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Power & Energy Systems LAB
● Power to X based Distribution System Analysis
Transition from a centralized power system to regionally oriented distribution networks
Emergence of regional power imbalances due to the expansion of renewable energy projects across different areas
Integration of renewable energy into local distribution networks and enhancement of distribution system stability through Power-to-X technologies
● Contingency analysis for Integrated Electricity and Gas Systems
Transmission lines may be damaged by natural disasters caused or intensified by rapid climate change.
Such disruptions can affect not only above-ground power transmission infrastructure but also natural gas pipeline networks.
Coupling electricity and gas networks through an IEGS enhances energy flexibility and improves the reliability and resilience of the overall energy system under contingency conditions.
● Renewable energy integration
The integration of large-scale renewable energy resources with intermittent output characteristics may cause power imbalances in the grid.
From the perspective of renewable energy developers, areas with high renewable energy saturation may not be suitable for further investment, creating a need for an appropriate evaluation indicator.
PRPI is proposed as a new index of renewable energy capability, providing system operators and renewable producers with information on the feasibility and potential of additional renewable energy integration at a given location
● Mathematical energy flow techniques
Energy flow analysis in coupled electricity and gas networks involves nonlinear equations, and the gas network model is particularly nonconvex, making optimization difficult using conventional methods.
This study develops a Taylor-series-based mathematical linearization method and proposes an integrated energy flow algorithm that converges faster than conventional approaches.
● Mathematical optimization for Integrated Energy Systems
Integrated energy systems involve multiple stakeholders, and practical integration requires an agreed-upon allocation of benefits among the participating entities.
The benefits received by each stakeholder may vary due to uncertainties in renewable energy generation, energy demand, market conditions, and other operational factors.
This study applies optimization methodologies that simultaneously account for stakeholder consensus and uncertainty in integrated energy system operation.
Game-Theoretic Approach to Multi-Objective Optimization
Optimization under Uncertainty: Stochastic, Robust, and Distributionally Robust Approaches
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