Energy demand forecasting using convolutional neural network and modified war strategy optimization algorithm.

Predicting the electricity demand is a key responsibility for the energy industry and governments in order to provide an effective and dependable energy supply. Traditional projection techniques frequently rely on mathematical models, which are limited in their ability to recognize complex patterns and correlations in data. Machine learning has emerged as a viable tool for estimating electricity in the last decade. In this study, the Modified War Strategy Optimization-Based Convolutional Neural Network (MWSO-CNN) has been provided for electricity demand prediction. To increase the precision of electricity demand prediction, the MWSO-CNN approach integrates the benefits of the modified war strategy optimization technique and the convolutional neural network. To improve efficiency, the modified war strategy optimization technique is employed to adjust the hyperparameters of the CNN algorithm. The suggested MWSO-CNN approach is tested on a real-world electricity demand dataset, and the findings show that it outperforms many state-of-the-art machine learning techniques for predicting electricity demand. In general, the suggested MWSO-CNN approach could offer a successful and cost-effective strategy for predicting energy consumption, which will benefit both the energy business and society as a whole.

Significant performance enhancement of a UASB reactor by using acyl homoserine lactones to facilitate the long filaments of Methanosaeta harundinacea 6Ac.

Methanosaeta strains are frequently involved in the granule formation during methanogenic wastewater treatment. To investigate the impact of Methanosaeta on granulation and performance of upflow anaerobic sludge blanket (UASB) reactors, three 1-L working volume reactors noted as R1, R2, and R3 were operated fed with a synthetic wastewater containing sodium acetate and glucose. R1 was inoculated with 1-L activated sludge, while R2 and R3 were inoculated with 200-mL concentrated pre-grown Methanosaeta harundinacea 6Ac culture and 800 mL of activated sludge. Additionally, R3 was daily dosed with 0.5 mL/L of acetyl ether extract of 6Ac spent culture containing its quorum sensing signal carboxyl acyl homoserine lactone (AHL). Compared to R1, R2 and R3 had a higher and more constant chemical oxygen demand (COD) removal efficiency and alkaline pH (8.2) during the granulation phase, particularly, R3 maintained approximately 90 % COD removal. Moreover, R3 formed the best granules, and microscopic images showed fluorescent Methanosaeta-like filaments dominating in the R3 granules, but rod cells dominating in the R2 granules. Analysis of 16S rRNA gene libraries showed increased diversity of methanogen species like Methanosarcina and Methanospirillum in R2 and R3, and increased bacteria diversity in R3 that included the syntrophic propionate degrader Syntrophobacter. Quantitative PCR determined that 6Ac made up more than 22 % of the total prokaryotes in R3, but only 3.6 % in R2. The carboxyl AHL was detected in R3. This work indicates that AHL-facilitated filaments of Methanosaeta contribute to the granulation and performance of UASB reactors, likely through immobilizing other functional microorganisms.

High-rate hydrogenotrophic methanogenesis for biogas upgrading: the role of anaerobic granules.

Hydrogenotrophic methanogenesis has been proved to be a feasible biological method for biogas upgrading. To improve its performance, the feasibility of typical anaerobic granules as the inoculum was investigated in both batch and continuous experiments. The results from batch experiments showed that glucose-acclimated granules seemed to perform better than granules acclimated to acidified products (AP, i.e. acetate, propionate and ethanol) in in situ biogas upgrading systems and a slightly higher H2 consumption rate (1.5 mmol H2 g VSS(-1) h(-1)) was obtained for glucose-acclimated granules. For AP-acclimated granules, the inhibition on anaerobic digestion and pH increase (up to 9.55±0.16) took place, and the upgrading performance was adversely affected. In contrast, better performance for AP-acclimated granules was observed in ex situ systems, possibly due to their higher hydrogenotrophic methanogenic activities (HMA). Moreover, when gas-liquid mass transfer limitations were alleviated, the upgrading performance was significantly improved (three-fold) for both glucose-acclimated and AP-acclimated granules. The HMA of anaerobic granules could be further enhanced to improve biogas upgrading performance via continuous cultivation with H2/CO2 as the sole substrate. During the three months' cultivation, secondary granulation and microbial population shift were observed, but anaerobic granules still remained intact and their HMA increased from 0.2 to 0.6 g COD g VSS(-1) d(-1). It indicated that the formation of hydrogenotrophic methanogenic granules, a new type of anaerobic granules specialized for high-rate hydrogenotrophic methanogenesis and biogas upgrading, might be possible. Conclusively, anaerobic granules showed great potential for biogas upgrading.