@conference{Pickering2016Comparisonof,
author = {Bryn Pickering and Shintaro Ikeda and Ruchi Choudhary and Ryozo Ooka},
booktitle = {CLIMA 2016 - proceedings of the 12th REHVA World Congress: volume 6},
address = {Aalborg, Denmark},
title = {Comparison of Metaheuristic and Linear Programming Models for the Purpose of Optimising Building Energy Supply Operation Schedule},
year = {2016},
month = {05},
abstract = {Increasing complexity of building energy systems has led to a wide range of methods to minimise cost of meeting demand for all types of energy. Metaheuristics and mixed integer linear programmes (MILP) are the two most prevalent optimisation methods in the field, with relative advantages which have not previously been compared under common criteria. The principle objective of this paper is to scrutinise these two optimisation methods when applied to a problem of finding the optimal operational schedule of an energy system serving a hotel. 11 technologies are modelled by both methods, but all exhibit nonlinear characteristics which must be linearised for use in MILP. Comparison of the two models results in variation between objective function below 1%, where piecewise linearised MILP gives the most optimal solution. The time to solution varies by orders of magnitude between models: 0.08s for simple linear MILP, 1.64s for piecewise linear MILP and 274s for metaheuristic. System designers, or controllers, must decide between solution time and realistic representation of technologies when choosing an optimisation method, a compromise which may be balanced by piecewise optimisation. Further, Proposed operation schedules vary slightly between methods, allowing some subjectivity in exact operation schedule, without compromising objective function. Metaheuristics favours qualitative subjectivity, while MILP favours quantitative subjectivity.},
url = {http://vbn.aau.dk/files/233775414/paper_529.pdf},
keywords = {Energy System Optimisation, Mixed Integer Linear Programming, Epsilon constrained differential evolution, Metaheuristics},
project = {district_energy}
}

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Metaheuristics and mixed integer linear programmes (MILP) are the two most prevalent optimisation methods in the field, with relative advantages which have not previously been compared under common criteria. The principle objective of this paper is to scrutinise these two optimisation methods when applied to a problem of finding the optimal operational schedule of an energy system serving a hotel. 11 technologies are modelled by both methods, but all exhibit nonlinear characteristics which must be linearised for use in MILP. Comparison of the two models results in variation between objective function below 1%, where piecewise linearised MILP gives the most optimal solution. The time to solution varies by orders of magnitude between models: 0.08s for simple linear MILP, 1.64s for piecewise linear MILP and 274s for metaheuristic. 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System designers, or controllers, must decide between solution time and realistic representation of technologies when choosing an optimisation method, a compromise which may be balanced by piecewise optimisation. Further, Proposed operation schedules vary slightly between methods, allowing some subjectivity in exact operation schedule, without compromising objective function. 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