Mathematical optimization of unbalanced networks operation with smart grid devices

• Ano de defesa: 2018
• Autor(a) principal: Sabillón Antúnez, Carlos Francisco
• Tipo de documento: Tese
• Tipo de acesso: Acesso aberto
• Idioma: eng
• Instituição de defesa: Universidade Estadual Paulista (Unesp)
• Palavras-chave em Português: Distribution network operation; Mathematical optimization; Mixed integer linear programming; Smart grids devices; Steady-state operation point; Dispositivos de redes inteligentes; Operação de rede de distribuição; Otimização matemática; Ponto de operação em regime permanente; Programação linear inteira mista
• Link de acesso: http://hdl.handle.net/11449/154075

Electric distribution networks should be prepared to provide an economic and reliable service to all customers, as well as to integrate technologies related to distributed generation, energy storage, and plug-in electric vehicles. A proper representation of the electric distribution network operation, taking into account smart grid technologies, is key to accomplish these goals. This work presents mathematical formulations for the steady-state operation of electric distribution networks, which consider the unbalance of three-phase grids. Mathematical models of the operation of smart grid-related devices present in electric distribution networks are developed (e.g., volt-var control devices, energy storage systems, and plug-in electric vehicles). Furthermore, features related to the voltage dependency of loads, distributed generation, and voltage and thermal limits are also included. These formulations constitute a mathematical framework for optimization analysis of the electric distribution network operation, which could assist planners in decision-making processes. Different objectives related to technical and/or economic aspects can be pursued within the framework; in addition, the extension to multi-period and multi-scenario optimization is discussed. The presented models are built based on mixed integer linear programming formulations, avoiding the use of conventional mixed integer nonlinear formulations. The application of the presented framework is illustrated throughout control approaches for plug-in electric vehicle charging coordination, voltage magnitude control, and renewable distributed generation control. Several methods are developed, based on this framework, to optimize the operation of unbalanced distribution systems considering not only different penetrations of electric vehicles and renewable energy sources but also the presence of storage systems and volt-var control devices. In this regard, dynamic scheduling and rolling multi-period optimization are often used to achieve optimal economic operation in the grid. The effective and robustness of the methodologies, as well as the reliability of the mathematical framework, are verified using many test systems (e.g., 123-node, 34-node, and 178-node) with medium and low voltage nodes, different operation control time frames, and several control availabilities related to the smart grid devices.