Wavelet transforms : practical applications in power systems.

An application of wavelet analysis to power system transient generated signals is presented in this paper. With the time-frequency localisation characteristics embedded in wavelets, the time and frequency information of a waveform can be presented as a visualised scheme. This feature is very important for non-stationary signals analysis such as the ones generated from power system disturbances. Unlike the Fourier transform, the wavelet transform approach is more efficient in monitoring fault signals as time varies. For time intervals where the function changes rapidly, this method can zoom in on the area of interest for better visualisation of signal characteristic

Teaching power system analysis courses using MATPOWER

One of the major constraints faced in the teaching of power system analysis courses has been non-availability of practical power system for demonstration. This paper focuses on a new and efficient method to the teaching of power system analysis courses to the upper-division undergraduate students. The intent is to present MATPOWER to students as a good instructional tool to complement the teaching of power system analysis courses in the class. This would certainly facilitate the teaching and understanding of the subject matter better. The features and the relative merits which make the package preferred to some of the commercially available software packages, in certain applications, are highlighted in the paper. With self study in mind, the paper is written to simplify the daunting task of carrying out power flow analyses especially on large power networks. One illustrative example is examined in the paper. The power flow solution by the Newton-Raphson method is demonstrated using the conventional approach prior to solving it using the MATPOWER package. The result obtained using the package is guaranteed to be accurate and reasonably fast

Distributed energy resources and benefits to the environment

The recently released report of the International Energy Outlook (IEO2009) projects an increase of 44% in the world energy demand from 2006 to 2030, and 77% rise in the net electricity generation worldwide in the same period. However, threatening in the said report is that 80% of the total generation in 2030 would be produced from fossil fuels. This global dependence on fossil fuels is dangerous to our environment in terms of their emissions unless specific policies and measures are put in place. Nevertheless, recent research reveals that a reduction in the emissions of these gases is possible with widespread adoption of distributed generation (DG) technologies that feed on renewable energy sources, in the generation of electric power. This paper gives a detailed overview of distributed energy resources technologies, and also discusses the devastating impacts of the conventional power plants feeding on fossil fuels to our environment. The study finally justifies how DG technologies could substantially reduce greenhouse gas emissions when fully adopted; hence, reducing the public concerns over human health risks caused by the conventional method of electricity generation

Generation expansion planning in electricity market considering uncertainty in load demand and presence of strategic GENCOs

This paper presents a new framework to study the generation capacity expansion in a multi-stage horizon in the presence of strategic generation companies (GENCOs). The proposed three-level model is a pool-based network-constrained electricity market that is presented under uncertainty in the predicted load demand modeled by the discrete Markov model. The first level includes decisions related to investment aimed to maximize the total profit of all GENCOs in the planning horizon, while the second level entails decisions related to investment aimed at maximizing the total profit of each GENCO. The third level consists of maximizing social welfare where the power market is cleared. The three-level optimization problem is converted to a one-level problem through an auxiliary mixed integer linear programming (MILP) using primal–dual transformation and Karush–Kuhn–Tucker (KKT) conditions. The efficiency of the proposed framework is examined on MAZANDARAN regional electric company (MREC) transmission network – a part of the Iranian interconnected power system. Simulation results confirm that the proposed framework could be a useful tool for analyzing the behaviour of investment in electricity markets in the presence of strategic GENCOs

INTELLIGENT TECHNIQUE FOR ELECTRICITY THEFT IDENTIFICATION USING AUTOREGRESSIVE MODEL

Various studies have investigated electricity theft, an illegally act, perpetrated to the detriment of the electricity power providers, however, less attention has been given to identification of the types of electricity theft. Data were acquired from the Consumer Load Prototype developed at two different levels using Sensor-A connected to the Pole Terminal Unit and Sensor-B connected to the Consumer Terminal Unit. The output of the sensors were connected to BNC-2110 device and linked to the PCI 6420E channel, which log the data in the computer for further analysis. LABVIEW (2012) software was programmed to acquires data at a sampling frequency of 500Hz and decimated at 10s interval before logging into the computer hard disk. The feature extraction of the data acquired was achieved using autoregressive technique and model order selectionwas based on minimum description length. The model coefficient AR (20), data acquired and predicted data were used for theft identification. Meter-bypassing theft was identified when the energy consumption from sensor A and sensor B are different, however sensor B reads zero value and there are disparities in the model coefficients. Illegal connection before the meter theft was identified whenever there is difference in energy consumption as evaluated form sensor A and sensor B and there is no zero value recorded from sensor B, while Meter tampering was detected when the energy consumption as evaluated form sensor A and sensor B are different and there are no disparities in the model coefficients

Critical lines identification for ATC assessment in power system planning

Ability to evaluate the accurate available transfer capability (ATC) has important impact on the trade of energy in power marketing. The impact of the transmission element status of transmission path has a possibility to severely change the statistics of the ATC. The impact of the line outage is more significant among the other component outages. The ATC assessment requires N-1 security assessment under line outages scenarios. Moreover, an efficient contingency ranking method to determine critical lines has significant impact on the ATC computational time. In this paper, MW loss, MVAR loss and Load Margin Index are described to find the critical lines for computing the ATC under contingencies. These methods are tested on IEEE 118 bus system and the ATC based on Krylov algebraic method are calculated for each critical line. Based on ATC results calculated from these contingency ranking methods, the efficiency of these methods compare together

A critical review of strategies for optimal allocation of Distributed Generations units in Electrical Power Systems

Recent research has shown that installation of distributed generation (DG) units in the utility’s distribution system of a power network would lead to attainment of numerous potential benefits. To maximise these benefits, it is crucial to find the optimal number or size of DG units and their appropriate locations in power distribution systems, since siting DG units in improper locations could jeopardise the system operation. However, the task to determine the optimal size and sites of DG sources in power systems is not an easy one, due to a number of factors. In tackling this problem, many approaches have been proposed by various researchers in recent years. This paper presents a critical review of different methodologies employed in solving this optimisation problem. For ease of reference, and to facilitate understanding, this literature categorises and discusses the various existing approaches into five different major headings. They are: the analytical approaches, the meta-heuristics, the genetic algorithms (GAs) approach, the GA-hybrids, and finally those that are categorised as other approaches. The benefits, as well as the drawbacks of each approach are thoroughly examined in the paper

Experiment on Power Quality of PV-grid System at FKEE UMP

This paper presents experiments of PV-grid system operation for a day light consisting of Photovoltaic (PV) – Inverter system as the renewable source connected to a network of induction motor as the load. A small-scale laboratory consists of Photovoltaic, Inverter, and loads system was setup. One power supplies from PV and grid were connected to single phase induction motors. In the experiment, both energy supplies from the grid and photovoltaic system were connected to the loads. Measurements have been done at both side of power transformer to analyze power quality in the system

Contingency evaluation for voltage security assessment of power systems

The demand for electricity is expected to continue to increase given the recent world population projection of about 30% increase in the next three decades. Consequently power systems are equally expected to be more heavily loaded than before. Unfortunately the environmental and economic constraints restrict the expansion of the existing power system facilities. This scenario requires a constant attention since it could result to voltage collapse which could in turn lead to a total blackout. This paper presents the procedure required to carry out a contingency assessment and ranking of the load buses and lines of power systems for voltage security. This would ensure that power systems are operated above a desired voltage stability margin to forestall voltage collapse. The impact of single line outage contingency on the static voltage stability margin, as well as the available transfer capability across the areas of the test system, are examined in the paper

Effective method for optimal allocation of distributed generation units in meshed electric power systems

Improper placement of distributed generation (DG) units in power systems would not only lead to an increased power loss, but could also jeopardise the system operation. To avert these scenarios and tackle this optimisation problem, this study proposes an effective method to guide electric utility distribution companies (DISCOs) in determining the optimal size and best locations of DG sources on their power systems. The approach, taking into account the system constraints, maximises the system loading margin as well as the profit of the DISCO over the planning period. These objective functions are fuzzified into a single multi-objective function, and subsequently solved using genetic algorithm (GA). In the GA, a fuzzy controller is used to dynamically adjust the crossover and mutation rates to maintain the proper population diversity (PD) during GA's operation. This effectively overcomes the premature convergence problem of the simple genetic algorithm (SGA). The results obtained on IEEE 6-bus and 30-bus test systems with the proposed method are evaluated with the simulation results of the classical grid search algorithm, which confirm its robustness and accuracy. This study also demonstrates DG's economic viability relative to upgrading substation and feeder facilities, when the incremental cost of serving additional load is considered