Calculation of CSP Yields with Probabilistic Meteorological Data Sets: A Case Study in Brazil

AbstractCurrent practice for yield prognosis of solar thermal power plants simulates the average annual performance by using a typical meteorological year data set (TMY). This represents the long-term average or a 50 % probability of exceedance(P50) ofdirect normal irradiance (DNI) at the project's location. For more conservative risk evaluation it is common practice to calculate the 90 % yield exceedance level (P90) by estimating the uncertainty of the long-term DNI which depends on data set uncertainty and inter-annual variability.A simple approach to calculate the P90 yieldis to assume a normal distribution for this uncertaintyand a direct 1:1 relation of DNI averages to the yields. However, since the relation of DNI to energy yield is actually not linear it becomes more and more popular to calculate it from annual meteorological data sets (MY90), which are representing P90 DNI averages at a realistic distribution of actual values in the same time resolution as the P50 TMY. Applying such MY90 data sets still has the shortcoming that they are synthetic, whilereal years of data should lead to more realistic yields. Thus, this paper proposes the use of multiple years of weather inputto realistically include the annual variability of DNI. To also represent the effect of the data set uncertainty,thetime-series are modifiedin such away that the annual DNI values follow a normal distribution with a 1-sigma width equivalent to the diagnosed data set uncertainty. The impact of this probabilistic approach on the energy yield of a CSP project is shown for thesite Bom Jesus da Lapa in Brazil.Since the estimation of a realistic uncertainty of the long-term DNI at this location was challenging, several uncertainties between 3-9 % were assumed that could possibly be inherent in such a data set. Using theseassumed data set uncertainties and theinter-annual variability of the data set, the deviations to the long-term meanof energy yield are shown for the current practice approaches and the new method. Hence for a data set uncertainty of 5 %the very basic risk analysis results in a single-year P90 yield11.1 % below P50,while using a MY90 single year data set is resulting in a P90 yield 9.7 % below P50. The probabilistic approach introduced here is leading to P90 yields 8.5 % below P50

Self-consumption of electricity from renewable sources

If the cost of energy production from renewable energy sources (RES) reduces below the level of electricity retail prices, self-consumption (SC) can contribute to market integration of RES. Support schemes such as feed-in tariffs could be phased out in view of parity of retail prices and RES production costs. In combination with electricity storage and demand response (DR), SC can facilitate the integration of variable renewables onto the grid and lower the overall costs of the energy system through load shifting particularly if storage and DR is managed using ICT and algorithms controlling charging cycles and usage of electric devices. Some issues remain however: Self-consumption potential is limited without further technical enhancements in storage or DR solutions. To organize self-consumption efficiently, measures on the grid side and energy storage have to be taken. Enabling the grid to provide necessary information back to prosumers and vice versa, as well as developing economic ways of storing energy is key to unleashing the potential that lies within the transition from passive consumers to active prosumers. Different policies, such as the support of investments to storage installations, can foster those developments. The impact of electricity retail prices has to be considered also. Self-consumption is profitable if the costs of locally produced RES are lower than the retail electricity price. There are, however, worries that a high penetration of self-consumption solutions might lead to an unfair distribution of network charges, taxes and levies even if storage and DR measures can lower additional costs arising from PV integration. Future energy policy can address the way how costs get allocated

Benthic-pelagic coupling and trophic relationships in northern Baltic Sea food webs

Understanding marine ecosystem structure and functioning is crucial in supporting sustainable management of natural resources and monitoring the health of marine ecosystems. The current study utilized stable isotope (SI) mixing models and trophic position models to examine energy flow, trophic relationships, and benthic-pelagic coupling between food web components. Roughly 1900 samples from different trophic levels in the food web, collected during 2001-2010 from four northern and central sub-basins of the Baltic Sea, were analyzed for SI ratios of carbon and nitrogen. Trophic structure of the food webs among the sub-basins was consistent, but there were differences between the proportions of energy in different trophic levels that had originated from the benthic habitat. Mysids and amphipods served as important links between the benthic and pelagic ecosystems. Much (35-65%) of their energy originated from the benthic zone but was transferred to higher trophic levels in the pelagic food web by consumption by herring (Clupea harengus). One percent to twenty-four percent of the energy consumption of apex seal predators (Halichoerus grypus and Pusa hispida) and predatory fish (Salmo salar) was derived from benthic zone. Diets of mysids and amphipods differed, although some overlap in their dietary niches was observed. The food web in the Gulf of Finland was more influenced by the benthic subsystem than food webs in the other sub-basins. The baseline levels of delta C-13 and delta N-15 differed between sub-basins of the Baltic Sea, indicating differences in the input of organic matter and nutrients to each sub-basin.peerReviewe

Future emerging technologies in the wind power sector: A European perspective

This paper represents an expert view from Europe of future emerging technologies within the wind energy sector considering their potential, challenges, applications and technology readiness and how they might evolve in the coming years. These technologies were identified as originating primarily from the academic sector, some start-up companies and a few larger industrial entities. The following areas were considered: airborne wind energy, offshore floating concepts, smart rotors, wind-induced energy harvesting devices, blade tip-mounted rotors, unconventional power transmission systems, multi-rotor turbines, alternative support structures, modular high voltage direct current generators, innovative blade manufacturing techniques, diffuser-augmented turbines and small turbine technologies. The future role of advanced multiscale modelling and data availability is also considered. This expert review has highlighted that more research will be required to realise many of these emerging technologies. However, there is a need to identify synergies between fundamental and industrial research by correctly targeting public and private funding in these emerging technology areas as industrial development may outpace more fundamental research faster than anticipated

Endogenous and food-derived polyamines: determination by electrochemical sensing

olyamines (PAs) are involved in a variety of fundamental physio-pathologic processes. The concentration of these polycations in organs and tissues depends on their endogenous production and oxidation rates, and on their intake from foods. Besides being largely accepted as markers for the progress of several pathologies, PAs may exert themselves different effects on humans, ranging from being positive to be drastically detrimental depending on the organism conditions. Thus, if the determination of polyamines content in tissue samples is of great importance as they could be indicators of several diseases, their quantification in food is fundamental for modulating the diet to respond to a specific human health status. Thus, the determination of PA content in food is increasingly urgent. Standard analytical methods for polyamine quantification are mainly based on chromatography, where high-performance liquid chromatography and gas chromatography are the most often used, involving pre-column or post-column derivatization techniques. Driven by the growing need for rapid in situ analyses, electrochemical biosensors, comprising various combinations of different enzymes or nanomaterials for the selective bio-recognition and detection, are emerging as competitors of standard detection systems. The present review is aimed at providing an up-to-date overview on the recent progresses in the development of sensors and biosensors for the detection of polyamines in human tissues and food samples. Basic principles of different electrochemical (bio)sensor formats are reported and the applications in human tissues and in foods was evidenced