A more recent version of this item is in the workflow of a user.
Optimal operation of energy systems with long-term constraints by time-series aggregation in receding horizon optimization
METADATA ONLY
Loading...
Author / Producer
Date
2019
Publication Type
Conference Paper
ETH Bibliography
no
Citations
Altmetric
METADATA ONLY
Data
Rights / License
Abstract
Operational optimization of energy systems needs to consider both forecast uncertainty and long-term constraints. Long-term constraints are often introduced by regulations such as network charge reduction policies. In principle, uncertainty can be handled via receding horizon optimization (RHO), which frequently optimizes the operation schedule based on updated forecast data. As fast reoptimization is required in real-time control applications, RHO typically considers the near-term future only and neglects long-term constraints. To explicitly account for long-term constraints in RHO, we propose a hybrid time-series approach that extends the high-resolution detailed block for near-term operation by an aggregated block for the more distant future. The aggregated block is constructed using the k-medoids algorithm. The new approach is applied to a case study and shown to adequately consider long-term constraints with a short computation time. In particular, we reduce operational expenditures by 5.4 % compared to a benchmark RHO that relies on a typical near-term prediction horizon of 48 h. The computation time for a single reoptimization is reduced by four orders of magnitude compared to the problem with the full-resolution time-series. Thus, the hybrid time-series approach enables the efficient operational optimization of energy systems with long-term constraints. © ECOS 2019 - Proceedings of the 32nd International Conference on Efficiency, Cost, Optimization, Simulation and Environmental Impact of Energy Systems. All rights reserved.
Permanent link
Publication status
published
External links
Book title
Proceedings of the 32nd International Conference on Efficiency, Cost, Optimization, Simulation and Environmental Impact of Energy Systems (ECOS 2019)
Journal / series
Volume
Pages / Article No.
1971 - 1980
Publisher
Institute of Thermal Technology
Event
32nd International Conference on Efficiency, Cost, Optimization, Simulation and Environmental Impact of Energy Systems (ECOS 2019)
Edition / version
Methods
Software
Geographic location
Date collected
Date created
Subject
Distributed energy systems; Long-term time-coupling constraints; Operational optimization; Receding horizon; Time-series aggregation
Organisational unit
09696 - Bardow, André / Bardow, André