Optimizing renewable integration in electrical grids: a comparative analysis of infrastructure enhancements, energy storage, and demand response

This thesis presents an optimization framework designed to integrate renewable energy sources (RES) into existing electrical grids, focusing on reducing operational costs, managing congestion, and ensuring grid stability. The framework evaluates the impact of integrating wind, solar energy, and ener...

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Detalles Bibliográficos
Autor: Bangi, Sanjay
Tipo de recurso: tesis de maestría
Fecha de publicación:2024
País:España
Institución:Universitat Politècnica de Catalunya (UPC)
Repositorio:UPCommons. Portal del coneixement obert de la UPC
Idioma:inglés
OAI Identifier:oai:upcommons.upc.edu:2117/419802
Acceso en línea:https://hdl.handle.net/2117/419802
Access Level:acceso abierto
Palabra clave:Electric power systems
Energy storage
Renewable energy sources
Sistemes de distribució d'energia elèctrica
Energia--Emmagatzematge
Energies renovables
Àrees temàtiques de la UPC::Energies::Recursos energètics renovables
Descripción
Sumario:This thesis presents an optimization framework designed to integrate renewable energy sources (RES) into existing electrical grids, focusing on reducing operational costs, managing congestion, and ensuring grid stability. The framework evaluates the impact of integrating wind, solar energy, and energy storage systems (ESS) into the Barcelona region's electrical grid. The key objective is to minimize total system costs while meeting grid constraints such as transmission line capacities and demand variability. The thesis develops and implements a linear optimization model using Python-based tools like scipy.optimize.linprog for optimization and pandapower for power flow simulations to ensure grid reliability. The study considers four different scenarios: a baseline with no renewables, peak load shifting, integrated renewable energy (wind and solar), and renewables coupled with energy storage. In each scenario, energy dispatch is optimized to minimize operational expenditures, taking into account congestion issues that occur when line loadings exceed 80%. The baseline scenario serves as a reference, relying solely on nuclear and Combined Cycle Gas Turbine (CCGT) plants. Peak load shifting attempts to reduce costs by shifting demand from peak to off-peak periods, while the integration of renewable energy introduces variability that requires additional grid management strategies. The final scenario, which includes energy storage, demonstrates the potential for stabilizing the grid by storing excess renewable energy during low demand periods and dispatching it during peak hours. Results from power flow simulations highlight the benefits of integrating RES, particularly when paired with ESS, which reduces the need for expensive backup generation and lowers overall system costs. However, challenges such as wind energy curtailment due to grid congestion persist, even after grid upgrades. The thesis concludes that while renewable integration with storage can enhance grid flexibility and reliability, further advancements in grid infrastructure and demand response strategies are necessary to fully harness renewable potential.