A practical eco-environmental distribution network planning model including fuel cells and non-renewable distributed energy resources

This paper presents a long-term dynamic multi-objective planning model for distribution network expansion along with distributed energy options. The proposed model optimizes two objectives, namely costs and emissions and determines the optimal schemes of sizing, placement and specially the dynamics (i.e., timing) of investments on distributed generation units and network reinforcements over the planning period. An efficient two-stage heuristic method is proposed to solve the formulated planning problem. The effectiveness of the proposed model is demonstrated by applying it to a distribution network and comparing the simulation results with other methods and models.     

Impact of carbon tax on internal combustion engine size selection in a medium scale CHP system

Combined heat and power (CHP) systems due to their high efficiency compared to the conventional power generation systems have received considerable attention as they have less harmful impact on the environment. Recently, the serious concern with reducing the greenhouse gas emissions has focussed the attention on the possibility of a carbon tax in some countries. Here, we address the impact of such tax on the sizing and economics of a CHP system.     

A Wavelet-ANFIS Hybrid Model for Groundwater Level Forecasting for Different Prediction Periods

Artificial neural network (ANN) and Adaptive Neuro-Fuzzy Inference System (ANFIS) have an extensive range of applications in water resources management. Wavelet transformation as a preprocessing approach can improve the ability of a forecasting model by capturing useful information on various resolution levels. The objective of this research is to compare several data-driven models for forecasting groundwater level for different prediction periods. In this study, a number of model structures for Artificial Neural Network (ANN), Adaptive Neuro-Fuzzy Inference System (ANFIS), Wavelet-ANN and Wavelet-ANFIS models have been compared to evaluate their performances to forecast groundwater level with 1, 2, 3 and 4 months ahead under two case studies in two sub-basins. It was demonstrated that wavelet transform can improve accuracy of groundwater level forecasting. It has been also shown that the forecasts made by Wavelet-ANFIS models are more accurate than those by ANN, ANFIS and Wavelet-ANN models. This study confirms that the optimum number of neurons in the hidden layer cannot be always determined by using a specific formula but trial-and-error method. The decomposition level in wavelet transform should be determined according to the periodicity and seasonality of data series. The prediction of these models is more accurate for 1 and 2 months ahead (for example RMSE?=?0.12, E?=?0.93 and R ²?=?0.99 for wavelet-ANFIS model for 1 month ahead) than for 3 and 4 months ahead (for example RMSE?=?2.07, E?=?0.63 and R ²?=?0.91 for wavelet-ANFIS model for 4 months ahead).     

Evaluation of Lepidium sativum seed and guar gum to improve dough rheology and quality parameters in composite rice–wheat bread

The effects of hydrocolloids in rice–wheat flour were studied. Hydrocolloids at 0%, 0.3%, 0.6% and 1% w/w (flour basis) and guar (G), Lepidium sativum seed (L) and guar-L. sativum seed (GL) gum were tested as additives to the rice/flour in various combinations. The quality parameters for the experiment were assessed with farinography, extensography, amylography and texture profile analysis. The evaluation of dough rheology showed that water absorption, dough development time, dough stability and viscosity all increased with the addition of hydrocolloids alone or in a combination. It was demonstrated that G₁L₁ promoted the highest effect. The mixing tolerance index and gelatinization temperature decreased with an increased hydrocolloid concentration. Extensibility value for the dough that incorporated guar and L. sativum seed gum increased with increasing hydrocolloid concentration from 0.3% to 0.6% and then decreased at 1%. The water activity of all bread didn't have significant differences with increasing hydrocolloids concentration but this parameter 24 decreased during storage. Firmness decreased with increasing hydrocolloid concentration and increased with increasing storage time. The sensory evaluation by a consumer panel gave the higher score for overall acceptability to G_0.3L_0.3 and G_0.3L_0.6 samples. The results also showed that G₁L₁, G₁L_0.6 and G_0.6L₁ samples had high specific volume and porosity.     

Methodology for Estimation of Local Convective Heat Transfer Coefficient for Vapor Condensation

This paper aims to present an effective two-dimensional inverse heat conduction technique and an experimental design for accurately estimating the local convective heat transfer coefficient of vapor condensation over a conical surface, given temperature measurements at some interior locations. The functional form for the heat transfer coefficient is not known a priori. The method uses a sequential procedure together with Beck's function specification approach. Solution accuracy and the effects of experimental errors are examined using simulated temperature data. It is concluded that a good estimation of space-variable heat transfer coefficient can be made from the knowledge of transient temperature recordings using the proposed inverse heat conduction problem method. The method is also used in a series of numerical experiments to provide the optimum experimental design for condensation heat transfer investigation.     

Inverse Identification of Thermal Properties of Charring Ablators

The modified Levenberg-Marquardt method is used for simultaneous estimation of decomposition kinetic coefficients and temperature-dependent thermophysical properties of charring ablators with a moving boundary over a wide temperature range. No prior information is used for the functional forms of the unknown thermal conductivity and specific heat. The procedure used differs from the traditional one in that it does not require prescribed time-dependent surface heat flux, recession rate, and pyrolysis gas mass flow rate. These time-dependent quantities may recover during an iterative procedure. The measured temperatures are simulated numerically by the Charring material ablation code, which accounts for unsteady ablation. The method can determine unknown parameters in an efficient manner with reasonable accuracy, without exact advance knowledge about the net surface heat flux, surface recession, and gas flux through the material.     

On the numerical solution of generalized convection heat transfer problems via the method of proper closure equations – part II: Application to test problems

ABSTRACT

In part I of this paper, a new physical-based computational approach for the solution of convection heat transfer problems on co-located non-orthogonal grids in the context of an element-based finite volume method was discussed. The test problems are presented here, in part II of the paper. These problems include five steady two-dimensional convection heat transfer problems. In all test cases, the convergence history, the required under-relaxations for the iterative solution of the linearized equations, and the order of accuracy of the method are discussed and the streamlines as well as isotherms are presented. The computational results show that the proposed method is second order accurate and might occasionally need mild under-relaxation in relatively complex problems. Excellent match between the computational results and the corresponding reliable published results is observed.     

A comparative study for synthesis methods of nano-structured (9Ni–2Mg–Y) alloy catalysts and effect of the produced alloy on hydrogen desorption properties of MgH2

9Ni–2Mg–Y alloy powders were prepared by arc melting, induction melting, mechanical alloying, solid state reaction and subsequent ball milling processes. The results showed that melting processes are not suitable for preparation of 9Ni–2Mg–Y alloy due to high losses of Mg and Y. Therefore, 9Ni–2Mg–Y alloy powder was prepared by three methods including: 1) mechanical alloying, 2) mechanical alloying + solid state reaction + ball milling, and 3) mixing + solid state reaction + ball milling. The prepared 9Ni–2Mg–Y alloy powders were compared for their catalytic effects on hydrogen desorption of MgH₂. It is found that 9Ni–2Mg–Y alloy powder prepared by mechanical alloying + solid state reaction + ball milling method has a smaller particle size (1–5 μm) and higher surface area (1.7 m² g⁻¹) than that of other methods. H₂ desorption tests revealed that addition of 9Ni–2Mg–Y alloy prepared by mechanical alloying + solid state reaction + ball milling to MgH₂ decreases the hydrogen desorption temperature of MgH₂ from 425 to 210 °C and improves the hydrogen desorption capacity from 0 to 3.5 wt.% at 350 °C during 8 min.     

Experimental and Numerical Investigation on Free Convection From a Horizontal Cylinder Located Above an Adiabatic Surface

Steady two-dimensional free convection heat transfer from an isothermal horizontal cylinder located above an adiabatic horizontal surface is studied experimentally and numerically. Experiments are carried out using a Mach–Zehnder interferometer for the ratios of cylinder spacing from the adiabatic surface to its diameter L/D = 0, 0.1, 0.2, 0.3, 0.5, 0.7, and 0.9 and the Rayleigh number range of 500 to 15,000. Also, a specifically developed computer code based on the finite-volume method, the SIMPLE algorithm, and nonorthogonal discretization grid system is used for the solution of the mass-, momentum-, and energy-governing equations for the Rayleigh numbers ranging from 100 to 100,000 and L/D ranging from 0.1 to 1.7. The effects of the Rayleigh number and spacing from the adiabatic surface on both local and average Nusselt numbers around the cylinder are investigated. A correlation based on the numerical data for the average Nusselt number of the cylinder as a function of Rayleigh number and L/D is presented in the aforementioned ranges.     

A stochastic security approach to energy and spinning reserve scheduling considering demand response program

In this paper a new algorithm for allocating energy and determining the optimum amount of network active power reserve capacity and the share of generating units and demand side contribution in providing reserve capacity requirements for day-ahead market is presented. In the proposed method, the optimum amount of reserve requirement is determined based on network security set by operator. In this regard, Expected Load Not Supplied (ELNS) is used to evaluate system security in each hour. The proposed method has been implemented over the IEEE 24-bus test system and the results are compared with a deterministic security approach, which considers certain and fixed amount of reserve capacity in each hour. This comparison is done from economic and technical points of view. The promising results show the effectiveness of the proposed model which is formulated as mixed integer linear programming (MILP) and solved by GAMS software.