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This paper presents studies of a single-phase induction machine driven by a micro wind turbine connected to an LV distribution system within a residential dwelling. The transient associated with grid connection and both local and electrically remote network faults are presented. Based on these studies conclusions will be drawn regarding the network impacts of microgenerators using single-phase induction generators and, conversely, the impact of network secondary systems such as protection (e.g. typical fault clearance times) on the behaviour of these generators, and also the threshold values of the machine speed and its retained terminal voltage when the system experiences a remote fault on the MV system are defined. The principle contribution of this paper is to highlight stability issues associated with such small scale generators, and to propose some remedial measures by which the stable operation of such generators may be improved.

The emerging international concepts for future distribution networks represent a more active mode of operation. This is now being reflected in the power industry, particularly within the UK, as distribution networks begin to become more active with a view towards facilitating the connection and operation of distributed generation (DG). Active network management (ANM) schemes are emerging that address the communications and control requirements of managing constraints on the distribution network in real time. This represents a significant change to the mode of operation, which is something the existing distribution network was not designed to support. This paper presents the issues associated with active networks, with a view towards the development of a modelling and analysis framework. The authors present the fundamental layers of the framework - to be expanded upon in future work - and a case study of the implementation of the proposed framework on a generic distribution system. (4 pages)

Loss-of-mains (LOM) protection is a safety requirement for distributed generators intending to prevent unintentional islanded operation of a section of the distribution network. With increased numbers of small and medium scale generators connected to the system the correct operation of the LOM protection becomes critical. This paper proposes a new countrywide solution for the detection of islanded operation based on satellite communication. The new method is compared with the existing approaches and the performance is tested with carefully prepared sensitivity and stability scenarios. Practical implications of utilising available satellite channels are also discussed.

Several recent and anticipated future developments in marine electrical system engineering will impact upon power system protection. Large-scale IFEP (integrated full electric propulsion) systems are being increasingly introduced. A consequence of this is that the role, reliability, availability and survivability of the power system have and will become more critical than before. This therefore impacts on the performance required of both main and backup protection systems. The relatively low inertia within the power system, the introduction of hybrid AC/ DC power systems and the proliferation of power-converter interfaces all influence the behaviour of the power system and the design of the protection system must cater for all of these developments. This paper will consider many of these issues and, through the use of examples and simulation exercises, discuss and propose a number of protection-oriented solutions addressing said issues.

Distributed generators (DGs) that are rated between several kVA and 250 kVA in size are increasingly being connected at the 400 V electrical distribution level. Therefore, new requirements for the traditional network protection schemes and the co-ordination between network protection and intertie protection are needed. Actual problems have been experienced relating to DG transient behaviour, thereby, more accurate analysis is required. This paper presents studies using a real time simulation platform to investigate the transient behaviour of the distributed generators' protection under external disturbances. Furthermore, an optimized DG protection setting for keeping most of the DG stable under such disturbances is proposed.

Microgeneration technologies connected to low-voltage distribution networks, such as small-scale wind turbines, photovoltaic (PV) arrays and micro combined heat and power (uCHP) offer the potential to reduce carbon emissions, to improve security of supply. These technologies can be based on either synchronous or asynchronous generators, although many of them are connected to the network via power electronic interfaces. Although the use of microgeneration provides many benefits it also imposes various challenges with regards to stability, control and protection. In particular, this paper investigates the transient behaviour of induction generator-based microgeneration in the event of a short- circuit fault. The influence of synchronous generator and converter-connected microgeneration on the dynamic performance of the induction generator is also investigated. The investigations were conducted in PSCAD/EMTDC.

The fault level rating of installed equipment in urban areas is a common restriction on the expansion of distributed generation (DG). One option for reducing fault level is to split the network at selected points by, for example, opening bus section circuit breakers that are normally run closed. This paper presents studies performed to evaluate the impact of network splitting on fault levels and various network performance measures such as reliability and power quality. Four generic test networks were used that reflect typical operating conditions and configurations of UK distribution networks, although the results are generally applicable to other networks. The studies provide valuable guidance on the potential benefits and costs of network splitting and so contribute to the debate on how to accommodate more DG on existing networks. Other issues like network operation and maintenance must also be considered when assessing if a particular network splitting option is acceptable from both a network and generation perspective.

This paper describes an architecture and methodology for transmission and distribution asset management. It is based on the use of multi-agent system technology to integrate all the condition monitoring and asset management functions. The concepts are described, and the design of the architecture detailed, through consideration of a power transformer monitoring application. The operation of a laboratory prototype is explained. This includes discussion of strategies for improving the system's diagnostic abilities. Finally, the paper describes how this methodology, architecture and technology can be extended to encompass all plant condition monitoring systems, supporting transmission and distribution network wide asset management.

Distributed generation (DG) poses new challenges in distribution network development and operation. Distribution Network Operators (DNOs) will face more active management of networks, new commercial arrangements, and new challenges in asset management. Resolving these will require new types of analysis that were previously unnecessary or very rare. Collecting and processing information to facilitate these analyses presents a significant new burden for DNOs. However, methods are available that may assist DNOs in the collection of information. Three such methods are discussed here: a structured approach to fundamental information requirements; standard formats; and generic device types or category descriptions. Examples are provided of how DNOs would use the information collected to analyse DG connection and operation. Effective management of information will enable DNOs to characterise DG and perform the analyses necessary to ensure that a reliable and high-quality electricity supply is maintained.

In order to meet national and international renewable energy targets, new methods of operating and managing electricity distribution networks are required. Renewable energy sources are abundant in Scotland but mainly exist in the west and north of the country, away from the main load centres. These sparsely populated areas are serviced by weaker distribution networks, which struggle to accommodate the introduction of large generator connections. These connections challenge the mode of operation of the distribution network, which was designed originally to operate passively and deliver unidirectional power flows to dispersed customers. If renewable energy connections to the distribution network are to be realised, without expensive uprating of existing network infrastructure, active network management is required.

A circuit breaker may be considered an ‘active link’, used to make and break an electrical circuit under conditions of varying severity. In the event of a circuit fault the circuit breaker must respond within tens of milliseconds in order to prevent damage to connected plant and safeguard personnel. As such, a circuit breaker will remain idle for the bulk of its lifetime, only being called into action periodically to interrupt load or fault current. This makes the circuit breaker one of the most safety critical, yet most unpredictable plant items on the power network. In addition, circuit breaker mal-operations account for a significant proportion of Customer Minutes Lost (CMLs), Customer Interruptions (CIs), plant replacement costs and safety issues. Conflicting regulatory and economic pressures to improve the performance, reliability and longevity of these, and other major plant items while reducing maintenance costs have forced many utilities to reassess their asset management and maintenance strategies [1]. This has led to significant investment in novel condition monitoring technologies, which in turn precipitate the need for new methods of analysing and interpreting new forms and increasing volumes of plant data.

Currently there is considerable R&D activity in the field of fuel cell (FC) technology as an efficient and clean power source for both stationary and transport applications. This paper describes the development of a fuel cell/battery hybrid power source for a stationary domestic power application, details the control systems underpinning this system and describes some preliminary experimental results. The authors believe that the fuel cell/battery hybrid power system is the most cost-effective solution for domestic power applications. This recognizes that a typical domestic power profile can have a peak to average power ratio of between around 9-15, and hence a fuel cell only system would significantly over-rate the fuel cell to satisfy peak power and consequently suffer from poor utilisation. The hybrid system avoids this by using battery power to meet instantaneous peak power and the fuel cell as a base load / battery charging element. The objective of this paper is to consider the power electronic interface from a fuel cell as a low voltage DC source, to a higher voltage storage battery and possible DC load, i.e DC/DC booster, and ultimately a DC/AC inverter for utility connection. This paper will describe the system design and experimental results over a 7-hour test period using a DC load profile only, monitored by an LF 2407 digital signal processor (DSP).

The paper introduces the idea of using Internet based distributed simulation resources for power system protection studies. The previously developed integrated modelling environment (IME) for protection has been utilised to demonstrate the principle of closed loop multi scheme protection simulation using web services. An example study of two different protection schemes connected to a power system model and performing protection switching sequence simulation is presented. Both the power system model represented alternating transient program (ATP) and protection system model coded in C++ are coordinated by a client software application. The potential benefits of the proposed solution for various customers are outlined in the concluding part of the paper.

In this paper, the authors present an approach for the capitalisation of switching knowledge centred around the creation of structured knowledge models in order to provide switching support for transmission networks. With this iterative process, the role of additional knowledge in the overall problem solving behaviour can be explicitly identified in the resulting models. This approach facilitates the incremental integration of knowledge that has originated from different sources, into a centralised framework which can be used for different purposes such as reference documentation, or specification of support systems.

Power system disturbance diagnosis is a complex and time consuming task, requiring skilled engineers. Existing intelligent systems which assist with data interpretation require the engineer to further interpret and collate generated information so that a comprehensive diagnosis can be produced. Furthermore, long-term extensibility and flexibility are also restricted. This paper presents a multi-agent approach to power system disturbance diagnosis where existing intelligent systems are wrapped up as intelligent agents and, through a process of inter-agent communication, collaborate to provide disturbance diagnosis. This novel approach enables timely automated disturbance diagnosis within a flexible and extensible architecture.

This paper discusses the concept of power system flexible alarm processing for provision of pertinent information to multiple and diverse information consumers. Flexibility is achieved by enabling the application of multiple alarm processing techniques and dynamic interpretation based on context, user and system requirements. The role Internet technologies could play in facilitating flexible alarm processing, including implementing the knowledge required to support alarm interpretation techniques, is also discussed. An example case study scenario is used to illustrate the potential operation of a flexible alarm processing system.

This paper proposes an approach to assessing generator connection requests that seeks to enhance flexibility and transparency by trading network reinforcement to accommodate generation against operational constraints on the generator that can reduce the required network reinforcement. The impact of dispersed generation and the passing on of costs to generators is briefly discussed. The trade-off concept is introduced and there is supplementary discussion of nondespatchable generation and the monitoring and control of generators. A method of evaluating generator connections is proposed and an example illustrates the resultant choice faced by generators. Finally, some conclusions are drawn.

This paper describes the use of a dynamic protection modelling system to investigate complex faults to determine whether protection equipment has performed correctly. An explanation of the modelling system is given and then the results of two case studies are presented. These are both real events that have occurred on the UK National Grid transmission system. The dynamic protection (DPM) system has been used to give a deeper understanding of how the individual protections performed and determine whether they performed correctly for the conditions presented or whether there was a defect within the protection scheme.

Gas circulators are critical to the safe and economic operation of nuclear power stations. When significant maintenance work or design changes are required for the gas circulators, plant engineers must provide detailed justifications of proposed changes which demonstrate that relevant technical and safety criteria have been satisfied. The paper describes the Gas Circulator Design Advisory System (GCDAS) which is a Web based decision support system utilising case based, knowledge based and database techniques to provide engineers with focused and prioritised information relating to a requested design change.

The paper has given a general introduction into the methods which can be used in determining which factors influence a successful bone marrow transplant for the treatment of patients with relapsed or resistant Hodgkin's Disease. By following the KDD process and applying various data reduction, data cleansing and data mining techniques to the original EBMT database several nuggets of knowledge have been created. Firstly the induction rules may provide the basis for predicting the outcome in patients depending upon their characteristics. The artificial neural networks shows which characteristics of the patients are the most relevant, and the association rules present the characteristics which generally appear together for the different outcomes. (8 pages)

The effective maintenance scheduling of power system generators is very important to a power utility for the economical and reliable operation of a power system. Many mathematical methods have been implemented for generator maintenance scheduling (GMS). However, these methods have many limitations and require many approximations. Here a Genetic Algorithm is proposed for GMS problems in order to overcome some of the limitations of the conventional methods. This paper formulates a general GMS problem using a reliability criterion as an integer programming problem, and demonstrates the use of GAs with three different problem encodings: binary, binary for integer and integer. The GA performances for each of these representations are analysed and compared for a test problem based on a practical power system scenario. The effects of different GA parameters are also studied. The results show that the integer GA is a very effective method for GMS problems.

Following a disturbance on the power network, protection engineers are required to determine if the protection schemes operated correctly. To aid protection engineers in this task, they have access to supervisory control and data acquisition (SCADA) system data and fault recorder data. This paper reports on a decision support system (DSS) for protection engineers which will automatically analyse this data to provide a comprehensive report on the protection scheme operation. The DSS comprises of two knowledge based systems which interpret the SCADA system data and a model based diagnosis module that can utilise both SCADA system data and fault recorder data. This paper concentrates in particular on the model based aspect, which provides the comprehensive analysis of the protection scheme operations. A case study is presented demonstrating the depth of diagnosis possible.

Knowledge discovery in databases (KDD) is defined as the non trivial process of identifying valid, novel, potentially useful, and ultimately understandable patterns in data (W.J. Frawley et al., 1991). KDD is an iterative process involving five steps which lead to the final goal of useful information. The five steps are: selection of data-determining which fields and records are to be analysed; preprocessing-cleaning the data, by removal of noise and outliers, if appropriate, and deciding on strategies for missing attribute values; transformation-representing the data by new features, and reducing its dimensionality; data mining-deciding which algorithms to apply to the data i.e., classification, regression, rule induction, neural networks; and interpretation/evaluation-feasibility analysis of the results from the data mining step. There are two general 'goals' in KDD: verification of a hypothesis; and discovery, where the 'system' autonomously discovers patterns. Within the KDD process a data warehouse is typically employed as the 'source' of the KDD exercise. The power industry has evolved to become dependent upon computerised environments with more online data being stored for later extraction and investigation. Two key areas where KDD has been shown to be applicable is in the analysis of energy pooling and settlement data, and for condition monitoring of power system plant.

This paper summarises work undertaken in collaboration with the National Grid Company (NGC) and ScottishPower to investigate the performance of dynamic models of the protection system. Models of commercially available relays have been developed, based on the manufacturers' specifications and algorithms. The concept of an integrated simulation system with an open architecture which can utilise (as input) primary power system simulation results (obtained from the standard EMTP program) as well as actual fault records from the network are presented. Possibilities for future development of the system in addition to benefits of the system for protection engineers will be discussed in the concluding part of the paper. The outcome of this work has been validated by protection engineers and contributes to the improvement of the reliability and security of the protection systems.

Engineers who make critical operational and strategic plant management decisions require high quality information. Intelligent systems provide engineers with information by applying knowledge of plant behaviour to plant data. Therefore, intelligent systems significantly extend and add value to the capabilities provided by existing condition monitoring systems while supporting enhanced plant management strategies. A range of intelligent systems techniques have been described which have been successfully applied to a range of condition monitoring problems. Experience in the use of these techniques has highlighted a range of strengths and weaknesses in ease of construction, scope and functionality, and computational performance. In particular, the domain coverage provided by each technique was limited by the availability of useful knowledge, models, cases and data. Therefore, an integrated approach to the application of intelligent systems in condition monitoring has been proposed which uses intelligent systems methods providing flexible and robust provision of plant management information for entire engineering processes and systems.

The advances made in the provision of system data pertinent to network management have resulted in much more data being made available than was previously possible. However, if the goals of improved network management are to be reached then effort must be invested in providing for the needs of these functions rather than merely for increased volumes of data. Intelligent systems provide a key technology for the provision of this support at various stages in the overall task of network management. This paper demonstrates this through three example application areas: control centre application, network support, and distributed control.

Modern artificial intelligence and signal processing techniques provide significant potential for deriving useful information about the state of the power system based upon an analysis of existing measurement and telemetry data. Additionally, the advent of integrated and coordinated substation monitoring, control and protection systems coupled with the gradual emergence of (and utility requirements for) “open”, nonproprietary communications (these protocols must exist in the public domain this is not always the case with some “open” protocols) standards have created an environment within which advanced functions could be realistically and cost-effectively implemented. This paper describes examples of two such functions which could be included within an overall substation secondary system in order to extract information from both the analogue waveform and the telemetry data (i.e. at two distinct levels of the power system data/information “hierarchy”).

This paper describes the application of expert system techniques to fault diagnosis in alternators. A structured approach to knowledge acquisition and analysis is discussed which has allowed the efficient construction of comprehensive knowledge models of design and operational expertise. In addition to being used in the creation of an auditable archive of alternator subsystem expertise, the knowledge models have been used in the development of enhanced generator diagnostics. The development of an expert system from the acquired knowledge models is described and its diagnostic capability demonstrated by an example of its diagnosis.

Significant improvements have been made 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 expectations of improved performance in 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. Through the description of the decision support system contained in this paper, the benefits to system operation are made evident.