Coordinated scheduling and optimization of networked microgrids in active distribution systems

Parsibenehkohal, Reza (2024) Coordinated scheduling and optimization of networked microgrids in active distribution systems. Masters thesis, Memorial University of Newfoundland.

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Abstract

The global shift towards renewable energy sources, such as solar and wind power, along with the increasing adoption of electric vehicles (EVs), is driving transformative changes in modern power systems. These developments are essential for reducing greenhouse gas emissions and advancing the transition towards a sustainable energy future. However, the decentralized and intermittent nature of renewable energy, coupled with the growing demand for EV charging, presents significant challenges in maintaining stability, reliability, and cost-effectiveness within active distribution networks. Traditional power systems, designed for centralized and predictable energy generation, struggle to adapt to these changes, necessitating innovative approaches to energy management. This thesis develops a comprehensive framework for the coordinated scheduling of networked microgrids, with a focus on the economic and environmental impacts of integrating hydrogen refueling stations and EV charging infrastructure. Microgrids, as localized energy systems that can operate independently or alongside the main grid, offer a promising solution to the challenges of integrating renewable energy. However, managing these microgrids, particularly in the context of EVs and hydrogen refueling stations, requires advanced optimization techniques to ensure that they operate reliably and efficiently while minimizing costs and environmental impacts. The proposed framework employs a two-stage stochastic programming approach to optimize microgrid operations under varying conditions. The first stage focuses on defining microgrid service areas, taking into account security constraints during emergency scenarios such as grid outages. The second stage addresses energy management, optimizing the integration of renewable energy sources, EV and fuel cell vehicle (FCV) charging stations, and flexible loads. The goal is to balance operational costs, maximize the use of renewable energy, and reduce emissions. The optimization model is implemented using the GUROBI solver within the GAMS (General Algebraic Modeling System) environment, enabling efficient computation of complex, multi-objective optimization problems. By balancing economic and environmental objectives, the framework provides a robust solution for managing microgrids under diverse conditions. To validate the framework, simulations were conducted using the IEEE 118-bus test system. This well-established benchmark represents a large-scale power grid and allows for rigorous testing of the framework’s performance in real-world scenarios. Simulation results demonstrate significant improvements in both economic and environmental performance. Specifically, the integration of flexible loads and smart EV and FCV charging strategies reduced operating costs by approximately 4.77% and emissions by 49.13%. These findings underscore the potential of the proposed framework to contribute to sustainable energy management by providing a scalable approach for optimizing microgrid operations. By promoting economic efficiency and supporting the integration of clean energy technologies, this research aligns with global efforts to decarbonize power systems and reduce reliance on fossil fuels. Additionally, the integration of hydrogen refueling stations within microgrids offers new opportunities for energy storage and management, further supporting the transition to a low-carbon transportation sector. In conclusion, this thesis makes a significant contribution to sustainable energy management by developing a robust framework for the coordinated scheduling of networked microgrids. The integration of hydrogen refueling and EV charging infrastructure enhances grid flexibility and resilience, while advanced optimization techniques ensure that economic and environmental goals are achieved. Validation of the framework using the IEEE 118-bus test system confirms its applicability to real-world power systems. The findings highlight the critical role of microgrids in the global transition to cleaner, more sustainable energy systems.

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