Multi-energy Grid Expansion Planning Under Uncertainty: A Robust Optimization Approach

Integrating the gas and district heating with the electrical grid in a multi-energy grid has been shown to provide flexibility and prevent bottlenecks in the operation of electrical distribution grids. This integration however presents new challenges, including uncertainties in demand prediction, energy prices, and renewable energy availability. In response to these challenges, this paper proposes a novel approach to apply robust optimization methods in the integrated planning of multi-energy grids, to reduce the risk of investment in grid expansion and to optimize the use of different carbon-neutral energy carriers. The uncertainty in energy prices is modeled using interval uncertainty with a proportional deviation. This allows planners, operators and regulators to prioritize the expansion of specific grids in certain areas of a city. By minimizing a cost function subject to various constraints, the strategy ensures robustness against uncertainties in energy prices. This robust optimization approach is applied to Hamburg as a case study. The study concludes that district heating expansion in high-density areas is a low-risk investment for carbon neutrality. In less dense areas, electrification supports decentralized heat pumps. Meanwhile, hydrogen gas grids are viable where electric expansion is impractical. Increased uncertainty leads to more conservative solutions. This novel approach can be implemented promptly and practically by grid planners and is an important component of a new holistic integrated planning process for multi-energy grids.