Optimal design of low carbon, multi-energy systems

The growing impact of climate change has made the transition to a low-carbon energy
system more urgent than ever. As cities are responsible for most energy consumption
and greenhouse gas emissions, integrating renewable energy sources and storage into
urban energy systems is critical to meeting global climate goals. This thesis aims to
develop and evaluate an optimization framework that enhances the design and operation
of urban energy systems by integrating various renewable energy sources and energy
storage technologies. The proposed framework addresses the key challenges of variable
renewable energy, such as solar energy, by employing multi-objective optimization, multi-
criteria evaluation, and uncertainty analysis to identify and assess effective solutions for
energy efficiency, reliability, and carbon neutrality.
Multi-energy systems, which integrate diverse energy sources and storage technolo-
gies, form the foundation of the proposed framework. It has been applied to several
energy systems, including District Heating systems, Renewable Energy Communities,
and Positive Energy Districts. Case studies were used to assess the economic and envi-
ronmental performance of various configurations, offering insights into strategies that
can facilitate the transition to low- or zero-carbon systems, such as increasing energy
efficiency, integrating diverse technologies, and expanding renewable energy shares.
First, this study focuses on the integration of Solar Thermal Collectors (STC) and
Thermal Energy Storage (TES) within existing Combined Heat and Power systems. The
findings indicate that integrating STC and TES can significantly enhance performance,
achieving a 10% reduction in carbon emissions and a 3% decrease in annual total costs.
This study highlights the importance of operational flexibility through peak load shaving
and load valley filling, ultimately increasing system efficiency from 88% to 92% with
the optimal configuration.
Next, Renewable Energy Communities are investigated by proposing a comprehen-
sive optimization framework incorporating short-term and long-term energy storage
solutions. The analysis demonstrates that a hybrid approach, including batteries, hydro-
gen production, and TES, can achieve an impressive Self-Sufficient Ratio (SSR) of 89%,
effectively doubling the SSR compared to systems without energy storage. It is empha-
sized that hydrogen storage is essential for exceeding SSR levels of 60%, illustrating
the synergistic relationship between local variable renewable energy sources and storage
capacities.
Hybrid Renewable Energy Systems are assessed under uncertainty, incorporating
various storage technologies such as batteries, TES, and hydrogen. The multi-objective
optimization framework examines trade-offs between levelized cost of energy (LCOE)
and carbon intensity. The comprehensive uncertainty analysis shows that adequate energy
storage is crucial for achieving zero emissions, with the hybrid configuration yielding
the lowest LCOE (0.446 C/kWh) at zero emissions.
Finally, a holistic framework is introduced for transitioning to Positive Energy Dis-
tricts (PED), emphasizing the importance of engaging multiple stakeholders and utilizing
diverse key performance indicators. A case study in the Usquare district of Brussels
demonstrates that expanding photovoltaic capacity is crucial for achieving PED targets.
Additionally, integrating demand-side management, battery storage, and retrofitting
existing buildings enhances system flexibility, reduces energy demand, and increases
profitability, all supporting carbon neutrality.
Overall, this thesis provides valuable insights and practical guidance for optimizing
the design and operation of low-carbon energy systems, contributing to the overarching
goal of achieving carbon neutrality in urban areas by 2050.