The goal of this one day workshop is to exhibit the opportunities to do interesting mathematical research inspired by the latest developments in energy networks.
This workshop will be held at the Amsterdam Science Park Conference Halls.
| 10:00 - 10:45 | Kees Vuik (Delft) |
| 10:45 - 11:30 | Han la Poutre (CWI) |
| 11:30 - 12:00 | break |
| 12:00 - 12:45 | Stella Kapodistria (Eindhoven) |
| 12:45 - 14:00 | lunch |
| 14:00 - 14:45 | Arjan van der Schaft (Groningen) |
| 14:45 - 15:30 | Rob Kooij (TNO) |
| 15:30 - 16:00 | break |
| 16:00 - 16:45 | Dan Bienstock (Columbia University) |
| 16:45 - 18:00 | drinks |
Participation is free, but please complete the registration form for catering purposes. Information
Travel directions can be found on the Science Park Congress Centre website. For further information, please contact the organisers
Daan CrommelinNetworks for the high-voltage distribution of electrical energy are currently undergoing far reaching developments. National power grids are evolving from static entities, producing mainly a uni-directional flow from generation to loads, to more dynamic and decentralized structures. These emerging power systems should accommodate the local generation by renewable sources and peak demands of electrical vehicle charging. The cross-border interconnection of power grids further imposes new challenges in the design, planning and daily operation of these networks. In this presentation an overview of the various research projects done in the chair of numerical analysis at the TU Delft are presented. Topics are:
Reference:
D. Lahaye and C. Vuik
Computational challenges in electrical power networks
Nieuw Archief voor Wiskunde, Vijfde serie, 16, 244-245, 2015
http://ta.twi.tudelft.nl/nw/users/vuik/papers/Lah15V.pdf
Sustainable energy becomes more and more important in our society, like from solar cells or wind turbines. However, sustainable energy generation typically is uncertain, since it is depending on e.g. local weather conditions. In addition, heavy energy demand will further grow, like for e-vehicles and heat pumps. Smart Grids, the future electricity networks, aim to deal with these kind of developments. In Smart Grids, ICT (Information and Communication Technology) will play an important role to deal with these uncertainties and developments. We will present important results, interesting developments, and open challenges for ICT in the field of Smart Grids.
We are interested in the performance of a wind turbine for maintenance and power pricing management purposes. For maintenance purposes, we will show how to explore the Supervisory Control and Data Acquisition (SCADA) data, available with every wind turbine, in order to build condition based maintenance (CBM) approaches for the main components of the system. More concretely, in this talk, we will explore concepts from statistics and connect them to stochastic processes. In particular, we will use statistical concepts stemming from Statistical Process Control (SPC) and we will connect them to CBM and first passage times. To this purpose, we will use as a paradigm, mainly for illustration and simplicity purposes, the connection between the Shewhart control chart with the “On-Off” stochastic process.
For the power pricing management purposes it is necessary to develop models that accurately forecast the power output of a wind turbine. As a first step and following the guidelines of the existing literature, see, e.g., [1], we used the SCADA data to model the wind turbine power curve (WTPC). We explored various parametric and non-parametric modelling techniques for the modelling of the WTPC, such as the linearised segmented model, polynomial power curve, maximum principle method, dynamical power curve, parametric logistic functions, copula power curve model, cubic spline interpolation technique. All of them (using a baseline from the historical data and performing comparisons) seem to have an intrinsic limitation in terms of accuracy, making the corresponding model inappropriate for forecasting. To avoid this conundrum, we will show that adding a properly scaled autoregressive–moving-average (ARMA) modelling layer increases short term prediction performance while keeping the long term prediction capabilities of WTPC models. Moreover, we will validate the ARMA model using historical data.
The first part on the maintenance is joint ongoing work with Alessandro Di Bucchianico (TU/e) and Bert Zwart (CWI) and the second part on the power pricing management is joint ongoing work with Sándor Kolumbán and Nazanin Nooraee (TU/e)
[1] Lydia, M., Kumar, S. S., Selvakumar, A. I., & Kumar, G. E. P. (2014). A comprehensive review on wind turbine power curve modeling techniques. Renewable and Sustainable Energy Reviews, 30, 452-460.
The increasing share of renewable energy sources in the electricity distribution has led to a major re-thinking of the operation of the power grid, posing several fundamental problems. The power grid is a fascinating example of a highly complex engineering network. The presence of several control mechanisms is adding to the complexity. The stability, robustness and optimality of the resulting dynamics is difficult to assess and to improve.
Furthermore, standard modeling approaches for power networks tend to be patchy, and do not provide a clear starting point for accurate and scalable analysis, control and optimization techniques. In this talk I will report about recent work on the combination of physical network dynamics of the grid with market dynamics, which is part of a larger effort on various aspects of modeling and control of power networks carried out in collaboration with the control engineering groups in Groningen.
Main references:
In this talk we present three results related to the assessment of the robustness of energy networks. The first result concerns cascading failures in power grids. It is known that cascading failures are one of the main reasons for blackouts in electric power transmission grids. The economic cost of such failures is in the order of tens of billion dollars annually. The loading level of power system is a key aspect to determine the amount of the damage caused by cascading failures. We will propose a model that quantifies the damage due to cascading failures in terms of spectral graph metrics, representing both the topology of the network as well as physical properties of the network. Experimental results applied to IEEE test systems demonstrate the applicability of these metrics. Next we look at the robustness of a communication network which depends on the proper functioning of an electricity network. The strategies involve selecting nodes of the communication network and removing their dependency to the electricity network. These selected nodes will be named autonomous nodes. We will model the electricity network realistically by not only looking at the topological structure, but also taking the essential characteristics of the power flow into account. The effect of cascading failures originating from the electrical grid, on the communication network is studied, where the coupling between those networks plays an important role. We have validated robustness optimization strategies by averaging over many configurations of communication networks, applied to electricity network formed by the IEEE-118 bus test system. Our method is also tested on a real-world interdependent network: the high voltage electricity grid in Italy coupled with a communication network, inspired by the Italy blackout in 2003. Finally, we present a method to compute the all-terminal availability and the k-terminal availability of a real life gas distribution network with 20567 nodes and 20749 edges. The method first performs reductions on the network and afterwards uses a decomposition algorithm. The decomposition algorithm is exponential in the pathwidth of the graph. Some improvements and extensions of the method are suggested.
The field of Electrical Power Engineering is undergoing rapid change, spurred by increasing demands for efficiency, the availability of new technologies, the drive to incorporate renewables and the need for increased security. As such, this field presents unparalleled opportunities for Operations Research.
To put it more precisely, there are substantial opportunities both for developing new research problems within the Operations Research domain, and also for creating contributions to the practice of Power Engineering.
In this talk we will survey a number of problem areas, survey previous work, and discuss challenges.