Advances in vegetation management for power line corridor monitoring using aerial remote sensing techniques

This paper presents a comprehensive discussion of vegetation management approaches in power line corridors based on aerial remote sensing techniques. We address three issues 1) strategies for risk management in power line corridors, 2) selection of suitable platforms and sensor suite for data collection and 3) the progress in automated data processing techniques for vegetation management. We present initial results from a series of experiments and, challenges and lessons learnt from our project.

Real-time power line extraction from unmanned aerial system video images

In this paper a real-time vision based power line extraction solution is investigated for active UAV guidance. The line extraction algorithm starts from ridge points detected by steerable filters. A collinear line segments fitting algorithm is followed up by considering global and local information together with multiple collinear measurements. GPU boosted algorithm implementation is also investigated in the experiment. The experimental result shows that the proposed algorithm outperforms two baseline line detection algorithms and is able to fitting long collinear line segments. The low computational cost of the algorithm make suitable for real-time applications.

The evolution of offshore wind power in the United Kingdom

In the United Kingdom wind power is recognised as the main source of renewable energy to achieve the European Union 2020 renewable energy targets. Currently over 50% of renewable power is generated from onshore wind with a large number of offshore wind projects in development. Recently the government has re-iterated its commitment to offshore wind power and has announced that offshore wind subsidies are to increase from £135/MWh to £140/MWh until 2019. This paper provides a detailed overview of the offshore wind power industry in the United Kingdom in terms of market growth, policy development and offshore wind farm costs. The paper clearly shows that the United Kingdom is the world leader for installed offshore wind power capacity as pro-active policies and procedures have made it the most attractive location to develop offshore wind farm arrays. The key finding is that the United Kingdom has the potential to continue to lead the world in offshore wind power as it has over 48 GW of offshore wind power projects at different stages of operation and development. The growth of offshore wind power in the United Kingdom has seen offshore wind farm costs rise and level off at approximately £3 million/MW, which are higher than onshore wind costs at £1.5–2 million/MW. Considering the recent increase in offshore wind power subsidies and plans for 48 GW of offshore wind power could see more offshore wind power becoming increasingly financially competitive with onshore wind power. Therefore offshore wind power is likely to become a significant source of electricity in the United Kingdom beyond 2020.

A review of ADP processing software

Data processing is an essential part of Acoustic Doppler Profiler (ADP) surveys, which have become the standard tool in assessing flow characteristics at tidal power development sites. In most cases, further processing beyond the capabilities of the manufacturer provided software tools is required. These additional tasks are often implemented by every user in mathematical toolboxes like MATLAB, Octave or Python. This requires the transfer of the data from one system to another and thus increases the possibility of errors. The application of dedicated tools for visualisation of flow or geographic data is also often beneficial and a wide range of tools are freely available, though again problems arise from the necessity of transferring the data. Furthermore, almost exclusively PCs are supported directly by the ADP manufacturers, whereas small computing solutions like tablet computers, often running Android or Linux operating systems, seem better suited for online monitoring or data acquisition in field conditions. While many manufacturers offer support for developers, any solution is limited to a single device of a single manufacturer. A common data format for all ADP data would allow development of applications and quicker distribution of new post processing methodologies across the industry.

Field Testing a Full-Scale Tidal Turbine Part 3: Acoustic Characteristics

Like any new technology, tidal power converters are being assessed for potential environmental impacts. Similar to wind power, where noise emissions have led to some regulations and limitations on consented installation sites, noise emissions of these new tidal devices attract considerable attention, especially due to the possible interaction with the marine fauna. However, the effect of turbine noise cannot be assessed as a stand-alone issue, but must be investigated in the context of the natural background noise in high flow environments. Noise measurements are also believed to be a useful tool for monitoring the operating conditions and health of equipment. While underwater noise measurements are not trivial to perform, this non-intrusive mon- itoring method could prove to be very cost effective. This paper presents sound measurements performed on the SCHOTTEL Instream Turbine as part of the MaRINET testing campaign at the QUB tidal test site in Portaferry during the summer of 2014. This paper demonstrates a comparison of the turbine noise emissions with the normal background noise at the test site and presents possible applications as a monitoring system.

Asset Tracking in Critical Power Communications Infrastructures using Passive Techniques

Active network scanning injects traffic into a network and observes responses to draw conclusions about the network. Passive network analysis works by looking at network meta data or by analyzing traffic as it traverses a fixed point on the network. It may be infeasible or inappropriate to scan critical infrastructure networks. Techniques exist to uniquely map assets without resorting to active scanning. In many cases, it is possible to characterize and identify network nodes by passively analyzing traffic flows. These techniques are considered in particular with respect to their application to power industry critical infrastructure.

Tidal Energy Resource Characterization in Alberni Inlet, B.C.

Senior thesis written for Oceanography 444

Reinforcement Learning Approaches to Power System Scheduling

One major component of power system operation is generation scheduling. The objective of the work is to develop efficient control strategies to the power scheduling problems through Reinforcement Learning approaches. The three important active power scheduling problems are Unit Commitment, Economic Dispatch and Automatic Generation Control. Numerical solution methods proposed for solution of power scheduling are insufficient in handling large and complex systems. Soft Computing methods like Simulated Annealing, Evolutionary Programming etc., are efficient in handling complex cost functions, but find limitation in handling stochastic data existing in a practical system. Also the learning steps are to be repeated for each load demand which increases the computation time.Reinforcement Learning (RL) is a method of learning through interactions with environment. The main advantage of this approach is it does not require a precise mathematical formulation. It can learn either by interacting with the environment or interacting with a simulation model. Several optimization and control problems have been solved through Reinforcement Learning approach. The application of Reinforcement Learning in the field of Power system has been a few. The objective is to introduce and extend Reinforcement Learning approaches for the active power scheduling problems in an implementable manner. The main objectives can be enumerated as:(i) Evolve Reinforcement Learning based solutions to the Unit Commitment Problem.(ii) Find suitable solution strategies through Reinforcement Learning approach for Economic Dispatch. (iii) Extend the Reinforcement Learning solution to Automatic Generation Control with a different perspective. (iv) Check the suitability of the scheduling solutions to one of the existing power systems.First part of the thesis is concerned with the Reinforcement Learning approach to Unit Commitment problem. Unit Commitment Problem is formulated as a multi stage decision process. Q learning solution is developed to obtain the optimwn commitment schedule. Method of state aggregation is used to formulate an efficient solution considering the minimwn up time I down time constraints. The performance of the algorithms are evaluated for different systems and compared with other stochastic methods like Genetic Algorithm.Second stage of the work is concerned with solving Economic Dispatch problem. A simple and straight forward decision making strategy is first proposed in the Learning Automata algorithm. Then to solve the scheduling task of systems with large number of generating units, the problem is formulated as a multi stage decision making task. The solution obtained is extended in order to incorporate the transmission losses in the system. To make the Reinforcement Learning solution more efficient and to handle continuous state space, a fimction approximation strategy is proposed. The performance of the developed algorithms are tested for several standard test cases. Proposed method is compared with other recent methods like Partition Approach Algorithm, Simulated Annealing etc.As the final step of implementing the active power control loops in power system, Automatic Generation Control is also taken into consideration.Reinforcement Learning has already been applied to solve Automatic Generation Control loop. The RL solution is extended to take up the approach of common frequency for all the interconnected areas, more similar to practical systems. Performance of the RL controller is also compared with that of the conventional integral controller.In order to prove the suitability of the proposed methods to practical systems, second plant ofNeyveli Thennal Power Station (NTPS IT) is taken for case study. The perfonnance of the Reinforcement Learning solution is found to be better than the other existing methods, which provide the promising step towards RL based control schemes for practical power industry.Reinforcement Learning is applied to solve the scheduling problems in the power industry and found to give satisfactory perfonnance. Proposed solution provides a scope for getting more profit as the economic schedule is obtained instantaneously. Since Reinforcement Learning method can take the stochastic cost data obtained time to time from a plant, it gives an implementable method. As a further step, with suitable methods to interface with on line data, economic scheduling can be achieved instantaneously in a generation control center. Also power scheduling of systems with different sources such as hydro, thermal etc. can be looked into and Reinforcement Learning solutions can be achieved.

Entry on the Brazilian renewable power market: a case study

Conferências internacionais sobre o clima, bem como crescente conscientização sobre as questões de sustentabilidade lançaram luz sobre o papel fundamental que as energias renováveis poderiam desempenhar na transição energética. Ao contrário de combustíveis fósseis, elas podem ser regeneradas em um curto período de tempo e, por conseguinte, espera-se que sejam uma parte da solução para reduzir o aquecimento global. O Brasil sempre teve um forte setor hidrelétrico, mas agora está na vanguarda em relação a todas as outras fontes de energias alternativas, como energia eólica, biomassa o energia solar. Estas indústrias são uma promessa para um futuro próspero, graças ao potencial natural do país, bem como uma legislação de apoio, e estão atraindo muitas empresas locais e internacionais. Este estudo tem como objetivo preencher uma lacuna na literatura analisando o exemplo de uma empresa estrangeira que entra no mercado da energia renovável no Brasil. Baseando-se na literatura como um fundo conceptual, um único estudo de caso têm sido realizados para delinear todos os aspectos do processo de entrada. Neste desenvolvimento, relações causais entre as orientações estratégicas e a evolução do negócio foram identificadas. Esta pesquisa traz uma contribuição para as discussões acadêmicas sobre as dinâmicas de entrada no setor de energia renovável através de evidências do mercado brasileiro.

Russian gas industry - current condition and prospects; New regional 'in-security' system in Central Asia; Caspian oil and gas: the facts at the end of the year 2000. OSW Study 1/2001

Russian gas industry: The current condition of the gas industry is one of the most crucial factors influencing the Russian state·s functioning, internal situation and international position. Not only is gas the principal energy resource in Russia, it also subsidises other sectors of the economy. Status of the main European gas exporter strengthens also Russia's importance in the international arena. New regional in-security: Ten years have passed since the Central Asian states declared their independence, but their relationship with Russia still remains close, and the latter treats them as its exclusive zone of influence. A crucial reason for keeping Central Asia within the orbit of Moscow·s influence is the fact that Russia exercises control over the most important transport routes out of the region of raw materials for the power industry, on which the economic development of Asia depends on. But this is the only manifestation of Central Asia·s economic dependence on Russia. Moscow lacks solid economic instruments (i.e. investment input or power industry dependence) to shape the situation in the region. Caspian oil and gas: Caspian stocks of energy resources are not, and most probably will not be, of any great significance on the world scale. Nevertheless it is the Caspian region which will have the opportunity to become an oil exporter which will reduce the dependence of the European countries on Arabian oil, and which will guarantee Russia the quantities of gas which are indispensable both for meeting its internal demands and for maintaining its current level of export. For Azerbaijan, Kazakhstan and Turkmenistan, the confirmation of the existence of successive oil strata is not only an opportunity to increase income, but also an additional bargaining chip in the game for the future of the whole region. The stake in this game is the opportunity to limit the economic, and by extension the political influences of Russia in the region.

Power system sensitivity analysis for probabilistic small signal stability assessment in a deregulated environment

Deregulations and market practices in power industry have brought great challenges to the system planning area. In particular, they introduce a variety of uncertainties to system planning. New techniques are required to cope with such uncertainties. As a promising approach, probabilistic methods are attracting more and more attentions by system planners. In small signal stability analysis, generation control parameters play an important role in determining the stability margin. The objective of this paper is to investigate power system state matrix sensitivity characteristics with respect to system parameter uncertainties with analytical and numerical approaches and to identify those parameters have great impact on system eigenvalues, therefore, the system stability properties. Those identified parameter variations need to be investigated with priority. The results can be used to help Regional Transmission Organizations (RTOs) and Independent System Operators (ISOs) perform planning studies under the open access environment.

Eco-efficiency considering the issue of heterogeneity among power plants

One of the main objectives in restructuring power industry is enhancing the efficiency of power facilities. However, power generation industry, which plays a key role in the power industry, has a noticeable share in emission amongst all other emission-generating sectors. In this study, we have developed some new Data Envelopment Analysis models to find efficient power plants based on less fuel consumption, combusting less polluting fuel types, and incorporating emission factors in order to measure the ecological efficiency trend. We then applied these models to measuring eco-efficiency during an eight-year period of power industry restructuring in Iran. Results reveal that there has been a significant improvement in eco-efficiency, cost efficiency and allocative efficiency of the power plants during the restructuring period. It is also shown that despite the hydro power plants look eco-efficient; the combined cycle ones have been more allocative efficient than the other power generation technologies used in Iran.

Do Changes in Current Flow as a Result of Arrays of Tidal Turbines Have an Effect on Benthic Communities?

Arrays of tidal energy converters have the potential to provide clean renewable energy for future generations. Benthic communities may, however, be affected by changes in current speeds resulting from arrays of tidal converters located in areas characterised by strong currents. Current speed, together with bottom type and depth, strongly influence benthic community distributions; however the interaction of these factors in controlling benthic dynamics in high energy environments is poorly understood. The Strangford Lough Narrows, the location of SeaGen, the world’s first single full-scale, grid-compliant tidal energy extractor, is characterised by spatially heterogenous high current flows. A hydrodynamic model was used to select a range of benthic community study sites that had median flow velocities between 1.5–2.4 m/s in a depth range of 25–30 m. 25 sites were sampled for macrobenthic community structure using drop down video survey to test the sensitivity of the distribution of benthic communities to changes in the flow field. A diverse range of species were recorded which were consistent with those for high current flow environments and corresponding to very tide-swept faunal communities in the EUNIS classification. However, over the velocity range investigated, no changes in benthic communities were observed. This suggested that the high physical disturbance associated with the high current flows in the Strangford Narrows reflected the opportunistic nature of the benthic species present with individuals being continuously and randomly affected by turbulent forces and physical damage. It is concluded that during operation, the removal of energy by marine tidal energy arrays in the far-field is unlikely to have a significant effect on benthic communities in high flow environments. The results are of major significance to developers and regulators in the tidal energy industry when considering the environmental impacts for site licences.

Corona discharges on the surfaces of high voltage composite insulators

The degradation of high voltage electrical insulation is a prime factor that can significantly influence the reliability performance and the costs of maintaining high voltage electricity networks. Little information is known about the system of localized degradation from corona discharges on the relatively new silicone rubber sheathed composite insulators that are now being widely used in high voltage applications. This current work focuses on the fundamental principles of electrical corona discharge phenomena to provide further insights to where damaging surface discharges may localize and examines how these discharges may degrade the silicone rubber material. Although water drop corona has been identified by many authors as a major cause of deterioration of silicone rubber high voltage insulation until now no thorough studies have been made of this phenomenon. Results from systematic measurements taken using modern digital instrumentation to simultaneously record the discharge current pulses and visible images associated with corona discharges from between metal electrodes, metal electrodes and water drops, and between waters drops on the surface of silicone rubber insulation, using a range of 50 Hz voltages are inter compared. Visual images of wet electrodes show how water drops can play a part in encouraging flashover, and the first reproducible visual images of water drop corona at the triple junction of water air and silicone rubber insulation are presented. A study of the atomic emission spectra of the corona produced by the discharge from its onset up to and including spark-over, using a high resolution digital spectrometer with a fiber optic probe, provides further understanding of the roles of the active species of atoms and molecules produced by the discharge that may be responsible for not only for chemical changes of insulator surfaces, but may also contribute to the degradation of the metal fittings that support the high voltage insulators. Examples of real insulators and further work specific to the electrical power industry are discussed. A new design concept to prevent/reduce the damaging effects of water drop corona is also presented.

Development of an autonomous helicopter for aerial powerline inspections

Autonomous mini-helicopters have been seen as a viable option for aerial-based powerline inspections, however there are numerous research and engineering challenges in developing a system capable of achieving this task in a dependable manner. We have developed an autonomous helicopter as a research platform which will allow us to demonstrate proof-of-concept capabilities for powerline inspections. Through numerous development cycles and from flight test experience we have gained insights into the key challenges in this area. We discuss these insights, describe the helicopter platform and present our research progress in the area of obstacle avoidance for mini-helicopters.