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Abstract
This paper presents a novel framework for economic cooling load dispatch in conventional watercooled chillers. Moreover, information gap decision theory (IGDT) is applied to the optimal chiller loading (OCL) problem to find the optimum operating point of the test system in three decisionmaking modes: (a) riskneutral approach, (b) riskaversion or robustness approach, and (c) risktaker or opportunistic approach. In the robustness mode of the IGDTbased OCL problem, the system operator enters a desired energy cost value in order to find the most appropriate loading points for the chillers so that the total electricity procurement cost over the study horizon is smaller than or equal to this critical value. Meanwhile, the cooling load increase is maximized to the highest possible level to find the most robust performance of the benchmark grid with respect to the overestimated load. Similarly, the risktaker optimization method finds the on/off status and the partial load ratio (PLR) of the chillers in order to keep the total energy cost as low as the given cost function. In addition, the minimum value of cooling load decrease can be found while satisfying the refrigeration capacity of the chiller and the loadgeneration balance constraint. Thus, a mixedinteger nonlinear programming problem is solved using the branch and reduce optimization (BARON) tool of the generalized algebraic mathematical modeling system (GAMS) for a fivechiller plant, to demonstrate that IGDT is able to find a good solution in robustness/risktaker OCL problem.
Original language  English 

Article number  1925 
Journal  Applied Sciences (Switzerland) 
Volume  9 
Issue number  9 
Pages (fromto)  9 
Number of pages  9 
DOIs  
Publication status  Published  May 2019 
Keywords
 Information gap decision theory (IGDT)
 Mixedinteger nonlinear programming problem (MINLP)
 Optimal chiller loading (OCL)
 Uncertain cooling demand
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 1 Finished

HeatReFlex: Green and Flexible District Heating/Cooling
AnvariMoghaddam, A., Guerrero, J. M., Nami, H. & Mohammadiivatloo, B.
01/05/2019 → 30/04/2022
Project: Research