| Abstract: |  This diploma thesis investigates the topic of intelligent optimisation of schedules for charging and discharging of electric vehicles (EVs). At first, we carry out a research on related topics of Smart Grids and vehicle-to-grid transactions, and then, we examine existing studies solving the problem, including an application of a binary particle swarm optimisation (BPSO). Subsequently, disadvantages and weaknesses of the investigated methods are identified.
We then reformulate the problem definition and its representation to dispose of the major drawbacks identified before. The modified formulation emerges a continuous optimisation problem, which for we propose a particle swarm optimisation (PSO) application. To eliminate remaining drawbacks, the algorithm implements a penalty function for penalising inconsistent solutions, and an alternative fitness function reflecting the battery degradation costs.
Finally, the implemented algorithm is confronted with the BPSO method, and it is verified that the proposed PSO implementation significantly outperforms the other algorithm in terms of quality of the best found solutions, and in terms of time efficiency as well.
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