A Cascading Chi-shapes based Decoder for Constraint-handling in Distributed Energy Management

Joerg Bremer, Sebastian Lehnhoff

2018

Abstract

A steadily rising share of small, distributed, and volatile energy units like wind energy converters solar panels, co-generation plants, or similar assigns new tasks and challenges to the smart grid regarding operation and control. The growing complexity of the grid also imposes a growing complexity of constraints that restrict the validity of solutions for operation schedules, resource capacity utilization or grid compliance. Using surrogate models as an abstraction layer has recently become a promising approach for constructing algorithms independently from any knowledge about the actual device or operation restricting constraints. So called decoders as a special constraint handling technique allow for systematically generating feasible solutions directly from a learned surrogate model. Some decoder approaches based on support vector machines have already been implemented, but suffer from performance issues and a sensible parametrization. We propose a new type of decoder based on a cascade of χ-shapes to overcome these problems. The applicability is demonstrated with a simulation study using different types of flexible energy units.

Paper Citation

in Harvard Style

Bremer J. and Lehnhoff S. (2018). A Cascading Chi-shapes based Decoder for Constraint-handling in Distributed Energy Management. In Proceedings of the 10th International Joint Conference on Computational Intelligence (IJCCI 2018) - Volume 1: IJCCI; ISBN 978-989-758-327-8, SciTePress, pages 184-191. DOI: 10.5220/0006926101840191

in Bibtex Style

@conference{ijcci18,
author={Joerg Bremer and Sebastian Lehnhoff},
title={A Cascading Chi-shapes based Decoder for Constraint-handling in Distributed Energy Management},
booktitle={Proceedings of the 10th International Joint Conference on Computational Intelligence (IJCCI 2018) - Volume 1: IJCCI},
year={2018},
pages={184-191},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006926101840191},
isbn={978-989-758-327-8},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 10th International Joint Conference on Computational Intelligence (IJCCI 2018) - Volume 1: IJCCI
TI - A Cascading Chi-shapes based Decoder for Constraint-handling in Distributed Energy Management
SN - 978-989-758-327-8
AU - Bremer J.
AU - Lehnhoff S.
PY - 2018
SP - 184
EP - 191
DO - 10.5220/0006926101840191
PB - SciTePress