Energy Conversion and Management

Matlab code

the experimental data used in the 'Parameter estimation of photovoltaic modules using a heuristic iterative algorithm'.

Data for all of the figures present in the article and the Aspen Plus simulation.

This zip file contains ORC data and BPNN and SVR models.

The data provide a Fuzzy-TOPSIS algorithm-based multi-criteria decision making platform based on an n-dimensional space of optimal integrated systems developed by applying multi-objective genetic algorithm on combined mathematical models.

Acetone-butanol-ethanol (ABE) fermentation process is a promising bioenergy option amid rising concerns over the environmental impact of fossil fuel usage. However, the commercialization of the ABE process has been marred by challenges of low product yield and titer, thereby non-competitive process economics. Here, we coupled low-cost reducing agents with a controlled feeding strategy to improve both product titer and yield. Reducing agents promote cofactor dependent butanol production while fed-batch operation enhances glucose consumption, final ABE titer, and partly mitigates product toxicity. We investigated the effects of ascorbic acid, L-cysteine, and dithiothreitol (DTT) on fed-batch ABE production using Clostridium acetobutylicum. Moreover, to study the metabolic modifications triggered by these reducing agents, we performed NADH, ATP, extracellular amino acid secretion, and NADH- dependent butanol dehydrogenase (BDH) assays. L-cysteine and DTT improved ABE solvent titer by 2-fold, producing 24.33 and 22.98 g/L ABE with solvent yields of 0.38 and 0.37 g/g, respectively. NADH, BDH, and ATP levels increased significantly which also reflected in elevated ABE titer and yield. Furthermore, histidine secretion emerged as an important factor in Clostridial acid stress in this study. The results demonstrate that reducing agents and the fed-batch combination enables efficient utilization of glucose and remarkably enhances ABE production.

Data set for training the RBFNN (Data set.xlsx). Optimized parameters for the OWSCs under different wave periods, wave heights, and water depths (Optimized parameters.xlsx).

This dataset provides reader to get real-time turbulence intensity data corresponding to the wind speed time series on multiple time resolutions. The dataset is comprised of two parts: original wind speed series, and multi-resolution wind speed and turbulence intensity. The original wind speed dataset gives the wind observation on different altitudes on the wind farm, such as speed, fluctuation, direction, maximum, minimum, as well as air conditions, with a sampling rate of 10 minutes from Jan. 1,2013 to Dec. 31, 2013. Multi-resolution wind speed and turbulence intensity dataset provides the average wind speed and turbulence intensity on different time scales (1 hour, 2 hours, 4 hours, 6 hours, 12 hours and 24 hours), which is calculated from the highest altitude where the wind speed is obtained.

These metadata are supplementary to the manuscript with title: “Monopile-mounted WEC for a Hybrid Wind-Wave Energy Converter”

These data are obtained from building automation system, field measurements, and simulation.