Evaluation of Grid-Connected Photovoltaic Plants Based on Clustering Methods

Photovoltaic (PV) systems are electric power systems designed to supply usable solar power by means of photovoltaics, which is the conversion of light into electricity using semiconducting materials. PV systems have gained much attention and are a very attractive energy resource nowadays. The substantial advantage of PV systems is the usage of the most abundant and free energy from the sun. PV systems play an important role in reducing feeder losses, improving voltage profiles and providing ancillary services to local loads. However, large PV grid-connected systems may have a destructive impact on the stability of the electric grid. This is due to the fluctuations of the output AC power generated from the PV systems according to the variations in the solar energy levels. Thus, the electrical distribution system with high penetration of PV systems is subject to performance degradation and instabilities. For that, this project attempts to enhance the integration process of PV systems into electrical grids by analyzing the impact of installing grid-connected PV plants. To accomplish this, an indicative representation of solar irradiation datasets is used for planning and power flow studies of the electric network prior to PV systems installation. Those datasets contain lengthy historical observations of solar energy data, that requires extensive analysis and simulations. To overcome that the lengthy historical datasets are reduced and clustered while preserving the original data characteristics. The resultant clusters can be utilized in the planning stage and simulation studies. Accordingly, studies related to PV systems integration into the electric grid are conducted in an efficient manner, avoiding computing resources and processing times with easier and practical implementation.     

Adaptive Discretization for Computerized Tomography

Two adaptive discretization frameworks are tested for computerized tomography (CT) data reconstruction. Removal of inactive pixels is primary motivation. Efficient and user independent entropy optimized masking is employed for spatial filtering purposes. Density of nodes at high gradient of reconstructed physical property is used as adaptation criterion. An alternative option, independent from noisy projection data and nature of the physical properties, is also discussed. Sensitivity analysis between the uniform and nonuniform (evolved via adaptive route) reconstruction grid reveals the utility of nonuniform grids. Iterative and transform based reconstruction techniques are used. Outcomes are tested successfully on three real world projection data from two different compact CT setups and one commercial high-resolution micro-CT scanner.     

Enhancement of tumor killing using a combination of tumor immunization and HSV-tk suicide gene therapy

Tumor cells genetically modified with the herpes simplex virus thymidine kinase (HSV-tk) gene in combination with ganciclovir (GCV) demonstrate a "bystander effect". Previous attempts to enhance the bystander tumor killing by combining cytokine genes with HSV-tk/GCV have met with varying results. The present study was designed to determine the effects of tumor immunization in combination with HSV-tk gene-modified tumor cells and GCV on tumor killing and to determine if the bystander tumor killing could be enhanced. Tumor-bearing mice immunized with syngeneic tumor (KBALB) prior to treatment with an i.p. injection of xenogeneic HSV-tk gene-modified tumor cells (PA-1STK) had prolonged animal survival (group 4, 56.4 days). In contrast, unimmunized tumor-bearing mice (group 2) or tumor-bearing mice immunized to the xenogeneic PA-1STK tumor cells (group 5) showed a mean survival of about 27 days after receiving an i.p. injection of PA-1STK cells and GCV. Control groups, which were either not immunized and did not receive HSV-tk cells (group 1) or immunized but treated only with GCV (group 3) showed short survival (16-18 days). Analysis of tumors for cytokine mRNA expression revealed increased TNF-alpha and IL-1alpha mRNA expression in group 4 mice. Furthermore, IL-2 mRNA expression was detectable on days 2 and 4 only in group 4 mice. Immunophenotypic analysis for tumor-infiltrating lymphocytes demonstrated an increase in macrophage (4%, p = 0.0001) and T cells (1.8%, p < 0.001) in group 4 mice with an enhanced T-cell response as compared with mice from groups 1, 2 and 3. Our results demonstrate that tumor immunization combined with HSV-tk/GCV treatment results in increased animal survival with enhanced immune response. Furthermore, the cytokine milieu observed in the present study can modulate the tumor micro-environment in vivo from one that is immunosuppressive to one that is immune-stimulatory.     

Oligoclonal protein bands and Ig isotype switching in multiple myeloma treated with high-dose therapy and hematopoietic cell transplantation

Multiple myeloma (MM) is usually characterized by production of a single serum monoclonal protein of constant isotype and light-chain restriction. Multiple Ig isotypes and isotype switches, which are rare in untreated patients, are reported to be more common in patients undergoing myeloablative therapy. These additional protein bands, detected by immunofixation electrophoresis (IFE), could be due to altered paraprotein production by the malignant plasma cell clone or oligoclonal Ig production during recovery of B-cell function after myeloablative therapy. We analyzed abnormal protein bands (APB), distinct from the presenting paraprotein, in 550 patients receiving high-dose therapy with autologous hematopoietic cell transplantation at a single institution. Fifty-five patients (10%) had APB, 48 had oligoclonal bands (OB), and 23 had an apparent isotype switch (IS) on IFE (16 had both OB and IS). Morphologic and flow cytometric examination of bone marrow in 17 patients with IS showed no evidence of a clonal plasma cell isotype switch. Patients with APB had significantly higher complete response to therapy (67% v 37%, P = .001). To assess the independent prognostic relevance of APB, a multivariate analysis was performed among 471 patients surviving at least 12 months from first transplant (all patients developing APB had done so by 12 months from first transplant). APB (in 50 patients) was a favorable feature for both event-free (rank 3, P = .004) and overall survival (rank 3, P = .0005). We propose that OB and IS are likely to be due to recovery of Ig production rather than alterations in the biology of the malignant plasma cell clone.     

Performance of iterative tomographic algorithms applied to non-destructive evaluation with limited data

Iterative tomographic algorithms have been applied to the reconstruction of a two-dimensional object with internal defects from its projections. Nine distinct algorithms with varying numbers of projections and projection angles have been considered. Each projection of the solid object is interpreted as a path integral of the light-sensitive property of the object in the appropriate direction. The integrals are evaluated numerically and are assumed to represent exact data. Errors in reconstruction are defined as the statistics of difference between original and reconstructed objects and are used to compare one algorithm with respect to another. The algorithms used in this work can be classified broadly into three groups, namely the additive algebraic reconstruction technique (ART), the multiplicative algebraic reconstruction technique (MART) and the maximization reconstruction technique (MRT). Additive ART shows a systematic convergence with respect to the number of projections and the value of the relaxation parameter. MART algorithms produce less error at convergence compared to additive ART but converge only at small values of the relaxation parameter. The MRT algorithm shows an intermediate performance when compared to ART and MART. An increasing noise level in the projection data increases the error in the reconstructed field. The maximum and RMS errors are highest in ART and lowest in MART for given projection data. Increasing noise levels in the projection data decrease the convergence rates. For all algorithms, a 20% noise level is seen as an upper limit, beyond which the reconstructed field is barely recognizable.