Incremental Conductivity Research Articles

OPTIMIZED CONTROL OF THE PHYSICAL BATTERY SYSTEM

Today, a significant issue for many nations worldwide is a shortage of energy. Renewable energy sources, particularly solar energy, are being investigated as additional energy sources to address the aforementioned issue. The high investment cost and poor performance of solar energy, however, provide the biggest challenge. This study only addresses the power optimization problem. It is suggested that the method used to determine the solar system's maximum power point modify incremental conductance. Adapted Incremental Conductance algorithm based on Incremental Conductance conventional techniques. The Modified Incremental Conductance method, however, has several exceptional advantages since it has a voltage change (V) that is not constant but fluctuates in an ideal manner to achieve the maximum power point as soon as possible. The voltage V is greater away from the peak power point while it is zero at the peak power point. Modified incremental conductivity algorithm to find peak power point faster than traditional algorithms. With maximum power point change reducing ambient power loss at the highest powers point. This helps to optimize voltage difference value.

Performance Analysis of Different Optimization Algorithms for MPPT Control Techniques under Complex Partial Shading Conditions in PV Systems

Classic algorithms show high performance in tracking the maximum power point (MPP) of photovoltaic (PV) panels under uniform irradiance and temperature conditions. However, when partial or complex partial shading conditions occur, they fail in capturing the global maximum power point (GMPP) and are trapped in one of the local maximum power points (LMPPs) leading to a loss in power. On the other hand, intelligent algorithms inspired by nature show successful performance in GMPP tracking. In this study, an MPPT system was set up in MATLAB/Simulink software consisting of six groups of serially connected PV panels, a DC-DC boost converter, and load. Using this system, the cuckoo search (CS) algorithm, the modified incremental conductivity (MIC) algorithm, the particle swarm optimization (PSO) algorithm, and the grey wolf optimization (GWO) algorithm were compared in terms of productivity, convergence speed, efficiency, and oscillation under complex shading conditions. The results showed that the GWO algorithm showed superior performance compared to the other algorithms under complex shading conditions. It was observed that GWO did not oscillate during GMPP tracking with an average convergence speed of 0.22 s and a tracking efficiency of 99%. All these evaluations show that GWO is a very fast, highly accurate, efficient, and stable MPPT method under complex partial shading conditions.

A New Model Predictive Control Method for Buck-Boost Inverter-Based Photovoltaic Systems

This study designed a system consisting of a photovoltaic system and a DC-DC boost converter with buck-boost inverter. A multi-error method, based on model predictive control (MPC), is presented for control of the buck-boost inverter. Incremental conductivity and predictive control methods have also been used to track the maximum power of the photovoltaic system. Due to the fact that inverters are in the category of systems with fast dynamics, in this method, by first determining the system state space and its discrete time model, a switching algorithm is proposed to reduce the larger error for the converter. By using this control method, in addition to reducing the total harmonic distortion (THD), the inverter voltage reaches the set reference value at a high speed. To evaluate the performance of the proposed method, the dynamic performance of the converter at the reference voltage given to the system was investigated. The results of system performance in SIMULINK environment were simulated and analyzed by MATLAB software. According to the simulation results, we can point out the advantage of this system in following the reference signal with high speed and accuracy.

Ex situ aging effect on sulfonated poly(ether ether ketone) membrane: Hydration-dehydration cycling and hydrothermal treatment

Prolonged hydrothermal treatment for sulfonated poly(ether ether ketone) membranes induces mechanical degradation and developing hydrophilic-hydrophobic phase separation, simultaneously. The enhanced phase separation provides incremental proton conductivity to the membranes, whereas mechanical degradation drastically reduces device stability. On this basis, we describe here the effects of two different ex situ aging processes on sulfonated poly(ether ether ketone) membranes: hydration-dehydration cycling and prolonged hydrothermal treatment. Both aged membranes exhibited enhanced phase separation under the hydrated conditions, as characterized by small angle X-ray scattering. However, when the aged membranes were dried again, the nanostructure of the membranes aged via the hydration-dehydration cycling was recoverable, whereas that of the membranes aged via prolonged hydrothermal treatment was irreversible. Furthermore, the two differently aged membranes showed clear differences in thermal, mechanical, and electrochemical properties. Finally, we implemented both aged membranes in fuel cell application. The sample aged via hydration-dehydration cycling maintained its improved cell performance, whereas the sample aged via hydrothermal treatment showed drastically reduced cell performance after durability test for 50 h.

Research on photovoltaic system MPPT based on IFOINC algorithm

Abstract Aiming at the shortcomings of traditional maximum power point tracking (MPPT) algorithm in photovoltaic system, such as slow tracking speed, easy oscillation and low tracking accuracy, an improved fractional order incremental conductivity (IFOINC) method is proposed. The algorithm combines the variable step-size Peturb and Observe (P & O) method based on power prediction and fractional order conductance increment method. Firstly, the variable step-size P & O method based on power prediction is used to quickly track the MPP, and then the fractional order incremental conductance method is used to further search the MPP. The structure of photovoltaic system, the equivalent model of photovoltaic cells and the DC/DC converter are studied. The IFOINC algorithm is designed, and the MPPT simulation model of photovoltaic system is established. The simulation is carried out in MATLAB/Simulink software environment. The simulation results show that the tracking speed of IFOINC is improved by 42.3% compared with the variable step-size P & O method based on power prediction, and the tracking accuracy of 3.9% higher than that of the variable step-size P & O method, based on power prediction, and the oscillation is eliminated.

A Novel Pigeon-Inspired Optimization Based MPPT Technique for PV Systems

The conventional maximum power point tracking (MPPT) method fails in partially shaded conditions, because multiple peaks may appear on the power–voltage characteristic curve. The Pigeon-Inspired Optimization (PIO) algorithm is a new type of meta-heuristic algorithm. Aiming at this situation, this paper proposes a new type of algorithm that combines a new pigeon population algorithm named Parallel and Compact Pigeon-Inspired Optimization (PCPIO) with MPPT, which can solve the problem that MPPT cannot reach the near global maximum power point. This hybrid algorithm is fast, stable, and capable of globally optimizing the maximum power point tracking algorithm. Therefore, the purpose of this article is to study the performance of two optimization techniques. The two algorithms are Particle Swarm Algorithm (PSO) and improved pigeon algorithm. This paper first studies the mechanism of multi-peak output characteristics of photovoltaic arrays in complex environments, and then proposes a multi-peak MPPT algorithm based on a combination of an improved pigeon population algorithm and an incremental conductivity method. The improved pigeon algorithm is used to quickly locate near the maximum power point, and then the variable step size incremental method INC (incremental conductance) is used to accurately locate the maximum power point. A simulation was performed on Matlab/Simulink platform. The results prove that the method can achieve fast and accurate optimization under complex environmental conditions, effectively reduce power oscillations, enhance system stability, and achieve better control results.

An improved MPPT control strategy based on incremental conductance method

Photovoltaic cells efficiency can be effectively improved by maximum power point tracking (MPPT) technology. An improved MPPT control strategy is proposed to solve the current problems of poor convergence speed and accuracy of incremental conductance method. In this method, the P–U characteristic curve is divided into three sections: non-MPP sections, MPP-like section and MPP sections. In the non-MPP section, the constant voltage method is adopted to reduce the tracking time. In the MPP-like section, the incremental conductance method is adopted and its step size is improved, which effectively reduces the tracking time. In MPP section, particle swarm algorithm is adopted to improve tracking accuracy. Taking light intensity and temperature variation as examples, the proposed method and the traditional method are simulated respectively. Simulation results show that compared with the constant voltage method, the accuracy can be improved by more than 4% when the temperature or light intensity is changed, while maintaining the tracking speed. Compared with the traditional incremental conductivity method, the method can reduce the tracking time by 33% and improve the tracking accuracy by 1% when the light intensity or temperature changes.

Comparative study of new MPPT control approaches for a photovoltaic system

<p>The output characteristics of the photovoltaic (PV) installation normally depend on solar radiation and ambient temperature, the charge impedance, its maximum power point (MPP) is not constant. In each state of the PV module has a point where it can produce its MPP. Therefore, MPPT (Maximum Power Point Tracking) methods can be used to keep the photovoltaic panel running on its MPP. In this article, the objective was to determine how the different maximum point power monitoring (MPPT) techniques applied to PV systems work. Therefore, two MPPT algorithms are presented and compared under different temperature and radiation conditions: MRAC methods and sliding mode controller combined with the Incremental Conductivity (IC) algorithm. These algorithms are widely used in PV systems because of their easy implementation and low cost. These techniques were analyzed and their performance evaluated using the PSIM software under different types of solar radiation and temperature.</p>

Highly graphitized 3D network carbon for shape-stabilized composite PCMs with superior thermal energy harvesting

One major barrier obstructing their scale engineered adoption of phase change materials (PCMs), currently, is their low thermal conductivity, which drastically constrains the power capacity. Our target is to enhance the PCMs thermal conductivity without evidently altering other thermal property criteria. Herein, we propose a facile, low-cost and controllable strategy to construct compactly interconnected 3D celosia-like highly graphitized thermally conductive network carbon via carbon quantum dots (CQDs) deriving from acetone and divinyl benzene (DVB). Novel function of CQDs is firstly developed for superior thermal energy harvesting, thus expanding their conventional fluorescence and catalysis field to novel thermal energy storage. Importantly, our constructed 3D graphitized network carbon better infiltrates macromolecule polyethylene glycol (PEG) and fully releases crystallization via controllable crosslinking reaction. This strategy simultaneously integrates sufficient power capacity and incremental thermal conductivity (enhanced by 236%) of the PCMs, and thermal enthalpy is considerably approaching the theoretical value. Alternatively, the composite PCMs are thermally and durably stable. These results indicate that resulting shape-stabilized PCMs are a very promising candidate for renewable thermal energy storage in virtue of the superior comprehensive properties.

Stability and thermal analysis of MWCNT-thermal oil-based nanofluids

Carbon nanotubes (CNTs) have gained much attention due to excellent thermal properties. Numerous studies have reported the incremental thermal conductivity of CNT-based nanofluids. However, limited studies are available on the complete thermal and viscous transport effects in oil-based nanofluids. Multi-wall carbon nanotubes (MWCNTs)-thermal oil-based nanofluids are prepared using two-step method. The high stability is achieved using mechanical mixing technique (ultrasonication) only. Surfactant-free nanofluids are prepared in various concentrations of 0–1wt.%. Dispersion behaviour of nanofluids is investigated to ensure high stability of nanofluids using different characterizations. The effective thermophysical properties such as density, viscosity, thermal conductivity, and specific heat capacity are experimentally investigated at different temperature ranges and nanoparticle concentrations. The experimental findings of the present work are compared with the theoretical models and good agreement is observed for effective density of nanofluids. However, other thermophysical properties show a significant deviation with the conventional models. The coefficient of thermal expansion is calculated for oil-based nanofluids. Correlations are developed for thermophysical properties of nanofluids. Thermogravimetric analysis (TGA) is carried out to understand the effect of nanotubes on the life-cycle and the degradation temperature of thermal oil.

The Dual-Mode Maximum Power Point Tracking Control Method Based on Improved Variable Step Size

In the entire PV system, the maximum power point tracking (MPPT) has become an important part of the essential, the maximum power point tracking can improve the output power of photovoltaic power generation system as to improve the overall system power. Constant Voltage Tracking (CVT), Perturbation and Observation (P&O), incremental Conductivity, Short circuit control, Hysteresis comparing are the most commonly used methods. Due to a variety of methods have their advantages and disadvantages to each other, to improve efficiency, control accuracy, speed up the response, this paper, put up a program based on reforming the progress in dual-mode maximum power point tracking and this program can be faster and more accurate to find the maximum power point in the current environment, also reduce the oscillation near the maximum power point and improve the efficiency of solar photovoltaic grid-connected system.

Counterion condensation and ionic conductivity

The occurrence of counterion condensation is demonstrated through measurements of the incremental ionic conductivity of pH buffered Na polyacrylate solutions. pH values were selected to allow variation of the charge density parameter ξ in the range between 0.4 and 2.8, that is, across ξ=1, the theoretical critical level for counterion condensation. The results show two regions where the incremental conductivity, ΔσP, varies differently with ξ. For ξ<1.3, ΔσP remains relatively constant. A sharp drop in ΔσP is observed between ξ=1.3 and ξ=1.7 corresponding to the onset of counterion condensation. It is suggested that this discontinuity reflects a drastic change in the polyion mobility caused by a structural rearrangement of the macromolecule. For ξ≳1.7, ΔσP decreases with approximately constant slope. This latter behavior agrees qualitatively but not quantitatively with the prediction of the counterion condensation model.

High-field microwave incremental conductivity characteriristics of cadmium sulphide at 77 K

High-field microwave incremental conductivity characteriristics of cadmium sulphide at 77 K

1/F Optimization For A Complementary Metal Oxide Semiconductor Focal Plane Array Input Circuit

In electro-optical detector systems, the noise characteristics of transresistance amplifiers are sensitive to the incremental conductivity of the photovoltaic detector. In this paper we show that the 1/f noise corner frequency contributed to the noise by the amplifier is a function of the bias applied to the detector. The 1/f noise corner frequency of the diode in cooled focal plane arrays is also a function of the reverse bias, but there is an optimum reverse bias that is not 0 V. This fact becomes important when it is necessary to use complementary metal oxide semiconductor amplifiers that have lame 1/f noise corner frequencies.

High-field microwave incremental conductivity of cadmium selenide at 77 K

The microwave conductivity of cadmium selenide has been calculated at 77 K assuming a displaced Maxwellian energy distribution function for the electrons. It is found that the microwave conductivity decreases monotonically with the applied electric field and has a lower value for higher impurity concentration. The frequency dependence of the microwave conductivity shows that it is substantially constant up to the millimeter wavelength range of frequencies.

High‐field microwave incremental conductivity of PbS at 77 K

High‐field microwave incremental conductivity of PbS at 77 K

High-field miceowave incremental conductivity of zinc-oxide

High-field miceowave incremental conductivity of zinc-oxide

Ion Migration and Frequency-Dependent Dielectric Loss

Abstract The frequency-dependent dielectric loss due to ion migration in a solvent with a given dielectric function ∊(ω) is calculated explicitIy within the following framework: i) The solvent is treated in the dielectric continuum model ii) The Navier-Stokes equation is solved for the velocity field iii) The limiting cases of (a) large ion radius (weak coupling) and (b) point ions (strong coupling) are treated explicitly. The most clearcut prediction of the theory is that the incremental frequency-dependent conductivity is proportional to ω¼ at high frequencies, the power law being independent of the form of ∊(ω). For arbitrary frequencies, in the limits (a) and (b) above, the incremental frequency-dependent conductivity can be calculated explicitly given the dielectric function of the solvent.

Hot electron microwave incremental conductivity of n-InSb at 77°K in the presence of impurity scattering

Hot electron microwave incremental conductivity of n-InSb at 77°K in the presence of ionized impurity scattering has been calculated using a displaced Maxwellian distribution function. Theoretical results are found to be in agreement with experiments for high impurity concentration but significant discrepancy remains for lower concentration.

Hot-electron microwave incremental conductivity of n type InSb

The contribution to the hot-electron microwaver incremental conductivity of n type InSb arising from the higher-order terms in the displaced Maxwellian distribution function (neglected in the earlier analysis) has been estimated using a computer. It is found that the contribution, though significant, is not enough to explain the disagreement between theory and experiment.