Exploring the Near-Optimal Solution Space for the Synthesis of Distributed Energy Supply Systems

Abstract

An optimization-based methodology is proposed for the synthesis of distributed energy supply systems (DESS) exploiting the near-optimal solution space inherent to DESS synthesis problems. The proposed synthesis method generates the optimal solution and a set of promising alternatives, thus providing valuable insight into the synthesis problem and a basis for rational and far-sighted design decisions. For economic optimization, first, single-objective optimization is performed maximizing the net present value. Secondly, integer-cut constraints are employed to automatically and systematically generate structurally different, near-optimal solutions. The methodology is exemplified by a real-world problem from industry, for which retrofit optimization generates a solution that improves the net present value by 39 %. Applying integer-cut constraints reveals a rich near-optimal solution space with many structurally different, but practically equally good solutions: The objective function values of the ten best solution structures lie within a tolerance of 0.17 %.