Volume 16, Issue 1 -

Under the case of ill-conditioning system, this paper is concerned with the AC/DC power flow calculation. The improved Levenberg–Marquardt (ILM) method with adaptive damping factor selection is applied to solve the AC/DC power flow problem. The main purpose of this paper is as follows: one is to provide comparison reference between Newton method, classical LM method (CLM) and ILM method under the well-conditioning system; the other is to research what is the maximal load withstood by power system, under the case of ill-conditioning. Finally, those methods are tested on the 22-bus, the IEEE 118-bus AC/DC system, respectively. Numerical results indicate that the ILM method has the advantage of fast convergent speed. When expanding loads in a certain extent, ILM method can at least find least square solutions, whereas Newton method and CLM method would divergent, and the convergent property of Newton method can be improved by taking some measurements using the information of a least square solution obtained by ILM method.

Generally, the characteristics of photovoltaic (PV) array are largely affected by solar temperature, solar irradiance, shading patterns, array configuration and location of shading modules. Partial shading is due to moving clouds and shadows of nearby obstacles and can cause a significant degradation in the output of PV system. Hence, the characteristics of PV array get more multifaceted with multiple peaks. The ultimate aim of the paper is to analyze the performance of PV module during such adverse condition based on simplified two-diode model. To reduce the computational time, the simplified two-diode model has a photocurrent source in parallel with two ideal diodes. Only four parameters are required to be calculated from datasheet in order to simulate the model. Moreover, the performance of PV array is evaluated at different shaded patterns and it is found that the model has less computational time and gives accurate results.

In this paper, a zigzag connected autotransformer-based 24-pulse AC-DC converter is designed, modeled and simulated to feed direct torque controlled induction motor drives. Winding arrangements and parameters of the autotransformer and interphase reactor are given. Moreover, the design procedure of the autotransformer is modified to make it suitable for retrofit applications. Simulation results indicate that the system is capable of eliminating up to 21st harmonics in the ac mains current. The effect of load variation and load character is also studied to demonstrate the performance and effectiveness of the proposed 24-pulse converters. A set of power quality indices at ac mains and dc side are presented to compare the performance of 6-, 12- and 24-pulse converters.

Underfrequency load shedding (UFLS) is a common practice to protect a power system during large generation deficit. The adaptive UFLS schemes proposed in the literature have the drawbacks such as requirement of transmission of local frequency measurements to a central location and knowledge of system parameters, such as inertia constant H and load damping constant D . In this paper, a UFLS scheme that uses only the local frequency measurements is proposed. The proposed method does not require prior knowledge of H and D . The scheme is developed for power systems with and without spinning reserve. The proposed scheme requires frequency measurements free from the oscillations at the swing mode frequencies. Use of an elliptic low pass filter to remove these oscillations is proposed. The scheme is tested on a 2 generator system and the 10 generator New England system. Performance of the scheme with power system stabilizer is also studied.

This paper proposes a synchrophasors-assisted intelligent relaying scheme for transmission lines compensated by Unified Power Flow Controller (UPFC). The algorithm uses a new relaying signal termed as imaginary part of integrated impedance (IPII). The synchronized phasor measurements at both ends of the transmission line are used to extract voltage and current phasors from instantaneous voltage and current signals. The voltage and current phasors are utilized to derive IPII of each phase. Further, IPII of each phase is used as input to a data-mining model termed as decision tree (DT) which provides the final relaying decision. The proposed algorithm is validated on real-time digital simulator (RTDS) platform, and the results obtained indicate that the proposed scheme is both dependable and secure in protecting transmission system compensated by UPFC.

Due to the concerns of global warming and the depletion of energy resources, renewable energies such as wind generation (WG) and photovoltaic generation (PV) are gaining attention in distribution systems. Efficient electric equipment such as heat pumps (HP) not only contribute low levels of carbon to society, but are also beneficial for consumers. In addition, gas instruments such as the gas engine (GE) and fuel cells (FC) are expected to reduce electricity cost by exhaust heat. Thus, it is important to clarify which systems (HP or GE) are more beneficial for consumers throughout the year. This paper compares the operational cost for the smart house between using the HP and the GE. Current electricity and gas prices are used to calculate the cost of the smart house. The system considered in this research comprises a PV, battery, solar collector (SC), uncontrolled load and either an HP or a GE. In order to verify the effectiveness of the proposed system, MATLAB is used for simulations.

In the research of complicated electrical engineering, the emergence of phasor measurement units (PMU) is a landmark event. The establishment and application of wide area measurement system (WAMS) in power system has made widespread and profound influence on the safe and stable operation of complicated power system. In this paper, taking full advantage of wide area synchronous phasor measurement information provided by PMUs, we have carried out precise fault localization based on the principles of maximum posteriori probability (MAP). Large numbers of simulation experiments have confirmed that the results of MAP fault localization are accurate and reliable. Even if there are interferences from white Gaussian stochastic noise, the results from MAP classification are also identical to the actual real situation.