Yenilenebilir enerji üretimi entegre edilmiş elektrik şebekelerinde trafo merkezlerinin planlanması

A suitable probabilistic scenario set of load demand and natural characteristics of renewable energy is becoming a crucial issue in power system planning studies. The optimal planning of substation expansion is achievable through proper modeling of input parameters which describes the characteristics of the service areas. In that point, the disparity between the required resources for adequate and flexible power systems and the budget available to planners necessitates choosing between different expansion strategies. Under these circumstances, making investment plans with a convenient risk management strategy is crucial in order to maintain the balance between the cost and system adequacy. In this thesis, the SEP problem is handled from a risk management point of view by integrating different investment strategies. On the one hand, the co-existence of PV plants and the load in a service area under three different states such as daytime with clear-sky and no-fault, daytime with abnormal events, and nighttime are incorporated into the stochastic dynamic sub-transmission SEP, in which the decision-maker chooses the risk-neutral and risk-averse strategies, through systematic probabilistic scenario tree generation. The comparison between integrating inherent characteristics of PV plants with and without considering abnormal events into the optimization is performed to show the impact of a suitable probabilistic model on the dynamic nature of investment decisions. On the other hand, the distribution SEP problem in which the decision-maker chooses the risk-seeker strategy is merged with the different geographical configurations of the zones within a mixed-integer linear programming (MILP) framework by using approximate lumped models.