231 resultados para grid integration


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Traditional internal combustion engine vehicles are a major contributor to global greenhouse gas emissions and other air pollutants, such as particulate matter and nitrogen oxides. If the tail pipe point emissions could be managed centrally without reducing the commercial and personal user functionalities, then one of the most attractive solutions for achieving a significant reduction of emissions in the transport sector would be the mass deployment of electric vehicles. Though electric vehicle sales are still hindered by battery performance, cost and a few other technological bottlenecks, focused commercialisation and support from government policies are encouraging large scale electric vehicle adoptions. The mass proliferation of plug-in electric vehicles is likely to bring a significant additional electric load onto the grid creating a highly complex operational problem for power system operators. Electric vehicle batteries also have the ability to act as energy storage points on the distribution system. This double charge and storage impact of many uncontrollable small kW loads, as consumers will want maximum flexibility, on a distribution system which was originally not designed for such operations has the potential to be detrimental to grid balancing. Intelligent scheduling methods if established correctly could smoothly integrate electric vehicles onto the grid. Intelligent scheduling methods will help to avoid cycling of large combustion plants, using expensive fossil fuel peaking plant, match renewable generation to electric vehicle charging and not overload the distribution system causing a reduction in power quality. In this paper, a state-of-the-art review of scheduling methods to integrate plug-in electric vehicles are reviewed, examined and categorised based on their computational techniques. Thus, in addition to various existing approaches covering analytical scheduling, conventional optimisation methods (e.g. linear, non-linear mixed integer programming and dynamic programming), and game theory, meta-heuristic algorithms including genetic algorithm and particle swarm optimisation, are all comprehensively surveyed, offering a systematic reference for grid scheduling considering intelligent electric vehicle integration.

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This paper presents a novel analysis of the utilisation of small grid scale energy storage to mitigate negative system operational impacts due to high penetrations of wind power. This was investigated by artificially lowering the minimum stable generation level of a gas thermal generating unit coupled to a storage device over a five hour storage charging window using a unit commitment and economic dispatch model. The key findings of the analysis were a 0.18% reduction in wind curtailment, a 2.35 MW/min reduction in the ramping rate required to be met by all generators in the test system during a representative period and a total generation cost reduction of €6.5 million.

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The key attributes of a smarter power grid include: pervasive interconnection of smart devices; extensive data generation and collection; and rapid reaction to events across a widely dispersed physical infrastructure. Modern telecommunications technologies are being deployed across power systems to support these monitoring and control capabilities. To enable interoperability, several new communications protocols and standards have been developed over the past 10 to 20 years. These continue to be refined, even as new systems are rolled out.

This new hyper-connected communications infrastructure provides an environment rich in sub-systems and physical devices that are attractive to cyber-attackers. Indeed, as smarter grid operations become dependent on interconnectivity, the communications network itself becomes a target. Consequently, we examine cyber-attacks that specifically target communications, particularly state-of-the-art standards and protocols. We further explore approaches and technologies that aim to protect critical communications networks against intrusions, and to monitor for, and detect, intrusions that infiltrate Smart Grid systems.

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Experiences from smart grid cyber-security incidents in the past decade have raised questions on the applicability and effectiveness of security measures and protection mechanisms applied to the grid. In this chapter we focus on the security measures applied under real circumstances in today’s smart grid systems. Beginning from real world example implementations, we first review cyber-security facts that affected the electrical grid, from US blackout incidents, to the Dragonfly cyber-espionage campaign currently focusing on US and European energy firms. Provided a real world setting, we give information related to energy management of a smart grid looking also in the optimization techniques that power control engineers perform into the grid components. We examine the application of various security tools in smart grid systems, such as intrusion detection systems, smart meter authentication and key management using Physical Unclonable Functions, security analytics and resilient control algorithms. Furthermore we present evaluation use cases of security tools applied on smart grid infrastructure test-beds that could be proved important prior to their application in the real grid, describing a smart grid intrusion detection system application and security analytics results. Anticipated experimental results from the use-cases and conclusions about the successful transitions of security measures to real world smart grid operations will be presented at the end of this chapter.

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Over the last two decades there has been ongoing debate about the impact of environmental practices on operational performance. In recent years, studies have started to move beyond assessing the direct impact of environmental management on different dimensions of performance to consider factors that might moderate or mediate this relationship. This study considers the extent to which environmental integration and environmental capabilities moderate the relationship between pollution prevention and environmental performance outcomes. The mediating influence of environmental performance on the relationship between pollution prevention and cost and flexibility performance is also considered. Data were collected from a sample of UK food manufacturers and analysed using multiple regression analysis. The findings indicate the existence of some moderated and mediated relationships suggesting that there is more to improving performance than implementing environmental practices.

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The power system of the future will have a hierarchical structure created by layers of system control from via regional high-voltage transmission through to medium and low-voltage distribution. Each level will have generation sources such as large-scale offshore wind, wave, solar thermal, nuclear directly connected to this Supergrid and high levels of embedded generation, connected to the medium-voltage distribution system. It is expected that the fuel portfolio will be dominated by offshore wind in Northern Europe and PV in Southern Europe. The strategies required to manage the coordination of supply-side variability with demand-side variability will include large scale interconnection, demand side management, load aggregation and storage in the concept of the Supergrid combined with the Smart Grid. The design challenge associated with this will not only include control topology, data acquisition, analysis and communications technologies, but also the selection of fuel portfolio at a macro level. This paper quantifies the amount of demand side management, storage and so-called ‘back-up generation’ needed to support an 80% renewable energy portfolio in Europe by 2050.

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Dependency on thermal generation and continued wind power growth in Europe due to renewable energy and greenhouse gas emissions targets has resulted in an interesting set of challenges for power systems. The variability of wind power impacts dispatch and balancing by grid operators, power plant operations by generating companies and market wholesale costs. This paper quantifies the effects of high wind power penetration on power systems with a dependency on gas generation using a realistic unit commitment and economic dispatch model. The test system is analyzed under two scenarios, with and without wind, over one year. The key finding of this preliminary study is that despite increased ramping requirements in the wind scenario, the unit cost of electricity due to sub-optimal operation of gas generators does not show substantial deviation from the no wind scenario.

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Bioenergy is a key component of the European Union long term energy strategy across all sectors, with a target contribution of up to 14% of the energy mix by 2020. It is estimated that there is the potential for 1TWh of primary energy from biogas per million persons in Europe, derived from agricultural by-products and waste. With an agricultural sector that accounts for 75% of land area and a large number of advanced engineering firms, Northern Ireland is a region with considerable potential for an integrated biogas industry. Northern Ireland is also heavily reliant on imported fossil fuels. Despite this, the industry is underdeveloped and there is a need for a collaborative approach from research, business and policy-makers across all sectors to optimise Northern Ireland’s abundant natural resources. ‘Developing Opportunities in Bio-Energy’ (i.e. Do Bioenergy) is a recently completed project that involved both academic and specialist industrial partners. The aim was to develop a biogas research action plan for 2020 to define priorities for intersectoral regional development, co-operation and knowledge transfer in the field of production and use of biogas. Consultations were held with regional stakeholders and working groups were established to compile supporting data, decide key objectives and implementation activities. Within the context of this study it was found that biogas from feedstocks including grass, agricultural slurry, household and industrial waste have the potential to contribute from 2.5% to 11% of Northern Ireland’s total energy consumption. The economics of on-farm production were assessed, along with potential markets and alternative uses for biogas in sectors such as transport, heat and electricity. Arising from this baseline data, a Do Bioenergy was developed. The plan sets out a strategic research agenda, and details priorities and targets for 2020. The challenge for Northern Ireland is how best to utilise the biogas – as electricity, heat or vehicle fuel and in what proportions. The research areas identified were: development of small scale solutions for biogas production and use; solutions for improved nutrient management; knowledge supporting and developing the integration of biogas into the rural economy; and future crops and bio-based products. The human resources and costs for the implementation were estimated as 80 person-years and £25 million respectively. It is also clear that the development of a robust bio-gas sector requires some reform of the regulatory regime, including a planning policy framework and a need to address social acceptance issues. The Action Plan was developed from a regional perspective but the results may be applicable to other regions in Europe and elsewhere. This paper presents the methodology, results and analysis, and discussion and key findings of the Do Bioenergy report for Northern Ireland.

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In multi-terminal high voltage direct current (HVDC) grids, the widely deployed droop control strategies will cause a non-uniform voltage deviation on the power flow, which is determined by the network topology and droop settings. This voltage deviation results in an inconsistent power flow pattern when the dispatch references are changed, which could be detrimental to the operation and seamless integration of HVDC grids. In this paper, a novel droop setting design method is proposed to address this problem for a more precise power dispatch. The effects of voltage deviations on the power sharing accuracy and transmission loss are analysed. This paper shows that there is a trade-off between minimizing the voltage deviation, ensuring a proper power delivery and reducing the total transmission loss in the droop setting design. The efficacy of the proposed method is confirmed by simulation studies.

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Title: Evaluating the integrating of life and social sciences teaching to first-year nursing and midwifery students

Objectives: To evaluate an integrated teaching and learning approach to first-year nursing students, combining the life, social sciences and public health with a more integrated and clinical focused approach to teaching delivery

Background: Historically within the School of Nursing and Midwifery the life sciences and social sciences had been taught as separate modules with separate teaching teams. This had reflected in a somewhat dis-integrated approach to student learning and understanding without clear clinical focus on application. With focus upon student learning the teaching teams engaged with a stepped, incremental and progressive movement towards developing and delivering a more integrated structure of learning, combining the life sciences, social sciences and public health teaching and learning within the one extended first-year module. The focus was particularly on integrated understanding and clinical relevance. This paper discusses both the approach to developing the integrated model of teaching and the evaluation of that teaching.

Results: The module, combining life, social science and Public health teaching was positively evaluated by the students. Evaluations are compared and contrasted from to nursing student intakes.

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This paper presents a framework for a telecommunications interface which allows data from sensors embedded in Smart Grid applications to reliably archive data in an appropriate time-series database. The challenge in doing so is two-fold, firstly the various formats in which sensor data is represented, secondly the problems of telecoms reliability. A prototype of the authors' framework is detailed which showcases the main features of the framework in a case study featuring Phasor Measurement Units (PMU) as the application. Useful analysis of PMU data is achieved whenever data from multiple locations can be compared on a common time axis. The prototype developed highlights its reliability, extensibility and adoptability; features which are largely deferred from industry standards for data representation to proprietary database solutions. The open source framework presented provides link reliability for any type of Smart Grid sensor and is interoperable with existing proprietary database systems, and open database systems. The features of the authors' framework allow for researchers and developers to focus on the core of their real-time or historical analysis applications, rather than having to spend time interfacing with complex protocols.