The impact of large scale atmospheric circulation patterns on wind power generation and its potential predictability: a case study over the UK

Over recent years there has been an increasing deployment of renewable energy generation technologies, particularly large-scale wind farms. As wind farm deployment increases, it is vital to gain a good understanding of how the energy produced is affected by climate variations, over a wide range of time-scales, from short (hours to weeks) to long (months to decades) periods. By relating wind speed at specific sites in the UK to a large-scale climate pattern (the North Atlantic Oscillation or "NAO"), the power generated by a modelled wind turbine under three different NAO states is calculated. It was found that the wind conditions under these NAO states may yield a difference in the mean wind power output of up to 10%. A simple model is used to demonstrate that forecasts of future NAO states can potentially be used to improve month-ahead statistical forecasts of monthly-mean wind power generation. The results confirm that the NAO has a significant impact on the hourly-, daily- and monthly-mean power output distributions from the turbine with important implications for (a) the use of meteorological data (e.g. their relationship to large scale climate patterns) in wind farm site assessment and, (b) the utilisation of seasonal-to-decadal climate forecasts to estimate future wind farm power output. This suggests that further research into the links between large-scale climate variability and wind power generation is both necessary and valuable.

Scientific materials blue book; equipment and supplies for chemical, metallurgical and biological laboratories

Mode of access: Internet.

Techno-Economic Assessment of LNG and Diesel Production and Global Trading Based on Hybrid PV-Wind Power Plants and PtG, GtL and PtL Technologies

With growing demand for liquefied natural gas (LNG) and liquid transportation fuels, and concerns about climate change and causes of greenhouse gas emissions, this master’s thesis introduces a new value chain design for LNG and transportation fuels and respective fundamental business cases based on hybrid PV-Wind power plants. The value chains are composed of renewable electricity (RE) converted by power-to-gas (PtG), gas-to-liquids (GtL) or power-to-liquids (PtL) facilities into SNG (which is finally liquefied into LNG) or synthetic liquid fuels, mainly diesel, respectively. The RE-LNG or RE-diesel are drop-in fuels to the current energy system and can be traded everywhere in the world. The calculations for the hybrid PV-Wind power plants, electrolysis, methanation (H2tSNG), hydrogen-to-liquids (H2tL), GtL and LNG value chain are performed based on both annual full load hours (FLh) and hourly analysis. Results show that the proposed RE-LNG produced in Patagonia, as the study case, is competitive with conventional LNG in Japan for crude oil prices within a minimum price range of about 87 - 145 USD/barrel (20 – 26 USD/MBtu of LNG production cost) and the proposed RE-diesel is competitive with conventional diesel in the European Union (EU) for crude oil prices within a minimum price range of about 79 - 135 USD/barrel (0.44 – 0.75 €/l of diesel production cost), depending on the chosen specific value chain and assumptions for cost of capital, available oxygen sales and CO2 emission costs. RE-LNG or RE-diesel could become competitive with conventional fuels from an economic perspective, while removing environmental concerns. The RE-PtX value chain needs to be located at the best complementing solar and wind sites in the world combined with a de-risking strategy. This could be an opportunity for many countries to satisfy their fuel demand locally. It is also a specific business case for countries with excellent solar and wind resources to export carbon-neutral hydrocarbons, when the decrease in production cost is considerably more than the shipping cost. This is a unique opportunity to export carbon-neutral hydrocarbons around the world where the environmental limitations on conventional hydrocarbons are getting tighter.

Instal•lació d'un parc eòlic de microgeneració juntament amb l'enllumenat d'una via pública

L’objectiu del projecte és realitzar la instal•lació d’enllumenat per a un tram del’autovia de Palafrugell a Calella de Palafrugell, aquesta instal•lació també disposaràd’una instal•lació de microgeneració. On a cada farola s’hi acoblarà un aerogeneradord’eix vertical de 4 kW per a la producció d’energia elèctrica.Com no es disposa de faroles prefabricades que compleixin aquesta funció desuport per a lluminàries i un aerogenerador, en aquest projecte també es faràal disseny de la farola.L’actuació prevista és la instal•lació de 12 faroles de nou dissenyamb un aerogenerador d’eix vertical acoblat a cada farola, en l’ espai de la mitjana de l’autovia

Anàlisi mitjançant mecànica de fluids computacional d’un aerogenerador minieòlic

A la UdGhi ha 2 aerogeneradors minieòlics: el del terrat del P2 i un de més petit allaboratori d’energies. Aquest segon aerogenerador minieòlic és el que s’ha utilitzat en aquestprojecte. Es tracta d’un Air-X de la casa Technosun amb les següents característiques:- Té un pes de 6Kg, un radi de 0,582 metres, un TSR de 8,8 i unapotència de 545W.- Perfil de la pala tipus SD2030.- Velocitat d’engegada de 3m/s.-Amb vents forts (més de 15m/s) un dispositiu electrònic redueix lavelocitat fins a 600rpm, reduint les càrregues sobre la turbina i l’estructuramentre encara segueix produint energia.- Baix manteniment. Només consta de dues parts mòbils.L’objecte que s’ha plantejat per aquest projecte ha estat trobar la corbade potència del minigenerador Air-X mitjançant simulació amb CFD, iutilitzant només les dades geomètriques de l’aparell

Statistical Analysis of Wind Power Generation in Europe

Studies have shown that large geographical spreading can reduce the wind power variability and smooth production. It is frequently assumed that storage and interconnection can manage wind power variability and are totally flexible. However, constraints do exist. In the future more and more electricity will be provided by renewable energy sources and more electricity interconnectors will be built between European Union (EU) countries, as outlines in many of the Projects of Common Interests. It is essential to understand the correlation of wind generation throughout Europe considering power system constraints. In this study the spatial and temporal correlation of wind power production across several countries is examined in order to understand how “the wind ‘travels’ across Europe”. Three years of historical hourly wind power generation from ten EU countries is analysed to investigate the geographic diversity and time scales influence on correlation of wind power variations. Results are then compared with two other studies and show similar general characteristics of correlation between EU country pairs to identify opportunities for storage optimisation, power system operations, and trading.

Short-term wind power forecasting in Portugal by neural networks and wavelet transform

This paper proposes artificial neural networks in combination with wavelet transform for short-term wind power forecasting in Portugal. The increased integration of wind power into the electric grid, as nowadays occurs in Portugal, poses new challenges due to its intermittency and volatility. Hence, good forecasting tools play a key role in tackling these challenges. Results from a real-world case study are presented. A comparison is carried out, taking into account the results obtained with other approaches. Finally, conclusions are duly drawn. (C) 2010 Elsevier Ltd. All rights reserved.

Optimal offering strategies for wind power producers considering uncertainty and risk

This paper provides a two-stage stochastic programming approach for the development of optimal offering strategies for wind power producers. Uncertainty is related to electricity market prices and wind power production. A hybrid intelligent approach, combining wavelet transform, particle swarm optimization and adaptive-network-based fuzzy inference system, is used in this paper to generate plausible scenarios. Also, risk aversion is explicitly modeled using the conditional value-at-risk methodology. Results from a realistic case study, based on a wind farm in Portugal, are provided and analyzed. Finally, conclusions are duly drawn.

A Multiple Criteria Utility-based Approa h for the Unit Commitment with Wind Power and Pumped Storage Hydro

The integration of wind power in eletricity generation brings new challenges to unit commitment due to the random nature of wind speed. For this particular optimisation problem, wind uncertainty has been handled in practice by means of conservative stochastic scenario-based optimisation models, or through additional operating reserve settings. However, generation companies may have different attitudes towards operating costs, load curtailment, or waste of wind energy, when considering the risk caused by wind power variability. Therefore, alternative and possibly more adequate approaches should be explored. This work is divided in two main parts. Firstly we survey the main formulations presented in the literature for the integration of wind power in the unit commitment problem (UCP) and present an alternative model for the wind-thermal unit commitment. We make use of the utility theory concepts to develop a multi-criteria stochastic model. The objectives considered are the minimisation of costs, load curtailment and waste of wind energy. Those are represented by individual utility functions and aggregated in a single additive utility function. This last function is adequately linearised leading to a mixed-integer linear program (MILP) model that can be tackled by general-purpose solvers in order to find the most preferred solution. In the second part we discuss the integration of pumped-storage hydro (PSH) units in the UCP with large wind penetration. Those units can provide extra flexibility by using wind energy to pump and store water in the form of potential energy that can be generated after during peak load periods. PSH units are added to the first model, yielding a MILP model with wind-hydro-thermal coordination. Results showed that the proposed methodology is able to reflect the risk profiles of decision makers for both models. By including PSH units, the results are significantly improved.

Wind Power in the Portuguese Landscape: Global Concerns and Local Costs

Wind turbines and solar panels are becoming second nature in Portugal, as its occurrence in the country becomes ubiquitous. Somehow, one could argue that renewable energy in Portugal is in the process of ‘naturalisation’ as part of a new – mechanised, but environmentally benign – landscape. Portuguese Institute for the Conservation of Nature and Biodiversity (ICNB) has shown an ambiguous stance on this issue, defending global concerns towards renewable energy, while at the same time attempting to engage locals in the preservation of extensive ‘classified areas’. In the course of this research, we tried to focus on these incongruities and to analyse how they are impacting local communities during the process of wind power installation.

The importance and accuracy of wind power forecasts

Due to the global crisis o f climate change many countries throughout the world are installing the renewable energy o f wind power into their electricity system. Wind energy causes complications when it is being integrated into the electricity system due its intermittent nature. Additionally winds intennittency can result in penalties being enforced due to the deregulation in the electricity market. Wind power forecasting can play a pivotal role to ease the integration o f wind energy. Wind power forecasts at 24 and 48 hours ahead of time are deemed the most crucial for determining an appropriate balance on the power system. In the electricity market wind power forecasts can also assist market participants in terms o f applying a suitable bidding strategy, unit commitment or have an impact on the value o f the spot price. For these reasons this study investigates the importance o f wind power forecasts for such players as the Transmission System Operators (TSOs) and Independent Power Producers (IPPs). Investigation in this study is also conducted into the impacts that wind power forecasts can have on the electricity market in relation to bidding strategies, spot price and unit commitment by examining various case studies. The results o f these case studies portray a clear and insightful indication o f the significance o f availing from the information available from wind power forecasts. The accuracy o f a particular wind power forecast is also explored. Data from a wind power forecast is examined in the circumstances o f both 24 and 48 hour forecasts. The accuracy o f the wind power forecasts are displayed through a variety o f statistical approaches. The results o f the investigation can assist market participants taking part in the electricity pool and also provides a platform that can be applied to any forecast when attempting to define its accuracy. This study contributes significantly to the knowledge in the area o f wind power forecasts by explaining the importance o f wind power forecasting within the energy sector. It innovativeness and uniqueness lies in determining the accuracy o f a particular wind power forecast that was previously unknown.

Business opportunities in power sector of Ukraine : focus small-scale hydro and wind power sectors

In the last few years, the Ukrainian investment market has constantly shown strong performance and significant growth. This is primarily due to the investment attractiveness of Ukraine. From the perspective of investments in energy sector, Ukraine can be described as a country providing significant number of opportunities to multiply invested funds. But there are numbers of risks which hamper large investments. The work objective was to discover opportunities in small-scale hydropower and wind power sectors of Ukraine and more importantly to prove economic expediency of such investments. Thesis covers major of issues, concerning entering the Ukrainian power market as a foreign investor. It provides basic information about the structure of power market, the state of renewables sector in Ukraine, development of power sector in the regions, functioning of Wholesale Electricity Market, formation of electricity prices, possibilities for implementing joint Implementation mechanism, while the most attention, nevertheless, is concentrated on the opportunities in small-scale hydro and wind power sectors. Theoretical part of the study disclosed that Crimea peninsula has perfect wind conditions and could be a prospective area for wind project development. Investment analysis revealed that project profits will be excellent if green tariff for renewable energy is adopted. By the moment uncertainties about green law adoption bring additional risk to the projects and complicate any investment decision.

An aggregated wind power generation model based on MERRA reanalysis data: MATLAB model and example data for the April 2014 wind farm distribution of Great Britain.

The MATLAB model is contained within the compressed folders (versions are available as .zip and .tgz). This model uses MERRA reanalysis data (>34 years available) to estimate the hourly aggregated wind power generation for a predefined (fixed) distribution of wind farms. A ready made example is included for the wind farm distribution of Great Britain, April 2014 ("CF.dat"). This consists of an hourly time series of GB-total capacity factor spanning the period 1980-2013 inclusive. Given the global nature of reanalysis data, the model can be applied to any specified distribution of wind farms in any region of the world. Users are, however, strongly advised to bear in mind the limitations of reanalysis data when using this model/data. This is discussed in our paper: Cannon, Brayshaw, Methven, Coker, Lenaghan. "Using reanalysis data to quantify extreme wind power generation statistics: a 33 year case study in Great Britain". Submitted to Renewable Energy in March, 2014. Additional information about the model is contained in the model code itself, in the accompanying ReadMe file, and on our website: http://www.met.reading.ac.uk/~energymet/data/Cannon2014/

Probabilistic wind power forecasts with an inverse power curve transformation and censored regression

Forecasting wind power is an important part of a successful integration of wind power into the power grid. Forecasts with lead times longer than 6 h are generally made by using statistical methods to post-process forecasts from numerical weather prediction systems. Two major problems that complicate this approach are the non-linear relationship between wind speed and power production and the limited range of power production between zero and nominal power of the turbine. In practice, these problems are often tackled by using non-linear non-parametric regression models. However, such an approach ignores valuable and readily available information: the power curve of the turbine's manufacturer. Much of the non-linearity can be directly accounted for by transforming the observed power production into wind speed via the inverse power curve so that simpler linear regression models can be used. Furthermore, the fact that the transformed power production has a limited range can be taken care of by employing censored regression models. In this study, we evaluate quantile forecasts from a range of methods: (i) using parametric and non-parametric models, (ii) with and without the proposed inverse power curve transformation and (iii) with and without censoring. The results show that with our inverse (power-to-wind) transformation, simpler linear regression models with censoring perform equally or better than non-linear models with or without the frequently used wind-to-power transformation.