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Nonlinear convex optimisation problems in the smart grid

Slager, Jarco (2019) Nonlinear convex optimisation problems in the smart grid.

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Abstract:The energy that is generated for our society is shifting from fossil fuels to renewable energy sources (i.e. wind and solar power). Due to the dependence on the sun and wind, power cannot always be generated when needed. To tackle this problem, smart grids have been introduced, in which we are able to store energy in and receive energy from smart appliances in the energy system. In order to distribute the energy efficiently, we formulate this distribution problem as a mathematical optimisation problem with the objective to minimise for example the power loss. These optimisation problems are nonlinear and convex and therefore solved via the primal-dual interior-point method (IPM). Even though this method is efficient, the algorithm will be run on embedded systems with low computational power. Therefore a gain in efficiency is desired. We discuss two models that arise in the smart grid, and show that the problem structure can be exploited to improve the computational complexity of the IPM algorithm. For both models, the time consuming step in the algorithm has been reduced from a worst-case time complexity of O(n^3) to O(n). Numerical tests for one of the models confirms this gain in efficiency in practice.
Item Type:Essay (Bachelor)
Faculty:EEMCS: Electrical Engineering, Mathematics and Computer Science
Subject:31 mathematics
Programme:Applied Mathematics BSc (56965)
Link to this item:https://purl.utwente.nl/essays/78669
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