利用动态变压器增容与动态网络重构协同优化消纳配电网中弃风弃光

Renewable energy sources (RESs) are highly integrated into today's distribution systems to provide a clean and sustainable supply for electric load demands. However, due to radial configuration, voltage limits, equipment capacity, and other constraints, a portion of RESs’ output power is inevitably curtailed, which is undesirable given the clean and fuel-free nature of RESs. In this paper, dynamic transformer rating (DTR) as a smart-grid technology is coordinated with dynamic distribution network reconfiguration (DDNR) to minimize photovoltaic (PV) and wind energy curtailment. The thermal model of the transformer and all network constraints are considered within an optimization model. The basic problem is a mixed-integer-nonlinear-programming (MINLP) model with non-convex nature. The model is reformulated as a mixed-integer quadratic-constrained programming (MIQCP) to achieve a convex model providing global optimum solution. Several experiments are simulated in the GAMS environment on the IEEE 33-node grid to demonstrate the efficacy of the proposed method. The results show that DTR enables maximizing renewable energies scheduling without loss of life (LOL) of the transformer while satisfying all the problem constraints. With the proposed model, the scheduling of solar and wind energies scheduling is increased by 8.22%, while energy loss is reduced by 21%.