Technical note: Evaluation of a novel enzymatic method to predict in situ undigested neutral detergent fiber of forages and nonforage fibrous feeds

The purpose of this study was to optimize the conditions of a previously proposed enzymatic method used to estimate in situ undigested neutral detergent fiber (uNDF). We used a multi-step enzymatic approach, in which samples were first solubilized in NaOH solutions as a preincubation (PreInc) phase. After rinsing, samples were incubated (24 h at 39°C) in a buffered solution (pH 6) containing hemicellulase, cellulase, and Viscozyme L enzymes (Sigma-Aldrich s.r.l., Milan, Italy), followed by incubation (24 h at 39°C) in a buffered solution (pH 5) containing xylanase. Two sets of experiments were performed: a calibration trial (that tested different PreInc conditions on 9 selected forages) and a validation trial (that verified the results by testing multiple samples of 6 different forage types and a group of fibrous by-products). In the calibration trial, samples (300 mg in Ankom F57 filter bags; Ankom Technology Corp., Fairport, NY) were preincubated at 39°C in a 0.1 M NaOH solution for 90, 180, or 240 min, or in 0.2, 0.5, 1.0, or 2.0 M NaOH solution for 90 min. The results indicated that the best PreInc method, in terms of intra-laboratory repeatability and estimation of reference in situ values, was 90 min in a 0.2 M NaOH solution. Thus, we used this PreInc condition to determine enzymatic uNDF of 257 samples in the validation trial. Although the selected method generally had good accuracy in predicting in situ uNDF, inconsistencies were noted for certain forage types. Overall, when enzymatic uNDF was used to predict the in situ uNDF of all samples, the regression was satisfactory (intercept = 7.098, slope = 0.920, R² = 0.73). The regression models developed for alfalfa hays, corn silages, and small grain silages had also acceptable regression performances and mean square error of prediction (MSEP) values, and the main sources of MSEP variation were error due to incomplete (co)variation and random error. Even when R² values were >0.70, the MSEP value of the regression model for grass hays was 149.55, and that for nonforage fibrous feeds was 155.16. Although enzymatic uNDF partially overestimated the in situ uNDF, particularly in grass silages, the proposed procedure seems to be promising for accurately predicting in situ uNDF, because it generally had good repeatability and provided satisfactory estimates of in situ uNDF.     

Performance investigation of the heat pump and power generation integration system

A novel heat pump and power generation integration system (HPPGIS) using solar energy as a low temperature heat source was presented in this study. This system could be operated in both an organic Rankine cycle power generation (ORC‐PG) mode and a reverse Carnot cycle heat pump (RCC‐HP) mode. Compared with a single heat pump and power generation system, this system improved the utilization efficiency of solar energy, thus showing potential for the generation of economic benefits. Contrastive analyses of different working fluids using ORC‐PG and RCC‐HP systems were conducted first, leading to the selection of R142b and R245fa as optimal fluids. Then, an experimental investigation of the system was carried out under different conditions. A heat pump and ORC system model was proposed and validated by comparing experimental and simulated values. The experimental results indicated that the HPPGIS had good feasibility and stability in both modes. In the ORC‐PG mode, HPPGIS had a power output of 1.29 kW and a thermal efficiency of 4.71% when the water inlet temperature of the evaporator was 90.03°C. In the RCC‐HP mode, HPPGIS had a COP of 3.16 and a heat capacity of 33.24 kW when the water outlet temperature of the condenser was 106.23°C.     

Design and analysis of an aging‐aware energy management system for islanded grids using mixed‐integer quadratic programming

The rapid increase of renewable energy sources made coordinated control of the distributed and intermittent generation units a more demanded task. Matching demand and supply is particularly challenging in islanded microgrids. In this study, we have demonstrated a mixed‐integer quadratic programming (MIQP) method to achieve efficient use of sources within an islanded microgrid. A unique objective function involving fuel consumption of diesel generator, degradation in a lithium‐ion battery energy storage system, carbon emissions, load shifting, and curtailment of the renewable sources is constructed, and an optimal operating point is pursued using the MIQP approach. A systematic and extensive methodology for building the objective function is given in a sequential and explicit manner with an emphasis on a novel model‐based battery aging formulation. Performance of the designed system and a sensitivity analysis of resulting battery dispatch, diesel generator usage, and storage aging against a range of optimization parameters are presented by considering real‐world specifications of the Semakau Island, an island in the vicinity of Singapore.     

Nitrogen‐doped self‐shrinking porous 3D graphene capacitor deionization electrode

Traditional three‐dimensional (3D) graphene has a large pore structure, which makes the graphene structure not well interact with the anion and cation during the desalination process, thereby restricting the capacitive deionization (CDI) ability of the 3D graphene. In this work, we prepared a nitrogen‐doped self‐shrinking porous 3D graphene electrode by adding a pyrrole monomer to a graphene oxide solution, which was then applied to a CDI electrode. The results show that the electrochemical performance of the as‐prepared nitrogen‐doped self‐shrinking porous 3D graphene (NSPG) is significantly improved. Compared with traditional 3D graphene, NSPG has a denser pore structure with a larger specific surface area, thus exhibiting a good CDI performance: The NSPG electrode has an electroadsorption capacity of 13.16 mg/g.     

Evaluation of a cloud cover based model for estimation of hourly global solar radiation in Western Canada

Cloud cover based solar radiation models are relatively simple and convenient as the models require the input of cloud cover data which are mostly available from the meteorological stations. In this study, the performance of a cloud cover based solar radiation model (Kasten–Czeplak model) with original or locally fitted coefficients was evaluated for estimating the hourly global solar radiation for four different locations in Western Canada. The average value of R², mean bias error, and root mean square error are 0.69, ?61.6, and 157.9?W?m^?2, respectively, for the model with original coefficients, whereas 0.82, 4.4, 107.1?W?m^?2 with locally fitted coefficients. Results show that the Kasten–Czeplak model with locally fitted coefficients satisfactorily estimated the hourly solar radiation of four different locations in Western Canada. Also, the results indicate that the model with original coefficients has very limited accuracy under intermediate cloud cover conditions.