Holger Teichgraeber

Time-series aggregation for the optimization of energy systems: goals, challenges, approaches, and opportunities

  • Holger Teichgraeber
  • Adam R. Brandt
    • Categories Data-Mining, Energy, Facility Planning and Design Tags , , , , ,

    The rising significance of renewable energy increases the importance of representing time-varying input data in energy system optimization studies. Time-series aggregation, which reduces temporal model complexity, has emerged in recent years to address this challenge. We provide a comprehensive review of time-series aggregation for the optimization of energy systems. We show where time series affect … Read more

    Designing reliable future energy systems by iteratively including extreme periods in time-series aggregation

  • Adam R. Brandt
  • Lucas Elias Kuepper
  • Holger Teichgraeber
    • Categories Energy, Facility Planning and Design

    Generation Capacity Expansion Planning (GCEP) requires high temporal resolution to account for the volatility of renewable energy supply. Because the GCEP optimization problem is often computationally intractable, time-series input data are often aggregated to representative periods using clustering. However, clustering removes extreme events, which are important to achieve reliable system designs. We present a method … Read more

    Optimal design of an electricity-intensive industrial facility subject to electricity price uncertainty: stochastic optimization and scenario reduction

  • Adam R. Brandt
  • Holger Teichgraeber
    • Categories Chemical Engineering, Production and Logistics, Stochastic Programming Tags , , , ,

    When considering the design of electricity-intensive industrial processes, a challenge is that future electricity prices are highly uncertain. Design decisions made before construction can affect operations decades into the future. We thus explore whether including electricity price uncertainty into the design process affects design decisions. We apply stochastic optimization to the design and operations of … Read more

    Clustering methods to find representative periods for the optimization of energy systems: an initial framework and comparison

  • Adam R. Brandt
  • Holger Teichgraeber
    • Categories Applications - Science and Engineering, Chemical Engineering, Energy Tags , , , , ,

    Modeling time-varying operations in complex energy systems optimization problems is often computationally intractable, and time-series input data are thus often aggregated to representative periods. In this work, we introduce a framework for using clustering methods for this purpose, and we compare both conventionally-used methods (k-means, k-medoids, and hierarchical clustering), and shape-based clustering methods (dynamic time … Read more