Session: 03-04: Innovative Energy Storage Solutions for Resilient Communities

Paper Number: 164841

164841 - Multi-Objective Optimization of Renewable Energy Communities: Integrating Hybrid Storage and Life Cycle Assessment for Sustainable Energy Management 

Abstract: 

Renewable Energy Communities (RECs) that incorporate renewable energy sources are redefining traditional power grids by decentralizing generation and enhancing local autonomy. This shift yields numerous benefits, including diminished reliance on external utilities and heightened energy self-sufficiency. Nevertheless, the inherent variability of resources such as photovoltaic (PV) and solar thermal energy necessitates sophisticated energy management strategies to uphold grid stability and optimize on-site consumption. In this context, energy storage technologies are indispensable, offering both rapid buffering to address immediate supply-demand imbalances and longer-term storage to accommodate seasonal fluctuations. This study introduces a comprehensive multi-objective optimization framework that concurrently addresses electrical and thermal demands. The framework employs Life Cycle Assessment (LCA) indicators - encompassing carbon emissions, mineral and metal depletion, water consumption, and land use - to inform both system sizing and operational scheduling. These environmental indicators are derived from an extensive literature review, which led to the development of a dataset with values normalized per unit of component capacity rather than per unit of energy delivered over the system’s lifetime. This methodological approach enhances the integration of environmental metrics into energy system optimal design, allowing for more straightforward incorporation into multi-objective optimization frameworks. By integrating these sustainability metrics alongside economic objectives, the approach identifies system configurations that minimize costs while mitigating overall environmental impacts, thereby providing a robust methodological basis for designing RECs with considerations of efficiency, affordability, and ecological control. The proposed energy system encompasses several key components. Solar thermal collectors feed heat into a thermal energy storage unit, thereby enabling consistent supply despite daily and seasonal variations in solar availability. Concurrently, PV panels generate electricity that can be consumed directly, stored in a battery energy storage system, or supplied to an electrolyzer for hydrogen production. This hydrogen is subsequently compressed and stored for later reconversion to electricity through a fuel cell, thus ensuring long-term system flexibility. A backup boiler addresses any residual heating needs, and surplus electricity can be exported to the main grid when generation exceeds demand. This hybrid scheme, integrating battery-based, hydrogen-based, and thermal storage solutions, significantly enhances resilience against fluctuations in renewable resource availability. This optimization framework is implemented in Calliope, an open-source energy system modeling tool designed for multi-carrier applications. Its weighted objective function accounts for both economic and environmental dimensions, refined by specialized features such as asynchronous production-consumption settings and storage-specific constraints. By co-optimizing system investment and operational decisions, the framework supports the exploration of various solutions, each embodying distinct trade-offs among cost, greenhouse gas mitigation, and resource depletion. The central research question focuses on effectively integrating and managing these diverse energy carriers - batteries, hydrogen, and thermal reserves - to achieve dual objectives of economic viability and ecological responsibility. The study further examines how embedding LCA-based criteria influences vital aspects of system configuration, including component sizing and scheduling policies, thereby highlighting the practical implications of incorporating environmental costs into decision-making. The anticipated outcomes of this analysis include increased self-sufficiency through the coordinated operation of multiple storage technologies that collectively address various timescales of intermittency. Additionally, the framework is expected to bolster operational flexibility, reducing dependence on external electricity markets while allowing the potential sale of surplus electricity during periods of excess generation. Furthermore, the intentional integration of LCA considerations is projected to facilitate significant reductions in greenhouse gas emissions and other environmental burdens. Nonetheless, the investigation acknowledges that these gains require a careful assessment of trade-offs among investment in specialized technologies, operational synergies, and broader ecological benefits.

Presenting Author: Elena Rozzi Politecnico di Torino

Presenting Author Biography: She received her master’s degree in Energy and Nuclear Engineering from Politecnico di Torino in 2018 and is currently a Ph.D. candidate in Energetics. Her research focuses on the decarbonization of the energy sector, with a particular emphasis on hydrogen storage and transport, energy management, and sector coupling. She works on optimization and machine learning models applied to energy networks, hydrogen integration into the gas system, and emission reduction in the energy sector.