Ranking of Prospective New Generation Location for a Power Network in a Deregulated System

In developing countries high rate of growth in demand of electric energy is felt, and so the addition of new generating units becomes necessary. In deregulated power systems private generating stations are encouraged to add new generations. Finding the appropriate location of new generator to be installed can be obtained by running repeated power flows, carrying system studies like analyzing the voltage profile, voltage stability, loss analysis etc. In this paper a new methodology is proposed which will mainly consider the existing network topology into account. A concept of T-index is introduced in this paper, which considers the electrical distances between generator and load nodes.This index is used for ranking significant new generation expansion locations and also indicates the amount of permissible generations that can be installed at these new locations. This concept facilitates for the medium and long term planning of power generation expansions within the available transmission corridors. Studies carried out on a sample 7-bus system, EHV equivalent 24-bus system and IEEE 39 bus system are presented for illustration purpose.

Protection of a Static Frequency Converter fed traction network, a case study

Aurizon, Australia's largest rail freight operator, is introducing the Static Frequency Converter (SFC) technology into its electric railway network as part of the Bauhinia Electrification Project. The introduction of SFCs has significant implications on the protection systems of the 50kV traction network. The traditional distance protection calculation method does not work in this configuration because of the effect that the SFC in combination with the remote grid has on the apparent impedance, and was substantially reviewed. The standard overcurrent (OC) protection scheme is not suitable due to the minimum fault level being below the maximum load level and was revised to incorporate directionality and under-voltage inhibit. Delta protection was reviewed to improve sensitivity. A new protection function was introduced to prevent back-feeding faults in the transmission network through the grid connection. Protection inter-tripping was included to ensure selectivity between the SFC protection and the system downstream.

Localisation of discrete change in a transformer winding: a network-function-loci approach

An entirely different approach for localisation of winding deformation based on terminal measurements is presented. Within the context of this study, winding deformation means, a discrete and specific change externally imposed at a particular position on the winding. The proposed method is based on pre-computing and plotting the complex network-function loci e.g. driving-point impedance (DPI)] at a selected frequency, for a meaningful range of values for each element (increasing and decreasing) of the ladder network which represents the winding. This loci diagram is called the nomogram. After introducing a discrete change, amplitude and phase of DPI are measured. By plotting this single measurement on the nomogram, it is possible to estimate the location and identify the extent of change. In contrast to the existing approach, the proposed method is fast, non-iterative and yields reasonably good localisation. Experimental results for actual transformer windings (interleaved and continuous disc) are presented.

Application of UPFC for system security improvement under normal and network contingencies

Electric power systems are exposed to various contingencies. Network contingencies often contribute to over-loading of network branches, unsatisfactory voltages and also leading to problems of stability/voltage collapse. To maintain security of the systems, it is desirable to estimate the effect of contingencies and plan suitable measures to improve system security/stability. This paper presents an approach for selection of unified power flow controller (UPFC) suitable locations considering normal and network contingencies after evaluating the degree of severity of the contingencies. The ranking is evaluated using composite criteria based fuzzy logic for eliminating masking effect. The fuzzy approach, in addition to real power loadings and bus voltage violations, voltage stability indices at the load buses also used as the post-contingent quantities to evaluate the network contingency ranking. The selection of UPFC suitable locations uses the criteria on the basis of improved system security/stability. The proposed approach for selection of UPFC suitable locations has been tested under simulated conditions on a few power systems and the results for a 24-node real-life equivalent EHV power network and 39-node New England (modified) test system are presented for illustration purposes.

Identification of prospective locations for generation expansion with least augmentation of network

With ever increasing demand for electric energy, additional generation and associated transmission facilities has to be planned and executed. In order to augment existing transmission facilities, proper planning and selective decisions are to be made whereas keeping in mind the interests of several parties who are directly or indirectly involved. Common trend is to plan optimal generation expansion over the planning period in order to meet the projected demand with minimum cost capacity addition along with a pre-specified reliability margin. Generation expansion at certain locations need new transmission network which involves serious problems such as getting right of way, environmental clearance etc. In this study, an approach to the citing of additional generation facilities in a given system with minimum or no expansion in the transmission facility is attempted using the network connectivity and the concept of electrical distance for projected load demand. The proposed approach is suitable for large interconnected systems with multiple utilities. Sample illustration on real life system is presented in order to show how this approach improves the overall performance on the operation of the system with specified performance parameters.

Ultrasonic Guided Wave Sensor Network Optimization for Monitoring Rivet Line

Guided waves using piezo-electric wafer active sensors (PWAS) is one of the useful techniques of damage detection. Sensor network optimization with minimal network hardware footprint and maximal area of coverage remains a challenging problem. PWAS sensors are placed at discrete locations in order to inspect damages in plates and the idea has the potential to be extended to assembled structures. Various actuator-sensor configurations are possible within the network in order to identify and locate damages. In this paper we present a correlation based approach to monitor cracks emanating from rivet line using a simulated guided wave signal whose sensor is operating in pulse echo mode. Discussions regarding the identification of phase change due to reflections from the crack are also discussed in this paper.

Enhanced Operation of Electricity Distribution Grids Through Smart Metering PLC Network Monitoring, Analysis and Grid Conditioning

Low Voltage (LV) electricity distribution grid operations can be improved through a combination of new smart metering systems' capabilities based on real time Power Line Communications (PLC) and LV grid topology mapping. This paper presents two novel contributions. The first one is a new methodology developed for smart metering PLC network monitoring and analysis. It can be used to obtain relevant information from the grid, thus adding value to existing smart metering deployments and facilitating utility operational activities. A second contribution describes grid conditioning used to obtain LV feeder and phase identification of all connected smart electric meters. Real time availability of such information may help utilities with grid planning, fault location and a more accurate point of supply management.

Extracted Memory from Temporal Patterns Using Adaptive Resonance and Recurrent Network

We can recognize objects through receiving continuously huge temporal information including redundancy and noise, and can memorize them. This paper proposes a neural network model which extracts pre-recognized patterns from temporally sequential patterns which include redundancy, and memorizes the patterns temporarily. This model consists of an adaptive resonance system and a recurrent time-delay network. The extraction is executed by the matching mechanism of the adaptive resonance system, and the temporal information is processed and stored by the recurrent network. Simple simulations are examined to exemplify the property of extraction.

Addressing non-linear hardware limitations and extending network coverage area for power aware wireless sensor networks

Science Foundation Ireland (07/CE/11147); Irish Research Council for Science Engineering and Technology (Embark Initiative)

Time dependent electric, magnetic and hydrodynamic interaction in aluminium electrolysis cells

The waves in commercial cells for electrolytic aluminium production originate at the interface between the liquid aluminium and electrolyte, but their effect can spread into the surrounding busbar network as electric current perturbation, and the total magnetic field acquires a time dependent component. The presented model for the wave development accounts for the nonuniform electric current distribution at the cathode and the whole network of the surrounding busbars. The magnetic field is computed for the continuous current in the fluid zones, all busbars and the ferromagnetic construction elements. When the electric current and the associated magnetic field are computed according to the actual electrical circuit and updated for all times, the instability growth rate is significantly affected. The presented numerical model for the wave and electromagnetic interaction demonstrates how different physical coupling factors are affecting the wave development in the electrolysis cells. These small amplitude self-sustained interface oscillations are damped in the presence of intense turbulent viscosity created by the horizontal circulation velocity field. Additionally, the horizontal circulation vortices create a pressure gradient contributing to the deformation of the interface. Instructive examples for the 500 kA demonstration cell are presented.

Impact of weather conditions on electric vehicle performance

Seasonal and day-to-day variations in travel behaviour and performance of private passenger vehicles can be partially explained by changes in weather conditions. Likewise, in the electricity sector, weather affects energy demand. The impact of weather conditions on private passenger vehicle performance, usership statistics and travel behaviour has been studied for conventional, internal combustion engine, vehicles. Similarly, weather-driven variability in electricity demand and generation has been investigated widely. The aim of these analyses in both sectors is to improve energy efficiency, reduce consumption in peak hours and reduce greenhouse gas emissions. However, the potential effects of seasonal weather variations on electric vehicle usage have not yet been investigated. In Ireland the government has set a target requiring 10% of all vehicles in the transport fleet to be powered by electricity by 2020 to meet part of its European Union obligations to reduce greenhouse gas emissions and increase energy efficiency. This paper fills this knowledge gap by compiling some of the published information available for internal combustion engine vehicles and applying the lessons learned and results to electric vehicles with an analysis of historical weather data in Ireland and electricity market data in a number of what-if scenarios. Areas particularly impacted by weather conditions are battery performance, energy consumption and choice of transportation mode by private individuals.

Electric Vehicles - a well to wheel analysis

The European Union has set a target for 10% renewable energy in transport by 2020, which will be met using both biofuels and electric vehicles. In the case of biofuels, for the purposes of meeting the target, the biofuel must achieve greenhouse gas savings of 35% relative to the fossil fuel replaced. For biofuels, greenhouse gas savings can be calculated using life cycle analysis, or the European Union default values. In contrast, all electricity used in transport is considered to be the same, regardless of the source or the type of electric vehicle. However, the choice of the electric vehicle and electricity source will have a major impact on the greenhouse gas savings. This paper examines different electric-vehicle scenarios in terms of greenhouse gas savings, using a well-to-wheel life cycle analysis.

A study of the 10% electric vehicles target of the single electricity market

In late 2008, the Government of the Republic of Ireland set a specific target that 10% of all vehicles in its transport fleet be powered by electricity by 2020 in order to meet European Union renewable energy targets and greenhouse gas emissions reduction targets. International there are similar targets. This is a considerable challenge as in 2009, transport accounted for 29% of non-emissions trading scheme greenhouse gas emissions, 32% of energy-related greenhouse gas emissions, 21% of total greenhouse gas emissions and approximately 50% of energy-related non-emission trading scheme greenhouse gas emissions. In this paper the impacts of 10% electric vehicle charging on the single wholesale electricity market for the Republic of Ireland and Northern Ireland is examined. The energy consumed and the total carbon dioxide emissions generated under different charging scenarios is quantified and the results of the charging scenarios are compared to identify the best implementation strategy.

Trajectory Control of Electro Hydraulic Excavator using Fuzzy Self Tuning Algorithm with Neural Network

This paper presents the trajectory control of a 2DOF mini electro-hydraulic excavator by using fuzzy self tuning with neural network algorithm. First, the mathematical model is derived for the 2DOF mini electro-hydraulic excavator. The fuzzy PID and fuzzy self tuning with neural network are designed for circle trajectory following. Its two links are driven by an electric motor controlled pump system. The experimental results demonstrated that the proposed controllers have better control performance than the conventional controller.

Day-Ahead Optimal Charging/Discharging Scheduling for Electric Vehicles in Micro-Grids

A micro-grid is an autonomous system which can be operated and connected to an external system or isolated with the help of energy storage systems (ESSs). While the daily output of distributed generators (DGs) strongly depends on the temporal distribution of natural resources such as wind and solar, unregulated electric vehicle (EV) charging demand will deteriorate the imbalance between the daily load and generation curves. In this paper, a statistical model is presented to describe daily EV charging/discharging behaviour. An optimisation problem is proposed to obtain economic operation for the micro-grid based on this model. In day-ahead scheduling, with estimated information of power generation and load demand, optimal charging/discharging of EVs during 24 hours is obtained. A series of numerical optimization solutions in different scenarios is achieved by serial quadratic programming. The results show that optimal charging/discharging of EVs, a daily load curve can better track the generation curve and the network loss and required ESS capacity are both decreased. The paper also demonstrates cost benefits for EVs and operators.