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EnBW Energie Baden-Württemberg AG, or simply EnBW, is a publicly traded electric utilities company headquartered in Karlsruhe, Germany. Wikipedia.


Schlechtingen M.,EnBW | Santos I.F.,Technical University of Denmark | Achiche S.,Ecole Polytechnique de Montreal
IEEE Transactions on Sustainable Energy | Year: 2013

Four data-mining approaches for wind turbine power curve monitoring are compared. Power curve monitoring can be applied to evaluate the turbine power output and detect deviations, causing financial loss. In this research, cluster center fuzzy logic, neural network, and k-nearest neighbor models are built and their performance compared against literature. Recently developed adaptive neuro-fuzzy-interference system models are set up and their performance compared with the other models, using the same data. Literature models often neglect the influence of the ambient temperature and the wind direction. The ambient temperature can influence the power output up to 20%. Nearby obstacles can lower the power output for certain wind directions. The approaches proposed in literature and the ANFIS models are compared by using wind speed only and two additional inputs. The comparison is based on the mean absolute error, root mean squared error, mean absolute percentage error, and standard deviation using data coming from three pitch regulated turbines rating 2 MW each. The ability to highlight performance deviations is investigated by use of real measurements. The comparison shows the decrease of error rates and of the ANFIS models when taking into account the two additional inputs and the ability to detect faults earlier. © 2010-2012 IEEE.


Schlechtingen M.,EnBW | Santos I.F.,Technical University of Denmark | Achiche S.,Ecole Polytechnique de Montreal
Applied Soft Computing Journal | Year: 2013

This paper proposes a system for wind turbine condition monitoring using Adaptive Neuro-Fuzzy Interference Systems (ANFIS). For this purpose: (1) ANFIS normal behavior models for common Supervisory Control And Data Acquisition (SCADA) data are developed in order to detect abnormal behavior of the captured signals and indicate component malfunctions or faults using the prediction error. 33 different standard SCADA signals are used and described, for which 45 normal behavior models are developed. The performance of these models is evaluated in terms of the prediction error standard deviations to show the applicability of ANFIS models for monitoring wind turbine SCADA signals. The computational time needed for model training is compared to Neural Network (NN) models showing the strength of ANFIS in training speed. (2) For automation of fault diagnosis Fuzzy Interference Systems (FIS) are used to analyze the prediction errors for fault patterns. The outputs are both the condition of the component and a possible root cause for the anomaly. The output is generated by the aid of rules that capture the existing expert knowledge linking observed prediction error patterns to specific faults. The work is based on continuously measured wind turbine SCADA data from 18 turbines of the 2 MW class covering a period of 30 months. The system proposed in this paper shows a novelty approach with regard to the usage of ANFIS models in this context and the application of the proposed procedure to a wide range of SCADA signals. The applicability of the set up ANFIS models for anomaly detection is proved by the achieved performance of the models. In combination with the FIS the prediction errors can provide information about the condition of the monitored components. In this paper the condition monitoring system is described. Part two will entirely focus on application examples and further efficiency evaluation of the system. © 2012 Elsevier B.V.


Grant
Agency: Cordis | Branch: H2020 | Program: IA | Phase: LCE-03-2015 | Award Amount: 25.07M | Year: 2016

DESTRESS is aimed at creating EGS (Enhanced geothermal systems) reservoirs with sufficient permeability, fracture orientation and spacing for economic use of underground heat. The concepts are based on experience in previous projects, on scientific progress and developments in other fields, mainly the oil & gas sector. Recently developed stimulation methods will be adapted to geothermal needs, applied to new geothermal sites and prepared for the market uptake. Understanding of risks in each area (whether technological, in business processes, for particular business cases, or otherwise), risk ownership, and possible risk mitigation will be the scope of specific work packages. The DESTRESS concept takes into account the common and specific issues of different sites, representative for large parts of Europe, and will provide a generally applicable workflow for productivity enhancement measures. The main focus will be on stimulation treatments with minimized environmental hazard (soft stimulation), to enhance the reservoir in several geological settings covering granites, sandstones, and other rock types. The business cases will be shown with cost and benefit estimations based on the proven changes of the system performance, and the environmental footprint of treatments and operation of the site will be controlled. In particular, the public debate related to fracking will be addressed by applying specific concepts for the mitigation of damaging seismic effects while constructing a productive reservoir and operating a long-term sustainable system. Industrial participation is particularly pronounced in DESTRESS, including large energy suppliers as well as SMEs in the process of developing their sites. The composition of the consortium involving major knowledge institutes as well as key industry will guarantee the increase in technology performance of EGS as well as an accelerated time to market.


Grant
Agency: Cordis | Branch: FP7 | Program: CP | Phase: ENERGY.2011.7.2-1 | Award Amount: 5.25M | Year: 2012

The growing share of electricity generation from intermittent renewable energy sources as well as increasing market-based cross border flows and related physical flows are leading to rising uncertainties in transmission network operation. In the mainland central Europe synchronous area due to large installations of renewable energy generation such as wind and photovoltaic, the difference between actual physical flows and the market exchanges can be very substantial. Remedial actions were identified by previous smart grid studies within the 6th European framework program in operational risk assessment, flow control and operational flexibility measures for this area. At the same time an efficient and sustainable electricity system requires an efficient usage of existing and future transmission capacities to provide a maximum of transportation possibilities. New interconnections and devices for load flow control will be integrated in future transmission networks and will offer new operational options. Further developments of coordinated grid security tools are one of the major challenges TSOs will face in future. The methods to be applied have to take into account all technological measures to enhance flexibility of power system operations. The zonal structure of the European energy market along with the legal responsibilities of TSOs for different system areas will continue to pose increasingly complex requirements to the system operators concerning the quality and accuracy of cooperation. The proposed UMBRELLA research and demonstration project is designed for coping with these challenging issues and boundary conditions. The toolbox to be developed will enable TSOs to ensure secure grid operation also in future electricity networks with high penetration of intermittent renewables. It enables TSOs to act in a coordinated European target system where regional strategies converge to ensure the best possible use of the European electricity infrastructure.


Grant
Agency: Cordis | Branch: FP7 | Program: CSA-CA | Phase: NMP.2013.4.0-6 | Award Amount: 1.33M | Year: 2013

The importance of aging of infrastructures, networks and industrial plants will continue to increase because of (a) need to continue operation of these infrastructures, networks and plants beyond the design life-time, (b) need to operate under changed conditions and (c) the increased role of existing plants in the optimized (smart) supply and utility networks of the future, e.g. as fall-back supply. The effective agreed strategies to address aging issues are yet to be developed and consistently applied. The project, SafeLife-X, will contribute to creating consensus on aging management including potential cascading and/or ripple effects. It will, thus, satisfy the demand within various industrial sectors and help match the EU Grand Challenges and the EU-2020 Strategy, and achieve goals of main stakeholders (e.g. EC, OECD, ECTP, ETPIS). The project will create a multi-disciplinary / multi-sector community able to answer the key issues related aging at EU & International level. The consortium includes members of the EU Technology Platforms ECTP (construction) and ETPIS (industrial safety) and a group of 25 experts to complement the expertise needed, and will be open to all interested parties. This community will meet, share experience and prepare a common vision for the future and main elements needed to realize it. The project will capitalize on best practices of modeling, asset integrity management, decision making, and cost-benefit analysis. CEN Workshop Agreement(s) will be initiated in the course of the project and the development of one European Standard (EN) on Risk-Based Inspection Framework pursued. New projects will propose input for Horizon 2020 within the Strategic Research Agenda & Roadmap. SafeLife-X will explore the issue of aging as an opportunity for new technologies, services and businesses primarily in service and construction sectors, the latter being the largest EU industrial employer representing 9.9% of the GDP and 14.9 million operatives.

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