Stochastic programming-based solution for active distribution network management considering energy efficiency

Author(s)

Darwin Alexis Quijano Rodezno

• Document type: Doctoral Thesis
• Press: Ilha Solteira. 2018-05-08.
• Institution: Universidade Estadual Paulista (Unesp). Faculdade de Engenharia. Ilha Solteira
• Defense date: 2018-04-19
• Advisor: Antonio Padilha Feltrin

Abstract

Nowadays, there is a trend to increase the participation of distributed generation (DG) based on renewable energy sources in supplying the global electricity consumption. This trend is being driven mainly by government initiatives to increase energy efficiency, convert the energy use to renewable sources and reduce greenhouse gas emissions. However, as its penetration level increases, the DG can give rise to a system unable to deliver energy reliably and according to quality standards. In this scenario, active network management (ANM) emerges as an alternative for the integration of large amounts of DG. ANM promotes the availability of commercial and regulatory instruments and the provision of distribution networks with automation technologies for procuring ancillary services and flexibility from the DG. ANM requires the development of computational tools to coordinate the implementation of intelligent control schemes, called ANM schemes, in order to optimize the utilization and operation of distribution networks. In this work, optimization models and solution techniques are proposed for ANM considering the integration of solar and wind-based DG and energy efficiency. The first model is developed to determine the maximum capacity of DG that can be allocated in a distribution network when considering the effect of voltage on load efficiency. In the second model, the procedure of controlling the voltage levels to reduce the load demand is implemented for energy saving and for balancing the demand and generation, in a strategy designed for the operation planning of active distribution networks. In both models the uncertainties are considered through two-stage stochastic programming formulations. The ANM schemes considered are the coordinated voltage control through voltage regulators and transformers with on-load tap changer, reactive power support from the DG, and DG generation curtailment. The solution technique involves the discretization of the probability density functions that define the uncertain parameters through a scenario generation and reduction process. Then, the Benders decomposition method is applied in order to reduce the computational effort required to solve the formulated problems. The developed algorithms were tested in two IEEE test systems and the results showed important benefits for the integration of DG and energy efficiency. (AU)

• FAPESP's process: 14/14201-0 - Integrated Volt-Var control in distribution networks with distributed generators
• Grantee: Darwin Alexis Quijano Rodezno
• Support Opportunities: Scholarships in Brazil - Doctorate