The optimum is not enough: A near-optimal solution paradigm for energy systems synthesis

An optimisation-based decision support methodology is presented for the synthesis of energy supply systems on the conceptual level. Previous work in this field has tended to focus on the generation of the single optimal solution. However, given that mathematical models never perfectly represent the real world and that planners are often not aware of all practical constraints, the mathematically optimal solution usually only approximates the real-world optimum, and thus has only limited significance. The presented approach therefore exploits the near-optimal solution space for more rational synthesis decisions. For this purpose, integer-cut constraints are employed to systematically generate a set of near-optimal solutions alongside the optimal solution. In place of the traditional analysis of the single optimal solution, we analyse the generated solution set to identify common features (the “must-haves”) and differences (the “real choices”) among the good solutions, and features not observed in any of the generated solutions (the “must-avoids”). This approach provides valuable insights into the synthesis problem and opens up a wide range of rational decision options.