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Abstract To achieve the EU climate and energy objectives, a transition towards a future sustainable energy system is needed. The integration of the huge potential for industrial waste heat recovery into smart energy system represents a main opportunity to accomplish these goals. To successfully implement this strategy, all the several stakeholders' conflicting objectives should be considered. In this paper an evolutionary multi-objective optimization model is developed to perform a sustainability evaluation of an energy system involving an industrial facility as the waste heat source and the neighbourhood as district heating network end users. An Italian case study of heat recovery from a steel casting facility shows how the model allows to properly select the district heating network set of users to fully exploit the available waste energy. Design directions such as the thermal energy storage capacity can be also provided. Moreover, the model enables the analysis of the trade-off between the stakeholders’ different perspectives, allowing to identify possible win-win solutions for both the industrial sector and the citizenship.

Abstract Forecasting the future price of crude oil, which has an important role in the global economy, is considered as a hot matter for both investment companies and governments. However, forecasting the price of crude oil with high precision is indeed a challenging task because of the nonlinear dynamics of the crude oil time series, including chaotic behavior and inherent fractality. In this study, a new forecasting model based on support vector regression (SVR) with a wrapper-based feature selection approach using multi-objective optimization technique is developed to deal with this challenge. In our model, features based on technical indicators such as simple moving average (SMA), exponential moving average (EMA), and Kaufman’s adaptive moving average (KAMA) are utilized. SMA, EMA, and KAMA indicators are obtained from Brent crude oil closing prices under different parameters. The features based on SMA and EMA indicators are formed by changing the period values between 3 and 10. The features based on the KAMA indicator are obtained by changing the efficiency ratio (ER) period value, which is considered as fractality efficiency, between 3 and 10. The features are selected by the wrapper-based approach consisting of multi-objective particle swarm optimization (MOPSO) and radial basis function based SVR (RBFSVR) techniques considering both the mean absolute percentage error (MAPE) and Theil’s U values. The obtained empirical results show that the proposed forecasting model can capture the nonlinear properties of crude oil time series, and that better forecasting performance can be obtained in terms of precision and volatility than the other current forecasting models.

Abstract The sustainable indicators are characterized by a low degree of aggregation and a high amount of information. An indicator must show a synthetic representation of a real environmental, by using a value or a parameter, so that they can be easily used by policy makers. It is necessary to connect, therefore, the various systems in an appropriately integrated sustainable system. The indicators need to be aggregated based on the structure of the data. Each indicator must to be defined through a weight with reference to another weighted indicator. In this paper is illustrated the calculation of the assigned weights that uses a procedure based on fuzzy logic and to define a model that allows us to estimate the sustainability of a city. The final result is, therefore, a combination of values assigned by expert opinion for the various criteria, processed using fuzzy logic to obtain a weight with significant objectivity and as it is possible to estimate the sustainability of the city through the weights.

Abstract A novel integrated energy system based on a geothermal heat source and a liquefied natural gas heat sink is proposed in this study for providing heating, cooling, electricity power, and drinking water simultaneously. The arrangement is a cascade incorporating a flash-binary geothermal system, a regenerative organic Rankine cycle, a simple organic Rankine cycle, a vapor compression refrigeration cycle, a regasification unit, and a reverse osmosis desalination system. Energy, exergy, and exergoeconomic methods are employed to analyze the suggested system. A parametric study based on decision variables is carried out to better assess the system performance. Four different multi-objective optimization problems are also carried out. At the most excellent trade-off solution specified by the TOPSIS method, the system attains 29.15% exergy efficiency and 1.512 $/GJ total product cost per exergy unit. The main output products are consequently calculated to be 101.07 kg/s cooling water, 570.44 kW net output power, and 81.57 kg/s potable water.

Abstract Recent studies suggest that the supplementation of powdered Fe° generates a positive effect on anaerobic fermentation processes but the exact relationship between metals with biological systems has not been fully elucidated. Experimental tests on dark fermentation (DF) were carried out at different Fe° concentrations. The anaerobic corrosion (AC) of Fe° and the production of H2 through DF of Organic Waste Market (OWM) were tested separately, and subsequently DF tests with Fe° at 1 g/L and 2 g/L were carried out. A macroscopic dynamic study was conducted, using Roels approach based on relaxation times (τR) to establish whether interactions between AC and DF phenomena exist. Experimental bioH2 production and Fe° AC were fit by Gompertz and saturative models, respectively to estimate τR. The results of the macro-analysis suggest that both phenomena are concurrent, with τR of the same order of magnitude, generating a positive symbiotic effect. The experimental tests of hydrogen production via DF in presence of 2 g/L of Fe° showed an increase of 46% compared with the control tests, of amount of gas and a greater H2/CO2 ratio. The results suggest an enhancement of key enzymes activity due to the action of iron increasing bioH2 production.

Abstract In order to evaluate non-steady phase contribution to the total emissions of a pellet stove in real domestic operations, particulate matter and gaseous emissions were determined separately for different operating conditions, i.e. ignition, partial load, increase in power and nominal load. TSP (Total suspended particulate) was sampled with a dilution system and characterized for TC (total carbon), PAHs (polycyclic aromatic hydrocarbons), the main soluble ions, Ni, As, Cd and Pb. Gas monitoring shows that CO and NO emission factors in ignition phase markedly differ from other operating conditions: NO emission factor is lower, while CO one is much higher, since it is a product of incomplete combustion. Start-up phase emission factors are also higher for TSP, Cd and other products of incomplete combustion, i.e. TC and PAHs. Despite being a non-steady phase, the increase in power phase emission factors appreciably differ from steady state ones only for PAHs. Moreover, the PAHs emitted in non-steady state phases have a higher toxicological burden. In conclusion, in order to evaluate the real impact of pellet stove on the environment, transient conditions should be taken into account. The ignition phase, even though it lasts only 20 min, can significantly contribute to pollutant emission.

Abstract The aim of the present research is to evaluate future primary energy consumption in the Italian thermoelectric sector. Despite its importance in the European context, researches addressing the primary energy consumption in the Italian power sector are not available in the literature. Therefore, to bridge this gap, a detailed representation of the power generation sector is proposed by modeling each individual thermal power station by considering its main features (i.e. maximum power, minimum stable level, efficiency, etc.), in order to estimate the future energy balances and the trend of power prices. An evolution of the generation fleet is designed according to available information from different sources and a simulation based on plant by plant competition is performed up to the year 2022. The impact of different fuel and carbon price scenarios is analyzed in terms of primary energy consumption. The analysis has shown that a high level of CO 2 prices does not foster the coal to gas transition, but it causes a relevant increase of power prices. In fact in the best case, it is detected that in 2022, for a carbon price of 30 €/t and a “base” price scenario for fossil fuels, there is a decrease of coal consumption of ∼5.6% and an increase of power price of +19% with respect to the base carbon prices. Therefore, it follows that final users are penalized, because they are expected to pay much higher electricity bills to obtain a modest reduction of coal consumption and carbon emissions.

Abstract A comparison of possible solutions for small scale (0.2–1 MWe) waste-to-energy gasification-based industrial application is presented. A pilot scale bubbling fluidized bed air blown gasifier, having a capacity of 500 kWe, provided experimental data: the syngas complete composition as well as the characterization of the bed material and contaminants downstream of the cyclone and wet scrubber. Mass and energy balances and material and substance flow analyses have been drawn to assess and compare design solutions utilizing a packaging derived fuel (PDF) obtained as scrap by food industrial processes. The related environmental, energetic and economic performances have been estimated on the basis of the experimental data and manufacturer’s specifications. In the scale range analyzed, the best solution is that of a power gasification coupled with an internal combustion engine, which provides high reliability and high internal rate of return.