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Among various bioreactors examined in anaerobic digestion and dark fermentation, UASB bioreactor has shown to be a promising alternative. However, mass transfer resistance and biomass washout have been the issues that reported as draw backs of the granular system in the literature. Another problem associated with such a system is its long start-up period as a result of biomass washout and long microbial granulation stage. In this paper, the results obtained from an UASFF bioreactor in methane (AD process) and hydrogen (DF process) production from POME, are presented to assess mass transfer of substrate into the granules and also study the role of internal packing used in the middle part of reactor in the process stability. The value of effectiveness factor, η, for AD and DF processes were calculated to be 0.96 and 0.94, respectively, indicating that there was no mass transfer resistance due to internal and/or external factors. The results showed that the packing material could retain biomass in the reactor and had outstanding contribution in the granulation enhancement. Its role as a supplementing treatment stage was more significant at low HRTs and up-flow velocities.

This paper presents a novel modified interactive honey bee mating optimization (IHBMO) base fuzzy stochastic long-term approach for determining optimum location and size of distributed energy resources (DERs). The Monte Carlo simulation method is used to model the uncertainties associated with long-term load forecasting. A proper combination of several objectives is considered in the objective function. Reduction of loss and power purchased from the electricity market, loss reduction in peak load level and reduction in voltage deviation are considered simultaneously as the objective functions. First, these objectives are fuzzified and designed to be comparable with each other. Then, they are introduced into an IHBMO algorithm in order to obtain the solution which maximizes the value of integrated objective function. The output power of DERs is scheduled for each load level. An enhanced economic model is also proposed to justify investment on DER. An IEEE 30-bus radial distribution test system is used to illustrate the effectiveness of the proposed method.

Abstract Thermal performance of three naturally ventilated public buildings in which the wind tower is an important architectural freature is studied. One of the three builidings as well as it's wind tower is instrumented for temperature, relative humidity and airflow velocity measurements, and the other two are instrumented for temperature measurement. The results have led to a discussion concerning the degree of wind tower effectiveness in achieving thermal comfort.

Abstract In-core nuclear fuel management is one of the most important concerns in the design of nuclear reactors. Two main goals in core fuel loading pattern design optimization are maximizing the core effective multiplication factor in order to extract the maximum energy, and keeping the local power peaking factor lower than a predetermined value to maintain the fuel integrity. Because of the numerous possible patterns of fuel assemblies in the reactor core, finding the best configuration is so important and challenging. Different techniques for optimization of fuel loading pattern in the reactor core have been introduced by now. In this study, a software is programmed in C# language to find an order of the fuel loading pattern of a VVER-1000 reactor core using the perturbation theory. Our optimization method is based on minimizing the radial power peaking factor. The optimization process launches by considering an initial loading pattern and the specifications of the fuel assemblies which are given as the input of the software. The results on a typical VVER-1000 reactor reveal that the method could reach to a pattern with an allowed radial power peaking factor and increases the cycle length 1.1 days, as well.

Abstract The power system needs to satisfy its customers demand with minimum cost and emission. Fuel cost has straight relationship with energy cost. This paper presents an advanced parallelized particle swarm optimization algorithm (PSPSO) for finding optimal combination of power generation units that minimizes the total fuel cost and emission. In this algorithm, time requirements for solving complex large-scale CEED problem can be substantially reduced using parallel computation and it performs the update of positions and velocities in the end of each iteration. The proposed approach is applied on four test systems and compared with other techniques. The results represent that PSPSO has better convergence than other techniques.

Abstract Commercial potential in developing countries has always received a great attention from international investors, but this is not the case in Waste-to-Energy sector. Waste-to-Energy is bound up with various uncertainties rooted in its long-term nature therefore incorporating risks regarding political matters in developing countries makes it more complex. The present study substantiates the incompatibility of classic valuation methods in risky projects. Consequently, to deal with the riskiness of Waste-to-Energy investment in less developed countries, the combination of binomial tree analysis and Decoupled NPV is proposed. The hybrid approach is deployed to value a Waste-to-Energy project in Iran, and all evidence attest to the robustness of the method. The contribution of this paper can open up new vistas for investing in Waste-to-Energy industry, thus abating the catastrophic effects of landfill gas emissions.

Abstract Economically harvesting energy from a microbial fuel cell (MFC), increasing its electrical power production, and developing its role as a practical energy supply, needs a low-cost and high-performance design of the MFC compartments. According to this strategy, a novel monolithic membrane electrode assembly (MEA) was fabricated and evaluated as an air–cathode in a single-chamber MFC (SCMFC). The MEA was made of bacterial cellulose (BC), conductive multi-walled carbon nanotubes (CNT), and nano-zycosil (NZ). BC, as a nano-celluloses with oxygen barrier property, can maintain anaerobic conditions for the anode compartment. Binder-less CNT coating on BC avoids costly binders such as poly-tetra fluoro ethylene (PTFE) and Nafion and decreases the MEA charge transfer resistance. NZ, as a very cheap modifier, not only prevents the anolyte leakage but also provides more MEA’s active sites for the oxygen reduction reaction (ORR). The electrochemical performance of the MEA was compared to a PTFE- based gas diffusion electrode (GDE) in the SCMFC. The MEA cell provided a pulse power density of 1790 mW/m2, roughly twice as high as the pulse power density of GDE (920 mW/m2). SCMFC’s internal resistance decreased from 1.84 KΩ (with GDE) to 0.8 KΩ (with MEA). Also, the cell’s columbic efficiency increased from 4.2% (with GDE) to11.7% (with MEA). Additionally, the capacitance of the MEA (65 mF) was much higher than the value for GDE (0.73 mF). Thus, the MEA compared to the GDE showed higher performance in the SCMFC for electricity generation and wastewater treatment at a lower cost.

Wastewater containing ammonia nitrogen compounds is considered as a harmful material to environment due to eutrophication and toxicity effects; hence, finding practical methods for treating this type of wastewater seems necessary. In this study, performance of two sequencing batch reactors have been assessed for simultaneous nitrification and denitrification in treating synthesized wastewater containing ammonium nitrogen, using leachate obtained from cow dung as the biomass. The leachate obtained from cow dung as the source of bio‐sludge added to the reactors. Experiments were designed according to central composition design and response surface methodology with four operating variables including pH (6, 7.5, 9), cycle time (CT) (4, 12, 20 h), ratio (5, 10, 15) and carbon source (Sodium acetate: , Glucose: ). According to statistical analysis, experimental responses were in acceptable agreement with model predictions. CT was the most important operating variable in chemical oxygen demand (COD) and removal. The maximum percentage of ammonium nitrogen removal was attained at pH 7.5 and CT 21.5 h. The optimum conditions were composed of pH 7.67, CT 19.15 h, 10.95 and sodium acetate as carbon source, while COD, and total nitrogen removals were 94.96%, 94.93% and 93.60%, respectively. © 2017 American Institute of Chemical Engineers Environ Prog, 37: 1638–1646, 2018

The effective utilization of the cryogenic exergy associated with liquefied natural gas (LNG) vaporization is important. In this paper, a novel combined power cycle is proposed which utilizes LNG in different ways to enhance the power generation of a power plant. In addition to the direct expansion in the appropriate expander, LNG is used as a low-temperature heat sink for a middle-pressure gas cycle which uses nitrogen as working fluid. Also, LNG is used to cool the inlet air of an open Brayton gas turbine cycle. These measures are accomplished to improve the exergy recovery of LNG. In order to analyze the performance of the system, the influence of several key parameters such as pressure ratio of LNG turbine, ratio of the mass flow rate of LNG to the mass flow rate of air, pressure ratio of different compressors, LNG pressure and inlet pressure of nitrogen compressor, on the thermal efficiency and exergy efficiency of the offered cycle is investigated. Finally, the proposed combined cycle is optimized on the basis of first and second laws of thermodynamics.