Sub-national variability of wind power generation in complex terrain and its correlation with large-scale meteorology

The future European electricity system will depend heavily on variable renewable generation, including wind power. To plan and operate reliable electricity supply systems, an understanding of wind power variability over a range of spatio-temporal scales is critical. In complex terrain, such as that found in mountainous Switzerland, wind speeds are influenced by a multitude of meteorological phenomena, many of which occur on scales too fine to capture with commonly used meteorological reanalysis datasets. Past work has shown that anticorrelation at a continental scale is an important way to help balance variable generation. Here, we investigate systematically for the first time the possibility of balancing wind variability by exploiting anticorrelation between weather patterns in complex terrain. We assess the capability for the Consortium for Small-scale Modeling (COSMO)-REA2 and COSMO-REA6 reanalyses (with a 2 and 6 km horizontal resolution, respectively) to reproduce historical measured data from weather stations, hub height anemometers, and wind turbine electricity generation across Switzerland. Both reanalyses are insufficient to reproduce site-specific wind speeds in Switzerland's complex terrain. We find however that mountain-valley breezes, orographic channelling, and variability imposed by European-scale weather regimes are represented by COSMO-REA2. We discover multi-day periods of wind electricity generation in regions of Switzerland which are anticorrelated with neighbouring European countries. Our results suggest that significantly more work is needed to understand the impact of fine scale wind power variability on national and continental electricity systems, and that higher-resolution reanalyses are necessary to accurately understand the local variability of renewable generation in complex terrain.ISSN:1748-9326ISSN:1748-931

Wind Energy Development Under Military Airspace

Wind is a valuable renewable resource supporting a rapidly growing wind energy industry. Executive Order 13212, signed by President George W. Bush in 2001, tasks the Departments of the Interior, Energy, Agriculture, and Defense to work together in support of wind energy development on public lands in the eleven western states. Over 28% of the land area in the eleven western states that is suitable for wind energy production lies under U.S. military training airspace. Since the wind turbines are vertical obstructions to both Special Use Airspace (SUAS) and military training routes (MTRs), this level of geospatial convergence threatens to reduce the viability of this valuable renewable resource. Technological innovation and modernization within the wind energy industry have pushed wind turbine heights higher into the airspace, beyond the minimum altitudes of some training airspace. This geospatial convergence creates a significant potential for encroachment. To support Executive Order 13212, while protecting training airspace from encroachment, this project assesses the geospatial relationship between military training airspace and wind energy development in the eleven western states. In follow-on analysis, this project transitions from the regional eleven western states perspective to a focus on the Fallon Range Training Complex (FRTC) in northern Nevada, analyzing 17 areas of interest (AOI) and assessing the potential for encroachment. The objective of the FRTC analysis is to further examine the encroachment conditions around the FRTC and quantify potential encroachment scenarios. The client is Navy Captain Scott Ryder, the Commanding Officer of Naval Air Station Fallon who is responsible to a large extent for the oversight of northern Nevada’s military training airspace. From the perspective of the client, this project yields valuable knowledge and an improved geospatial understanding of the physical relationship between wind energy development and military training airspace. That knowledge and understanding will be directed towards the development of the most appropriate management policy and procedures. This project effectively predicts the amount of wind energy related encroachment that could occur within the study areas. It also identifies the most likely encroachment points around the FRTC perimeter, where encroachment will most likely occur, and from what direction it will likely come. The project effectively demonstrates fundamental GIS problem solving concepts, integrating many relevant factors, and demonstrating the power and advantage of GIS. This analysis presented in this project does not limit wind energy development, but identifies potential encroachment as well as where wind energy developers should focus and where they should limit their exploration

Wind and wind power ramp variability over Northern Mexico

The seasonal and diurnal variability of the wind resource in Northern Mexico is examined. Fourteen weather stations were grouped according to the terrain morphology and weather systems that affect the region to evaluate the impact on wind ramps and high wind persistent events. Four areas driven by weather systems seasonality are identified. Wind power ramps and persistent generation events are produced by cold fronts in winter, while mesoscale convective systems and local circulations are dominant in summer. Moreover, the 2013 wind forecast of the RAP and NAM forecast systems were also assessed. In general both systems have less skill to predict mesoscale events and local circulations over complex topography, underestimating strong winds and overestimating weak winds. Wind forecast variations in the mesoscale range are smoother than observations due to effects of spatial and temporal averaging, producing fewer wind power ramps and longer lasting generation events. The study carried out shows the importance of evaluating operational models in terms of wind variability, wind power ramps and persistence events to improve the regional wind forecast. The characteristics of weather systems and topography of Mexico requires model refinements for proper management of the wind resource

Spatio-temporal estimation of wind speed and wind power using machine learning: predictions, uncertainty and technical potential

The growth of wind generation capacities in the past decades has shown that wind energy can contribute to the energy transition in many parts of the world. Being highly variable and complex to model, the quantification of the spatio-temporal variation of wind power and the related uncertainty is highly relevant for energy planners. Machine Learning has become a popular tool to perform wind-speed and power predictions. However, the existing approaches have several limitations. These include (i) insufficient consideration of spatio-temporal correlations in wind-speed data, (ii) a lack of existing methodologies to quantify the uncertainty of wind speed prediction and its propagation to the wind-power estimation, and (iii) a focus on less than hourly frequencies. To overcome these limitations, we introduce a framework to reconstruct a spatio-temporal field on a regular grid from irregularly distributed wind-speed measurements. After decomposing data into temporally referenced basis functions and their corresponding spatially distributed coefficients, the latter are spatially modelled using Extreme Learning Machines. Estimates of both model and prediction uncertainties, and of their propagation after the transformation of wind speed into wind power, are then provided without any assumptions on distribution patterns of the data. The methodology is applied to the study of hourly wind power potential on a grid of 250 by 250 squared meters for turbines of 100 meters hub height in Switzerland, generating the first dataset of its type for the country. The potential wind power generation is combined with the available area for wind turbine installations to yield an estimate of the technical potential for wind power in Switzerland. The wind power estimate presented here represents an important input for planners to support the design of future energy systems with increased wind power generation.Comment: 45 pages, 21 figures. Stoch Environ Res Risk Assess (2022

Spatio-temporal estimation of wind speed and wind power using extreme learning machines: predictions, uncertainty and technical potential

With wind power providing an increasing amount of electricity worldwide, the quantification of its spatio-temporal variations and the related uncertainty is crucial for energy planners and policy-makers. Here, we propose a methodological framework which (1) uses machine learning to reconstruct a spatio-temporal field of wind speed on a regular grid from spatially irregularly distributed measurements and (2) transforms the wind speed to wind power estimates. Estimates of both model and prediction uncertainties, and of their propagation after transforming wind speed to power, are provided without any assumptions on data distributions. The methodology is applied to study hourly wind power potential on a grid of 250×250 m2 for turbines of 100 m hub height in Switzerland, generating the first dataset of its type for the country. We show that the average annual power generation per turbine is 4.4 GWh. Results suggest that around 12,000 wind turbines could be installed on all 19,617 km2 of available area in Switzerland resulting in a maximum technical wind potential of 53 TWh. To achieve the Swiss expansion goals of wind power for 2050, around 1000 turbines would be sufficient, corresponding to only 8% of the maximum estimated potential

Rural biomass energy 2020: People's Republic of China

The developing world is looking for effective, creative ideas for upscaling clean, renewable energy. No place will gain more socially, economically, and environmentally from increased access to clean, reliable energy than poor, rural areas. Biomass energy, produced from animal and crop wastes, is a sensible renewable energy option for rural areas and it can be cost-effective at community and industry scales if guided effectively by governments. This publication explores the potential of biomass energy to close the urban–rural energy gap, raise farmer incomes, and mend the environment in the People’s Republic of China (PRC). Its findings are instructive for other developing and medium-income countries exploring energy-for-all strategies. The report examines the promises and limitations of leading biomass energy technologies and resources for various distribution scales, including but not limited to household biogas digesters. The information is based on lessons learned and experiences from the Asian Development Bank–financed Efficient Utilization of Agricultural Wastes Project in the PRC, as well as findings and conclusions from a technical assistance grant to assist the government draft a national strategy for developing rural biomass energy.rural biomass energy; rural development; biomass resources; biomass technologies; China

Database on wind characteristics - Contents of database bank

The main objective of IEA R&D Wind Annex XVII - Database on Wind Characteristics - has been to provide wind energy planners, designers and researchers, as well as the international wind engineering community in general, with a source of actual wind fielddata (time series and resource data) observed in a wide range of different wind climates and terrain types. Connected to an extension of the initial Annex period, the scope for the continuation was widened to include also support to the international windturbine standardisation efforts.. The project partners are Sweden, Norway, U.S.A., The Netherlands and Denmark, with Denmark as the Operating Agent. The reporting of the continuation of Annex XVII falls in two separate parts. Part one accounts in detailsfor the available data in the established database bank, and part two describes various data analyses performed with the overall purpose of improving the design load cases with relevance for to wind turbine structures. The present report constitutes thesecond part of the Annex XVII reporting. Both fatigue and extreme load aspects are dealt with, however, with the main emphasis on the latter. The work has been supported by The Ministry of Environment and Energy, Danish Energy Agency, The NetherlandsAgency for Energy and the Environment (NOVEM), The Norwegian Water Resources and Energy Administration (NVE), The Swedish National Energy Administration (STEM) and The Government of the United States of America

Towards a More Employment-Intensive and Pro-Poor Economic Growth in Bolivia

The reform program and growth pattern exhibited by the Bolivian economy in the last decade did not favour employment creation and consequently not an effective reduction of poverty. During the last decade, those sectors where the bulk of employment is concentrated, presented the lowest growth rates of GDP, labour productivity and real incomes. The present paper analyzes in detail the two sectors where the bulk of employment and poverty is concentrated (agriculture and the urban informal sector) in order to determine the critical constraints to improvements in productivity, employment generation, and reductions in poverty.Employment, Poverty, Growth, Bolivia