Development of an environmental and economic optimization model for distributed generation energy systems

The reduction of pollutant emissions is one of the current main targets fixed by the most important international authorities. The reduction of the energy needs in the residential-tertiary sector can help achieving this goal, as it represents one of the dominant energy consuming sectors in industrialized societies. However the adoption of an energy system still depend on technical and economical evaluations, while environmental considerations are not taken into consideration yet. For this reason, a development of a tool for the selection of an energy system which allows the reduction of the overall costs containing in the meanwhile the pollutant emissions could help reaching the environmental targets. The thesis proposes a methodology for the Multiobjective optimization of a Dis- tributed Generation Energy System. Such a system is normally constituted by several users connected to each other and to a central unit through a District Heating Network. Furthermore, each unit can be equipped with an internal production unit for the production of its energy needs. Therefore, the determination of the optimal energy system requires the simultaneous optimization of the synthesis, design and operation of the whole energy system. The total annual cost for owning, operating and maintaining the whole system is considered as economic objective function, while the total annual operation CO2 emissions is considered as environmental objective function. An optimization MILP model for the optimization of tertiary sector Distributed Generation Energy Systems is developed and is applied to a real case study, made up of nine tertiary sector users located in a small town city center situated in the North-East of Italy. A preliminary energy audit allowed the determination of the users\u2019 energy needs. The energy system is optimized for different configurations in order to understand how different components affect the optimal solution

Optimization of a Distributed Cogeneration System with solar district heating

The aim of the paper is to identify the optimal energy production system and its optimal operation strategy required to satisfy the energy demand of a set of users in an industrial area. A distributed energy supply system is made up of a district heating network, a solar thermal plant with long term heat storage, a set of Combined Heat and Power units and conventional components also, such as boilers and compression chillers. In this way the required heat can be produced by solar thermal modules, by natural gas cogenerators, or by conventional boilers. The decision variable set of the optimization procedure includes the sizes of various components, the solar field extension and the thermal energy recovered in the heat storage, while additional binary decision variables describe the existence/absence of each considered component and its on/off operation status. The optimization algorithm is based on a Mixed Integer Linear Programming (MILP) model that minimizes the total annual cost for owning, maintaining and operating the whole energy supply system. It allows to calculate both the economic and the environmental benefits of the solar thermal plant, cooperating with the cogeneration units, as well as the share of the thermal demand covered by renewable energy, in the optimal solutions. The results obtained analyzing different system configurations show that the minimum value of the average useful heat costs is achieved when cogenerators, district heating network, solar field and heat storage are all included in the energy supply system and optimized consistently. Thus, the integrated solution turns out to be the best from both the economic and environmental points of view

Impact of SARS-CoV-2 Omicron and Delta variants in patients requiring intensive care unit (ICU) admission for COVID-19, Northern Italy, December 2021 to January 2022

This multicenter observational study included 171 COVID-19 adult patients hospitalized in the ICUs of nine hospitals in Lombardy (Northern Italy) from December, 1st 2021, to February, 9th 2022. During the study period, the Delta/Omicron variant ratio of cases decreased with a delay of two weeks in ICU patients compared to that in the community; a higher proportion of COVID-19 unvaccinated patients was infected by Delta than by Omicron whereas a higher rate of COVID-19 boosted patients was Omicron-infected. A higher number of comorbidities and a higher comorbidity score in ICU critically COVID-19 inpatients was positively associated with the Omicron infection as well in vaccinated individuals. Although people infected by Omicron have a lower risk of severe disease than those infected by Delta variant, the outcome, including the risk of ICU admission and the need for mechanical ventilation due to infection by Omicron versus Delta, remains uncertain. The continuous monitoring of the circulating SARS-CoV-2 variants remains a milestone to counteract this pandemic