Security-constrained line loss minimization in distribution systems with high penetration of renewable energy using UPFC

Abstract Focused on the challenges raised by the large-scale integration of renewable energy resources and the urgent goal of energy saving, a novel control scheme for the unified power flow controller (UPFC) series converter is proposed to achieve line loss reduction and security enhancement in distribution systems with a high penetration of renewable energy. Firstly, the line loss minimum conditions of a general distribution system with loop configurations are deduced. Secondly, security constraints including the permissible voltage range, the line loading limits and the UPFC ratings are considered. System security enhancement with the least increase in line loss is tackled by solving a much reduced optimal power flow (OPF) problem. The computational task of the OPF problem is reduced by deducing the security-constrained line loss minimum conditions and removing the equality constraints. Thirdly, a hybrid control scheme is proposed. Line loss minimization is achieved through a dynamic controller, while an OPF calculator is integrated to generate corrective action for the dynamic controller when the security constraints are violated. The validity of the proposed control strategies is verified in a modified IEEE 33 bus test system

Preventive Security-Constrained Optimal Power Flow Considering UPFC Control Modes

The successful application of the unified power flow controller (UPFC) provides a new control method for the secure and economic operation of power system. In order to make the full use of UPFC and improve the economic efficiency and static security of a power system, a preventive security-constrained power flow optimization method considering UPFC control modes is proposed in this paper. Firstly, an iterative method considering UPFC control modes is deduced for power flow calculation. Taking into account the influence of different UPFC control modes on the distribution of power flow after N-1 contingency, the optimization model is then constructed by setting a minimal system operation cost and a maximum static security margin as the objective. Based on this model, the particle swarm optimization (PSO) algorithm is utilized to optimize power system operating parameters and UPFC control modes simultaneously. Finally, a standard IEEE 30-bus system is utilized to demonstrate that the proposed method fully exploits the potential of static control of UPFC and significantly increases the economic efficiency and static security of the power system

Mitigation of power system forced oscillations based on unified power flow controller

Abstract Forced oscillations (FOs), or low-frequency oscillations (LFOs) caused by periodic, continuous, small power disturbances, threaten the security and stability of power systems. Flexible AC transmission system (FACTS) devices can effectively mitigate LFOs via stability control. We propose a novel method that mitigates FOs by shifting the resonant frequency. Based on the features of the linearized swing equation of a generator, a resonant frequency shift can be achieved by controlling the synchronous torque coefficient using a unified power flow controller (UPFC). Because of the resonance mechanism, the steady-state response of an FO can be effectively mitigated when the resonant frequency changes from the original one, which was close to the disturbance frequency. The principle is that a change in resonant frequency affects the resonance condition. Simulations are conducted in a single-machine infinite-bus (SMIB) system, and the simulation results verify that the method is straightforward to implement and can significantly mitigate FOs. The controller robustness when the resonant frequency is not accurately estimated is also analyzed in the simulations

Concepts and Application of DNA Origami and DNA Self-Assembly: A Systematic Review

With the arrival of the post-Moore Era, the development of traditional silicon-based computers has reached the limit, and it is urgent to develop new computing technology to meet the needs of science and life. DNA computing has become an essential branch and research hotspot of new computer technology because of its powerful parallel computing capability and excellent data storage capability. Due to good biocompatibility and programmability properties, DNA molecules have been widely used to construct novel self-assembled structures. In this review, DNA origami is briefly introduced firstly. Then, the applications of DNA self-assembly in material physics, biogenetics, medicine, and other fields are described in detail, which will aid the development of DNA computational model in the future

Classification and Design of HIV-1 Integrase Inhibitors Based on Machine Learning

A key enzyme in human immunodeficiency virus type 1 (HIV-1) life cycle, integrase (IN) aids the integration of viral DNA into the host DNA, which has become an ideal target for the development of anti-HIV drugs. A total of 1785 potential HIV-1 IN inhibitors were collected from the databases of ChEMBL, Binding Database, DrugBank, and PubMed, as well as from 40 references. The database was divided into the training set and test set by random sampling. By exploring the correlation between molecular descriptors and inhibitory activity, it is found that the classification and specific activity data of inhibitors can be more accurately predicted by the combination of molecular descriptors and molecular fingerprints. The calculation of molecular fingerprint descriptor provides the additional substructure information to improve the prediction ability. Based on the training set, two machine learning methods, the recursive partition (RP) and naive Bayes (NB) models, were used to build the classifiers of HIV-1 IN inhibitors. Through the test set verification, the RP technique accurately predicted 82.5% inhibitors and 86.3% noninhibitors. The NB model predicted 88.3% inhibitors and 87.2% noninhibitors with correlation coefficient of 85.2%. The results show that the prediction performance of NB model is slightly better than that of RP, and the key molecular segments are also obtained. Additionally, CoMFA and CoMSIA models with good activity prediction ability both were constructed by exploring the structure-activity relationship, which is helpful for the design and optimization of HIV-1 IN inhibitors

Association among retinal health, self-reported depressive symptoms, and demographic, lifestyle and health markers: the META-KLS cohort analysis

Background: Retinal health indices were suggested to be related to psychopathological symptoms, such as depressive symptoms. However, large-scale studies using optical coherence tomography (OCT) are missing to investigate the associations among them. Methods: In the META-KLS cohort study, 1456 participants (mean age [standard deviation]= 54.6 [11.91] years; n= 680 [47.8%] women) completed the Patient Health Questionnaire (PHQ-9) to measure depressive symptoms and underwent OCT. Poor-quality OCTs and multivariate outliers were excluded, and principal component analysis was performed to obtain retinal health indices separately for macular (n= 930) and optic nerve head (ONH) thicknesses (n= 800). Linear regressions were run controlling for covariates. Exploratory interaction models were run with demographic, lifestyle and health markers. Results: Although there were no direct significant associations between the retinal indices and depressive symptoms (macular: B= −0.05, 95% CI= [-0.15, 0.05], p= 0.32; ONH index: B= -0.02, 95% CI= [-0.11, 0.08], p= 0.71), their associations were moderated by demographic and health factors, e.g., C-reactive protein (CRP) (macular index: B= −0.03, 95% CI= [-0.05, −0.01], p= 0.002; ONH index: B= 0.05, 95% CI= [0.02, 0.08], p= 0.002). Limitations: Study was cross-sectional and there were no functional assessments of vision. Conclusions: In a large cohort, we observed associations between retinal indices and self-reported depressive symptoms depending on demographic and health factors, notably CRP. Following up, the study will investigate the prospective prediction of retinal health on depressive symptoms, especially in persons who may have chronic inflammation

Targeting loop3 of sclerostin preserves its cardiovascular protective action and promotes bone formation

Antibodies targeting sclerostin can ameliorate postmenopausal osteoporosis but present some cardiovascular risk. Here the authors show that the cardiovascular and skeletal effects of sclerostin are mediated by different loops, suggesting ways to preserve the positive effects on bone formation while avoiding the negative cardiovascular consequences