Economic valuation of an offshore wind farm in Greece: the role of individual’s base-state influences and beliefs in the value formation process

The increased concern for the impacts of climate change on the environment, along with the growing industry of renewable energy sources, and especially wind power, has made the valuation of environmental services and goods of great significance. Offshore wind energy is being exploited exponentially and its importance for renewable energy generation is increasing. We apply a double-bound dichotomous Contingent Valuation Method analysis in order to both a) estimating the Willingness to Pay (WTP) of Greek residents for green electricity produced by offshore wind farm located between the islands of Tinos and Andros and b) identifying factors behind respondents’ WTP including individual’s behaviour toward environment and individual’s views on climate change and renewable energy. A total of 141 respondents participated in the questionnaire. Results show that the respondents are willing to pay on average 20€ every two months through their electricity bill in return for carbon-free electricity and water saving from the wind farm. Respondents’ environmental consciousness and their perception towards climate change and renewable energy have a positive effect on their WTP.

Challenges in quantifying wind generation's contribution to securing peak demand

Wind generation's contribution to supporting peak electricity demand is one of the key questions in wind integration studies. Differently from conventional units, the available outputs of different wind farms cannot be approximated as being statistically independent, and hence near-zero wind output is possible across an entire power system. This paper will review the risk model structures currently used to assess wind's capacity value, along with discussion of the resulting data requirements. A central theme is the benefits from performing statistical estimation of the joint distribution for demand and available wind capacity, focusing attention on uncertainties due to limited histories of wind and demand data; examination of Great Britain data from the last 25 years shows that the data requirements are greater than generally thought. A discussion is therefore presented into how analysis of the types of weather system which have historically driven extreme electricity demands can help to deliver robust insights into wind's contribution to supporting demand, even in the face of such data limitations. The role of the form of the probability distribution for available conventional capacity in driving wind capacity credit results is also discussed.

Suprathermal electron evolution in a Parker spiral magnetic field

Suprathermal electrons (>70 eV) form a small fraction of the total solar wind electron density but serve as valuable tracers of heliospheric magnetic field topology. Their usefulness as tracers of magnetic loops with both feet rooted on the Sun, however, most likely fades as the loops expand beyond some distance owing to scattering. As a first step toward quantifying that distance, we construct an observationally constrained model for the evolution of the suprathermal electron pitch-angle distributions on open field lines. We begin with a near-Sun isotropic distribution moving antisunward along a Parker spiral magnetic field while conserving magnetic moment, resulting in a field-aligned strahl within a few solar radii. Past this point, the distribution undergoes little evolution with heliocentric distance. We then add constant (with heliocentric distance, energy, and pitch angle) ad-hoc pitch-angle scattering. Close to the Sun, pitch-angle focusing still dominates, again resulting in a narrow strahl. Farther from the Sun, however, pitch-angle scattering dominates because focusing is effectively weakened by the increasing angle between the magnetic field direction and intensity gradient, a result of the spiral field. We determine the amount of scattering required to match Ulysses observations of strahl width in the fast solar wind, providing an important tool for inferring the large-scale properties and topologies of field lines in the interplanetary medium. Although the pitch-angle scattering term is independent of energy, time-of-flight effects in the spiral geometry result in an energy dependence of the strahl width that is in the observed sense although weaker in magnitude.

Energy substitutability in transition agriculture: estimates and implications for Hungary

Subsidised energy prices in pre-transition Hungary had led to excessive energy intensity in the agricultural sector. Transition has resulted in steep input price increases. In this study, Allen and Morishima elasticities of substitution are estimated to study the effects of these price changes on energy use, chemical input use, capital formation and employment. Panel data methods, Generalised Method of Moments (GMM) and instrument exogeneity tests are used to specify and estimate technology and substitution elasticities. Results indicate that indirect price policy may be effective in controlling energy consumption. The sustained increases in energy and chemical input prices have worked together to restrict energy and chemical input use, and the substitutability between energy, capital and labour has prevented the capital shrinkage and agricultural unemployment situations from being worse. The Hungarian push towards lower energy intensity may be best pursued through sustained energy price increases rather than capital subsidies. (C) 2003 Elsevier B.V. All rights reserved.

Limit-feeding a high-energy diet to meet energy requirements in the dry period alters plasma metabolite concentrations but does not affect intake or milk production in early lactation

Limit-feeding dry cows a high-energy diet may enable adequate energy intake to be sustained as parturition approaches, thus reducing the extent of negative energy balance after parturition. Our objective was to evaluate the effect of dry period feeding strategy on plasma concentrations of hormones and metabolites that reflect energy status. Multiparous Holstein cows (n = 18) were dried off 45 d before expected parturition, paired by expected calving date, parity, and previous lactation milk yield, and randomly assigned to 1 of 2 dry-period diets formulated to meet nutrient requirements at ad libitum or limited intakes. All cows were fed the same diet for ad libitum intake after parturition. Prepartum dry matter intake (DMI) for limit-fed cows was 9.4 kg/d vs. 13.7 kg/d for cows fed ad libitum. During the dry period, limit-fed cows consumed enough feed to meet calculated energy requirements, and ad libitum-fed cows were in positive calculated net energy for lactation (NEL) balance (0.02 vs. 6.37 Mcal/d, respectively). After parturition, milk yield, milk protein concentration, DMI, body condition score, and body weight were not affected by the prepartum treatments. Cows limit fed during the dry period had a less-negative calculated energy balance during wk 1 postpartum. Milk fat concentration and yield were greater for the ad libitum treatment during wk 1 but were lower in wk 2 and 3 postpartum. Plasma insulin and glucose concentrations decreased after calving. Plasma insulin concentration was greater in ad libitum-fed cows on d -2 relative to calving, but did not differ by dietary treatment at other times. Plasma glucose concentrations were lower before and after parturition for cows limit-fed during the dry period. Plasma nonesterified fatty acid concentrations peaked after parturition on d 1 and 4 for the limit-fed and ad libitum treatments, respectively, and were greater for limit-fed cows on d -18, -9, -5, and -2. Plasma tumor necrosis factor-alpha concentrations did not differ by treatment in either the pre- or postpartum period, but tended to decrease after parturition. Apart from a reduction in body energy loss in the first week after calving, limit feeding a higher NEL diet during the dry period had little effect on intake and milk production during the first month of lactation.

The need of sustainable buildings construction in the Kingdom of Bahrain

This thesis is aimed to initiate implementing sustainable building construction in the kingdom of Bahrain, i.e. Building-Integration PhotoVoltaic (BIPV) or Wind Energy (BIWE). It highlights the main constrains that discourage such modern concept in building and construction. Three groups have been questioned using a questionnaire. These are the policy and decision makers, the leading consultants and the contractors. The main constrains of the dissemination of BIVP and BIWE, according to the policy and decision makers, are: lack of knowledge and awareness of the public in sustainable technology, low cost of electricity, low cost of gas and oil and difficulty in applying local environmental taxes. The consultants had attributed the constrains to ignorance of life cycle cost of PV and Wind turbines systems, lack of education and knowledge in sustainable design, political system, shortage of markets importing sustainable technologies and client worries in profitability and pay-back period. The contractors are found to be very enthusiastic and ready to take over any sustainable building project and prefer to have a construction manger to coordinate between the design and contracting team. Design and Build is found the favorable procurement method in Bahrain for conducting BIPV or BIWE projects.

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.

The role of atmosphere feedbacks during ENSO in the CMIP3 models. Part II: using AMIP runs to understand the heat flux feedback mechanisms

Several studies using ocean–atmosphere general circulation models (GCMs) suggest that the atmospheric component plays a dominant role in the modelled El Niño-Southern Oscillation (ENSO). To help elucidate these findings, the two main atmosphere feedbacks relevant to ENSO, the Bjerknes positive feedback (μ) and the heat flux negative feedback (α), are here analysed in nine AMIP runs of the CMIP3 multimodel dataset. We find that these models generally have improved feedbacks compared to the coupled runs which were analysed in part I of this study. The Bjerknes feedback, μ, is increased in most AMIP runs compared to the coupled run counterparts, and exhibits both positive and negative biases with respect to ERA40. As in the coupled runs, the shortwave and latent heat flux feedbacks are the two dominant components of α in the AMIP runs. We investigate the mechanisms behind these two important feedbacks, in particular focusing on the strong 1997–1998 El Niño. Biases in the shortwave flux feedback, α SW, are the main source of model uncertainty in α. Most models do not successfully represent the negative αSW in the East Pacific, primarily due to an overly strong low-cloud positive feedback in the far eastern Pacific. Biases in the cloud response to dynamical changes dominate the modelled α SW biases, though errors in the large-scale circulation response to sea surface temperature (SST) forcing also play a role. Analysis of the cloud radiative forcing in the East Pacific reveals model biases in low cloud amount and optical thickness which may affect α SW. We further show that the negative latent heat flux feedback, α LH, exhibits less diversity than α SW and is primarily driven by variations in the near-surface specific humidity difference. However, biases in both the near-surface wind speed and humidity response to SST forcing can explain the inter-model αLH differences.

‘Nudging’ energy users: regulatory measures to address the risk of aggregate peak demand in European electricity markets

For decades regulators in the energy sector have focused on facilitating the maximisation of energy supply in order to meet demand through liberalisation and removal of market barriers. The debate on climate change has emphasised a new type of risk in the balance between energy demand and supply: excessively high energy demand brings about significantly negative environmental and economic impacts. This is because if a vast number of users is consuming electricity at the same time, energy suppliers have to activate dirty old power plants with higher greenhouse gas emissions and higher system costs. The creation of a Europe-wide electricity market requires a systematic investigation into the risk of aggregate peak demand. This paper draws on the e-Living Time-Use Survey database to assess the risk of aggregate peak residential electricity demand for European energy markets. Findings highlight in which countries and for what activities the risk of aggregate peak demand is greater. The discussion highlights which approaches energy regulators have started considering to convince users about the risks of consuming too much energy during peak times. These include ‘nudging’ approaches such as the roll-out of smart meters, incentives for shifting the timing of energy consumption, differentiated time-of-use tariffs, regulatory financial incentives and consumption data sharing at the community level.

Variation in the global-scale impacts of climate change on crop productivity due to climate model uncertainty and adaptation

Crop production is inherently sensitive to fluctuations in weather and climate and is expected to be impacted by climate change. To understand how this impact may vary across the globe many studies have been conducted to determine the change in yield of several crops to expected changes in climate. Changes in climate are typically derived from a single to no more than a few General Circulation Models (GCMs). This study examines the uncertainty introduced to a crop impact assessment when 14 GCMs are used to determine future climate. The General Large Area Model for annual crops (GLAM) was applied over a global domain to simulate the productivity of soybean and spring wheat under baseline climate conditions and under climate conditions consistent with the 2050s under the A1B SRES emissions scenario as simulated by 14 GCMs. Baseline yield simulations were evaluated against global country-level yield statistics to determine the model's ability to capture observed variability in production. The impact of climate change varied between crops, regions, and by GCM. The spread in yield projections due to GCM varied between no change and a reduction of 50%. Without adaptation yield response was linearly related to the magnitude of local temperature change. Therefore, impacts were greatest for countries at northernmost latitudes where warming is predicted to be greatest. However, these countries also exhibited the greatest potential for adaptation to offset yield losses by shifting the crop growing season to a cooler part of the year and/or switching crop variety to take advantage of an extended growing season. The relative magnitude of impacts as simulated by each GCM was not consistent across countries and between crops. It is important, therefore, for crop impact assessments to fully account for GCM uncertainty in estimating future climates and to be explicit about assumptions regarding adaptation.

The role of conventional generation in managing variability

As electricity systems incorporate increasing levels of variable renewable generation, conventional plant will be required to operate more flexibly, with potential impacts for economic viability and reliability. Northern Ireland is pursuing an ambitious target of 40% of electricity to be supplied from renewable sources by 2020. The dominant source of this energy is anticipated to come from inherently variable wind power, one of the most mature renewable technologies. Conventional thermal generators will have a significant role to play in maintaining security of supply. However, running conventional generation more flexibly in order to cater for a wind led regime can reduce its efficiency, as well as shortening its lifespan and increasing O&M costs. This paper examines the impacts of variable operation on existing fossil fuel based generators, with a particular focus on Northern Ireland. Access to plant operators and industry experts has provided insight not currently evident in the energy literature. Characteristics of plant operation and the market framework are identified that present significant challenges in moving to the proposed levels of wind penetration. Opportunities for increasing flexible operation are proposed and future research needs identified.

Influence of probabilistic climate projections on building energy simulation

The Chartered Institute of Building Service Engineers (CIBSE) produced a technical memorandum (TM36) presenting research on future climate impacting building energy use and thermal comfort. One climate projection for each of four CO2 emissions scenario were used in TM36, so providing a deterministic outlook. As part of the UK Climate Impacts Programme (UKCIP) probabilistic climate projections are being studied in relation to building energy simulation techniques. Including uncertainty in climate projections is considered an important advance to climate impacts modelling and is included in the latest UKCIP data (UKCP09). Incorporating the stochastic nature of these new climate projections in building energy modelling requires a significant increase in data handling and careful statistical interpretation of the results to provide meaningful conclusions. This paper compares the results from building energy simulations when applying deterministic and probabilistic climate data. This is based on two case study buildings: (i) a mixed-mode office building with exposed thermal mass and (ii) a mechanically ventilated, light-weight office building. Building (i) represents an energy efficient building design that provides passive and active measures to maintain thermal comfort. Building (ii) relies entirely on mechanical means for heating and cooling, with its light-weight construction raising concern over increased cooling loads in a warmer climate. Devising an effective probabilistic approach highlighted greater uncertainty in predicting building performance, depending on the type of building modelled and the performance factors under consideration. Results indicate that the range of calculated quantities depends not only on the building type but is strongly dependent on the performance parameters that are of interest. Uncertainty is likely to be particularly marked with regard to thermal comfort in naturally ventilated buildings.

A dwelling-level investigation into the physical and socio-economic drivers of domestic energy consumption in England

The UK Government's Department for Energy and Climate Change has been investigating the feasibility of developing a national energy efficiency data framework covering both domestic and non-domestic buildings. Working closely with the Energy Saving Trust and energy suppliers, the aim is to develop a data framework to monitor changes in energy efficiency, develop and evaluate programmes and improve information available to consumers. Key applications of the framework are to understand trends in built stock energy use, identify drivers and evaluate the success of different policies. For energy suppliers, it could identify what energy uses are growing, in which sectors and why. This would help with market segmentation and the design of products. For building professionals, it could supplement energy audits and modelling of end-use consumption with real data and support the generation of accurate and comprehensive benchmarks. This paper critically examines the results of the first phase of work to construct a national energy efficiency data-framework for the domestic sector focusing on two specific issues: (a) drivers of domestic energy consumption in terms of the physical nature of the dwellings and socio-economic characteristics of occupants and (b) the impact of energy efficiency measures on energy consumption.

Projections of global warming-induced impacts on winter storm losses in the German private household sector

We present projections of winter storm-induced insured losses in the German residential building sector for the 21st century. With this aim, two structurally most independent downscaling methods and one hybrid downscaling method are applied to a 3-member ensemble of ECHAM5/MPI-OM1 A1B scenario simulations. One method uses dynamical downscaling of intense winter storm events in the global model, and a transfer function to relate regional wind speeds to losses. The second method is based on a reshuffling of present day weather situations and sequences taking into account the change of their frequencies according to the linear temperature trends of the global runs. The third method uses statistical-dynamical downscaling, considering frequency changes of the occurrence of storm-prone weather patterns, and translation into loss by using empirical statistical distributions. The A1B scenario ensemble was downscaled by all three methods until 2070, and by the (statistical-) dynamical methods until 2100. Furthermore, all methods assume a constant statistical relationship between meteorology and insured losses and no developments other than climate change, such as in constructions or claims management. The study utilizes data provided by the German Insurance Association encompassing 24 years and with district-scale resolution. Compared to 1971–2000, the downscaling methods indicate an increase of 10-year return values (i.e. loss ratios per return period) of 6–35 % for 2011–2040, of 20–30 % for 2041–2070, and of 40–55 % for 2071–2100, respectively. Convolving various sources of uncertainty in one confidence statement (data-, loss model-, storm realization-, and Pareto fit-uncertainty), the return-level confidence interval for a return period of 15 years expands by more than a factor of two. Finally, we suggest how practitioners can deal with alternative scenarios or possible natural excursions of observed losses.