Wind Energy Planning Research Articles

Over a decade of failure to implement UNEP/EUROBATS guidelines in wind energy planning: A call for action

AbstractWind power generation has grown exponentially over the past 20 years to meet international goals of increasing the share of renewables in energy production. Yet, this process has too often been conducted at the cost of airborne biodiversity such as birds and bats. The latter are severely threatened due to deaths by collision at wind turbine. The UNEP/EUROBATS agreement that came into force in 1994 is now ratified by 37 countries; since 2008, it recommends to site wind turbines at least 200 m away from woody edges to decrease bat fatality risks. However, 14 years later we still do not know to what extent this international recommendation has been applied in Europe. We assessed siting distances between woody edges and wind turbines for the largest wind energy producers among the UNEP/EUROBATS parties: the UK, Germany, and France. We show that 61%, 78%, and 56%, respectively, of the installed wind turbines did not comply with UNEP/EUROBATS guidelines, without improvement over time. We identified probable causes of these findings and provided key policy recommendations to achieve compliance to UNEP/EUROBATS guidelines such as better: (i) inclusion in regulatory texts, (ii) notification of the environmental authorities, and (iii) strategic, well‐informed, forward planning of areas suitable for wind turbine development.

Spatial biases revealed by LiDAR in a multiphysics WRF ensemble designed for offshore wind

Numerical weather predictions (NWPs) have become essential in offshore wind energy planning and operations. Thus, rigorous assessments of NWP model performance are critical to integrating offshore wind power into existing power systems. Taking advantage of two LiDAR buoys launched off the coast of New York in 2019, we assess the performance of a multiphysics Weather Research and Forecast (WRF) model ensemble with a 1.33-km spatial resolution for estimating the power system impacts associated with New York’s offshore wind target. Our work is the first to report WRF horizontal wind speed biases not only at multiple heights above sea level but also at two locations while still considering all seasons. WRF tends to overpredict wind speeds during spring and summer and underpredict wind speeds during winter. However, the patterns in wind speed biases differ substantially between the two buoys offering compelling evidence against spatially uniform biases, which impacts the performance of numerous bias correction methods frequently used to post-process WRF data. Therefore, additional measurements of wind speeds throughout the lower atmosphere are necessary to fully characterize bias patterns. With the recent goal set by the U.S. to install 30 GW of offshore wind by 2030 — largely along the East Coast, mispredictions carry important policy implications. Absent accurate offshore wind uncertainty forecasts, power system operators throughout the Eastern Interconnection will be forced to dispatch their most expensive and likely high emitting power plants to compensate for periods of underperformance.

Over a decade of failure to implement UNEP/EUROBATS guidelines in wind energy planning: a call for action

Over a decade of failure to implement UNEP/EUROBATS guidelines in wind energy planning: a call for action

The Global Atlas for Siting Parameters project: Extreme wind, turbulence, and turbine classes

SummaryThe Global Atlas for Siting Parameters project compiles a suite of models into a complex modeling system, uses up‐to‐date global datasets, and creates global atlases of siting parameters at a spatial resolution of 275 m. These parameters include the 50‐year wind, turbulence, and turbine class recommendations based on relevant generic turbines. The suite of models includes the microscale Linear Computational Model (LINCOM), a statistical, spectral correction method here revised for strong convective areas and tropical cyclone affected areas, two turbulence models with four setups, and load models. To this complexity, an uncertainty model was developed to classify the various sources of uncertainties for both the extreme wind and the turbulence calculations, and accordingly, atlases of uncertainty classification were created. Preliminary validation of the global calculations of the 50‐year wind and turbulence is done through comparisons with measurements, and the results are promising. This is the first time the siting parameters are obtained with such a high spatial resolution and shared on open data portal. It is expected to benefit the global wind energy planning and development.

Optimal Planning of Co-Located Wind Energy and Hydrogen Plants: A Techno-Economic Analysis

Green hydrogen produced using renewable electricity could play an important role in a clean energy future. This paper seeks to analyze the techno-economic performance of integrated wind and hydrogen systems under different conditions. A co-located wind and hydrogen hybrid system is optimized to reduce the total system cost. We have adopted and improved a state-of-the-art techno-economic tool REopt, developed by the National Renewable Energy Laboratory (NREL), for optimal planning of the integrate energy system (IES). In addition to wind and electrolyzer components, we have also considered battery energy storage, hydrogen tank, and hydrogen fuel cell in the IES. The results show that (i) adding electrolyzers to the grid-connected wind energy system could reduce the total system cost by approximately 8.9%, and (ii) adding electrolyzers, hydrogen tank, and hydrogen fuel cells could reduce the total system cost by approximately 30%.

Participatory Mapping and Counter-Representations in Wind Energy Planning

Participatory mapping for landscape planning is gaining in popularity. With a participatory geographic information system, the local spatial knowledge of the affected public can be collected and included in planning decisions. For its proponents, participatory mapping is deemed useful not only for rendering planning more inclusive but also for facilitating consensus in planning. Here, we present a case study of wind energy planning in a region in Switzerland in which we applied a participatory mapping approach that resulted in providing spatial data not for consensus-making but for creating counter-maps. Using a critical cartography approach, we identified from our sample data the distinct wind energy discourses of supporters, opponents, and people who were indifferent; these revealed three different representations of the same place, which leaves little room for reaching a consensus. Drawing on the agonistic planning theory of radical democracy, however, we could demonstrate why this outcome is not necessarily problematic but rather bears potential for more democracy and pluralism in controversial landscape planning. This case study builds the foundation for discussions about how to implement energy transition in the face of the climate crisis and touches on other cutting-edge issues, including the handling of dissensus, conflict, and polarization in planning.

The impact of tropical cyclones on potential offshore wind farms

The climate crisis has led to an increased interest in renewable energy, and in wind energy in particular. Wind farms with the largest generating potential are generally located offshore. In this study we consider the case of Mexico, a sub-tropical country in North-America. Due to Mexico's location, offshore wind farms (OWF) would be at risk of damage from strong winds associated with tropical cyclones (TCs) in both the Pacific and the Gulf of Mexico basins. Thus, here we ask whether there are any regions in Mexico combining a high generating potential and a low risk from tropical cyclones. To answer this question, the ERA5 reanalysis has been used to identify two sites on the Pacific coast and two sites in the Gulf of Mexico with high wind power potential. Then, using the ERA5 reanalysis and TC best-track observational data, the potential effects of four major hurricanes and the climatological hazard posed by TC-related damaging winds on OWFs at those sites have been investigated. The return period for TCs with near-surface winds exceeding 50m s−1, a threshold associated with increased structural damage likelihood, has been estimated at as low as 8 years for the Gulf of Mexico and above 64 years for Pacific coast. Therefore, in terms of the magnitude of the TC-related hazard, the Pacific coast sites are found to be preferred as locations for the development of OWFs. These results are relevant for any planning of offshore wind energy in Mexico, and the methodology applicable to any other sub-tropical region in which the risk of tropical cyclones is present.

“After the leases are signed, it's a done deal”: Exploring procedural injustices for utility-scale wind energy planning in the United States

Expanding wind energy deployment to meet climate and policy goals requires willing communities to host wind projects. Wind power acceptance is inextricably linked to perceptions of projects' planning process, but it is less understood what makes wind planning processes more or less fair. Using a mixed-methods case study research design, this paper evaluates the planning process for two state-approved wind farms in Ohio and Minnesota using four analytical themes relating to procedural justice: participation, information, decision-making, and local context. In doing so, we provide one of the few detailed mappings of a United States wind farm planning process. Our findings confirm other results in the wind planning literature, particularly with respect to the limited opportunities for participation and decision-making input afforded to the public. However, our study also argues that to realize procedural justice in utility-scale wind project planning, planning processes need to evolve to: (1) afford non-compensated neighbors of wind projects similar information and participation opportunities as compensated landowners, (2) provide additional resources for and knowledge-sharing opportunities among local (county and township) governments, (3) create structures for participation, information provision, and decision-making surrounding wind farm construction, operation, and decommissioning (not just siting), and (4) consider local contexts of historical power generation and resident connections to the land.

Balancing profitability of energy production, societal impacts and biodiversity in offshore wind farm design

The global demand for renewable energy is on the rise. Expansion of onshore wind energy is in many parts of the world limited by societal acceptance, and also ecological impacts are a concern. Here, pragmatic methods are developed for the integration of high-dimensional spatial data in offshore wind energy planning. Over 150 spatial data layers are created, which either oppose or support offshore wind energy development, and represent ecological, societal, and economic factors. The method is tested in Finland, where interest in developing offshore wind energy is growing.Analyses were done using a spatial prioritization approach, originally developed for the prioritization of high-dimensional ecological data, and rarely used in planning offshore wind energy. When all criteria are integrated, it is possible to find a balanced solution where offshore wind farms cause little disturbance to biodiversity and society, while at the same time yielding high profitability for wind energy production. Earlier proposed areas for offshore wind farms were also evaluated. They were generally well suited for wind power, with the exception of a couple of areas with comparatively high environmental impacts.As an outcome, new areas well suited for large scale wind power deployment were recognized, where construction costs would be moderate and disturbance to biodiversity, marine industries and people limited. A novel tradeoff visualization method was also developed for the conflicts and synergies of offshore energy deployment, which could ease the dialogue between different stakeholders in a spatial planning context.Overall, this study provides a generic and transparent approach for well-informed analysis of offshore wind energy development potential when conflict resolution between biodiversity, societal factors and economic profits is needed. The proposed approach is replicable elsewhere in the world. It is also structurally suitable for the planning of impact avoidance and conflict resolution in the context of other forms of construction or resource extraction.

Contentious governance of wind energy planning: strategic dilemmas in collaborative resistance by local governments and citizen action groups

ABSTRACT Local governments are at the heart of implementing increasingly ambitious national plans for wind energy. While support by local governments for these plans has been studied extensively, only few studies have looked into local governments’ contestation of wind energy development. In this paper we analyze contentious governance processes in which local governments join efforts with citizen action groups to oppose projects proposed by developers or the national government. We focus on the strategic dilemmas that local governments face while engaging in contentious governance. Uncovering strategic dilemmas helps to see contestation by local governments as part of a web of governance relationships, thus moving beyond dichotomous understandings of the players involved in wind farm conflicts. Strategic dilemmas also allow understanding of how stances of local governments and their citizen allies change over time, and how strategic and tactical considerations emerge from interaction patterns.

Changes in surface wind speed and its different grades over China during 1961–2020 based on a high‐resolution dataset

AbstractChanges in surface wind speed are important for wind energy planning, especially in China, which has the highest new and total wind power capacities globally. In this article, based on a daily high‐resolution observation dataset for the period of 1961–2020, changes in the surface wind speed and its different grades over China were analysed. The results showed that following significant declines from 1961 to 2002, the annual and seasonal mean surface wind speeds began to increase over China and most of its subregions (all subregions except for East China) after 2002. Opposite trends were found in the probabilities for most different grades of surface wind speed from 1961 to 2002 and from 2002 to 2020. In addition, we compared the results with those from NCEP‐1, JRA‐55, and ERA5, which showed that all of the reanalysis data could reasonably reproduce the observed spatial distributions of the surface wind speed and its different grades, although with bias in values and smaller interannual variabilities. The wind reversal over China was closely related to changes in the trends of the sea level pressure gradient. Moreover, the variation in the Pacific Decadal Oscillation (PDO) has a significantly negative correlation coefficient with the surface wind speed over East, Central, and South China.

WIND ENERGY MAPPING BASED ON QUANTUM GIS, MEASURED AND PREDICTED WIND SPEED IN KATSINA STATE

Before a wind energy system is installed, modelling and prediction of wind speed plays an important role during wind energy planning stage. The short term wind speed of Katsina was measured at 5 m elevation at different locations using hand held digital rotating cup. In order to obtain long term wind speed, a prediction model using artificial neural network (ANN) was developed. The model was implemented using Matlab/Simulink 2019, which consists of 3 layers with back propagation algorithm. The model has 5 inputs which were selected using trial and error techniques. The model was trained, tested and validated using available 1 year data obtained from Katsina state agricultural and rural development agency KATARDA in 34 ground stations situated in each local government. After, the development of the ANN wind speed prediction model, the best architecture has root mean square error (RMSE) of 8.9%, mean biased error (MBE) 4.3% while the optimum correlation value of 0.9380 was realized. The predicted annual wind speeds are in the range of 0.9-13.1 m/s and the yearly evaluated wind speed are 3.2, 2.6 and 4.7 m/s for Katsina central, Katsina south and Katsina north respectively. The wind speed map of the study area was developed; the map shows the locations wind high, moderate and low wind energy potential. The map will serve as a reference for wind energy development in the state and will provide the policy makers and potential investors as a blue print for wind energy development.

A Novel Automatic Method for the Urban Canyon Parametrization Needed by Turbulence Numerical Simulations for Wind Energy Potential Assessment

The energy transition to more sustainable forms is currently ongoing worldwide, because of the environmental impacts produced by the non-renewable energy sources employed in the last decades. Among the main alternatives, wind plays a key role and, nowadays, innovative instruments, such as small-scale turbines allow for installation of wind turbines in urban areas. Their energy potential assessment requires high-accuracy simulations of the turbulent flows in the urban canopy layer, which, in turn, require detailed information about the geometrical properties of the basic element to classify urban surfaces, i.e., the urban canyon, often not available. In this work, we propose a novel automatic method, based on Voronoi graph, to univocally identify urban canyons and to extract their geometrical parameters from online available GIS (Geographic Information System) data, and test it on four European cities that differ in size, story and location. Results show the capability of the method to identify the single urban canyon and to properly extract its geometrical parameters, which tend to assume similar values for the largest cities. Moreover, we first attempt to propose and test some curves to generally describe the data probability distribution, which may be useful for turbulence simulations for urban wind energy assessment and planning. The best results are found for the canyon aspect ratio.

Determination of Tekirdağ (Turkey) wind energy potential and evaluation of selected wind turbines in terms of techno-economic and environmental aspects

In this study, the wind energy potential of Tekirdağ was investigated obtaining the wind data from meteorology stations located in nine districts of the province and recorded hourly at 10 m altitude between the years of 2014 and 2018. Moreover, monthly average wind and Weibull and Rayleigh probability distributions, as well as hourly wind speeds, were analyzed for each district. Furthermore, monthly dominant wind directions and the ratio of dominant winds to all wind blowing numbers were determined for each district and wind speeds and wind power densities by month were compared. In addition to determination of wind energy potential, four different types of wind turbines which can be installed in the examined regions were assessed in terms of techno-economic and environmental aspects by using RETScreen Expert software. Capacity factors of selected wind turbines, initial installation costs, annual savings incomes, and annual energy amounts were determined by district. The gross greenhouse gas emission amounts that can be prevented from being released into the environment have been determined via the usage of wind turbine. Finally, the most suitable wind turbines for the districts were determined through financial sustainability analysis. Correspondingly, it has been determined that if the Enercon E2-82 wind turbine is installed in the Marmara Ereğlisi district, optimal results will be obtained. It is thought that this study will contribute to the development of the wind energy potential and planning of the wind power plants in the regions showing the similar characteristics with the examined one with regard to wind energy.

Wind Farm Location Special Optimization Based on Grid GIS and Choquet Fuzzy Integral Method in Dalian City, China

Selecting an appropriate wind farm location must be specific to a particular administrative region, which involves restrictions balance and trade-offs. Multi-criteria decision making (MCDM) and GIS are widely used in wind energy planning, but have failed to achieve the selection of an optimal location and make it difficult to establish a set of independent factors. Fuzzy measurement is an effective method to evaluate intermediate synthesis and calculates the factor weight through fuzzy integrals. In this paper, optimal wind farm location is analyzed through coupling Grid GIS technique with λ fuzzy measure. Dalian City is selected as the study area for proving the feasibility of the proposed method. Typography, meteorological, transmission facilities, biological passage, and infrastructure are taken into the index system. All the indexes are specialized into victor grid cells which are taken as the base wind farm location alternative unit. The results indicate that the Grid GIS based λ fuzzy measure and Choquet fuzzy integral method could effectively deal with the special optimization problem and reflect optimal wind farm locations.

The good process or the great illusion? A spatial perspective on public participation in Danish municipal wind turbine planning

ABSTRACT This paper explores limitations and potentials of the public space for participation in Danish municipal wind energy planning. Although the Danish procedure for involving citizens in wind energy developments is often praised for its participatory merits, the approach is not without problems. Based on explorative case study research of three Danish wind energy projects at the planning stage, and qualitative interviews with both citizens and planners, the paper reveals shortcomings in terms of perceived procedural fairness and the powerful role ascribed to developers in a planning process. A general conclusion is that the implementation of limited participation requirements of the inherent invited space decouples citizens’ perspectives while providing a space for economic and strategic interests that is closed in its character. However, the study also localizes public input which is not limited to formal participation mechanisms. Self-initiated participation representing a ‘claimed’, ‘uninvited’ and ‘self-organized’ space exerts pressure from the outside and may carry important answers to future energy challenges. The paper suggests that a successful nurturing of such potentials could help to reconfigure a public space that encourages collective reflection between established and oppositional understandings of wind energy and society.

Wind Speed Prediction based on Spatio-Temporal Covariance Model Using Autoregressive Integrated Moving Average Regression Smoothing

It is essential to enhance the ability of wind speeds forecasting for wind energy and wind resource planning. For this purpose, a hybrid strategy has been proposed based on spatio-temporal covariance model which combined the spatio-temporal ordinary kriging (STOK) technology with autoregressive integrated moving average (ARIMA) regression smoothing method. This is because wind speed time series exhibits a long-term dependency. In the case study, both STOK method and ARIMA method are employed and their performances are compared. The ARIMA model can obtain a necessary and sufficient smoothing condition for them to be smoothed. Meanwhile, further theoretical analysis is provided to discuss why the STOK method is potentially more accurate than the ARIMA method for wind speed time series prediction. Results show that the proposed method outperforms the Non-Sep-Gneiting model by 9% and 7.2% in terms of mean absolute error (MAE) and root-mean-square error (RMSE).

Short-Term Time Wind Speed Forecasting Based on Spatio-Temporal Geostatistical Approach and Kriging Method

Short-term wind speed prediction is an essential task for wind resource and wind energy planning. However, most of this literature does not take into account the spatio-termporal correlation of wind data from the geographical field. For this reason, we propose an integrated spatio-temporal kriging and functional kriging strategy to exploit such spatio-temporal correlation into the wind speed prediction. First, the deterministic trend component in wind data is estimated to be removed. The residuals are used for spatio-temporal modeling and prediction. Based on the spatio-temporal kriging framework, four spatio-temporal covariance models (product-sum model, separable exponential product model, separable and nonseparable Gneiting models) are considered which describe the spatio-temporal correlation of wind data. In particular, the flexibility of using the nonseparable Gneiting model is highlighted. More specifically, four spatio-temporal random fields are modeled from the 12 wind monitoring stations over Ireland. We also use an involved weighted least squares method for estimating parameters of the four covariance models involved in the spatio-temporal kriging strategy. We apply the fitted covariance models to generate day-ahead wind speed predictions at both observed and nonobserved locations where wind station already exist but also to nearby locations. Leave-one-out cross-validation is applied to check the significance of the difference among the four models, these spatio-temporal ordinary kriging (STOK), functional ordinary kriging (FOK) and autoregressive integrated moving average (ARIMA) methods are compared for day-ahead wind speed predictions. Forecasting results indicate that the predicting accuracy is improved almost 33.5% using FOK compared with three approaches which confirm the effectiveness of the functional kriging method in the paper.

A hybrid prediction model for wind speed using support vector machine and genetic programming in conjunction with error compensation

Wind energy resources are a clean renewable energy source. Accurate prediction of wind speed has important theoretical significance and practical value for sustainable use of wind energy, energy planning, and economic development. This paper proposes a hybrid model for prediction of wind speed using support vector machine and genetic programming models, with error compensation for the prediction residuals. Wind speed and the residuals generated using the hybrid model are simulated and predicted. The proposed model is applied to monthly average wind speed data observed over the period January 2005–December 2014 from the Tuoli and Hetian stations in Xinjiang, China. For each time series, eight prediction schemes, including independent support vector machine model and genetic programming model and their combination, were tried. At the same time, phase space reconstruction method was used to select model input factors. The results clearly show the performance differences of the eight wind speed prediction schemes in the prediction effect of the two time series. The combination of the support vector machine wind speed prediction model and the genetic programming residual prediction model has the best prediction effect, with a correlation coefficient value above 0.9, mean square value below 0.1, and mean absolute error value below 0.2. This combined model is found to be quite efficient and, therefore, the proposed approach is highly suitable to predict the monthly average wind speed.

WRF-Simulated Springtime Low-Level Jets over Iowa: Implications for Wind Energy

High-resolution simulations with the Weather Research and Forecasting (WRF) model are analyzed to characterize the frequency, intensity, height, and duration of springtime low-level jets (LLJ) and their implications for wind energy resource assessment and planning in Iowa. The time evolution of short-duration LLJ is analyzed to understand wind behavior around LLJ events and to illustrate their importance for high-frequency (few hours) variability in wind speeds and rotor plane turbulent kinetic energy (TKE). During spring, the LLJ core height has a spatiotemporal mean value of 217 m, but the LLJ depth means it frequently intersects typical wind turbine rotor planes. Nearly one-quarter of LLJ exhibit a maximum within the height interval 50-150 m AGL. LLJ profiles are found to have higher mean wind speeds across typical wind turbine rotor planes than non-LLJ profiles and to exhibit lower values of TKE. LLJ occur under stable stratification (i.e. positive Richardson numbers) and are associated with low TKE and the occurrence of high vertical wind shear. The frequency and duration of LLJ exhibit geospatial variability across Iowa with highest values in the northeast of the state. Analyses of daytime and night-time LLJ indicate topographic variability is an important factor in the development of LLJ.