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A Novel Design Method for Optimizing an Indirect Forced Circulation Solar Water Heating System Based on Life Cycle Cost Using a Genetic Algorithm
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Energies 2015, 8(11), 13137-13161; doi:10.3390/en81112360

Multi-Objective Optimization Design for Indirect Forced-Circulation Solar Water Heating System Using NSGA-II

Urban Development Institute, Incheon National University, Incheon 406-772, Korea
Academic Editor: Timothy Anderson
Received: 8 September 2015 / Revised: 4 November 2015 / Accepted: 10 November 2015 / Published: 19 November 2015
(This article belongs to the Special Issue Solar Heating & Cooling)
View Full-Text   |   Download PDF [3545 KB, uploaded 19 November 2015]   |  

Abstract

In this study, the multi-objective optimization of an indirect forced-circulation solar water heating (SWH) system was performed to obtain the optimal configuration that minimized the life cycle cost (LCC) and maximized the life cycle net energy saving (LCES). An elitist non-dominated sorting genetic algorithm (NSGA-II) was employed to obtain the Pareto optimal solutions of the multi-objective optimization. To incorporate the characteristics of practical SWH systems, operation-related decision variables as well as capacity-related decision variables were included. The proposed method was used to conduct a case study wherein the optimal configuration of the SWH system of an office building was determined. The case study results showed that the energy cost decreases linearly and the equipment cost increases more significantly as the LCES increases. However, the results also showed that it is difficult to identify the best solution among the Pareto optimal solutions using only the correlation between the corresponding objective function values. Furthermore, regression analysis showed that the energy and economic performances of the Pareto optimal solutions are significantly influenced by the ratio of the storage tank volume to the collector area (RVA). Therefore, it is necessary to simultaneously consider the trade-off and the effect of the RVA on the Pareto optimal solutions while selecting the best solution from among the optimal solutions. View Full-Text
Keywords: solar water heating system; multi-objective optimization; life cycle cost; life cycle net energy saving; non-dominated sorting genetic algorithm; Pareto optimal solution solar water heating system; multi-objective optimization; life cycle cost; life cycle net energy saving; non-dominated sorting genetic algorithm; Pareto optimal solution
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Ko, M.J. Multi-Objective Optimization Design for Indirect Forced-Circulation Solar Water Heating System Using NSGA-II. Energies 2015, 8, 13137-13161.

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