Local Wind Power Research Articles

The Response of the Upper Ocean to Tropical Cyclones in the South Pacific

AbstractConsecutive Argo float profiles are used to observe upper ocean changes resulting from the passage of tropical cyclones (TCs) in the South Pacific between 2001 and 2023. Cross‐sectional composites of the ocean response are produced by normalizing the distance between the profile and cyclone track by the 34‐knot wind radius (R34) of each TC to better resolve the average changes in water properties. Surface cooling in the initial mixed layer (ML) extends from the center to about twice R34 and is stronger to the left of the TC track. Subsurface warming at the base of the ML is observed between 0.4 and 2 R34 on both sides of the track. Strong cooling is observed in a distinct core directly under the TC path, reaching temperature changes of over −1.6°C between 70 and 450 m depth. Significant upwelling of over 40 m displacement is observed within ±0.05 R34, extending to 1,000 m depth. Surface cooling (and subsurface warming at the base of the ML) are positively correlated with wind stress on the ocean from the TC, quantified by the Local Wind Power Dissipation (PDL), and negatively correlated with the energy required to destratify the upper ocean, defined by a Cooling Inhibition index (CI). Subsurface warming is common with low CI but is not observed with high CI. We demonstrate an improved method to analyze Argo float data for measuring TC‐upper ocean interaction in remote oceans and the usefulness of PDL and CI in calibrating the TC‐ocean interaction.

The impacts of local wind power objection on the power system of the Midcontinent Independent System Operator area

Using the Regional Energy Deployment System (ReEDS) model, we estimate the deadweight loss imposed by county-level wind power development restrictions in the form of increased electricity costs due to suboptimal siting. This is accomplished by optimizing the power system of the United States' Midcontinent Independent System Operator (MISO) from 2020 to 2050. We perform the optimization with and without land-use constraints arising from simulated potential local ordinances restricting wind power development, and under multiple scenarios reflecting different renewable portfolio standards (RPS). We find that local restrictions on wind power increase the total system cost by 0.15%–0.3% and the wholesale electricity price by 1.8%–2.7%, depending on the RPS scenario. Changes in the generation and installed capacity mixes are more substantial and depend on both the level of county restrictions on wind power, and RPS requirements, thus indicating an interaction between RPS requirements and local wind power restrictions. We also find that plausible restrictions on wind development do not pose major barriers to meeting renewable energy targets in a cost-effective manner.

Assessment of wind energy potential within through-building openings under twisted wind flows

Integrating wind turbines into high-rise buildings can generate renewable energy on-site. Through-building openings can effectively increase the utilization of wind energy in high-rise buildings. However, current research on wind energy potential within these openings is limited to conventional wind conditions. Meteorological observations indicate that cities near mountainous terrain, such as Hong Kong and Tokyo, often experience twisted wind flows due to topography. These wind flows cause changes in the wind direction angle with increasing vertical height, and previous studies have demonstrated significant differences in flow fields around high-rise buildings in twisted wind fields as compared to conventional wind fields. Consequently, the wind energy potential within through-building openings of high-rise buildings may be significantly impacted by twisted winds. This paper applies high-fidelity methods (LES) to evaluate the wind energy potential within through-building openings of buildings with different heights under twisted wind field conditions, and compares the results with those obtained under conventional wind conditions. The results show that the passage near the inflow experiences higher wind speed and wind power compared to the passage far from the inflow under the twisted wind profile. The twisted wind flows cause an increase in local wind power density within the through-building openings, but it also results in an elevation of turbulence intensity, which is unfavorable for enhancing the efficiency of wind turbines. Furthermore, the degree of enhancement in local wind power and local turbulence intensity within the through-building openings gradually intensifies as the wind twisted angle increases.

Analysis and forecast of the substitution potential of China's wind power-hydrogen production for fossil fuel hydrogen production

The predominant utilization of fossil fuels for hydrogen production in China leads to substantial carbon emissions, posing a challenge to China's objective of achieving carbon neutrality. With the rapid development of wind power in China, hydrogen can be produced through water electrolysis powered by wind-generated electricity. This process offers the potential to gradually replace the hydrogen production from fossil fuel (grey hydrogen), thus promoting the low-carbon transformation of China's hydrogen energy industry. However, further investigation is required to determine the potential displacement of grey hydrogen through the production of hydrogen from wind power in China in the future. To address this issue, this study first obtained wind speed data for the entire China region from the MERRA-2 database. Subsequently, based on the wind speed data for each specific area, the wind turbine model with the lowest power generation cost was selected from the eight available wind turbine models. On this basis, the mixed integer linear programming method is used to construct the cost analysis model of wind power-hydrogen production (WPHP). Based on the local wind power generation data, calculations are performed to determine the optimal installed capacity of the wind turbine, electrolyzer, and hydrogen storage tank within the WPHP system. Additionally, the optimal scheduling of the WPHP system is determined. These optimizations collectively result in the best WPHP cost. Based on this research, the optimal cost of WPHP for each geographical grid in China can be calculated and compared with the local grey hydrogen cost. The analysis reveals that in some areas of Xinjiang, Gansu, and Guizhou, exhibit low costs of wind power. This suggests that the substitution of grey hydrogen with WPHP can be achieved in these areas. Based on technological progress and changes in carbon trading prices, this paper predicts that WPHP in China could potentially replace 16.35–28.69 million tons of grey hydrogen by 2040. Moreover, by 2060, WPHP in China is projected to replace 76.72–92.01 million tons of grey hydrogen. According to the sensitivity analysis conducted, it has been determined that the efficiency of the electrolyzer and the price of the wind power equipment exert the greatest impact on the cost of hydrogen production.

Wind-storage combined system based on just-in-time-learning prediction model with dynamic error compensation

High-performance wind power prediction (WPP) models can decrease the uncertainty of the whole energy system to balance energy supply and demand more effectively. However wind power process is characterized by the complicated mechanism and strong nonlinearity, which makes it difficult to establish a high-performance WPP model. In this paper, wind-storage combined system (WSCS) based on just-in-time-learning (JITL) prediction model with dynamic error compensation is proposed for high-performance WPP. This method can describe the characteristics of local wind power process efficiently and accurately by approximating the nonlinear process into a composite process with dynamic linear autoregression and static nonlinear error compensation. What's more, a WSCS model is proposed to indirectly improve the prediction accuracy. The model employs energy storage systems (ESS) to complement wind farm output to improve the wind power fluctuation and the performance of WPP. Simulation results verify that the proposed model has high prediction performance and generalization ability. Specifically, the RMSE, MAE and MAPE are 58.8728KW, 33.1277KW, 4.5877 % for gale season in a month. The RMSE, MAE and MAPE are 52.2014KW 33.2680KW, 2.3628 % for breeze season in a month. And WSCS indirectly improved the accuracy of the day-ahead prediction that reduced the RMSE from 414.4409KW to 182.2397KW. Accordingly, the research results can improve the WPP technology and reduce the redundant energy of wind power through ESS to facilitate the storage of ESS and improve the wind power fluctuation.

Comparative Analysis of Wind Farm Simulators for Wind Farm Control

This paper conducts a comparative analysis of three wind farm simulators, examining the influence of wake on the local wind speed and power output for downstream turbines using experimental data. The study features experiments in three distinct scenarios, evaluating differences among the simulators by calculating the local wind speed and power for each. Each simulator employs a unique wake model, which substantially affects the local wind speed experienced by downstream turbines. Furthermore, the experiment involves adjusting parameter values for each simulator to assess their respective impacts on wind farm performance. The findings of this research are expected to play an important role in investigations related to power optimization and wake effects in the wind farm control.

Vegetation impact on atmospheric moisture transport under increasing land-ocean temperature contrasts

Destabilization of the water cycle threatens human lives and livelihoods. Meanwhile our understanding of whether and how changes in vegetation cover could trigger transitions in moisture availability remains incomplete. This challenge calls for better evidence as well as for the theoretical concepts to describe it. Here we briefly summarize the theoretical questions surrounding the role of vegetation cover in the dynamics of a moist atmosphere. We discuss the previously unrecognized sensitivity of local wind power to condensation rate as revealed by our analysis of the continuity equation for a gas mixture. Using the framework of condensation-induced atmospheric dynamics, we then show that with the temperature contrast between land and ocean increasing up to a critical threshold, ocean-to-land moisture transport reaches a tipping point where it can stop or even reverse. Land-ocean temperature contrasts are affected by both global and regional processes, in particular, by the surface fluxes of sensible and latent heat that are strongly influenced by vegetation. Our results clarify how a disturbance of natural vegetation cover, e.g., by deforestation, can disrupt large-scale atmospheric circulation and moisture transport: an increase of sensible heat flux upon deforestation raises land surface temperature and this can elevate the temperature difference between land and ocean beyond the threshold. In view of the increasing pressure on natural ecosystems, successful strategies of mitigating climate change require taking into account the impact of vegetation on moist atmospheric dynamics. Our analysis provides a theoretical framework to assess this impact. The available data for the Northern Hemisphere indicate that the observed climatological land-ocean temperature contrasts are close to the threshold. This can explain the increasing fluctuations in the continental water cycle including droughts and floods and signifies a yet greater potential importance for large-scale forest conservation.

Winding down the wind power curtailment in China: What made the difference?

The carbon neutrality goal requires significant acceleration of the renewable energy transition. In China, this acceleration is hampered because of the concerns regarding the recent high-rate wind power curtailment. However, post-2016, wind power curtailment shows notable reductions. Therefore, it is vital to understand the fundamental factors driving such improvements, the curtailment reduction patterns across the countries and key regions, the experiences from the regional heterogeneity of curtailment reductions, and the policy implications available to strengthen wind power curtailment mitigation strategies in the short and long term to accelerate China's clean energy transition. This study constructs an evaluation framework based on the logarithmic mean Divisia index approach to investigate these concerns. Furthermore, it reveals that the eminent contributors at the national scale are local power demand, power exports, and power structures. However, the regional factor patterns oscillate significantly. In northwest China, power transmission is vital to reduce wind power curtailment. In north China, thermal power remains dominant because of its importance to national energy security, impeding its curtailment. Northeast China implements the peak-shaving auxiliary service market, promoting the power grid's capability to consume more local wind power. The fundamental settlement of the curtailment issue calls for market-oriented energy structure reforms to ensure sustainable low-carbon development. This study explains the essence of China's renewable energy development and seeks reliable paths to accelerate wind power integration with policy measures and technical transformations to enhance the adaptability of the power grid system.

Vegetation Impact on Atmospheric Moisture Transport Under Increasing Land-Ocean Temperature Contrasts

Destabilization of the water cycle threatens human lives and livelihoods. Meanwhile our understanding of whether and how changes in vegetation cover could trigger abrupt transitions in moisture regimes remains incomplete. This challenge calls for better evidence as well as for the theoretical concepts to describe it. Here we briefly summarise the theoretical questions surrounding the role of vegetation cover in the dynamics of a moist atmosphere. We discuss the previously unrecognized sensitivity of local wind power to condensation rate as revealed by our analysis of the continuity equation for a gas mixture. Using the framework of condensation-induced atmospheric dynamics, we then show that with the temperature contrast between land and ocean increasing up to a critical threshold, ocean-to-land moisture transport reaches a tipping point where it can stop or even reverse. Land-ocean temperature contrasts are affected by both global and regional processes, in particular, by the surface fluxes of sensible and latent heat that are strongly influenced by vegetation. Our results clarify how a disturbance of natural vegetation cover, e.g., by deforestation, can disrupt large-scale atmospheric circulation and moisture transport. In view of the increasing pressure on natural ecosystems, successful strategies of mitigating climate change require taking into account the impact of vegetation on moist atmospheric dynamics. Our analysis provides a theoretical framework to assess this impact. The available data for Eurasia indicate that the observed climatological land-ocean temperature contrasts are close to the threshold. This can explain the increasing fluctuations in the continental water cycle including droughts and floods and signifies a yet greater potential importance for large-scale forest conservation.

Mapping Bio-CO2 and Wind Resources for Decarbonized Steel, E-Methanol and District Heat Production in the Bothnian Bay

Hydrogen is a versatile feedstock for various chemical and industrial processes, as well as an energy carrier. Dedicated hydrogen infrastructure is envisioned to conceptualize in hydrogen valleys, which link together the suppliers and consumers of hydrogen, heat, oxygen, and electricity. One potential hydrogen valley is the Bay of Bothnia, located in the northern part of the Baltic Sea between Finland and Sweden. The region is characterized as having excellent wind power potential, a strong forest cluster with numerous pulp and paper mills, and significant iron ore and steel production. The study investigates the hydrogen-related opportunities in the region, focusing on infrastructural requirements, flexibility, and co-operation of different sectors. The study found that local wind power capacity is rapidly increasing and will eventually enable the decarbonization of the steel sector in the area, along with moderate Power-to-X implementation. In such case, the heat obtained as a by-product from the electrolysis of hydrogen would greatly exceed the combined district heat demand of the major cities in the area. To completely fulfil its district heat demand, the city of Oulu was simulated to require 0.5–1.2 GW of electrolyser capacity, supported by heat pumps and optionally with heat storages.

How well do atmospheric reanalyses reproduce observed winds in coastal regions of Mexico?

AbstractAtmospheric reanalyses are widely used for understanding the past and present climate. They have become increasingly used within the renewable energy sector for assessing wind and solar resources for different regions of the globe in conjunction with observations. Mexico is a country with considerable potential for wind energy production, especially around coastal sites and therefore the characterization of wind resource in these areas of the country is imperative for the most beneficial use of these resources. In this study, we assess how well three global reanalyses, namely ERA‐Interim, ERA5 and MERRA‐2, can reproduce wind observations at a number of key sites across the country. We find that the reanalyses' ability to reproduce these observations is highly variable between different regions in Mexico. Correlation coefficients are around 0.9 in the south of the country where the winds are strongest, but much lower (around 0.5) in Baja California Sur due to the complex coastal topography of the region. ERA5 outperforms ERA‐Interim and MERRA‐2 consistently across the vast majority of sites and so this reanalysis is recommended for local wind power studies. The consistently improved performance compared with ERA‐Interim shows the value of the increased spatial resolution of ERA5. However, in the south and east of Mexico, despite having the highest correlations, ERA5 also has the largest bias, meaning that it underestimates winds consistently across most of the country. Poor correlations between ERA5 and the observations in Veracruz are considered as a case study to understand potential drivers of low wind biases.

Transition pathways towards a deep decarbonization energy system—A case study in Sichuan, China

China has set ambitious carbon emission reduction targets to combat climate change, however, there has been little scientific focus on the achievement of deep decarbonization at the provincial level. The contradiction between rapid economic development and increasing energy utilization exacerbates the difficulty of achieving this goal. Here, we explored the feasibility of fulfilling deep decarbonization in the energy system by 2050 in Sichuan, one of the leading provinces in economic growth in China. Three transition pathways sustained by imported electricity, biomass, and natural gas were developed and simulated using the EnergyPLAN model. All the pathways utilized local hydropower, wind power, and solar photovoltaic resources. These pathways were evaluated using multi-dimensional analysis considering energy self-sufficiency, environmental sustainability, and economic affordability. We found that the energy self-sufficiency rate of the 100% electricity pathway was less than 68%, whereas those of the other pathways were nearly 100%. The CO2 emission reduction differed by pathway, with 100% electricity achieving 91.52%, biomass achieving 90.48%, and natural gas achieving 58.17%. Moreover, all the pathways achieved zero direct CO2 emissions with carbon capture and sequestration (CCS) technology. From an economic perspective, the highest system cost, i.e. 1.3 times that of the reference system, appeared in the 100% electricity pathway after introducing CCS technology, and was comparable to the energy system costs of other provinces in 2050. The methods and results of this study can serve as a basis for facilitating decarbonization in any provincial energy system in the long term.

The Impact of Low-Resource Periods on the Reliability of Wind Power Systems for Rural Electrification in Africa

Decentralized electricity systems based on variable renewable energy (VRE) sources such as wind power can provide affordable, dependable, and modern energy in a manner consistent with the Paris Agreement. Such sources are, however, sensitive to extreme values of climatic factors—an issue that may jeopardize power system reliability. As a resource-rich region with a high proportion of rural population without access to electricity, Africa has been of wide interest in studies on VRE-based electricity generation. Nevertheless, there is still a major gap in our continent-scale understanding of the wind power potential and its variability at different time scales, as well as the influence of low-wind-resource periods in Africa. Using ERA5 hourly estimates of wind speed, the present study investigated the adequacy and temporal variability of local wind power potential across Africa over the 2000–2017 period. The results indicated that design requirements of wind power systems are, on average, fulfilled in regions in the North, South, and Horn of Africa at different time scales. However, low-resource periods were shown to have a significant impact on the reliability of wind power potential in the majority of the continent. Demand flexibility can reduce the severity of these periods and help to achieve design requirements.

A techno-economic analysis of an optimal self-sufficient district

Many cities and districts have announced that their ultimate goal is to be energy self-sufficient, but there are many technical and economic challenges that are required to be studied. The aim of this study is to find cost-optimal technical solutions for districts with high energy self-sufficiency rates that can cover their electricity demand. Two methods are applied, a rule-based method and an optimization method, to find the renewable energy system capacities for local centralized wind power, solar photovoltaic, battery, heat storage and heat pump in a district with a minimum life cycle cost. The Kalasatama district in Helsinki-Finland, is taken as a case study. The results show that the full energy self-sufficiency target requires very high investments in the renewable energy systems. For the studied case, reducing the self-sufficiency rate to 76% can bring down the life cycle cost by 66% and achieve a net-zero annual energy balance. It is economically and technically more feasible to aim achieving Positive Energy District or Net-Zero Energy District instead of full energy self-sufficiency. Based on the obtained results, the main investment should be made in wind power, due to its higher utilization rate around the year compared to solar photovoltaic. Investments in the expensive centralized battery storage sharply drops when the self-sufficiency rate is reduced from 100%. It is revealed that due to the high population density and limited availability of renewables, the physical boundary of a district may not fit the required renewable energy installations if high self-sufficiency is targeted. This will frequently lead to expanding the district boundary towards a virtual balancing boundary.

Incentivising flexible power-to-heat operation in district heating by redesigning electricity grid tariffs

The Danish district heating sector constitutes a large potential for power-to-heat technology utilisation and thereby for increasing energy system flexibility and integration of the heat- and electricity sectors. Though the potential is there, it is uncertain whether the current flat-rate electricity grid tariff structure best incentivises a flexible integration. This study investigates how a redesign of the current flat-rate electricity grid tariffs influences the business-economic incentive for flexible power-to-heat operation in a district heating area, and how tariff schemes can incentivise increased integration of local wind power. The simulation tool energyPRO is used to investigate the influence of three redesigned tariff schemes; a flat-rate tariff reduction, a fixed time-of-use tariff scheme and a dynamic tariff scheme. It is concluded that the redesigned tariff schemes show potential for improving business-economic viability of flexible power-to-heat operation and increased integration of variable renewable electricity. However, measures and careful planning must be undertaken in the design of future tariff schemes to ensure that the necessary income for grid operators remains in place. The study thus suggests a redesign of the current tariff scheme and provides policymakers with tangible results of how a district heating company is affected by changes to the structure of electricity grid tariffs.

Архитектурная концепция экопоселения в Челябинской области

The aim was to develop an architectural concept of an ecovillage in the Chelyabinsk region, which meets the requirements of ecologization of the living environment. The concept is described at the 3 levels: the general layout, architectural structure and operation. A multifaceted approach was used to examine the background information, including regulatory documentation. A comparative analysis of the existing settlements and architectural structures approved for implementation was conducted. Technologies of energy-efficient architecture, urban and spatial planning, alternative energy sources were used. Foreign modern settlements and their domestic equivalents, as well as energy-efficient low-rise residential apartment buildings, were considered. The city-planning conditions of the design area, its planning constraints and climate references were described. A project proposal for the devel-oped architectural concept of an ecovillage includes urban planning site surveys, as well as an archi-tectural planning and engineering development of detached and multi-apartment residential buildings that meet the requirements of energy performance and environmental friendliness. The location of a local wind power plant was determined based on an assessment of the wind availability of wind-powered generators using the methods of computational fluid dynamics. Thus, the study demonstrates the applicability of the research findings in the development of an architectural concept of an ecovil-lage in the Chelyabinsk region in light of international best practice in ecological architecture design.

Machine Learning Techniques for Improving Self-Consumption in Renewable Energy Communities

Renewable Energy Communities consist in an emerging decentralized market mechanism which allows local energy exchanges between end-users, bypassing the traditional wholesale/retail market structure. In that configuration, local consumers and prosumers gather in communities and can either cooperate or compete towards a common objective, such as the minimization of the electricity costs and/or the minimization of greenhouse gas emissions for instance. This paper proposes data analytics modules which aim at helping the community members to schedule the usage of their resources (generation and consumption) in order to minimize their electricity bill. A day-ahead local wind power forecasting algorithm, which relies on state-of-the-art Machine Learning techniques currently used in worldwide forecasting contests, is in that way proposed. We develop furthermore an original method to improve the performance of neural network forecasting models in presence of abnormal wind power data. A technique for computing representative profiles of the community members electricity consumption is also presented. The proposed techniques are tested and deployed operationally on a pilot Renewable Energy Community established on an Medium Voltage network in Belgium, involving 2.25MW of wind and 18 Small and Medium Enterprises who had the possibility to freely access the results of the developed data modules by connecting to a dedicated web platform. We first show that our method for dealing with abnormal wind power data improves the forecasting accuracy by 10% in terms of Root Mean Square Error. The impact of the developed data modules on the consumption behaviour of the community members is then quantified, by analyzing the evolution of their monthly self-consumption and self-sufficiency during the pilot. No significant changes in the members behaviour, in relation with the information provided by the models, were observed in the recorded data. The pilot was however perturbed by the COVID-19 crisis which had a significant impact on the economic activity of the involved companies. We conclude by providing recommendations for the future set up of similar communities.

Energy management strategy of active distribution network with integrated distributed wind power and smart buildings

Aiming to achieve the flexible operation of distribution network (ADN), an energy management strategy of ADN with integrated distributed wind power and smart buildings is proposed in this study. First, based on the thermal storage characteristics of buildings, the resistor–capacitor model is used to develop an energy consumption prediction model of smart buildings. Second, the smart buildings are modelled as flexible resources of ADN. A multi-objective ADN model is further formulated based on analytic hierarchy process (AHP) by comprehensively considering constraints of power grid and smart buildings. Then, the unified model of ADN is transformed by second-order conic relaxation to guarantee the global optimal solution. Finally, the scheduling results for the unified model of ADN under different control methods for heating ventilation and air-conditioning (HVAC) systems are compared in the winter heating scenario. In addition, the impact of the demand response capability for smart buildings on the economic and secure operation of the ADN is further analysed. Numerical studies demonstrate that the proposed method can increase the penetration of local wind power, reduce peak-valley load difference and network loss of the grid while ensuring the comfort temperature of customers, and further achieve the flexible operation of ADN.

Research lift coefficient on the distance between the revolving cylinders a turbulent stream

In this paper the possibilities of using a system of revolved cylinders as part of a wind turbine are considered. The aerodynamic forces in the cross-flow of a cylinder and a system of two cylinders have been measured. A method for determining the optimal distance between the cylinders in their cross-flow has been developed. We experimentally determined the conditions under which the Magnus effect contributes to the largest increase of a lift force and, correspondingly, to the increase of the wind turbine efficiency. This can be used to create multi-bladed wind turbines of a new generation based on the Magnus effect. The aerodynamic characteristics of the cylinders with diameters 10 cm in diameter, that is the rotary motion, is determined by the maximum value with the coefficient of lifting force and the frontal impedance coefficient. These results are useful for us in practice, as these results can be used in smaller wind speed engines. In the local economy, the use of local wind power is a convenient, affordable, and environmentally friendly, with a minimal wind speed engine focused on reducing the deficit of electricity, which is one of the key issues in rural areas.

Future of Local Government Wind Power Generation System

Future of Local Government Wind Power Generation System