A Bi-Level Multi-Objective System for Renewable Energy Self-Consumption: A Resident-Aware Approach to Leveraging Energy Flexibility

The efficient exploitation of renewable energy sources is crucial for addressing the global energy crisis and increase in CO2 emissions. Energy management system aggregators, functioning as nonprofit cooperatives within energy communities, manage renewable energy resources and incentivize residents...

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Bibliographic Details
Published in:IEEE transactions on evolutionary computation p. 1
Main Authors: Papakyriakou, Thalis, Pamboris, Andreas, Konstantinidis, Andreas
Format: Journal Article
Language:English
Published: IEEE 2025
Subjects:
bi-level optimization
Computational modeling
Costs
Decision making
Energy management systems
Evolutionary computation
evolutionary multi-objective optimization
evolutionary transfer optimization
Load modeling
multi-criteria decision making
Optimization
Production
Renewable energy sources
self-consumption
Stakeholders
ISSN:1089-778X, 1941-0026
Online Access:Get full text
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Summary:The efficient exploitation of renewable energy sources is crucial for addressing the global energy crisis and increase in CO2 emissions. Energy management system aggregators, functioning as nonprofit cooperatives within energy communities, manage renewable energy resources and incentivize residents towards self-consumption through dynamic, cost-attractive pricing schemes, receiving subsidies and long-term contracts as reward. This interaction between aggregator and residents is typically modeled using bi-level optimization frameworks, however, research studies often ignore the role of aggregators as self-consumption catalysts and the conflicting nature of the residents' objectives. Moreover, lack of cooperation between the decision levels results in inflexible decision making when prioritizing between the respective objectives. This paper defines and formulates a bi-level multi-objective optimization problem for optimizing self-consumption in energy communities, while considering the residents' welfare by maximizing satisfaction of their appliance-scheduling preferences and minimizing energy costs. We introduce the Bi-level Multi-Objective Energy Management System II (BiMO-EMS-II), composed of an Adaptive Population Transfer strategy, a Uniform Partially Mapped Crossover and a Decision Making heuristic with Cooperation. Our experimental evaluation has shown that BiMO-EMS-II simultaneously offers near-optimal self-consumption at the aggregator level and a high-quality trade-off between the conflicting objectives at the resident level, subject to different objective prioritization and decision-making assumptions.
ISSN:1089-778X
1941-0026
DOI:10.1109/TEVC.2025.3598236