Intelligent Global Maximum Power Point Tracking Strategies Based on Shading Perception for Photovoltaic Systems

When a Photovoltaic (PV) system is partially shaded in the environment, the current-voltage (I-V) and power-voltage (P-V) curves exhibit multiple stairs/peaks and the locus of Maximum Power Point (MPP) varies over a wide range. Such Partial Shading Conditions (PSC) bring challenges to the Maximum Power Point Tracking (MPPT) systems. This thesis presents some novel shading information to characterize the complex PSC and MPPT techniques based on the shading perception. Shading information is the mathematical indicator to express the shading patterns. The existing shading information, such as shading rate and shading strength, has the limitations that they can only characterize the PSC with two irradiation levels. To improve the application range of the shading information, the shading matrix and shading vector are proposed in this thesis. The identification and detection methods for the proposed shading information are also included. Results from simulations and experiments have shown the effectiveness and accuracy of the proposed shading detection methods. Under PSC, the power characteristics of the PV systems are too complicated that there exist multiple MPPs. The traditional MPPT techniques may be trapped in the Local MPPs (LMPPs) instead of the Global MPP (GMPP). In this thesis, some novel methods are proposed to estimate the GMPP location from the detected shading information. The proposed MPPT techniques based on the shading perception are capable of tracking the GMPP fast and accurately. Simulations and experiments are conducted to validate the performance of the proposed MPPT methods with the comparison with some well-known MPPT methods

A solar irradiance estimation technique via curve fitting based on dual-mode Jaya optimization

Solar irradiance is a crucial environmental parameter for optimal control of photovoltaic (PV) systems. However, precise measurements of the solar irradiance are difficult since the irradiation sensors (i.e., pyranometer or pyrheliometer) are expensive and hard to calibrate. This paper proposes a cost-effective and accurate method for estimating the solar irradiance with a PV module via curve fitting. A dual-mode Jaya (DM-Jaya) optimization algorithm is introduced to extract the real-time value of solar irradiance from the measured PV characteristics data by using two search strategies. The step sizes of a random walk are taken from even and Lévy distribution distributions in different searching phases. Compared with the traditional irradiance sensors, the proposed estimator does not require additional circuit and obtains relatively lower error rates. A comparative study of seven population-based optimization algorithms for the optimal design of the estimator is presented. These algorithms include particle swarm optimization (PSO), cuckoo search (CS), Jaya, simulated annealing (SA), genetic algorithm (GA), supply-demand-based optimization (SDO), and the proposed DM-Jaya algorithm. Simulations and experimental results reveal that DM-Jaya outperforms the other optimization algorithms in terms of the estimation speed and accuracy

ANFIS-Based Modeling for Photovoltaic Characteristics Estimation

Due to the high cost of photovoltaic (PV) modules, an accurate performance estimation method is significantly valuable for studying the electrical characteristics of PV generation systems. Conventional analytical PV models are usually composed by nonlinear exponential functions and a good number of unknown parameters must be identified before using. In this paper, an adaptive-network-based fuzzy inference system (ANFIS) based modeling method is proposed to predict the current-voltage characteristics of PV modules. The effectiveness of the proposed modeling method is evaluated through comparison with Villalva’s model, radial basis function neural networks (RBFNN) based model and support vector regression (SVR) based model. Simulation and experimental results confirm both the feasibility and the effectiveness of the proposed method

ANFIS-Based Modeling for Photovoltaic Characteristics Estimation

Due to the high cost of photovoltaic (PV) modules, an accurate performance estimation method is significantly valuable for studying the electrical characteristics of PV generation systems. Conventional analytical PV models are usually composed by nonlinear exponential functions and a good number of unknown parameters must be identified before using. In this paper, an adaptive-network-based fuzzy inference system (ANFIS) based modeling method is proposed to predict the current-voltage characteristics of PV modules. The effectiveness of the proposed modeling method is evaluated through comparison with Villalva’s model, radial basis function neural networks (RBFNN) based model and support vector regression (SVR) based model. Simulation and experimental results confirm both the feasibility and the effectiveness of the proposed method

Meta analysis of retinal and choroidal structural changes in patients with internal carotid artery stenosis

AIM:To systematically evaluate the changes in retinal and choroidal thickness in patients with internal carotid artery stenosis by using optical coherence tomography(OCT)through Meta-analysis.METHODS: Literatures on the measurement of retinal and choroidal structure in patients with internal carotid artery stenosis by using OCT from CNKI, VIP, WF, PubMed, the Cochrane Library, SinoMed, and Embase databases were searched for relevant studies. The retrieval time was from the establishment of the databases to January 2024. In addition, quality of the included literatures was assessed by the Newtle-Ottawa scale(NOS), and RevMan 5.4.1 and Stata 16.0 were used for statistical analysis.RESULTS: A total of 17 articles(including 18 studies)were included, and the Meta-analysis results showed that, patients with internal carotid artery stenosis had significantly thinner peripapillary retinal nerve fiber layer(pRNFL), ganglion cell complex(GCC), center macular thickness(CMT), and subfoveal choroidal thickness(SFCT)than the healthy control group(age matched normal population). The pRNFL and SFCT of the ipsilateral eye in patients with internal carotid artery stenosis become thinner compared with the contralateral eye.CONCLUSION:To a certain extent, the morphological structure of the retina and choroid can be altered by stenosis of the internal carotid artery. OCT can non-invasively detect the microstructural changes of the retina and choroid in patients with internal carotid artery stenosis, and can be used for the evaluation of internal carotid artery stenosis

Comparison of short and long-time outcomes between laparoscopic and conventional open multivisceral resection for primary T4b colorectal cancer

Summary: Background: This study aimed to compare laparoscopic multivisceral resection (LMVR) with conventional open multivisceral resection (OMVR) for primary T4b colorectal cancer (CRC) in short and long-time outcomes. Methods: Patients receiving LMVR or OMVR for primary T4b CRC from January 2009 to June 2016 were enrolled. Patients’ clinicopathological characteristics and survival data were collected and analyzed. Multivariable analysis was performed to find the factors related with survival. All statistical analysis was performed by SPSS 22.0. Results: A total of 91 patients (LMVR 38, OMVR 53) were included in this study. Patients undergoing LMVR were associated with smaller incision length (P < 0.001), less blood loss (P = 0.01) and comparable operative time (P = 0.071). Patients in LMVR group also had less time to first flatus (P = 0.025). The results also suggested LMVR could reduce the incidence of postoperative complication. The conversion rate was 28.9%. The 3-year OS was 64.2%, 68.4% in OMVR, LMVR group respectively and the 3-year DFS was 56.6%, 52.6% in OMVR, LMVR group respectively. The Kaplan curves demonstrated that LMVR group had similar OS (P = 0.896) and DFS (P = 0.806) when compared with OMVR group. In addition, the multivariate analysis demonstrated that laparoscopic surgery was not associated with poorer survival. Conclusion: Not all MVR for T4b CRC should be performed by open procedure, LMVR can be safe and feasible for primary T4b CRC in selected patients. It can faster the postoperative recovery and reduce the incidence of postoperative complication. The OS and DFS are also not inferior to open group. Keywords: Laparoscopic, Open, Multivisceral resection, T4b, Colorectal cancer, Outcome