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The power industry in many parts of the industrialized world faces major challenges over the next two decades to renew ageing networks, accommodate new generation, especially renewables, and make grid operation “smarter”. This requires increasing numbers of professionals, but in many places, the industry faces great losses in personnel and experience as senior engineers retire. As a consequence, the industry needs to recruit a new generation of well-qualified electrical engineering graduates. This paper describes one particular initiative to attract school leavers into engineering and electric power engineering in particular: the U.K.'s “Power Academy”. The main features of the scheme and its success to date are described along with the new challenges and various issues that remain to be addressed. These include the need for “engineering leadership” and career progression for technical specialists. It is argued that companies' continued investment in schemes like the Power Academy is essential to meet the challenges faced by the power industry and to ensure a healthy future supply of professional engineers.

In this paper an analytical method by which the transient stability of an induction machine is maintained regardless of the fault clearance times is introduced. The method can be applied in order to improve the transient stability of a large penetration of low-voltage (LV) connected microgeneration that can be directly interfaced by single-phase induction generators within domestic premises. The analysis investigates the effectiveness of using resistive-type superconducting fault current limiters (RSFCLs) as remedial measures to prevent the microgenerators from reaching their speed limits during remote faults, and hence improving their transient stability. This will prevent unnecessary disconnection of a large penetration of LV-connected microgeneration and thus avoiding the sudden appearance of hidden loads, and unbalanced voltage conditions. The minimum required value of a resistive element of RSFCL for mitigating the transient instability phenomena of LV-connected microgeneration based on the system and connected machine parameters is determined. The analytical method has been validated by conducting informative transient studies by using detailed models of a small microwind turbine with constant mechanical output interfaced directly within residential dwellings by a single-phase induction generator, a transient model of resistive superconducting fault current limiter (RSFCL), and a typical suburban distribution network with residential loads. All the models are developed in the time-domain PSCAD/EMTDC dynamic simulation.

The effect of a short circuit fault and a voltage sag fault on a distributed grid-connected solid oxide fuel cell (SOFC) is investigated in this paper. The fuel cell is modeled in Simulink and the performance is verified against experimental load testing data. Grid faults are simulated, and conclusions are drawn on the fuel cell response and the effects of the fault condition on internal fuel cell parameters.

Two tradeoffs in the effectiveness of automatic voltage regulators (AVRs) and power system stabilizers (PSSs) are investigated together for the first time. The first is the effect of a high-gain fast response AVR on decreasing power system oscillation stability as well as increasing transient stability, and vice versa. The second is that a PSS can reduce transient stability by overriding the voltage signal to the exciter as well as increasing oscillation stability, and vice versa. In essence, the actions of the AVR and PSS devices are dynamically interlinked. A novel Bode frequency response framework for dynamic analysis of AVR and PSS performance and tradeoffs is presented. Bode frequency response also assists with the determination of suitable generator locations for PSSs and the assessment of robustness under changing power system operating conditions.

A novel methodology is proposed for the customer security assessment with high penetration of wind power in modern distribution networks. The customer security is quantified through customer damage costs by operating wind farms without standing reserve, which causes an inadequate supply of power to meet loads at some operating conditions. Necessary reserve to mitigate intermittency of wind is quantified through shed load. The ability to estimate a network firm import capacity that can be replaced with a wind plant, which is operated with the necessary reserve, is an added advantage of the approach. Monte Carlo simulation is the prime tool of the assessment, which incorporates linear programming-based re-dispatching of generation and load shedding to eliminate constraint violations. Steady-state analysis is used for the assessment incorporating random contingencies, subsequent tripping, intermittency of wind power, and demand variations. A case study is presented considering a medium voltage island network that has a grid connection, and this is used to demonstrate the customer security assessment integrating uncertainty models and a formulation to extract the impact of intermittency.

This paper proposes an innovative way of making a decision to island (or synchronize) distributed generators when operating conditions of a distribution system are varied. Islanding decisions are made when a network undergoes disturbances. In this approach, there is a decision-making mechanism, which samples states of the network operating condition to either synchronize or island in an identified period of time. Decision making is achieved through extended sequential sampling, which manages generator states within specific time periods. The approach can minimize the duration of islanded operation and manage generators' re-connection to the grid. Use of the proposed mechanism and sampling approach offer benefits over conventional relays; incorrect operations due to errors in measurements are reduced because the operational actions are not based on a single decision sample, but instead rely on extended sequential sampling over a number of samples. A case study is investigated using the IEEE 30-bus test system and the results are presented for this new approach

Online diagnostics and online condition monitoring are important functions within the operation and maintenance of a power plant. When there is knowledge of the relationships between the raw data and the underlying phenomena within the plant item, typical intelligent system-based interpretation algorithms can be implemented. Increasingly, health data is captured without any underlying knowledge concerning the link between the data and their relationship to physical and electrical phenomena within the plant item. This leads to the requirement for dynamic and learning condition monitoring systems that are able to determine the expected and normal plant behavior over time. This paper describes how multi-agent system technology can be used as the underpinning platform for such condition monitoring systems. This is demonstrated through a prototype multi-agent anomaly detection system applied to a 2.5-MW diesel engine driven alternator system.

This paper describes a software-based toolset which aids the application and development of model-based reasoning systems for validation and diagnosis in power systems applications. The validation of the operation of power systems protection equipment using disturbance recorder data is used as an example throughout the paper.

Significant improvements have been taking place in the power and extent of the monitoring and control systems employed by electrical power utilities, with the result that strategic decisions are having to be made concerning the use of the increased data now available. The evolutionary changes being made to power systems are introducing increased expectations of the performance of system management and control. However, more effective system control can only be exercised if the increased volume of data is matched by an increased capacity to interpret system conditions from the control room. The decision support system described in this paper makes use of expert system techniques in order to provide intelligent reasoning based on the incoming alarm data. Both the readily available benefits, and the advance towards the next generation of power systems which this type of system will afford shall be presented along with a description of the decision support system.

The authors present two expert system developments which are each concerned with utilizing, to the best effect, the increasing volume of SCADA (supervisory control and data acquisition) system data available to power system control staff. The systems presented, APEX and RESPONDD, are aimed at the two related fields of alarm processing and fault diagnosis, respectively. The areas of commonality between these systems are discussed, as well as details specific to each separate system, including a case of study illustrating the practical operation of each. >

This letter presents the outcomes of a trial of an active network management (ANM) scheme on part of the North-Scotland electricity network. The ANM scheme has as its goal the facilitation of increased connections of distributed generation (DG) from renewable resources on the Orkney Isles. The ANM scheme is the first multigenerator application of ANM at distribution level in the U.K. The ANM scheme is briefly discussed prior to the trial of the ANM scheme being introduced. The implications of the trial for full ANM roll-out are discussed. The results of the trial of the ANM scheme are of direct relevance to those working in the areas of ANM, smart grids, and advanced distribution automation. The results confirm that wind farms can be controlled within the thermal constraints of a distribution network subject to certain operating margin considerations.

This paper discusses a novel approach to model integration applied within electrical power engineering. A model integration methodology, exploiting the novel approach developed and underpinned by agent technology, is proposed.