Scenario-based decision-making for power systems investment planning

TL;DR

This paper explores scenario-based decision-making in power system investment planning under complex uncertainties, proposing a Nash equilibrium approach that is computationally efficient and provides a natural decision and scenario ranking.

Contribution

It introduces a Nash equilibrium method for power system planning under uncertainty, offering computational advantages and a natural interpretation for decision and scenario selection.

Findings

Nash equilibrium approach reduces computational costs.

The method naturally ranks decisions and scenarios.

Provides a matrix of outcomes for critical decisions and scenarios.

Abstract

The optimization of power systems involves complex uncertainties, such as technological progress, political context, geopolitical constraints. Negotiations at COP21 are complicated by the huge number of scenarios that various people want to consider; these scenarios correspond to many uncertainties. These uncertainties are difficult to modelize as probabilities, due to the lack of data for future technologies and due to partially adversarial geopolitical decision makers. Tools for such difficult decision making problems include Wald and Savage criteria, possibilistic reasoning and Nash equilibria. We investigate the rationale behind the use of a two-player Nash equilibrium approach in such a difficult context; we show that the computational cost is indeed smaller than for simpler criteria. Moreover, it naturally provides a selection of decisions and scenarios, and it has a natural interpretation in the sense that Nature does not make decisions taking into account our own decisions. The algorithm naturally provides a matrix of results, namely the matrix of outcomes in the most interesting decisions and for the most critical scenarios. These decisions and scenarios are also equipped with a ranking.