Computation of current-resistance photovoltaic model using reverse triangular number for photovoltaic emulator application

PV emulator (PVE) is a power supply that produces similar current‑voltage (I‑V) characteristic as the PV module. It simplifies the testing of the PV system during the development phase. Since the output voltage and current of the PVE change based on various factors (load, irradiance and temperature), the computation of the operating point for the PVE is crucial. The resistance feedback control strategy is a robust and fast approach to find the operating point for the PVE. Nonetheless, it uses an uncommon current‑resistance PV model, which cannot be computed using the conventional approach. This work introduces the reverse triangular number to compute the PV model and obtained the operating point of the PVE. The reverse triangular number is based on the variable step sizes that allow fast computation of the PV model. The operating point is then used by the PI controller and the buck converter to produce the output voltage and current similar to the PV module. The results show that the reverse triangular number is able to compute the PV model accurately. In addition, the proposed PVE not only works well with resistive load but adapts accurately under the integration with maximum power point tracking converter

Control of the photovoltaic emulator using fuzzy logic based resistance feedback and binary search

Photovoltaic (PV) emulator is a power supply that produces similar currentvoltage (I-V) characteristics as the PV module. This device simplifies the testing phase of PV systems under various conditions. The essential part of the PV emulator (PVE) is the control strategy. Its main function is to determine the operating point based on the load of the PVE. The direct referencing method (DRM) is the widely used control strategy due to its simplicity. However, the main drawback of DRM is that the output voltage and current oscillate due to the inconsistent operating point under fixed load. This thesis proposes an improved and robust control strategy named resistance feedback method (RFM) that yields consistent operating point under fixed load, irradiance and temperature. The RFM uses the measured voltage and current to determine the load of the PVE in order to identify the accurate operating point instantaneously. The conventional PV models include the I-V and voltage-current PV model. These PV models are widely used in various control strategies of PVE. Nonetheless, the RFM requires a modified PV model, the current-resistance (I-R) PV model, where the mathematical equation is not available. The implementation of the I-R PV model using the look-up table (LUT) is feasible, but it requires a lot of memory to store the data. A mathematical equation based I-R PV model computed using the binary search method is proposed to overcome the drawback of the LUT. The RFM consists of the I-R PV model and the closed-loop buck converter. In this work, the RFM is investigated with two different controllers, namely the proportional-integral (PI) and fuzzy logic controllers. The RFM using the PI controller (RFMPI) and the RFM using the fuzzy logic controller (RFMF) are tested with resistive load and maximum power point tracking (MPPT) boost converter. The perturb and observe algorithm is selected for the MPPT boost converter. In order to properly design the boost converter for the MPPT application, the sizing of the passive components is proposed, derived and confirmed through simulation. This derivation allows adjustment on the output voltage and current ripple of the PVE when connected to the MPPT boost converter. The simulation results of the proposed control strategies are benchmarked with the conventional DRM. To validate the simulation results, all controllers are implemented using dSPACE ds1104 rapid prototyping hardware platform. The RFM computes an operating point of the PVE at 20% faster than the DRM. The generated output PVE voltage and current using RFMPI and the RFMF are up to 90% more accurate compared to the DRM. The efficiency of the PVE is beyond 90% when tested under locus of maximum power point. In transient analysis, the settling time of RFMF is faster than the RFMPI. In short, the proposed RFMF is robust, accurate, quick respond and compatible with the MPPT boost converter

Small business innovation research. Abstracts of 1988 phase 1 awards

Non-proprietary proposal abstracts of Phase 1 Small Business Innovation Research (SBIR) projects supported by NASA are presented. Projects in the fields of aeronautical propulsion, aerodynamics, acoustics, aircraft systems, materials and structures, teleoperators and robots, computer sciences, information systems, data processing, spacecraft propulsion, bioastronautics, satellite communication, and space processing are covered

Collective analog bioelectronic computation

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2009.This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.Cataloged from student submitted PDF version of thesis.Includes bibliographical references (p. 677-710).In this thesis, I present two examples of fast-and-highly-parallel analog computation inspired by architectures in biology. The first example, an RF cochlea, maps the partial differential equations that describe fluid-membrane-hair-cell wave propagation in the biological cochlea to an equivalent inductor-capacitor-transistor integrated circuit. It allows ultra-broadband spectrum analysis of RF signals to be performed in a rapid low-power fashion, thus enabling applications for universal or software radio. The second example exploits detailed similarities between the equations that describe chemical-reaction dynamics and the equations that describe subthreshold current flow in transistors to create fast-and-highly-parallel integrated-circuit models of protein-protein and gene-protein networks inside a cell. Due to a natural mapping between the Poisson statistics of molecular flows in a chemical reaction and Poisson statistics of electronic current flow in a transistor, stochastic effects are automatically incorporated into the circuit architecture, allowing highly computationally intensive stochastic simulations of large-scale biochemical reaction networks to be performed rapidly. I show that the exponentially tapered transmission-line architecture of the mammalian cochlea performs constant-fractional-bandwidth spectrum analysis with O(N) expenditure of both analysis time and hardware, where N is the number of analyzed frequency bins. This is the best known performance of any spectrum-analysis architecture, including the constant-resolution Fast Fourier Transform (FFT), which scales as O(N logN), or a constant-fractional-bandwidth filterbank, which scales as O (N2).(cont.) The RF cochlea uses this bio-inspired architecture to perform real-time, on-chip spectrum analysis at radio frequencies. I demonstrate two cochlea chips, implemented in standard 0.13m CMOS technology, that decompose the RF spectrum from 600MHz to 8GHz into 50 log-spaced channels, consume < 300mW of power, and possess 70dB of dynamic range. The real-time spectrum analysis capabilities of my chips make them uniquely suitable for ultra-broadband universal or software radio receivers of the future. I show that the protein-protein and gene-protein chips that I have built are particularly suitable for simulation, parameter discovery and sensitivity analysis of interaction networks in cell biology, such as signaling, metabolic, and gene regulation pathways. Importantly, the chips carry out massively parallel computations, resulting in simulation times that are independent of model complexity, i.e., O(1). They also automatically model stochastic effects, which are of importance in many biological systems, but are numerically stiff and simulate slowly on digital computers. Currently, non-fundamental data-acquisition limitations show that my proof-of-concept chips simulate small-scale biochemical reaction networks at least 100 times faster than modern desktop machines. It should be possible to get 103 to 106 simulation speedups of genome-scale and organ-scale intracellular and extracellular biochemical reaction networks with improved versions of my chips. Such chips could be important both as analysis tools in systems biology and design tools in synthetic biology.by Soumyajit Mandal.Ph.D

Laboratory Directed Research and Development Program FY 2004 Annual Report

The Oak Ridge National Laboratory (ORNL) Laboratory Directed Research and Development (LDRD) Program reports its status to the U.S. Department of Energy (DOE) in March of each year. The program operates under the authority of DOE Order 413.2A, 'Laboratory Directed Research and Development' (January 8, 2001), which establishes DOE's requirements for the program while providing the Laboratory Director broad flexibility for program implementation. LDRD funds are obtained through a charge to all Laboratory programs. This report describes all ORNL LDRD research activities supported during FY 2004 and includes final reports for completed projects and shorter progress reports for projects that were active, but not completed, during this period. The FY 2004 ORNL LDRD Self-Assessment (ORNL/PPA-2005/2) provides financial data about the FY 2004 projects and an internal evaluation of the program's management process. ORNL is a DOE multiprogram science, technology, and energy laboratory with distinctive capabilities in materials science and engineering, neutron science and technology, energy production and end-use technologies, biological and environmental science, and scientific computing. With these capabilities ORNL conducts basic and applied research and development (R&amp;D) to support DOE's overarching national security mission, which encompasses science, energy resources, environmental quality, and national nuclear security. As a national resource, the Laboratory also applies its capabilities and skills to the specific needs of other federal agencies and customers through the DOE Work For Others (WFO) program. Information about the Laboratory and its programs is available on the Internet at &lt;http://www.ornl.gov/&gt;. LDRD is a relatively small but vital DOE program that allows ORNL, as well as other multiprogram DOE laboratories, to select a limited number of R&amp;D projects for the purpose of: (1) maintaining the scientific and technical vitality of the Laboratory; (2) enhancing the Laboratory's ability to address future DOE missions; (3) fostering creativity and stimulating exploration of forefront science and technology; (4) serving as a proving ground for new research; and (5) supporting high-risk, potentially high-value R&amp;D. Through LDRD the Laboratory is able to improve its distinctive capabilities and enhance its ability to conduct cutting-edge R&amp;D for its DOE and WFO sponsors. To meet the LDRD objectives and fulfill the particular needs of the Laboratory, ORNL has established a program with two components: the Director's R&amp;D Fund and the Seed Money Fund. As outlined in Table 1, these two funds are complementary. The Director's R&amp;D Fund develops new capabilities in support of the Laboratory initiatives, while the Seed Money Fund is open to all innovative ideas that have the potential for enhancing the Laboratory's core scientific and technical competencies. Provision for multiple routes of access to ORNL LDRD funds maximizes the likelihood that novel and seminal ideas with scientific and technological merit will be recognized and supported

Particle Physics Reference Library

This second open access volume of the handbook series deals with detectors, large experimental facilities and data handling, both for accelerator and non-accelerator based experiments. It also covers applications in medicine and life sciences. A joint CERN-Springer initiative, the “Particle Physics Reference Library” provides revised and updated contributions based on previously published material in the well-known Landolt-Boernstein series on particle physics, accelerators and detectors (volumes 21A,B1,B2,C), which took stock of the field approximately one decade ago. Central to this new initiative is publication under full open access

Review of Particle Physics

The Review summarizes much of particle physics and cosmology. Using data from previous editions, plus 2,143 new measurements from 709 papers, we list, evaluate, and average measured properties of gauge bosons and the recently discovered Higgs boson, leptons, quarks, mesons, and baryons. We summarize searches for hypothetical particles such as supersymmetric particles, heavy bosons, axions, dark photons, etc. Particle properties and search limits are listed in Summary Tables. We give numerous tables, figures, formulae, and reviews of topics such as Higgs Boson Physics, Supersymmetry, Grand Unified Theories, Neutrino Mixing, Dark Energy, Dark Matter, Cosmology, Particle Detectors, Colliders, Probability and Statistics. Among the 120 reviews are many that are new or heavily revised, including a new review on Machine Learning, and one on Spectroscopy of Light Meson Resonances. The Review is divided into two volumes. Volume 1 includes the Summary Tables and 97 review articles. Volume 2 consists of the Particle Listings and contains also 23 reviews that address specific aspects of the data presented in the Listings