Strategie di ottimizzazione di reti energetiche complesse in presenza di generazione distribuita

This project has been conceived in order to analyze and try to answer to the new issues created by complex energy networks and distributed generation scenarios. The carried our research project can be divided into two main parts. The first one focuses on thermal energy networks, i.e. on district heating networks: existing case studies have been modeled and analyzed with an in-house developed software and the new concept of smart district heating has been developed (different configurations for the bidirectional heat exchange at final users have been developed and tested). The second part of the PhD project aims to the definition of optimal strategies within complex energy networks, when thermal, electric and cooling energies are required by a certain number of users, eventually in a distributed generation scenario. In particular, a specific calculation code based on genetic algorithms has been developed and different cases studies have been analyzed, also in isolated energy grid application. Finally, a comparison between the genetic algorithm approach and a mixed integer linear programming based software has been carried out during a research period abroad, at EPFL University in Switzerland

Modelling a Prototype of Bidirectional Substation for District Heating with Thermal Prosumers

The performance of the innovative configurations of the “efficient” thermal networks is a key topic in scientific research, focusing on distribution temperatures and integration with high-efficiency plants and renewable sources. As it already happens for the electricity prosumers, a thermal prosumer may feed the district heating network through a bidirectional exchange substation with the excess of the locally produced thermal energy (e.g., by means of solar thermal plant) or with the waste heat recovered in the industrial processes. The Italian National Agency for New Technologies, Energy and Sustainable Economic Development (ENEA) and the Alma Mater Studiorum University of Bologna (UNIBO) designed a bidirectional substation prototype, based on a return-to-supply configuration, and tested steady-state and dynamic conditions to evaluate performances and optimization measures. In this paper, the Modelica language and Dymola software were used to run a multi-domain simulation and model-based design of the substation, starting from a new heat exchanger model featuring variable efficiency, based on the thermal resistance scaling method. Control systems and components were customized from models in standard libraries in order to reproduce the substation behavior under defined operating settings, and the model was validated on the abovementioned experimental tests. Numerical results in terms of exchanged powers, temperatures and flow rates were systematically compared to experimental data, demonstrating a sufficient agreement. In particular, the absolute mean deviation—in terms of temperature—between experimental and numerical data assessed over the entire tests remains contained in +/-1 °C. As further step of the analysis, an optimized model could be included as a component in a district heating network for further investigations on the prosumers’ effects on an existing traditional grid (e.g., in case of deep renovation of urban areas connected to district heating and/or creation of micro energy communities)

Low temperature district heating networks for complete energy needs fulfillment

In order to reduce fossil fuels consumption and pollutant emissions, high contribution is given by district heating. In particular, the integration with renewable energy may lead to a significant increase in energy conversion efficiency and energy saving. Further benefits can be achieved with low temperature district heating, reducing the thermal dissipations through the network and promoting the exploitation of low enthalpy heat sources. The aim of the paper is the analysis of the potential related to the conversion of existing district heating networks, to increase the exploitation of renewable sources and eliminate pollutant emissions in the city areas. Further aim, in this context, is the optimization – from both energy production and operation management viewpoints – of a low temperature district heating network for the fulfillment of the connected users’ energy needs. To this respect, a traditional network with a fossil fuel driven thermal production plant has been considered and compared with a low temperature district heating scenario, including geothermal heat pumps, photovoltaic panels and absorption chillers. These scenarios have been analyzed and optimized with an in-house developed software, allowing to demonstrate the reduction of primary energy consumption and CO2 pollutant emissions achievable with low temperature networks. In addition, a preliminary economic evaluation has been carried out to compare the proposed solution with traditional district heating

Efficient District Heating in a Decarbonisation Perspective: A Case Study in Italy

The European and national regulations in the decarbonisation path towards 2050 promote district heating in achieving the goals of efficiency, energy sustainability, use of renewables, and reduction of fossil fuel use. Improved management and optimisation, use of RES, and waste heat/cold sources decrease the overall demand for primary energy, a condition that is further supported by building renovations and new construction of under (almost) zero energy buildings, with a foreseeable decrease in the temperature of domestic heating systems. Models for the simulation of efficient thermal networks were implemented and described in this paper, together with results from a real case study in Italy, i.e., University Campus of Parma. Activities include the creation and validation of calculation codes and specific models in the Modelica language (Dymola software), aimed at investigating stationary regimes and dynamic behaviour as well. An indirect heat exchange substation was coupled with a resistive-capacitive model, which describes the building behaviour and the thermal exchanges by the use of thermos-physical parameters. To optimise indoor comfort conditions and minimise consumption, dynamic simulations were carried out for different operating sets: modulating the supply temperature in the plant depending on external conditions (Scenario 4) decreases the supplied thermal energy (-2.34%) and heat losses (-8.91%), even if a lower temperature level results in higher electricity consumption for pumping (+12.96%), the total energy consumption is reduced by 1.41%. A simulation of the entire heating season was performed for the optimised scenario, combining benefits from turning off the supply in the case of no thermal demand (Scenario 3) and from the modulation of the supply temperature (Scenario 4), resulting in lower energy consumption (the thermal energy supplied by the power plant -3.54%, pumping +7.76%), operating costs (-2.40), and emissions (-3.02%). The energy balance ex-ante and ex-post deep renovation in a single user was then assessed, showing how lowering the network operating temperature at 55 degrees C decreases the supplied thermal energy (-22.38%) and heat losses (-22.11%) with a slightly higher pumping consumption (+3.28%), while maintaining good comfort conditions. These promising results are useful for evaluating the application of low-temperature operations to the existing district heating networks, especially for large interventions of building renovation, and confirm their potential contribution to the energy efficiency targets

The rapid spread of SARS-COV-2 Omicron variant in Italy reflected early through wastewater surveillance

The SARS-CoV-2 Omicron variant emerged in South Africa in November 2021, and has later been identified worldwide, raising serious concerns. A real-time RT-PCR assay was designed for the rapid screening of the Omicron variant, targeting characteristic mutations of the spike gene. The assay was used to test 737 sewage samples collected throughout Italy (19/21 Regions) between 11 November and 25 December 2021, with the aim of assessing the spread of the Omicron variant in the country. Positive samples were also tested with a real-time RT-PCR developed by the European Commission, Joint Research Centre (JRC), and through nested RT-PCR followed by Sanger sequencing. Overall, 115 samples tested positive for Omicron SARS-CoV-2 variant. The first occurrence was detected on 7 December, in Veneto, North Italy. Later on, the variant spread extremely fast in three weeks, with prevalence of positive wastewater samples rising from 1.0% (1/104 samples) in the week 5-11 December, to 17.5% (25/143 samples) in the week 12-18, to 65.9% (89/135 samples) in the week 19-25, in line with the increase in cases of infection with the Omicron variant observed during December in Italy. Similarly, the number of Regions/Autonomous Provinces in which the variant was detected increased from one in the first week, to 11 in the second, and to 17 in the last one. The presence of the Omicron variant was confirmed by the JRC real-time RT-PCR in 79.1% (91/115) of the positive samples, and by Sanger sequencing in 66% (64/97) of PCR amplicons. In conclusion, we designed an RT-qPCR assay capable to detect the Omicron variant, which can be successfully used for the purpose of wastewater-based epidemiology. We also described the history of the introduction and diffusion of the Omicron variant in the Italian population and territory, confirming the effectiveness of sewage monitoring as a powerful surveillance tool

The rapid spread of SARS-COV-2 Omicron variant in Italy reflected early through wastewater surveillance

The SARS-CoV-2 Omicron variant emerged in South Africa in November 2021, and has later been identified worldwide, raising serious concerns. A real-time RT-PCR assay was designed for the rapid screening of the Omicron variant, targeting characteristic mutations of the spike gene. The assay was used to test 737 sewage samples collected throughout Italy (19/21 Regions) between 11 November and 25 December 2021, with the aim of assessing the spread of the Omicron variant in the country. Positive samples were also tested with a real-time RT-PCR developed by the European Commission, Joint Research Centre (JRC), and through nested RT-PCR followed by Sanger sequencing. Overall, 115 samples tested positive for Omicron SARS-CoV-2 variant. The first occurrence was detected on 7 December, in Veneto, North Italy. Later on, the variant spread extremely fast in three weeks, with prevalence of positive wastewater samples rising from 1.0% (1/104 samples) in the week 5–11 December, to 17.5% (25/143 samples) in the week 12–18, to 65.9% (89/135 samples) in the week 19–25, in line with the increase in cases of infection with the Omicron variant observed during December in Italy. Similarly, the number of Regions/Autonomous Provinces in which the variant was detected increased fromone in the first week, to 11 in the second, and to 17 in the last one. The presence of the Omicron variant was confirmed by the JRC real-time RT-PCR in 79.1% (91/115) of the positive samples, and by Sanger sequencing in 66% (64/97) of PCR amplicons

The Role of Attitudes Toward Medication and Treatment Adherence in the Clinical Response to LAIs: Findings From the STAR Network Depot Study

Background: Long-acting injectable (LAI) antipsychotics are efficacious in managing psychotic symptoms in people affected by severe mental disorders, such as schizophrenia and bipolar disorder. The present study aimed to investigate whether attitude toward treatment and treatment adherence represent predictors of symptoms changes over time. Methods: The STAR Network \u201cDepot Study\u201d was a naturalistic, multicenter, observational, prospective study that enrolled people initiating a LAI without restrictions on diagnosis, clinical severity or setting. Participants from 32 Italian centers were assessed at three time points: baseline, 6-month, and 12-month follow-up. Psychopathological symptoms, attitude toward medication and treatment adherence were measured using the Brief Psychiatric Rating Scale (BPRS), the Drug Attitude Inventory (DAI-10) and the Kemp's 7-point scale, respectively. Linear mixed-effects models were used to evaluate whether attitude toward medication and treatment adherence independently predicted symptoms changes over time. Analyses were conducted on the overall sample and then stratified according to the baseline severity (BPRS < 41 or BPRS 65 41). Results: We included 461 participants of which 276 were males. The majority of participants had received a primary diagnosis of a schizophrenia spectrum disorder (71.80%) and initiated a treatment with a second-generation LAI (69.63%). BPRS, DAI-10, and Kemp's scale scores improved over time. Six linear regressions\u2014conducted considering the outcome and predictors at baseline, 6-month, and 12-month follow-up independently\u2014showed that both DAI-10 and Kemp's scale negatively associated with BPRS scores at the three considered time points. Linear mixed-effects models conducted on the overall sample did not show any significant association between attitude toward medication or treatment adherence and changes in psychiatric symptoms over time. However, after stratification according to baseline severity, we found that both DAI-10 and Kemp's scale negatively predicted changes in BPRS scores at 12-month follow-up regardless of baseline severity. The association at 6-month follow-up was confirmed only in the group with moderate or severe symptoms at baseline. Conclusion: Our findings corroborate the importance of improving the quality of relationship between clinicians and patients. Shared decision making and thorough discussions about benefits and side effects may improve the outcome in patients with severe mental disorders

Clinical features and outcomes of elderly hospitalised patients with chronic obstructive pulmonary disease, heart failure or both

Background and objective: Chronic obstructive pulmonary disease (COPD) and heart failure (HF) mutually increase the risk of being present in the same patient, especially if older. Whether or not this coexistence may be associated with a worse prognosis is debated. Therefore, employing data derived from the REPOSI register, we evaluated the clinical features and outcomes in a population of elderly patients admitted to internal medicine wards and having COPD, HF or COPD + HF. Methods: We measured socio-demographic and anthropometric characteristics, severity and prevalence of comorbidities, clinical and laboratory features during hospitalization, mood disorders, functional independence, drug prescriptions and discharge destination. The primary study outcome was the risk of death. Results: We considered 2,343 elderly hospitalized patients (median age 81 years), of whom 1,154 (49%) had COPD, 813 (35%) HF, and 376 (16%) COPD + HF. Patients with COPD + HF had different characteristics than those with COPD or HF, such as a higher prevalence of previous hospitalizations, comorbidities (especially chronic kidney disease), higher respiratory rate at admission and number of prescribed drugs. Patients with COPD + HF (hazard ratio HR 1.74, 95% confidence intervals CI 1.16-2.61) and patients with dementia (HR 1.75, 95% CI 1.06-2.90) had a higher risk of death at one year. The Kaplan-Meier curves showed a higher mortality risk in the group of patients with COPD + HF for all causes (p = 0.010), respiratory causes (p = 0.006), cardiovascular causes (p = 0.046) and respiratory plus cardiovascular causes (p = 0.009). Conclusion: In this real-life cohort of hospitalized elderly patients, the coexistence of COPD and HF significantly worsened prognosis at one year. This finding may help to better define the care needs of this population

Defining Kawasaki disease and pediatric inflammatory multisystem syndrome-temporally associated to SARS-CoV-2 infection during SARS-CoV-2 epidemic in Italy: results from a national, multicenter survey

Background: There is mounting evidence on the existence of a Pediatric Inflammatory Multisystem Syndrome-temporally associated to SARS-CoV-2 infection (PIMS-TS), sharing similarities with Kawasaki Disease (KD). The main outcome of the study were to better characterize the clinical features and the treatment response of PIMS-TS and to explore its relationship with KD determining whether KD and PIMS are two distinct entities. Methods: The Rheumatology Study Group of the Italian Pediatric Society launched a survey to enroll patients diagnosed with KD (Kawasaki Disease Group - KDG) or KD-like (Kawacovid Group - KCG) disease between February 1st 2020, and May 31st 2020. Demographic, clinical, laboratory data, treatment information, and patients' outcome were collected in an online anonymized database (RedCAP®). Relationship between clinical presentation and SARS-CoV-2 infection was also taken into account. Moreover, clinical characteristics of KDG during SARS-CoV-2 epidemic (KDG-CoV2) were compared to Kawasaki Disease patients (KDG-Historical) seen in three different Italian tertiary pediatric hospitals (Institute for Maternal and Child Health, IRCCS "Burlo Garofolo", Trieste; AOU Meyer, Florence; IRCCS Istituto Giannina Gaslini, Genoa) from January 1st 2000 to December 31st 2019. Chi square test or exact Fisher test and non-parametric Wilcoxon Mann-Whitney test were used to study differences between two groups. Results: One-hundred-forty-nine cases were enrolled, (96 KDG and 53 KCG). KCG children were significantly older and presented more frequently from gastrointestinal and respiratory involvement. Cardiac involvement was more common in KCG, with 60,4% of patients with myocarditis. 37,8% of patients among KCG presented hypotension/non-cardiogenic shock. Coronary artery abnormalities (CAA) were more common in the KDG. The risk of ICU admission were higher in KCG. Lymphopenia, higher CRP levels, elevated ferritin and troponin-T characterized KCG. KDG received more frequently immunoglobulins (IVIG) and acetylsalicylic acid (ASA) (81,3% vs 66%; p = 0.04 and 71,9% vs 43,4%; p = 0.001 respectively) as KCG more often received glucocorticoids (56,6% vs 14,6%; p < 0.0001). SARS-CoV-2 assay more often resulted positive in KCG than in KDG (75,5% vs 20%; p < 0.0001). Short-term follow data showed minor complications. Comparing KDG with a KD-Historical Italian cohort (598 patients), no statistical difference was found in terms of clinical manifestations and laboratory data. Conclusion: Our study suggests that SARS-CoV-2 infection might determine two distinct inflammatory diseases in children: KD and PIMS-TS. Older age at onset and clinical peculiarities like the occurrence of myocarditis characterize this multi-inflammatory syndrome. Our patients had an optimal response to treatments and a good outcome, with few complications and no deaths