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Abstract The selection of an appropriate Multi-Criteria Decision Analysis method or a combination thereof, is essential to support sustainability decision-making in the waste management sector. None of the methods is ideal, so that sometimes a combination of methods may be necessary. The aim of this study is to examine the ability the Analysis and Synthesis of Parameters under Information Deficiency method to be used in sustainable waste management, as never been used method in this sector. In order to do this, scenario ranking is done using the Analytic Hierarchy Process, and the results are compared with results obtained by the Analysis and Synthesis of Parameters under Information Deficiency method. Four waste treatment scenarios were developed based on the waste composition in city of Nis, and nine indicators were selected. The obtained results indicate that there is no significant difference in the scenario ranking, regardless of the method used, the Analytic Hierarchy Process or the Analysis and Synthesis of Parameters under Information Deficiency method. The best sustainable waste management scenario is the scenario which involves composting of organic waste and recycling of inorganic waste (39.3% ranking priority). This study has illustrated how the Analysis and Synthesis of Parameters under Information Deficiency method, that has a capability to work with a lack of information, which is often the case in waste management, can be applied to assessment sustainability of waste management scenario.

The functional design of a decision support system for a state-of-the-art vehicle sharing system (VSS) inevitably includes the selection or definition of methodologies for planning and managing the observed VSS. In this paper, our focus is on an innovative VSS that utilizes light electric vehicles. Our goal is to specify the functions of a comprehensive decision making solution for such a VSS through a qualitative and systematic literature and system analysis. To achieve this goal, we rely on the holistic VSS management framework developed in our previous research. As a result of our study, we identify possible solution methodologies or algorithms for implementing functions of the designed decision making solution, and propose the necessary adjustments for their application in the case of light electric vehicles, or note any research gap. With these findings, we provide justified guidance to practitioners in creating these solutions, with the aim of reducing development time.

Abstract One of the solutions to greenhouse gases emission is the use of biodiesels, since their mixtures with petro-diesel can be used as fuel in existing diesel engines without additional corrections in engines’ design. In order to estimate engine performance and increase its efficiency, it is necessary to know the basic properties of fuels under different operating conditions, and among the most important ones are density and viscosity. Therefore, the densities of pure petro-diesel, as well as densities of its blends with sunflower oil methyl and ethyl esters, in the ratio of 10 vol% and 20 vol% of the biodiesel, at temperatures 293.15–413.15 K and at pressures of 0.1–60 MPa, are presented here. Measurements were taken at an Anton Paar DMA HP densimeter. For the device calibration the classical calibration method with one reference fluid was applied. Also, for the same samples, the viscosities at 288.15–373.15 K and the refractive indices at 288.15–343.15 K at atmospheric pressure were measured. Measured densities decrease linearly as temperature rises along isobars and increase with pressure rise at a constant temperature for all examined samples. Refractive index, also, decreases linearly with temperature rise, while viscosity decreases exponentially with increase in temperature. Densities and refractive indices are higher for blends with sunflower oil methyl esters than with its ethyl esters, opposite to viscosity. Densities of blends increase linearly with rise in biodiesel share, while the increase of viscosity is exponential. Density data were fitted to the modified Tammann-Tait equation and the obtained results were used for calculation of derived thermodynamic properties such as the isothermal compressibility, the isobaric thermal expansivity, the internal pressure and the difference between specific heat capacity at constant pressure and the specific heat capacity at constant volume. The absolute average percentage deviations of the measured densities from those calculated using the modified Tammann-Tait equation were about 0.01%, for all studied samples, assessing positively the correlation procedure. The dependence of the measured and calculated properties of the blends on biodiesel amount was also examined.

Abstract In order to uncover the inner working mechanism and performance of solid oxide fuel cell (SOFC) with biomass gasification syngas as fuel, a two dimensional SOFC multi-physical field model is established. This study makes up for the deficiency that the previous studies of coupling biomass gasification unit and SOFC stack mostly stay at the system level. The results show that the SOFC fueled by the syngas produced from gasification of biomass with steam as the agent has the best performance. The peak power density could achieve approximately 10240 W m−2. With the improvement of operating temperature, the peak power density of SOFC will be increased. At the temperature of 1123 K, the peak power density could achieve about 15128 W m−2. The average reaction rate of water gas shift (WGS) reaction is −29.73 mol m−3 s−1 when the operating temperature is 1123 K. This indicates that the WGS reaction will proceed in reverse direction at high temperatures, thereby reducing the hydrogen concentration. In addition, increase in the anode flux and decrease in the cell length lead to the increase of SOFC current density. In general, this work could provide guidance for the optimization and practical application of SOFC using biomass syngas as fuel.

District heating systems operation can be improved by control strategies. One of the options is the introduction of predictive control model. Predictive models of heat load can be applied to improve district heating system performances. In this article, short-term multistep-ahead predictive models of heat load for consumers connected to district heating system were developed using SVMs (Support Vector Machines) with FFA (Firefly Algorithm). Firefly algorithm was used to optimize SVM parameters. Seven SVM-FFA predictive models for different time horizons were developed. Obtained results of the SVM-FFA models were compared with GP (genetic programming), ANNs (artificial neural networks), and SVMs models with grid search algorithm. The experimental results show that the developed SVM-FFA models can be used with certainty for further work on formulating novel model predictive strategies in district heating systems.

In this paper, a novel intervals-based distribution short-circuit calculation algorithm is proposed. In distribution networks, there are various renewable energy-based generators (solar panels, wind generators, small hydro turbines, etc.), as well as loads with uncertain generation and consumption. Therefore, short-circuit calculation has to consider all these uncertainties. The algorithm proposed in this paper deals with above-mentioned uncertainties, as well as correlations among them. Algorithm testing is performed on two test examples of distribution networks, 6-bus and 1003-bus, for the verification of its robustness and efficiency on real-life, large-scale systems. The results demonstrate that the proposed algorithm provides highly accurate results and that it is able to solve real-life short-circuit problems with a higher precision than the traditional deterministic short-circuit calculation algorithms.

Sustainability assessment of a waste management system is a very complex problem for numerous reasons. Firstly, it is a problem of environmental assessment, economic viability and social acceptability, and also a choice of the most practical waste treatment technique, taking into account all the specific areas in which a waste management system is implemented. For these reasons, among others, it is very important to benchmark, cooperate and exchange experiences in areas with similar characteristics. In this study, a comparison of waste management scenarios in the Cities of Niš and Sofia was performed. Based on the amount and composition of municipal solid waste, and taking into account local specifics (economic conditions, social acceptance, etc.), different scenarios were developed: landfilling without energy recovery, landfilling with energy recovery, mechanical-biological treatment, anaerobic digestion with biogas utilization and incineration with energy recovery. Scenario ranking was done using multi-criteria analysis and 12 indicators were chosen as the criteria. The obtained results show that the most sustainable scenario in both case studies is the mechanical-biological treatment (recycling, composting and Refuse Derived Fuel production). Having in mind that this scenario is the current waste management system in Sofia, these results can help decision-makers in the City of Niš in choosing a successful and sustainable waste management system.

Exergy as a measure of useful work can be used in the design, simulation and performance evaluation of different energy systems. In this paper it is investigated the Serbian residential building with photovoltaics and solar collectors on the roof, and with three different heating systems: electrical heating, district heating and central heating with gas boiler. Exergy optimization was performed with the aim to determine the optimal area of the PV array and solar collectors on the roof (including embodied exergy). With these values, the maximum exergy efficiency of installed solar systems is obtained, and building primary energy consumption is minimized. The residential buildings with variable temperature in domestic hot water system, variable PV cell efficiency and variable hot water consumption are investigated in order to achieve positive-net energy building. The buildings were simulated in EnergyPlus software and Genopt was used for software execution control during optimization. The obtained results show that positive-net energy building with optimally sized photovoltaics and solar collectors’, can be achieved in a case of gas heating system, and in the cases of PV cell efficiency of 14% and 16%. Also, an environmental and economic analysis of the most favourable solutions from exergetic optimization was performed. Total CO2 emission (with embedded emissions of CO2) increases with increasing amount of generated energy – for PV system of cell efficiency of 12%, 14% and 16%, total CO2 emission of solar systems is 20.8 kg CO2/m2, 23.5 kg CO2/m2 and 26.2 kg CO2/m2, respectively. The emission payback time decreases with increasing PV cell efficiency from 1.11 to 1.04 years. With the increase of PV cell efficiency, there is an increase in the annual financial profit (from 1518 to 4305 €), while at the same time, the investment payback period decreases (from 16.9 to 6.1 years). Best results are obtained for the building with gas heating system ; Published