Publication Date:
2020-08-05
Description:
To attain the highest performance of energy supply systems, it is necessary to
rationally determine types, capacities, and numbers of equipment in consideration of
their operational strategies corresponding to seasonal and hourly variations in energy
demands. In the combinatorial optimization method based on the mixed-integer linear
programming (MILP), integer variables are used to express the selection, numbers, and
on/off status of operation of equipment, and the number of these variables increases
with those of equipment and periods for variations in energy demands, and affects the computation efficiency significantly. In this paper, a MILP method utilizing the
hierarchical relationship between design and operation variables is proposed to solve the optimal design problem of energy supply systems efficiently: At the upper level, the
optimal values of design variables are searched by the branch and bound method; At
the lower level, the values of operation variables are optimized independently at each period by the branch and bound method under the values of design variables given
tentatively during the search at the upper level; Lower bounds for the optimal value of the objective function are evaluated, and are utilized for the bounding operations at both the levels. This method is implemented into open and commercial MILP solvers. Illustrative and practical case studies on the optimal design of cogeneration systems are conducted, and the validity and effectiveness of the proposed method are clarified.
Language:
English
Type:
reportzib
,
doc-type:preprint
Format:
application/pdf
