This article assesses the impact of extensive deployment of indigenous and external renewable energy sources on a local electricity system (Sardinia Island) and discusses the main challenges faced by the European power grids in integrating high shares of renewable-based generation technologies. It presents the 2030 scenarios for the Sardinian power system and the results of steady-state analyses in extreme (renewable) generation and consumption conditions. These results are eventually combined with the assessment of key technology development trends to explain how this can affect the development of a European supergrid. In general, the article stresses that rendering the bulk-power system capable of accommodating high renewable energy penetration not only requires reinforcing the electricity highways but also demands carefully planning the architecture of and the interface with regional power systems. 相似文献
Life cycle assessment (LCA) of waste treatment processes is often associated with considerable uncertainties. The aim of this study is to estimate the total uncertainty in the modelled composting system and the influence of material and process parameters on the uncertainty. Four composting combinations with fresh (FC) and mature substrate compost (MSC) from partially enclosed (PEC) and open composting (OC) were investigated. Perturbation analysis was used to determine the effect of parameters on the result and Monte Carlo simulation was used to estimate the total uncertainty. This study showed that the production of MSC using PEC had the lowest overall impacts across all impact categories except ozone depletion. Results of the Monte Carlo simulation showed that comparing composting options was challenging. The sensitivity ratios obtained from the perturbation analysis showed that the process parameter percentage of carbon fraction degraded was the most influential for FC. In MSC, the moisture content in the input material and the substitution factor used for peat were the most influential. Monte Carlo simulations demonstrated the overall uncertainty of the model and its relevance when comparing results between combinations. The perturbation analysis identified the parameters that required more accurate data to reduce the uncertainty in the model.