Flexible fault ride through strategy for wind farm clusters in power systems with high wind power penetration

This paper investigates a flexible fault ride through strategy for power systems in China with high wind power penetration. The strategy comprises of adaptive fault ride through requirements and maximum power restrictions of the wind farms with weak fault ride through capabilities. The slight faults and moderate faults with high probability are the main defending objective of the strategy. The adaptive fault ride through requirement in the strategy consists of two sub fault ride through requirements, a temporary slight voltage ride through requirement corresponding to a slight fault incident, with a moderate voltage ride through requirement corresponding to a moderate fault. The temporary overloading capability of the wind farm is reflected in both requirements to enhance the capability to defend slight faults and to avoid tripping when the crowbar is disconnected after moderate faults are cleared. For those wind farms that cannot meet the adaptive fault ride through requirement, restrictions are put on the maximum power output. Simulation results show that the flexible fault ride through strategy increases the fault ride through capability of the wind farm clusters and reduces the wind power curtailment during faults.

New SR drive with integrated charging capacity for plug-in hybrid electric vehicles (PHEVs)

Plug-in hybrid electric vehicles (PHEVs) provide much promise in reducing greenhouse gas emissions and, thus, are a focal point of research and development. Existing on-board charging capacity is effective but requires the use of several power conversion devices and power converters, which reduce reliability and cost efficiency. This paper presents a novel three-phase switched reluctance (SR) motor drive with integrated charging functions (including internal combustion engine and grid charging). The electrical energy flow within the drivetrain is controlled by a power electronic converter with less power switching devices and magnetic devices. It allows the desired energy conversion between the engine generator, the battery, and the SR motor under different operation modes. Battery-charging techniques are developed to operate under both motor-driving mode and standstill-charging mode. During the magnetization mode, the machine's phase windings are energized by the dc-link voltage. The power converter and the machine phase windings are controlled with a three-phase relay to enable the use of the ac-dc rectifier. The power converter can work as a buck-boost-type or a buck-type dc-dc converter for charging the battery. Simulation results in MATLAB/Simulink and experiments on a 3-kW SR motor validate the effectiveness of the proposed technologies, which may have significant economic implications and improve the PHEVs' market acceptance

Highly Electrocatalytic Activity of RuO2 Nanocrystals for Triiodide Reduction in Dye-Sensitized Solar Cells

Dye-sensitized solar cells (DSCs) are promising alternatives to conventional silicon devices because of their simple fabrication procedure, low cost, and high efficiency. Platinum is generally used as a superior counter electrode (CE) material, but the disadvantages such as high cost and low abundance greatly restrict the large-scale application of DSCs. An efficient and sustainable way to overcome the limited supply of Pt is the development of high-efficiency Pt-free CE materials, which should possess both high electrical conductivity and superior electrocatalytic activity simultaneously. Herein, for the first time, a two-step strategy to synthesize ruthenium dioxide (RuO2) nanocrystals is reported, and it is shown that RuO2 catalysts exhibit promising electrocatalytic activity towards triiodide reduction, which results in comparable energy conversion efficiency to that of conventional Pt CEs. More importantly, by virtue of first-principles calculations, the catalytic mechanism of electrocatalysis for triiodide reduction on various CEs is investigated systematically and it is found that the electrochemical triiodide reduction reaction on RuO2 catalyst surfaces can be enhanced significantly, owing to the ideal combination of good electrocatalytic activity and high electrical conductivity.

Turning Indium Oxide into a Superior Electrocatalyst:Deterministic Heteroatoms

The efficient electrocatalysts for many heterogeneous catalytic processes in energy conversion and storage systems must possess necessary surface active sites. Here we identify, from X-ray photoelectron spectroscopy and density functional theory calculations, that controlling charge density redistribution via the atomic-scale incorporation of heteroatoms is paramount to import surface active sites. We engineer the deterministic nitrogen atoms inserting the bulk material to preferentially expose active sites to turn the inactive material into a sufficient electrocatalyst. The excellent electrocatalytic activity of N-In2O3 nanocrystals leads to higher performance of dye-sensitized solar cells (DSCs) than the DSCs fabricated with Pt. The successful strategy provides the rational design of transforming abundant materials into high-efficient electrocatalysts. More importantly, the exciting discovery of turning the commonly used transparent conductive oxide (TCO) in DSCs into counter electrode material means that except for decreasing the cost, the device structure and processing techniques of DSCs can be simplified in future.

Unidirectional suppression of hydrogen oxidation on oxidized platinum clusters

Solar-driven water splitting to produce hydrogen may be an ideal solution for global energy and environment issues. Among the various photocatalytic systems, platinum has been widely used to co-catalyse the reduction of protons in water for hydrogen evolution. However, the undesirable hydrogen oxidation reaction can also be readily catalysed by metallic platinum, which limits the solar energy conversion efficiency in artificial photosynthesis. Here we report that the unidirectional suppression of hydrogen oxidation in photocatalytic water splitting can be fulfilled by controlling the valence state of platinum; this platinum-based cocatalyst in a higher oxidation state can act as an efficient hydrogen evolution site while suppressing the undesirable hydrogen back-oxidation. The findings in this work may pave the way for developing other high-efficientcy platinum-based catalysts for photocatalysis, photoelectrochemistry, fuel cells and water-gas shift reactions.

Selective deuterium ion acceleration using the Vulcan petawatt laser

We report on the successful demonstration of selective acceleration of deuterium ions by target-normal sheath acceleration (TNSA) with a high-energy petawatt laser. TNSA typically produces a multi-species ion beam that originates from the intrinsic hydrocarbon and water vapor contaminants on the target surface. Using the method first developed by Morrison et al. [Phys. Plasmas 19, 030707 (2012)], an ion beam with >99% deuterium ions and peak energy 14 MeV/nucleon is produced with a 200 J, 700 fs, > 10 20 W/cm 2 laser pulse by cryogenically freezing heavy water (D<inf>2</inf>O) vapor onto the rear surface of the target prior to the shot. Within the range of our detectors (0°-8.5°), we find laser-to-deuterium-ion energy conversion efficiency of 4.3% above 0.7 MeV/nucleon while a conservative estimate of the total beam gives a conversion efficiency of 9.4%.

A biogeography-based optimization algorithm with mutation strategies for model parameter estimation of solar and fuel cells

Mathematical models are useful tools for simulation, evaluation, optimal operation and control of solar cells and proton exchange membrane fuel cells (PEMFCs). To identify the model parameters of these two type of cells efficiently, a biogeography-based optimization algorithm with mutation strategies (BBO-M) is proposed. The BBO-M uses the structure of biogeography-based optimization algorithm (BBO), and both the mutation motivated from the differential evolution (DE) algorithm and the chaos theory are incorporated into the BBO structure for improving the global searching capability of the algorithm. Numerical experiments have been conducted on ten benchmark functions with 50 dimensions, and the results show that BBO-M can produce solutions of high quality and has fast convergence rate. Then, the proposed BBO-M is applied to the model parameter estimation of the two type of cells. The experimental results clearly demonstrate the power of the proposed BBO-M in estimating model parameters of both solar and fuel cells.

Design of an automated solar concentrator for the pyrolysis of scrap rubber

An automated solar reactor system was designed and built to carry out catalytic pyrolysis of scrap rubber tires at 550°C. To maximize solar energy concentration, a two degrees-of-freedom automated sun tracking system was developed and implemented. Both the azimuth and zenith angles were controlled via feedback from six photo-resistors positioned on a Fresnel lens. The pyrolysis of rubber tires was tested with the presence of two types of acidic catalysts, H-beta and H-USY. Additionally, a photoactive TiO<inf>2</inf> catalyst was used and the products were compared in terms of gas yields and composition. The catalysts were characterized by BET analysis and the pyrolysis gases and liquids were analyzed using GC-MS. The oil and gas yields were relatively high with the highest gas yield reaching 32.8% with H-beta catalyst while TiO<inf>2</inf> gave the same results as thermal pyrolysis without any catalyst. In the presence of zeolites, the dominant gasoline-like components in the gas were propene and cyclobutene. The TiO<inf>2</inf> and non-catalytic experiments produced a gas containing gasoline-like products of mainly isoprene (76.4% and 88.4% respectively). As for the liquids they were composed of numerous components spread over a wide distribution of C<inf>10</inf> to C<inf>29</inf> hydrocarbons of naphthalene and cyclohexane/ene derivatives.

Orange Zinc Germanate with Metallic Ge-Ge Bonds as a Chromophore-Like Center for Visible-Light-Driven Water Splitting

The efficiency of solar-energy-conversion devices depends on the absorption region and intensity of the photon collectors. Organic chromophores, which have been widely stabilized on inorganic semiconductors for light trapping, are limited by the interface between the chromophore and semiconductor. Herein we report a novel orange zinc germanate (Zn-Ge-O) with a chromophore-like structure, by which the absorption region can be dramatically expanded. Structural characterizations and theoretical calculations together reveal that the origin of visible-light response can be attributed to the unusual metallic Ge-Ge bonds which act in a similar way to organic chromophores. Benefiting from the enhanced light harvest, the orange Zn-Ge-O demonstrates superior capacity for solar-driven hydrogen production.

A novel TRNSYS type for short-term borehole heat exchanger simulation: B2G model

Models of ground source heat pump (GSHP) systems are used as an aid for the correct design and optimization of the system. For this purpose, it is necessary to develop models which correctly reproduce the dynamic thermal behavior of each component in a short-term basis. Since the borehole heat exchanger (BHE) is one of the main components, special attention should be paid to ensuring a good accuracy on the prediction of the short-term response of the boreholes. The BHE models found in literature which are suitable for short-term simulations usually present high computational costs. In this work, a novel TRNSYS type implementing a borehole-to-ground (B2G) model, developed for modeling the short-term dynamic performance of a BHE with low computational cost, is presented. The model has been validated against experimental data from a GSHP system located at Universitat Politècnica de València, Spain. Validation results show the ability of the model to reproduce the short-term behavior of the borehole, both for a step-test and under normal operating conditions.

Data-Driven Dynamic Modeling of Coupled Thermal and Electric Outputs of Microturbines

Microturbines are among the most successfully commercialized distributed energy resources, especially when they are used for combined heat and power generation. However, the interrelated thermal and electrical system dynamic behaviors have not been fully investigated. This is technically challenging due to the complex thermo-fluid-mechanical energy conversion processes which introduce multiple time-scale dynamics and strong nonlinearity into the analysis. To tackle this problem, this paper proposes a simplified model which can predict the coupled thermal and electric output dynamics of microturbines. Considering the time-scale difference of various dynamic processes occuring within microturbines, the electromechanical subsystem is treated as a fast quasi-linear process while the thermo-mechanical subsystem is treated as a slow process with high nonlinearity. A three-stage subspace identification method is utilized to capture the dominant dynamics and predict the electric power output. For the thermo-mechanical process, a radial basis function model trained by the particle swarm optimization method is employed to handle the strong nonlinear characteristics. Experimental tests on a Capstone C30 microturbine show that the proposed modeling method can well capture the system dynamics and produce a good prediction of the coupled thermal and electric outputs in various operating modes.

Identification of Microturbine Model for Long-term Dynamic Analysis of Distribution Networks

As one of the most successfully commercialized distributed energy resources, the long-term effects of microturbines (MTs) on the distribution network has not been fully investigated due to the complex thermo-fluid-mechanical energy conversion processes. This is further complicated by the fact that the parameter and internal data of MTs are not always available to the electric utility, due to different ownerships and confidentiality concerns. To address this issue, a general modeling approach for MTs is proposed in this paper, which allows for the long-term simulation of the distribution network with multiple MTs. First, the feasibility of deriving a simplified MT model for long-term dynamic analysis of the distribution network is discussed, based on the physical understanding of dynamic processes that occurred within MTs. Then a three-stage identification method is developed in order to obtain a piecewise MT model and predict electro-mechanical system behaviors with saturation. Next, assisted with the electric power flow calculation tool, a fast simulation methodology is proposed to evaluate the long-term impact of multiple MTs on the distribution network. Finally, the model is verified by using Capstone C30 microturbine experiments, and further applied to the dynamic simulation of a modified IEEE 37-node test feeder with promising results.

Data-Driven Dynamic Prediction of Interrelated Heat and Electric Outputs of Microturbines

Microturbines are among the most successfully commercialized distributed energy resources, especially when they are used for combined heat and power generation. However, the interrelated thermal and electrical system dynamic behaviors have not been fully investigated. This is technically challenging due to the complex thermo-fluid-mechanical energy conversion processes which introduce multiple time-scale dynamics and strong nonlinearity into the analysis. To tackle this problem, this paper proposes a simplified model which can predict the coupled thermal and electric output dynamics of microturbines. Considering the time-scale difference of various dynamic processes occuring within microturbines, the electromechanical subsystem is treated as a fast quasi-linear process while the thermo-mechanical subsystem is treated as a slow process with high nonlinearity. A three-stage subspace identification method is utilized to capture the dominant dynamics and predict the electric power output. For the thermo-mechanical process, a radial basis function model trained by the particle swarm optimization method is employed to handle the strong nonlinear characteristics. Experimental tests on a Capstone C30 microturbine show that the proposed modeling method can well capture the system dynamics and produce a good prediction of the coupled thermal and electric outputs in various operating modes.