Strategic Decision Making in the Planning of Integrated Multi-energy Networks Under Uncertainty

This paper proposes a framework for the integrated planning of multi-energy networks, including electricity and district heating systems, to optimize the use of different energy carriers and reduce the carbon footprint of energy systems. Integrating multiple energy carriers in the planning of distribution networks presents new challenges, including uncertainties in demand prediction, energy prices, and renewable energy availability. In response to these challenges, we propose an approach that aims to aid strategic decision-making in a new planning process for integrated multi-energy networks using robust optimization. The uncertainty in energy prices is modeled using interval uncertainty with a proportional deviation. This allows network operators and regulators to forecast the likely decision to be made by the household customer to choose one heating technology that minimizes a cost function subject to various constraints while ensuring robustness against the uncertainty in energy prices. The results show that the expansion of the district heating infrastructure results in the lowest total economic costs in most cases and cells. The results also show that an increase in the size of the uncertainty sets causes an increase in the total economic costs of heating. The paper concludes with a discussion of future directions to expand this approach to model more uncertain parameters.