31 research outputs found
International Journal of Smart Grid and Clean Energy Generator output and static capacitor control considering voltage stability for large penetration of photovoltaic power
Abstract In Japan, the introduction of large capacity of clean energy such as PV (photovoltaic power generation) is planned to reduce environmental burdens. The Japanese government has set the target of 53 GW of PV by 2030. However, large penetration of PV will cause several problems in power systems. One of these problems is that voltage values increase with the amount of PV penetration. Thus, we focus our attention on the upper voltage limit for a large penetration of PV in terms of voltage stability. In this paper, we consider a smart generator output and static capacitor control for the large penetration of PV. For the generator output control we propose to use the optimal power flow in terms of minimizing bus voltage deviations from the prescribed values. Simulations are run using the IEEJ WEST 10-machine O/V system model to confirm the validity of the proposed method
International Journal of Smart Grid and Clean Energy Generator output and static capacitor control considering voltage stability for large penetration of photovoltaic power
Abstract Keywords: Voltage stability, VMPI, generator output control, static capacitor control, photovoltaic powe
Machine learning-assisted medium optimization revealed the discriminated strategies for improved production of the foreign and native metabolites
The composition of medium components is crucial for achieving the best performance of synthetic construction in genetically engineered cells. Which and how medium components determine the performance, e.g., productivity, remain poorly investigated. To address the questions, a comparative survey with two genetically engineered Escherichia coli strains was performed. As a case study, the strains carried the synthetic pathways for producing the aromatic compounds of 4-aminophenylalanine (4APhe) or tyrosine (Tyr), common in the upstream but differentiated in the downstream metabolism. Bacterial growth and compound production were examined in hundreds of medium combinations that comprised 48 pure chemicals. The resultant data sets linking the medium composition to bacterial growth and production were subjected to machine learning for improved production. Intriguingly, the primary medium components determining the production of 4PheA and Tyr were differentiated, which were the initial resource (glucose) of the synthetic pathway and the inducer (IPTG) of the synthetic construction, respectively. Fine-tuning of the primary component significantly increased the yields of 4APhe and Tyr, indicating that a single component could be crucial for the performance of synthetic construction. Transcriptome analysis observed the local and global changes in gene expression for improved production of 4APhe and Tyr, respectively, revealing divergent metabolic strategies for producing the foreign and native metabolites. The study demonstrated that ML-assisted medium optimization could provide a novel point of view on how to make the synthetic construction meet the designed working principle and achieve the expected biological function