Demand-side management via optimal production scheduling in power-intensive industries: The case of metal casting process

The increasing challenges to the grid stability posed by the penetration of renewable energy resources urge a more active role for demand response programs as viable alternatives to a further expansion of peak power generators. This work presents a methodology to exploit the demand flexibility of energy-intensive industries under Demand-Side Management programs in the energy and reserve markets. To this end, we propose a novel scheduling model for a multi-stage multi-line process, which incorporates both the critical manufacturing constraints and the technical requirements imposed by the market. Using mixed integer programming approach, two optimization problems are formulated to sequentially minimize the cost in a day-ahead energy market and maximize the reserve provision when participating in the ancillary market. The effectiveness of day-ahead scheduling model has been verified for the case of a real metal casting plant in the Nordic market, where a significant reduction of energy cost is obtained. Furthermore, the reserve provision is shown to be a potential tool for capitalizing on the reserve market as a secondary revenue stream

Probabilistic electric load forecasting through Bayesian Mixture Density Networks

Probabilistic load forecasting (PLF) is a key component in the extended tool-chain required for efficient management of smart energy grids. Neural networks are widely considered to achieve improved prediction performances, supporting highly flexible mappings of complex relationships between the target and the conditioning variables set. However, obtaining comprehensive predictive uncertainties from such black-box models is still a challenging and unsolved problem. In this work, we propose a novel PLF approach, framed on Bayesian Mixture Density Networks. Both aleatoric and epistemic uncertainty sources are encompassed within the model predictions, inferring general conditional densities, depending on the input features, within an end-to-end training framework. To achieve reliable and computationally scalable estimators of the posterior distributions, both Mean Field variational inference and deep ensembles are integrated. Experiments have been performed on household short-term load forecasting tasks, showing the capability of the proposed method to achieve robust performances in different operating conditions.Comment: 56 page

The cardiovascular risk of young women with polycystic ovary syndrome: an observational, analytical, prospective case-control study

To evaluate the cardiovascular risk of polycystic ovary syndrome (PCOS), we investigated lipid profile, metabolic pattern, and echocardiography in 30 young women with PCOS and 30 healthy age- and body mass index (BMI)-matched women. PCOS women had higher fasting glucose and insulin levels, homeostasis model assessment score of insulin sensitivity, total cholesterol (TC) and low density lipoprotein cholesterol (LDL-C) levels, and TC/high density lipoprotein cholesterol (HDL-C) ratio and lower HDL-C levels than controls. Additionally, PCOS women had higher left atrium size (32.0 +/- 4.9 vs. 27.4 +/- 2.1 mm; P < 0.0001) and left ventricular mass index (80.5 +/- 18.1 vs. 56.1 +/- 5.4 g/m(2); P < 0.0001) and lower left ventricular ejection fraction (64.4 +/- 4.1 vs. 67.1 +/- 2.6%; P = 0.003) and early to late mitral flow velocity ratio (1.6 +/- 0.4 vs. 2.1 +/- 0.2; P < 0.0001) than controls. When patients and controls were grouped according to BMI [normal weight (BMI, >18 and <25 kg/m(2)), overweight (BMI, 25.1-30 kg/m(2)), and obese (BMI, >30 kg/m(2))], the differences between PCOS women and controls were maintained in overweight and obese women. In normal weight PCOS women, a significant increase in left ventricular mass index and a decrease in diastolic filling were observed, notwithstanding no change in TC, LDL-C, HDL-C, TC/HDL-C ratio, and TG compared with controls. In conclusion, our data show the detrimental effect of PCOS on the cardiovascular system even in young women asymptomatic for cardiac disease

preliminary design of a mw class demo system for co2 capture with mcfc in a university campus cogeneration plant

Abstract One of the most promising, short-term options for efficiently capturing CO 2 from combustion exhaust gases – potentially from any combustion process source - is based on the operating principle of Molten Carbonate Fuel Cells (MCFC): their electrochemical reactions promote the transport of both CO 2 and O 2 molecules from the cathode side (which can be fed with combustion effluents) to the CO 2 -rich atmosphere of the anode side (fed with internally reformed natural gas), by means of a CO 3 2- -ion conducting electrolyte. In the present work, the preliminary design of a 1 MW el MCFC demo plant operating downstream a Combined Heat and Power (CHP) Internal Combustion Engine (ICE) installed at the Politecnico di Milano campus is investigated, with the aim of promoting a valid solution for high efficiency, de-carbonised heat and electricity production. The study envisages two purification strategies for the CO 2 -rich stream at the MCFC anode outlet: i) the CO 2 is separated and compressed in a cryogenic unit and the unconverted fuel is either recycled at the anode inlet or burned and sent to the MCFC cathode inlet ii) the anode exhausts are burned in a catalytic oxy-combustor, increasing both the thermal energy available in the cogeneration unit and the CO 2 concentration in the stream sent to the storage site. Subsequently to a thermodynamic analysis carried out with a 0D model calibrated upon experimental data available for a commercial MCFC unit, the main components are designed by taking into account all the operating constraints of the machines and the CO 2 capture limitations associated to the size of the MCFC modules currently available on the market. Moreover, an economic analysis is performed in order to assess the feasibility of such an installation within the university campus cogeneration grid. As a main finding, the use of MCFCs to capture CO 2 at a distributed generation scale allows reaching interesting energy and environmental performances, highlighted by promising values of the Specific Primary Energy Consumption for CO 2 Avoided (SPECCA=0.9-1.9 MJ/kgCO 2 ) and Carbon Capture Ratios (CCR=68-84%). Within a mid-term perspective for MCFC specific cost, the economic analyses reveal acceptable values for the cost of electricity and the cost of CO 2 avoided, respectively close to 130 €/MWh el and 100 €/tCO 2

Application of Molten Carbonate Fuel Cells in Cement Plants for CO2 Capture and Clean Power Generation

Abstract Cement production process features intrinsically large CO 2 emission due to the decomposition of limestone by calcination reaction and to fuel combustion, necessary for sustaining the endothermic calcination process and the formation of clinker. Conventional approaches to CO 2 emission reduction in cement plants are based on post-combustion capture with chemical solvents, requiring a substantial energy consumption for regeneration, or oxycombustion in the cement kiln, involving a deep redesign of the plant. The aim of this work is investigating the application of Molten Carbonate Fuel Cells in cement plants for CO 2 capture from the plant exhaust gases, using the fuel cells as active CO 2 concentrators of combustion flue gases and eventually obtaining a purified CO 2 stream through a cryogenic process. A novel configuration with MCFCs added along the exhaust line has been assessed by means of process simulations. The results show a remarkable potential in terms of equivalent avoided CO 2 emissions (exceeding 1000 g/kWh), high share of CO 2 avoided (up to about 70%) and low energy penalties

NATURWALL© - A Solar Timber Façade System for Building Refurbishment: Optimization Process through in Field Measurements

Building renovation is one of the key issues of recent European policies towards energy efficiency. The concept of an opaque, modular and prefabricated vertical façade, made of wood and lightweight components, is proposed in this framework. Naturwall© is an Italian patented project intended for the retrofitting of existing buildings, to improve both the energy performance of the building and its architectural aspect. Different prototypes of the façade were tested during an experimental campaign carried out in outdoor test cells. The here presented results describe the winter and summer behavior of the façade through the use of synthetic indexes i.e. the U-value and pre-heating efficiency