EURO 2024 Copenhagen
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3161. Automated Grid Expansion and Reinforcement Planning Considering Multiple Objectives

Invited abstract in session TC-37: Multiobjective Mixed-Integer Nonlinear Optimization, stream Multiobjective Optimization.

Tuesday, 12:30-14:00
Room: 33 (building: 306)

Authors (first author is the speaker)

1. Hendrik Maschke
Fraunhofer IEE
2. Lars-Peter Lauven
Chair of Energy Management and Power System Operation, University of Kassel

Abstract

The transition towards renewable energy sources presents increasing challenges in operating, maintaining, and planning electrical grids. With the growing complexity of planning tasks, various planning criteria impact the decisions on specific measures for grid reinforcement and expansion.
To address such a growing number of criteria, it becomes necessary to develop suitable models and simulation tools. Therefore, an existing automated power grid expansion algorithm based on pandapower is enhanced to handle multiple objectives. So far, using stochastic local search algorithms like hill climbing or iterated local search, a solution has been found to minimize cost as the sole objective. In addition to cost, other objectives like reliability, security, sociology, or environment are often considered as well. A decision-support approach in grid planning is therefore proposed that considers these additional criteria.
We propose a methodology that aims to optimize grid reinforcement and expansion by considering multiple objectives. The genetic NSGA-II algorithm is employed to find solutions that balance these considerations effectively. The approach aligns with sustainable development principles and fosters resilient and sustainable grid planning. Pareto front solutions, representing trade-offs between different objectives, offer a range of alternatives that can be considered in grid planning processes and therefore address the complex challenges of energy grid planning.

Keywords

Status: accepted

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