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Capítulos en libros This paper assesses the scalability and replicability of smart grid projects, by means of the identification of limitations and barriers faced by these projects. Factors have been identified that impact a project s scalability and replicability by means of a review of demonstration projects. The factors are of technical, economic, regulatory and social acceptance nature, and they describe requirements for scalability and replicability. Data was collected from ongoing European smart grid demonstration projects through the use of an elaborated questionnaire on the identified factors. Which allowed to quantify the status quo to what extent projects have taken these factors into account. Dew to their nature the derived factors can be categorized in technical, economic and regulatory & stakeholder related factor areas The obtained results allowed the identification of barriers, i.e. limitations regarding the scalability and replicability of smart grid projects. In particular projects face barriers regarding the absence of standards, the physical limits of the existing infrastructure, the absence of cost-benefit analyses, the neglect of varying macro-economic factors, stakeholder involvement and from the dependency of projects on regional or national regulatory frameworks and market designs. info:eu-repo/semantics/publishedVersion

The potential of offshore wind energy has been commonly recognized and explored globally. Many countries have implemented and planned offshore wind farms to meet their increasing electricity demands and public environmental appeals, especially in Europe. With relatively less space limitation, an offshore wind farm could have a capacity rating to hundreds of MWs or even GWs that is large enough to compete with conventional power plants. Thus the impacts of a large offshore wind farm on power system operation and security should be thoroughly studied and understood. This paper investigates the impacts of integrating a large-scale offshore wind farm into the transmission system of a power grid through VSC-HVDC connection. The concerns are focused on steady-state voltage stability, dynamic voltage stability and transient angle stability. Simulation results based on an exemplary power system are presented and analyzed.

About 25 million tons of food go wasted or lost in Iran which has socio-economic and environmental consequences for both the country and the households. The main objective of this research is to develop a model to examine the relationship between FCM components and the amount of FW of households in Tehran city, with a focus on urban women. By means of a structural model, this study provides a novel approach to exploring relationships between the food-related behavior of urban households and waste control (n = 1197). Besides, this study is the first attempt to quantify food waste in Iran at the household level. According to the adopted self-reporting procedure, in Tehran, every consumer wastes about 27.6 kg of edible food annually. It is found that households with better food consumption management (FCM (have a lower level of food waste. Moreover, the results have proved that other determinants such as demographic factors, economic power, information use, ability, and motivation have direct and indirect significant effects on FCM as well as on the amount of food waste generation. The findings suggest that the above-mentioned determinants are crucial and should be considered when developing a strategically sustainable food waste prevention plan.

Abstract This paper focuses on the impact of EUAs on the optimal policy of a competitive electricity producer. The effect of grandfathering is consistently shown to introduce significant distortions to the system. It is theoretically shown that there is a threshold value of carbon price so that, for prices above this, the EUA becomes an incentive for reduced production rather than a penalty for inefficient producers. These theoretical results are supported by the data of one producer from Italy and one from Germany. Furthermore, the empirical evidence concludes that the high level of free allowances may generate a shift in production from less to more polluting technologies.

This work has the purpose to analyze thermal performance of emergency shelters with the aim to develop different solutions which can improve the internal environmental conditions, in accordance to the parameters that describe thermo-hygrometric comfort, to the materials of which they are generally made of and to the climatic conditions under which they may be exposed. The object of the study was a tent equipped with a photovoltaic system produced by CHOSE (Center for Hybrid and Organic Solar Energy) at the University of Rome Tor Vergata. Through the use of the software IDA Indoor Climate and Energy 4.5, a simulation model was built based on experimental data collected from May 7 to May 15, 2013; model calibration was carried out comparing the simulation with the experimental data and the model was used for the formulation of different improvement solutions. The shelter model was analyzed in two different Italian climatic conditions using climatic data from Torino (winter) and Palermo (summer). The suggested optimization solutions were proven to be useful to improve the indoor climate and energy needs of the unit. The procedure can be applied to various climatic conditions and to different locations.

Abstract The contribution of wind power systems to the reduction of the impact of fossil fuels sources has increased more and more during the last decades leading to a greater attention to the estimation of the performances of renewable power plants. However, forecast methods of productivity of onshore/offshore wind farms still suffer, in terms of accuracy, the innate variability of the energy resources and the effect of components failures. This paper proposes a novel “hybrid” approach for the estimation of the energy conversion of onshore wind farms. The model combines the Jensen wake mathematical theory with a stochastic dependability model, a Fault Tree, to better forecast the energy production. A new key index was conceived to optimize the preventive maintenance of wind turbines. This model was tested on a real case study, a wind farm (25.5 MWp) located in the south of Italy. Results were promising because the model achieved a twofold objective to improve the accuracy of the energy conversion forecast and to provide a support decision system for the activities of maintenance planning.

Ilam municipality’s rapid transformation into Nepal’s ‘Green City’ illustrates a development strategy based on the aesthetic ordering of the urban environment. Aimed at creating environmentally con...

Small but numerically dominant species such as the cyanobacteria Prochlorococcus play a pivotal role in major nutrient cycles. To understand how Prochlorococcus populations affect nutrient flows, we present and analyze two alternative population models. These models − one including over-shading effects and one not − are based on Dynamic Energy Budget (DEB) theory to describe how growth may be affected by the availability of CO2 and/or inorganic nutrients and by changes in light conditions. In these models individuals have reserves for C, N, and P from which fluxes for maintenance and growth are mobilized. Time series data from laboratory studies of growth under three different nutrient concentrations are used to calibrate the models. The model with carbon, nitrogen and phosphate as limiting factors can reasonably describe the growth in the low N and low P media experiments, while the model with over-shading gives a proper description of the growth under all tested experimental conditions. Modeled C:N:P ratios are within range of reported in scientific literature ones and similar to measured ratios. The results suggest that (1) reserves play a critical role for cyanobacteria to thrive under the often oligotrophic conditions in which they live, and (2) over-shading has a considerable effect as co-limiting factor on the growth of cyanobacteria. We argue that an individual DEB-based model in which multiple nutrient limitations are presented can be used to successfully describe cyanobacterium growth patterns in batch cultures.