Abstract
The global shift to clean energy is transforming how energy is produced and consumed, driven by the need to reduce carbon emissions and reliance on fossil fuels. This transition is accelerating the electrification of sectors such as transportation and heating, increasing the integration of renewable energy sources and stressing the electricity grid due to the mismatch between renewable supply and fluctuating demand. As a result, traditional centralized grids are evolving into decentralized networks with bidirectional energy flows, supported by adaptive management solutions like demand-side management and smart devices.
A key development in this transition is the rise of Energy Communities (ECs) and Energy Management Systems (EMSs). ECs allow households, businesses, and institutions to collaborate within local energy systems, while EMSs coordinate resources like solar panels, batteries, and flexible loads. This thesis introduces a decentralized EMS framework designed for future ECs, leveraging multi-objective optimization to efficiently manage distributed energy resources (DERs) and flexible assets. The approach models both physical and cyber layers of energy systems, enabling real-time data exchange and decentralized control.
The thesis first presents a Multi-Objective Energy Management System (MOEMS) that uses advanced optimization to balance cost, emissions, and grid stability, with a centralized controller adapting to user preferences. Building on MOEMS, a Decentralized Multi-Objective EMS (DMOEMS) distributes decision-making among local controllers, enhancing scalability and resilience. DMOEMS integrates conflicting objectives, cost, emissions, PV curtailment, self-consumption, congestion, and voltage management, using user-defined weights, with controllers optimizing local assets while the EC controller coordinates aggregated profiles.
Simulation studies in real-world settings, including the Aardehuizen community and KEZO research lab, demonstrate the adaptability of MOEMS and DMOEMS. MOEMS achieves up to 22% annual electricity cost savings and 37% CO2 reduction compared to traditional EMSs. DMOEMS further improves CO2 emissions, cost savings, PV curtailment, and computational efficiency, while fostering user engagement and satisfaction. The frameworks enable effective integration of communal assets, mitigating grid congestion and stabilizing voltage profiles.
A key development in this transition is the rise of Energy Communities (ECs) and Energy Management Systems (EMSs). ECs allow households, businesses, and institutions to collaborate within local energy systems, while EMSs coordinate resources like solar panels, batteries, and flexible loads. This thesis introduces a decentralized EMS framework designed for future ECs, leveraging multi-objective optimization to efficiently manage distributed energy resources (DERs) and flexible assets. The approach models both physical and cyber layers of energy systems, enabling real-time data exchange and decentralized control.
The thesis first presents a Multi-Objective Energy Management System (MOEMS) that uses advanced optimization to balance cost, emissions, and grid stability, with a centralized controller adapting to user preferences. Building on MOEMS, a Decentralized Multi-Objective EMS (DMOEMS) distributes decision-making among local controllers, enhancing scalability and resilience. DMOEMS integrates conflicting objectives, cost, emissions, PV curtailment, self-consumption, congestion, and voltage management, using user-defined weights, with controllers optimizing local assets while the EC controller coordinates aggregated profiles.
Simulation studies in real-world settings, including the Aardehuizen community and KEZO research lab, demonstrate the adaptability of MOEMS and DMOEMS. MOEMS achieves up to 22% annual electricity cost savings and 37% CO2 reduction compared to traditional EMSs. DMOEMS further improves CO2 emissions, cost savings, PV curtailment, and computational efficiency, while fostering user engagement and satisfaction. The frameworks enable effective integration of communal assets, mitigating grid congestion and stabilizing voltage profiles.
| Original language | English |
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| Qualification | Doctor of Philosophy |
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| Award date | 24 Sept 2025 |
| Place of Publication | Enschede |
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| Print ISBNs | 978-90-365-6799-2 |
| Electronic ISBNs | 978-90-365-6800-5 |
| DOIs | |
| Publication status | Published - 24 Sept 2025 |