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Sargassum spp is an invasive macroalgae and an alternative feedstock for bioethanol production. Sargassum spp biomass was subjected to high-pressure technology for biomass fractionation under different operating conditions of temperature and residence time to obtain glucan enriched pretreated solids (32.22 g/100 g of raw material). Enzyme hydrolysis process at high pretreated solid loading (13%, w/v) and enzyme loading of 10 FPU/g of glucan was performed, obtaining 43.01 g/L of glucose corresponding to a conversion yield of 92.12%. Finally, a pre-simultaneous saccharification and fermentation strategy (PSSF) was performed to produce bioethanol. This operational strategy produced 45.66 g/L of glucose in the pre-saccharification stage, and 18.14 g/L of bioethanol was produced with a glucose to bioethanol conversion yield of 76.23%. The development of this process highlights the feasibility of bioethanol production from macroalgal biomass in the biorefinery concept.

This study aims to investigate the water spray uniformity and collection ratio of sprinkler in an evaporative condenser of a water chiller. Experiments of water droplet distribution are conducted with 50 water collectors during the tests. Three different combinations of nozzle opening length and width were tested with the flow rates varied at 135 LPM and 176.4 LPM. Measured results show that the cross-sectional area of nozzle opening and flow rate significantly affect the water spray uniformity. In this work, at high flow rate, the Nozzle 2 with opening of 4 cm in length and 1 cm in width has better water spray uniformity compared to the nozzle 1 with opening of 4 cm in length and 0.7 cm in width. On the other hand, at low flow rate, the Nozzle 1 provides better impacting effect with the nozzle spacing of 17 cm, yet the Nozzle 2 performed better with the nozzle spacing of 15 cm. The latter case, with the smaller nozzle spacing and bigger nozzle opening size, led to a shorter impact distance of the spraying flow from two facing nozzles. Subsequently the spattering of water droplets was more pronounced, and distributed more uniformly. Keywords: Water spray uniformity, Collection ratio of sprinkler, Evaporative condenser, Nozzle opening

This paper presents several advances for the PMU placement problem (PPP). Existing approaches have difficulty scaling to full-scale systems, and are not guaranteed to be resilient to multiple component failures. This paper expands PPP to a more general k-resilient PPP, where any k PMUs and/or lines can fail without jeopardizing the problem's full supervision criterion. Our PPP model — a novel formulation based on maximum-flow network design — is unique in that it is amenable to efficient decomposition, which significantly improves tractability and scalability. We present two cutting plane algorithms to support this decomposition — the first such algorithms for the PPP to our knowledge. The improvements in computational efficiency afforded by the network decomposition suggest that our approach can solve the PPP for large-scale systems.

Etude des resultats obtenus en matiere de reduction des emissions de gaz a effet de serre, suite a la mise en oeuvre des politiques definies, au cours des conferences internationales de la decennie 90. Etude des perspectives a moyen et long terme, en fonction des differents scenarios envisages lors de congres internationaux

Abstract Most work in dynamic heat exchanger modeling for control design can be classified as either a finite volume or a moving boundary formulation. These approaches represent fundamentally different discretization approaches and are often characterized as contrasting accuracy with simulation speed. This work challenges that characterization by validating finite volume and moving boundary heat exchanger models with experimental data from a vapor compression system in order to demonstrate that these approaches are capable of achieving similar levels of accuracy. However, there are differences. The moving boundary model is found to have faster simulation speed, while the finite volume model is more flexible for adaptation to heat exchangers of different physical configuration. The formulation of each modeling approach used in this work is described in detail and techniques to increase simulation speed and avoid numerical issues in implementation are discussed.

Abstract Hydrothermal conversion coupled with high pressure water and steam of three de-oiled non-edible seed cakes of Jatropha curcasa, Pongammia pinnata and Tung to biocrude is explored in this work. The cakes were characterized for proximate, ultimate and ligno-cellulosic compositions using ASTM and TAPPI standard methods. All studies were conducted at high temperature and pressure in a semi-batch autoclave. Highest conversion with maximum biocrude yield (∼35.3%) was obtained with P. pinnata cake. Silica adsorption chromatography result showed higher oxygenated aromatics subfraction in both Tung biocrude and Jatropha biocrude. GC/MS qualitative analysis confirmed the presence of heavy, oxygenated/ nitrogenous and poly aromatic hydrocarbons with carbon number ranging from C 5 -C 47 in the biocrude. The viscosity, pH, density, total acidic number (TAN) and water content of biocrudes were evaluated using various standard methods. 34.2 to 45.8% increases in the calorific value is observed for biomass to biocrude. Biochar obtained were characterized using proximate and ultimate analysis and SEM, TGA techniques. Higher calorific values (24.7–26.3 MJ/kg) of all the biochar make them suitable for their potential application as briquettes in the furnace for power generation.

In recent years, Smart Grid was introduced to achieve an environmentally-friendly, adequate, secure and fossil fuel-independent power system. The large scale smart grid studies require accurate state estimation to obtain an acceptable adequacy level. There exist some challenges regarding anomalous power flow studies which motivate grid operators to utilize robust and accurate estimation methods. Therefore, power system state estimators play a pivotal role in real-time grid management. In this paper, a sequential linear minimum mean square error (LMMSE) estimator is utilized to solve the DC power flow problem. First, we introduce the classic linear estimator model which assumes that to-be-estimated parameter values are unknown but deterministic. The LMMSE estimator will be discussed which treats the to-be-estimated parameter as a random variable with a known prior probability density function (pdf). We evaluate the accuracy of the LMMSE estimator by comparing it with maximum likelihood estimator (MLE). Finally, the effect of covariance matrix topology will be studied by defining three scenarios with different noise covariance matrices.

Recently, there has been an increasing interest in the development of an approach to characterize the as-built heat loss coefficient (HLC) of buildings based on a combination of on-board monitoring (OBM) and data-driven modeling. OBM is hereby defined as the monitoring of the energy consumption and interior climate of in-use buildings via non-intrusive sensors. The main challenge faced by researchers is the identification of the required input data and the appropriate data analysis techniques to assess the HLC of specific building types, with a certain degree of accuracy and/or within a budget constraint. A wide range of characterization techniques can be imagined, going from simplified steady-state models applied to smart energy meter data, to advanced dynamic analysis models identified on full OBM data sets that are further enriched with geometric info, survey results, or on-site inspections. This paper evaluates the extent to which these techniques result in different HLC estimates. To this end, it performs a sensitivity analysis of the characterization outcome for a case study dwelling. Thirty-five unique input data packages are defined using a tree structure. Subsequently, four different data analysis methods are applied on these sets: the steady-state average, Linear Regression and Energy Signature method, and the dynamic AutoRegressive with eXogenous input model (ARX). In addition to the sensitivity analysis, the paper compares the HLC values determined via OBM characterization to the theoretically calculated value, and explores the factors contributing to the observed discrepancies. The results demonstrate that deviations up to 26.9% can occur on the characterized as-built HLC, depending on the amount of monitoring data and prior information used to establish the interior temperature of the dwelling. The approach used to represent the internal and solar heat gains also proves to have a significant influence on the HLC estimate. The impact of the selected input data is higher than that of the applied data analysis method.