Towards an optimal energy network topology by applying the cross‐entropy method

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Abstract

During the last decades awareness regarding the problems related to the future of our energy supply increased significantly. E.g. changing relations between countries threaten a secure and constant supply of energy towards those countries not able to meet their own energy demand. The melting of the ice caps due to global warming and the resulting sea level rise can be attributed to the increased amount of fossil fuels in the last few decades. To cope with these problems a transition from fossil fuels towards renewable energy sources is required. Although this process is ongoing, the current energy networks are not suited to support mass integration of distributed renewable energy sources. Nor has the current energy distribution system the possibility to cope with unexpected fluctuations in the supply of energy. In this presentation we will illustrate the ongoing development of an algorithm which can eventually determine the optimal layout of an energy distribution network that can handle mass integration of renewable energy sources and can cope with fluctuations in the supply of energy. Coping with these fluctuations requires the topology optimization of all different energy networks and their possible interaction. Therefore the fundamentals of the optimization algorithm can be applied to different energy carriers. By altering the boundary conditions it can be applied to a network with an arbitrary carrier. Those details involve the calculations required to determine the flow or current and involve the calculations required to determine the operating and investment costs. This method uses path finding algorithms in combination with thermal energy flow models. The first, when applied to the pipelines in the district thermal network, help maximizing the number of connected consumers, while the latter help minimize e.g. energy losses. Different optimization algorithms have been applied, e.g. the genetic algorithm, simulated annealing and the cross-entropy method. The advantages and disadvantages of each method will be explained. In the near future, with the application of the presented approach, energy networks can cope with current and future problems, while being constructed against optimized investment and operating costs.
Original languageEnglish
Title of host publicationSustainable Places Conference Proceedings, 1-3 October 2014, Nice, France
EditorsH. Andrianantenaina, R. Decorme, S. Robert
Pages29-
Publication statusPublished - 2014

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