Smart transformer Modelling in Optimal Power Flow Analysis
The smart transformer (ST) implemented using power electronics converters, has the capability of independent voltage control and reactive power isolation between its primary and secondary terminals. This capability provides a flexibility in the power system to support the voltage at the primary side and control the demand at the secondary side. Using this flexibility, the system power flow could, for example, be optimized for lower costs. This paper proposes an ST model suitable for OPF analysis. The effects of using multiple STs at different penetration levels, on the daily generation costs in an IEEE 39 bus test system are presented.
Code (0)
등록된 구현이 없습니다.
Tasks
STSSimilar Papers 제목 키워드 기반
A Comprehensive Multi-Period Optimal Power Flow Framework for Smart LV Networks
This paper presents an extensive multi-period optimal power flow framework, with new modelling elements, for smart LV distribution systems that rely on residential flexibility for combating operational issues. A detailed…
Optimal Power Flow for Integrated Primary-Secondary Distribution Networks with Center-Tapped Service Transformers
Secondary distribution networks (SDNets) play an increasingly important role in smart grids due to a high proliferation of distributed energy resources (DERs) in SDNets. However, most existing optimal power flow (OPF) pr…
Decision MakingScalable Heterogeneous Graph Foundation Models for Data-Driven Optimal Power Flow in Smart Grids
Fast and reliable optimal power flow (OPF) approximation is essential for reliable smart-grid operation, yet many learning-based surrogates either flatten the native heterogeneous structure of power networks, target a li…
Hyperparameter OptimizationGraph Neural NetworkSmart-PGSim: Using Neural Network to Accelerate AC-OPF Power Grid Simulation
The optimal power flow (OPF) problem is one of the most important optimization problems for the operation of the power grid. It calculates the optimum scheduling of the committed generation units. In this paper, we devel…
SchedulingOptimal Management of the Peak Power Penalty for Smart Grids Using MPC-based Reinforcement Learning
The cost of the power distribution infrastructures is driven by the peak power encountered in the system. Therefore, the distribution network operators consider billing consumers behind a common transformer in the functi…
ManagementModel Predictive ControlReinforcement Learning (RL)