Research on Distribution Transformer Layout Planning Model of Distribution Networks Considering the Impact of Distributed Generation and Electric Vehicles
DOI:
https://doi.org/10.13052/spee1048-5236.4527Keywords:
Distributed generation, electric vehicles, transformer layout, probabilistic power flowAbstract
Under the background of the “dual-carbon” strategy and the ongoing energy structure transition, the rapid penetration of distributed generation (DG) and electric vehicles (EVs) has introduced bidirectional uncertainties on both the supply and demand sides of distribution networks. To address the limitations of traditional transformer planning methods that fail to simultaneously capture the stochastic characteristics of DG and EVs, this paper proposes a multi-objective optimization model for transformer layout planning considering source-load uncertainties. The model characterizes the stochastic outputs of photovoltaic and wind power using Beta and Weibull distributions, respectively, and adopts a Monte Carlo simulation framework to represent the spatiotemporal distribution patterns of EV charging loads, thereby achieving coordinated modeling of source-load randomness. On this basis, a probabilistic optimization framework is established to minimize the total life-cycle cost-including transformer investment, network losses, and outage losses-subject to voltage, current, and capacity constraints. Simulation results on the enhanced IEEE 33-bus network verify that the proposed method can effectively improve voltage regulation, cut line losses and operating costs, and sustain system stability under substantial DG and EV penetration. The research provides a systematic modeling approach and optimization reference for transformer planning in distribution networks with high renewable energy and EV integration.
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