Volume 18, Issue 5 -

Phasor measurement unit (PMU) is a GPS-based monitoring equipment employed for the improvement of the stability and reliability of the electrical grid. In this work, an optimal PMU placement has been considered to utilize the least number of units in order to make the power network fully observable. Further, this article also suggests to not only determine the minimal number and optimal locations of PMUs but also installation of the maximum number of PMUs on the weakest bus in an electrical network. Thus, the weak bus based on line stability index utilizing load flow measurement is determined. Then a novel numerical methodology which depends upon binary integer linear programming, constrained by weak bus measurement is proposed in this paper. Also, the effect of a single PMU loss considering weak buses is shown. The developed approach has been conducted on standard IEEE -14, -118, -300 and New England 39- bus test systems. Finally, obtained results and comparison with different weak bus methodologies are shown and examined.

The power producers in Indian electricity market face risks pertaining to real time frequency deviation and spot price volatility. An increase in real time demand lowers the system frequency. This forces the producers to draw unscheduled interchange (UI) power by paying a penalty, known as availability based tariff (ABT). The paper proposes a novel framework for optimal portfolio strategy selection of a power producer using uncertainty of frequency deviation and spot electricity market. Mean variance portfolio theory is used to model the stochastic optimization problem. In Stage 1, the operational ABT uncertainty structure is modeled and optimization is performed to determine optimal portfolio allocation, considering spot market and bilateral contract as available trading options. In stage 2, optimal involvement of options to hedge the cost side risk of unscheduled power interchange (UPI) is studied. Spot price volatility is introduced during hedging analysis and mean absolute percentage error (MAPE) technique is used to forecast the spot price range. A stochastic pseudo inspired particle swarm optimization (PIPSO) technique is proposed for enhanced profit-risk tradeoff. The model reflects that, spot and option trading could offer high risk protection vis-à-vis bilateral contract and can predominantly help in managing frequency penalty risk.

In this paper, the lifting based second generation Wavelet Transform (SGWT) is implemented along with the widely used discrete Wavelet Transform (DWT) for the detection and localization of ten different types of power quality (PQ) disturbance signals. The SGWT provides the time domain interpretation which is an opposition to the frequency domain analysis of DWT. Further, the selected features are extracted from the detail coefficient of the variants of WT and given as inputs to the classifiers in order to characterize the signals. Moreover, a comparative assessment of the PQ signal carried out with different classifiers such as Support Vector Machine (SVM), Decision Tree (DT) and Random Forest (RF) have been presented along with aforementioned detection techniques. The RF is an ensemble decision tree and used for the classification of large number of data set. Hence, various single as well as combined power quality disturbance signals have been simulated in noisy and noise free environment in order to demonstrate the efficiency of the proposed techniques. Moreover, in order to represent in realistic environment, these proposed techniques are tested with both the single phase and tree phase signals captured from different transmission panels. Further, to aid this PQ disturbance detection, different types of real time fault signals are characterized with these aforementioned approaches.

This paper develops and suggests modified teaching-learning-based optimization to solve non-smooth non-convex combined heat and power economic dispatch (CHPED) problem. The valve-point loading and forbidden working regions of conventional thermal generator are taken into account. Modified teaching–learning-based optimization (MTLBO) introduces Gaussian random variables in the ‘Teacher phase’ and ‘Learner phase’ which perks up search efficiency and assurances a high probability of acquiring the global optimum without considerably impairing the convergence speed and the simplicity of the structure of teaching-learning-based optimization (TLBO). The efficacy of the suggested MTLBO technique has been confirmed on three test systems and 15 benchmark functions. Test results of the suggested technique have been matched up to those achieved by other evolutionary techniques. It has been observed from the comparison that the suggested MTLBO technique has the ability to endow with superior solution.

In response to mounting concerns regarding environmental problem and depletion of Energy Resources, the introduction of Renewable Energy Sources (RESs), has been advancing in recent years. The system frequency deviation is a serious problem for a RESs-integrated power system. In this paper, we propose a system frequency control method using the automated demand response (ADR) for an isolated power system with RESs. The ADR can automatically adjust the consumption power of appliances after receiving the DR signal. It is assumed that consumption power of controllable loads is automatically varied based on the electricity price information from the real-time pricing (RTP). This method improves the supply-demand balancing, and hence the system frequency control is achieved. Furthermore, the stability of controller is demonstrated by indicating the poles of the control system.

Rural electrification is often considered to be the backbone of the rural economy. In spite of launching of ambitious schemes to achieve 100% rural electrification, millions of people, particularly in rural areas are away from grid electricity and its benefits. Renewable energy sources (RES) coupled with pumped storage provides a technically viable solution for continuous power supply in remote areas. Therefore, this paper presents a solar-wind hybrid system with pumped storage generation unit to meet the basic load demands of domestic consumers, using Pico hydro turbine (PHT). A prototype of this system is developed in the laboratory and investigates its operational aspects. This scheme utilizes a PHT (300 W), usually employed in run-off river schemes, in domestic level application. The developed model is evaluated on sunny and cloudy day. It operates on a daily basis, storing the surplus energy from renewable sources by pumping water to an upper reservoir, and retrieve this energy through its PHT. Therefore, this system satisfies the basic load demands of domestic consumers who are away from access to the grid. The control and energy management of the proposed system is carried out using labVIEW.

Multicarrier pulse width modulation (MC-PWM) techniques such as Level-shifted PWM (LS-PWM) and Phase-shifted PWM (PS-PWM) are the popular methods to control the output voltage of Multilevel Inverters (MLIs). The advantage of LS-PWM techniques over PS-PWMs is that they produce better harmonic profile, but the un-equal power distribution problem of LS-PWMs imposes limitation to their usage in high power and medium voltage applications. For achieving the equal conduction periods and to evenly distribute the power among different cells, carrier rotation should be employed in LS-PWM. This paper proposes two rotation schemes introduced to LS-PWM for producing the collective benefit of equal power distribution from PS-PWM and better harmonic profile from LS-PWM. MATALB/Simulink has been used to create simulation models and the experimental validations are performed by a hardware setup using dSPACE-DS1104 R&D Controller board. Furthermore, experimental results of device conduction periods, conduction losses of individual cells, total harmonic distortions (THDs) and fundamental output voltages have been measured. The effectiveness of proposed methods are verified by comparing the obtained results with traditional MC-PWM techniques.

This paper proposes a methodology to improve the transient stability (TS) of a system with wind energy generators. Induction machines are used widely as generators in the wind power plants. As these induction machines also have the stability problem like other synchronous machines, it is very important to analyze the TS of a system including the wind power plants. In this paper, the simulations and analysis of TS of power system including the induction generators during the short circuit fault conditions are carried out. The effect of pitch angle control on the stability of power system is analyzed. From the simulation results, it can be observed that the pitch control system which prevents the excess wind speed has the significant effect on the TS enhancement of the system. It can also be observed that the controller gain and time constant values have considerable effect on the pitch control system.

Rolling element bearings faults may lead to fatal breakdown of machines. Therefore, it is significant to be study bearings diagnosis, and the vibration-based methods have received intensive study because vibration signals collected from bearings carry rich information on machine health conditions, and it is possible to obtain vitalcharacteristic information from the vibration signals through using signal processing techniques. This paper proposes a novel vibration-based diagnosis method about bearing faults, first, a new pattern recognition method is proposed to diagnose bearing faults through using the interval value of the spectral peak frequency in the frequency domain; second, vibration signals of different parts faults of the bearings will be processed by different algorithm for precisely extracting the fault characteristics; and third, in order to extract transient characteristics from a noisy signal, the filter need to be developed and to further improve the signal-to-noise ratio (SNR), band pass filter is designed based on the PSD of vibration signals in this paper. The vibration signals collected from rolling element bearings are used to demonstrate the performance of the proposed method, andthe results verify the effectiveness of the method in extracting fault characteristics and diagnosing faults of rolling element bearings.

Nowadays, ancillary services in electrical distribution networks (e.   g. voltage support and reactive power control), usually provided by capacitor banks, start to be performed by distributed generation units (DGs). In this way, several papers have been studying the use of DGs as reactive power providers, and the power electronic/market regulation involved in this new scenario. However, the authors commonly consider a full implementation of Smart Grid philosophy, i.   e., there are appropriate communications between DGs and distribution network operator (DNO)’s control centers, but it is not a close reality in many developing countries, due to high costs involved in their implementation. Therefore, this paper proposes a new method in order to use DGs as ancillary services providers in a short and medium-term (called in the literature Pre Smart Grid), in which there are not effective communications between DGs and control centers of DNOs. The proposed method uses a non-uniform DGs distribution, obtained from local atlas of wind, solar, hydraulic and biomass power. The methodology presented accurate results when compared with a PSO-based method, widely used to solve optimization problems, but needs a complete Smart Grid philosophy implementation to work.