Effect of some operating variables on citrate recovery from model solutions by electrodialysis
The effect of pH and temperature (straight theta) on the overall performance indicators (i.e., solute recovery, rho, and Faraday, eta, efficiencies; specific energy consumption, epsilon, solute, JS, and water, JW, fluxes) of batch electrodialytic recovery of citric acid from model solutions was assessed at different values of feed solute concentration (cSf) and electric current density (j). Regardless of the initial feed concentration used, rho and JS were found to be independent of straight theta; eta and JW exhibited a positive trend with respect to straight theta, while epsilon a negative one. At the maximum temperature tested (33 degrees C), as the pH of the feed solution was varied from 3 to 7, rho increased from 0.90 +/- 0.08 to 0.97 +/- 0.02, eta grew from 0.09 +/- 0.02 to 0.50 +/- 0.01, JS practically doubled, epsilon reduced about 8 times, but JW increased from 3 to 4 times. So, the optimal conditions for this technique are to be determined by balancing the savings in the investment and maintenance costs against the energy costs. Copyright John Wiley & Sons, Inc.
Modelling of Soy Sauce Desalting by Electrodialysis
In this work, the main features of electrodialytic (ED) desalting of microfiltered samples of a traditional soy sauce under constant electric current in the range of 1.25 to 6.5 A were quite well reconstructed using a mathematical model based on the Nernst–Planck equation. Amino nitrogen migration was characterised by a small effective transport number (tAN = 0.070 ± 0.01), resulting in an average loss in amino nitrogen of about 30% whatever the electric current tested. The sodium chloride transport number (tB = 0.969 ± 0.05) and diffusion rate (LB ≈ 0), as well as the effective membrane surface area, essentially coincided with those previously established when dealing with concentrated model brines. On the contrary, there was a significant diversity in the water transport number (tW = 8.3 ± 0.1) and diffusion rate [LW = (6.9 ± 0.2) × 10−5 mol m−2 s−1 bar−1], as well as in the anion- and cation-exchange membrane resistances (Ra = Rc ≈ 0.04 Ω). The experimental procedure and mathematical model described in this work may be recommended not only to optimise the ED desalination of soy sauce but also to generate a first-cut design for ED desalting of other natural seasonings.
A Short-Term and High-Resolution Distribution System Load Forecasting Approach Using Support Vector Regression With Hybrid Parameters Optimization
This paper proposes an approach for distribution system load forecasting, which aims to provide highly accurate short-term load forecasting with high resolution utilizing a support vector regression (SVR) based forecaster and a two-step hybrid parameters optimization method. Specifically, because the load profiles in distribution systems contain abrupt deviations, a data normalization is designed as the pretreatment for the collected historical load data. Then an SVR model is trained by the load data to forecast the future load. For better performance of SVR, a two-step hybrid optimization algorithm is proposed to determine the best parameters. In the first step of the hybrid optimization algorithm, a designed grid traverse algorithm (GTA) is used to narrow the parameters searching area from a global to local space. In the second step, based on the result of the GTA, particle swarm optimization is used to determine the best parameters in the local parameter space. After the best parameters are determined, the SVR model is used to forecast the short-term load deviation in the distribution system. The performance of the proposed approach is compared to some classic methods in later sections of this paper.