The forecasting of energy and natural gas consumption is a topic that spans different temporal and spatial scales and addresses scenarios that vary significantly in consistency and extension. Therefore, although forecasting models share common aims, the specific scale at which each model has been developed strongly impacts its features and the parameters that are to be considered or neglected. There are models designed to handle time scales, such as decades, years, and months, down to daily or hourly models of consumption. Similarly, there are patterns of forecasted consumption that range from continents or groups of nations down to the most limited targets of single individual users, passing through all intermediate levels. This paper describes a model that is able to provide a short-term profile of the hourly heat demand of end-users of a District Heating Network (DHN). The simulator uses the hourly natural gas consumptions of large groups of users and their correlation with the outside air temperature. Next, a procedure based on standards for estimating the energy performance of buildings is defined to scale results down to single-user consumption. The main objective of this work is to provide a simple and fast tool that can be used as a component of wider models of DHNs to improve the control strategies and the management of load variations. The novelty of this work lies in the development of a plain algebraic model for predicting hourly heat demand based only on average daily temperature and historical data of natural gas consumption. Whereas aggregated data of natural gas consumption for groups of end users are measured hourly or even more frequently, the thermal demand is typically evaluated over a significantly longer time horizon, such as a month or more. Therefore, the hourly profile of a single user's thermal demand is commonly unknown, and only long-term averaged values are available and predictable. With this model, used in conjunction with common weather forecasting services that reliably provide the average temperature of the following day, it is possible to predict the expected hourly heat demand one day in advance and day-by-day
Ports are characterized by several complex operations. Accordingly, the analysis of noise results is complicated due to the presence in the same area of diverse sound from ships, trade and also from industrial and shipyards activities as well as auxiliary services producing negative effects on natural ecosystem and the urban population. The ENPI CBC MED project Managing the Environmental Sustainability of Ports for a durable development (MESP) addressed the pollution reduction from port activities through the implementation of a multidisciplinary approach in air, noise and water sectors, encompassing technological, regulatory and administrative solutions to ensure natural and urban sustainability and high level of life quality in surrounding territories. To prevent a heterogeneous development, the "status quo" of ports in Northern and Southern Shores of the Mediterranean Sea was analyzed and a guideline on methodologies, good practices and measurement assessment, adaptable and transferable in different port contexts was elaborated. To assess the procedures, validation tests have been carried out to different real cases. In noise sector pilot projects in the ports of Patras, Greece, and Tripoli, Lebanon, have been implemented. Due to the dissimilar scenarios, in terms of orography, facilities and activities, different noise mitigation actions and interventions were consequently accomplished.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.