Method for determining customer contribution to harmonic variations in a large power network
A method for identifying the source of harmonic emission and for determining its contribution to the harmonic distortion at different points on a large power supply grid is presented in this paper. The proposed method is based on vector analysis of the harmonic currents, measured synchronously at multiple points on the electrical grid. This approach allows real time locating of the responsible customer (harmonic cause) for a given harmonic current disturbance and determining its contribution to the harmonic voltage and current variations at all measured points (harmonic effect). A physical model, representing a power network supplying three non-linear loads, has been used to illustrate the performances of this method. The presented method can be used to analyze the harmonic current and voltage variations in a large power network in real time, thus assisting the electrical power utility to rapidly identify the harmonic causes and their effect and to better understand different problems associated with the harmonics.
Complex blind source separation based harmonic contribution assessment
Harmonic contribution assessment is the precondition of harmonic responsibility-sharing and mitigating and its difficulty lies in real-time assessment of harmonic impedance. In order to solve this problem, this paper proposed a complex blind source separation (CBSS) based harmonic contribution assessment method. Use linear filter to abstract fast changing components from measuring data at the point of common coupling (PCC) and establish a CBSS based harmonic contribution assessment model; use complex maximization of non-Gaussianity (CMN) to assess demixing matrix, impedance matrix, and harmonic sources and the process of harmonic contribution assessment is studied in detail on this basis. The proposed method is validated by simulation, comparing with current methods, and the results prove that the proposed method can separate harmonic contribution directly with measuring data and it is suitable for resonance and non-resonance cases.
Influence of filler addition, storage medium and evaluation time on biaxial flexure strength and modulus of adhesive systems
Abstract Objective. This study evaluated the effects of filler addition, storage medium and time on biaxial flexural strength and flexural modulus of six adhesive systems. Materials and methods. The adhesives were either unfilled resins: Single Bond, Prime&Bond 2.1 and One-Step; or filled resins: Single Bond Plus, Prime&Bond NT and One-Step Plus. Resin discs of each product (0.5 mm thick × 6.0 mm diameter) were prepared using silicon molds (n = 10). The discs were stored dry, in water, mineral oil or ethanol for 1 week or 3 months before biaxial flexural testing. Data were statistically analyzed by 3-way ANOVA and Tukey's post-hoc test (α = 0.05). The specimens were tested in a universal testing machine at 1.27 mm/min until failure occurred. Results. In general, the storage in ethanol led to significantly lower flexural strength and flexural modulus values than the other storage conditions for all adhesives in both storage periods. Filler addition increased flexural strength and flexural modulus for Prime&Bond NT, when it was stored dry or in water for 1 week. For Single Bond Plus, the filler addition resulted in higher flexural modulus, when it was stored for 1 week in oil and in ethanol. No significant differences in flexural modulus were observed between One-Step and One-Step Plus in any storage medium. Conclusions. Results suggested that filler addition does not necessarily have to increase the flexural strength and flexural modulus. Ethanol and oil storages tended to yield opposite effects.