Market equilibrium analysis considering electric vehicle aggregators and wind power producers without storage capabilities

This document is devoted to analyze market equilibrium solutions when new market agents, such as renewable/intermittent producers, elastic demands and electric vehicles, are exposed to time-varying Locational Marginal Prices in the context of a competitive electricity market. We consider three main features for these market agents: Load demands are deemed to be elastic, being fully responsive to price changes Renewable-based producers, such as wind farms are not dispatchable in real power and deprived of storage capabilities. Electric-vehicle retailers --defined as EV aggregators-- are able to manage charge-discharge pattern of EV's batteries in order to enhance daily profits due to energy traded in the wholesale electricity market. After a brief discussion about different economic equilibrium models in power systems (Perfect competition, Nash-Cournot, Stackelberg and Monopoly), two economic equilibrium models are studied in detail. First, we analyze the perfect competition solution driven by a benevolent planner in which real and reactive power dispatches as well as the battery charge-discharge schedule aims to maximize the global social welfare. Secondly, we also address the monopolistic solution where the total profit of EV aggregators and renewable generators are maximized considering that both producers belong to the same firm. Solutions were obtained using a multi-period alternating current optimal power flow (AC-OPF) formulation in which nodal reactive power injections can be modified by renewable generators and EV aggregators in order to shift the locational marginal prices to their own benefit. The 24-hour AC-OPF was stated as the maximization problem subject to active and reactive power equilibrium equations as well as battery capacity constraints. The perfect competition and monopolistic system models were applied to an illustrative 3-node test system. Optimization problems were solved using MATLAB's fmincon optimization tool.

• Autores: Díaz Caballero, Óscar Andrés
• Tipo de recurso: Trabajo de grado de pregrado
• Fecha de publicación: 2019
• Institución: Universidad de los Andes
• Repositorio: Séneca: repositorio Uniandes
• Idioma: eng
• OAI Identifier: oai:repositorio.uniandes.edu.co:1992/45179
• Acceso en línea: http://hdl.handle.net/1992/45179
• Palabra clave: Sistemas de energía eléctrica; Teoría de los juegos; Bienestar social; Ingeniería
• Rights: openAccess
• License: https://repositorio.uniandes.edu.co/static/pdf/aceptacion_uso_es.pdf