy Market (LEM) trading framework meticulously designed for efficient energy trading among distribution network participants. The proposed LEM hybrid modeling framework aims to maximize social welfare by considering the behavior of market participants and incorporating network constraints into the transactional framework. To address the consumption behavior of market participants, the concept of the utility function with peer risk attributes is employed, differentiating between flexible and inflexible demands. Additionally, it adeptly manages various generation types, including diesel generators, wind and solar generators, and storage, each characterized by a unique cost function. The investigation extends to the analysis of the Japan Electric Power Exchange market (JEPX), taking into account the residential electricity demand in Tokyo, Japan, by comparing with community-based (CB) and peer-to-peer (P2P) markets and scrutinizing market player behavior across multiple scenarios. These scenarios include comparisons of different market structures, variations in prices, considerations of grid constraints, and diverse weather scenarios. The proposed framework undergoes rigorous evaluation utilizing the IEEE 33-bus and 69-bus standard test systems, with results demonstrating its practicality, superiority of the proposed market compared to the CB and P2P markets, and providing valuable insights into the intricate interplay between market players’ behavior and the dynamics of diverse market structures, price fluctuations, grid constraints, and weather scenarios.

Diverse decarbonization pathways under near cost-optimal futures

Energy system optimization models offer insights into energy and emissions futures through least-cost optimization. However, real-world energy systems often deviate from deterministic scenarios, necessitating rigorous uncertainty exploration in macro-energy system modeling. This study uses modeling techniques to generate diverse near cost-optimal net-zero CO2 pathways for the United States’ energy system. Our findings reveal consistent trends across these pathways, including rapid expansion of solar and wind power generation, substantial petroleum use reductions, near elimination of coal combustion, and increased end-use electrification. We also observe varying deployment levels for natural gas, hydrogen, direct air capture of CO2, and synthetic fuels. Notably, carbon-captured coal and synthetic fuels exhibit high adoption rates but only in select decarbonization pathways. By analyzing technology adoption correlations, we uncover interconnected technologies. These results demonstrate that diverse pathways for decarbonization exist at comparable system-level costs and provide insights into technology portfolios that enable near cost-optimal net-zero CO2 futures.

How Fisheries Biologists Can Facilitate the Clean Energy Transition

Fisheries and aquatic biologists play a critical role in creating environmentally protective hydropower flow requirements that govern flow timing, frequency, magnitude, and rate of change. Hydropower's role in the U.S. electrical grid is expected to evolve in response to increased wind and solar generation as hydropower will be called upon to quickly ramp up and down in response to changes in wind and solar generation. For this reason, hydropower is expected to have increased value as fossil generation is phased out, even as rapid flow fluctuations linked with hydropower flexibility may strand fish, alter habitat, and create unsafe recreational conditions. We face a new challenge in facilitating the renewable energy transition—designing environmental flow requirements that protect against the impacts of flow fluctuations while allowing adequate hydropower flexibility to support a stable grid. In this paper, we discuss hydropower environmental flow requirements, operational flexibility, and electrical grid stability, their potential interactions, and opportunities to align environmental and power system needs to support healthy ecosystems, multiple water uses, and decarbonization of the electric grid.

Electromagnetic and Mechanical Stress Analysis of a 5 MW High-Pole Non-Overlap Winding Wound-Rotor Synchronous Wind Generator

Electromagnetic and Mechanical Stress Analysis of a 5 MW High-Pole Non-Overlap Winding Wound-Rotor Synchronous Wind Generator

El impacto de las energías renovables sobre el precio mayorista de la electricidad

Rationale Renewable electricity generation capacity is rising significantly in Spain. Given the merit order pricing system used in the wholesale electricity market, this could have profound implications for electricity price dynamics. Takeaways •The share of wind and solar energy in total electricity generation increased from 26% in 2019 to over 40% in 2024 H1. In the first half of this year, wholesale electricity prices were more than 40% lower than they would have been had wind and solar generation remained at 2019 levels. •The model estimated in this article suggests that under the renewable generation deployment scenarios envisaged in the update of the National Energy and Climate Plan, wholesale electricity prices could drop by an additional 50% by 2030. •In any event, the future behaviour of these prices is subject to considerable uncertainty, influenced by various supply-side factors and how demand responds to the new levels of renewable generation.

Probabilistic co‐expansion planning for natural gas and electricity energy systems with wind curtailment mitigation considering uncertainties

AbstractIn response to growing reliance on electricity and gas systems, this paper introduces a stochastic bi‐level model for the optimized integration of these systems. This integration is achieved through sizing and allocating of power‐to‐gas (P2G) and gas‐to‐power (G2P) units. The first level of the model focuses on decisions related to P2G and G2P unit installations, while the second level addresses optimal system operation considering decisions made from first level and stochastic scenarios. The primary aim is to enhance energy‐sharing capabilities through coupling devices and mitigate wind generation curtailment. An economic evaluation assesses the model's effectiveness in reducing costs. N − 1 contingency analysis gauges the integrated system's ability to supply load under emergency conditions. Two new indices, performance of the electricity system and performance of the natural gas system, are proposed for N − 1 contingency analysis. These indices quantify the proportion of the supplied load to the total load, thereby illustrating the system's capacity to meet demand. For numerical investigation, the proposed model is applied to a modified IEEE 14‐bus power system and a 10‐node natural gas system. Numerical results demonstrate a 9.426% reduction in investment costs and a significant 10.6% reduction in wind curtailment costs through proposed planning model.

Time-domain harmonic state estimation of three-phase power networks including wind generation sources

Time-domain harmonic state estimation of three-phase power networks including wind generation sources