232. On the effects of unexpected extreme events in an ex-post analysis of integrated energy system planning
Invited abstract in session WB-3: Uncertainty and energy, stream Energy and Sustainability.
Wednesday, 10:45-12:15Room: H5
Authors (first author is the speaker)
| 1. | Richard Schmitz
|
| Energy Economics and System Analysis, Fraunhofer IEE | |
| 2. | Felix Frischmuth
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| Energy Economics and System Analysis, Fraunhofer IEE | |
| 3. | Magnus Korpås
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| Department of Electric Power Engineering, Norwegian University of Science and Technology | |
| 4. | Philipp Härtel
|
| Energy Economics and System Analysis, Fraunhofer IEE |
Abstract
The required pace of energy system transformation involves significant uncertainties and complexities. Furthermore, the rising frequency of extreme events, coupled with ongoing climate change, underscores the urgent need to enhance the resilience of energy systems. These extreme events encompass natural phenomena such as earthquakes and severe weather, as well as human-induced incidents such as wars, terrorism, and accidents.
The aim of this paper is to show the influence of selected extreme events on the cost-optimised planning of integrated energy systems. For this purpose, we use EMPRISE, a multi-stage stochastic linear programming framework for modelling and optimising integrated energy system planning. First, investment and operational planning is conducted for the energy system transformation pathway leading to 2045, serving as a regular reference scenario. This analysis may incorporate various meteorological years as uncertainties. Second, the expanded capacities of power plants (such as gas turbines, solar photovoltaics, and onshore/offshore wind power), storage technologies (e.g. batteries), and consumer technologies (including electrolysers and heat pumps) are then utilised in a subsequent dispatch calculation influenced by unexpected extreme events. Our approach allows for an ex-post impact analysis of the amount and frequency of uncovered loads in the system and identifies the recourse options chosen by the model when additional capacity expansion is not permitted. The results aim to illustrate the essential shift from deterministic optimisation with subsequent parameter sensitivities to stochastic optimisation including extreme events, also referred to as resilient planning, in energy system modelling.
Keywords
- Capacity Planning
- Disaster and Crisis Management
- Large Scale Optimization
Status: accepted
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