Session: 09-07-01: Energy Sustainability for Buildings and Cities

Paper Number: 165412

Enhancing Flexibility in Integrated Building Energy Systems: A Marginal Cost and Demand-Side Optimization Approach 

The building sector accounts for a significant portion of global energy consumption and greenhouse gas (GHG) emissions, making it a key focus for achieving climate and sustainability goals. In the context of increasing renewable energy penetration, improving energy flexibility in buildings is becoming a crucial strategy for enhancing grid stability, reducing peak demand, and minimizing fossil fuel reliance. Energy flexibility refers to a building’s ability to dynamically adjust its energy demand and supply in response to external conditions such as fluctuating electricity prices, grid congestion, and renewable energy availability. Traditional building energy systems typically follow static rule-based control strategies, which often result in suboptimal performance due to their limited ability to adapt to changing conditions. This inefficiency not only leads to higher operational costs but also restricts the full potential of renewable energy utilization. This study aims to address these challenges by employing an optimization-based approach to enhance energy flexibility in buildings. Specifically, a mixed-integer programming (MIP) model is developed using Python and the GLPK solver to optimize energy dispatch and demand-side management. The methodology is applied to a case study of a building in Dublin, which is equipped with a heat pump, a gas boiler, photovoltaic panels, and thermal energy storage The objective is to evaluate the building's flexibility potential by comparing two control strategies: (i) a traditional rule-based approach, which follows predefined operational schedules for heating and electricity use and (ii) a dynamic optimization algorithm, which minimizes daily operational costs while managing both thermal and electrical demands in response to real-time grid conditions.

The results demonstrate that the optimization-based control strategy significantly outperforms traditional rule-based methods in multiple aspects. The optimized approach leads to lower operational costs, improved energy efficiency, and reduced fossil fuel consumption, primarily by intelligently coordinating the use of thermal storage and renewable generation. The ability to shift energy consumption to periods of higher renewable energy availability also contributes to greater grid flexibility and a more stable electricity system. Scenarios that prioritize renewable energy integration and flexible energy use show the highest potential for cost savings and emission reductions. By shifting peak loads and utilizing stored energy effectively, the optimized strategy smooths demand peaks, making buildings more responsive to grid signals and electricity price variations. These findings highlight the crucial role of advanced optimization algorithms in future-proofing buildings for a decarbonized energy landscape.

This study provides valuable insights for building owners, energy policymakers, and researchers, demonstrating that intelligent control strategies can significantly enhance energy flexibility while contributing to a more resilient and sustainable built environment. Future research should expand this approach to district-level energy management, incorporate a wider range of demand-response strategies, and explore higher-resolution temporal models to further refine flexibility-driven energy solutions.

Presenting Author: Annalisa Bringiotti Università degli Studi di Genova

Presenting Author Biography: I am a PhD student in mechanical engineering at the University of Genoa, with previous research experience at Maynooth University. My research focuses on building retrofitting, with particular interest in energy flexibility, optimization algorithms, and demand-side management. Throughout my work, I have explored innovative approaches to enhancing energy efficiency in buildings, aiming to develop optimized control strategies that reduce operational costs, lower fossil fuel dependency, and support grid stability. I am committed to advancing research and practical applications in sustainable energy systems, leveraging both theoretical insights and hands-on experience to contribute to the decarbonization of the built environment.

Authors:

Annalisa Bringiotti Università degli Studi di Genova
Mehdi Ali Ehyaei Università degli Studi di Genova
Fabiano Pallonetto Maynooth University
Mattia De Rosa Università degli Studi di Genova