Desenvolvimento de uma plataforma Python/PSCAD para gerenciamento ativo de recursos energéticos distribuidos em redes elétricas

Abstract

The operation of electric energy networks has become a challenge due to the incentive for Distributed Generation (DG) and the high insertion of variable alternative sources, which can generate technical and economic impacts, whose evaluation must be associated with control techniques that mitigate possible problems. With this, a solution known as Active Network Management (ANM), allows a decision-making algorithm to adjust parameters of equipment connected to the electrical system, based on the detection of violation of restrictions technical and/or economic. In this scenario, Energy Storage Systems (ESSs) can be crucial in controlling the power injected by renewable sources, however, due to their high cost, the management of ESSs by the ANM must consider, in addition to technical criteria to support the grid, criteria to make such investments attractive. With this, the present work proposes the development of a simulation platform that integrates software PSCAD with the Python language, seeking to create a tool that portrays realistic and dynamic characteristics of the operation of an electrical system with PSCAD, in addition to enable the application of a control algorithm through the Python environment. Using the Python/PSCAD platform, an electrical network with photovoltaic systems (PVs), electric vehicles (EVs) and battery banks will be modeled in software PSCAD, as well as local, coordinated and optimization controls. Local and coordinated controls were implemented in PSCAD programmable blocks and act on network undervoltage and overvoltage problems. In the python Interface, the optimized control was implemented, an optimization algorithm based on a Model Predictive Control (MPC), which determines the optimal operating curve of the battery banks at each hour of simulation, with the objective of reducing the cost of operating the system. Local controls are applied to PV system converters. The coordinated and optimized controls, in turn, act together in the bidirectional converter of the battery banks, with the coordinated control having priority for acting on the voltage profiles of the electrical network in times of violation and the optimized control in times when the voltage of the system is within established limits. The obtained results show that the local and coordinated controls are able to act and correct under and overvoltage problems, while the optimized control is able to reduce the cost of operating the network when enabled. Thus, the proposed platform performs the technical-economic monitoring of the distribution system, becoming a promising tool for the creation of algorithms for active management of electrical networks in dynamic simulations.