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 %.
[1]
Ferenc Friedler,et al.
Combinatorial algorithms for process synthesis
,
1992
.
[2]
François Maréchal,et al.
Methods for multi-objective investment and operating optimization of complex energy systems
,
2012
.
[3]
E. Balas,et al.
Canonical Cuts on the Unit Hypercube
,
1972
.
[4]
Enrico Sciubba,et al.
A Brief Review of Methods for the Design and Synthesis Optimization of Energy Systems
,
2002
.
[5]
G. Wozny,et al.
Utility systems operation: Optimisation-based decision making
,
2011
.
[6]
Daniel S. Kirschen,et al.
Centralised and distributed electricity systems
,
2008
.
[7]
André Bardow,et al.
Automated superstructure-based synthesis and optimization of distributed energy supply systems
,
2013
.
[8]
Ryohei Yokoyama,et al.
A MILP decomposition approach to large scale optimization in structural design of energy supply systems
,
2002
.