Optimal sizing of a solar thermal building installation using particle swarm optimization

Bornatico, Raffaele; Pfeiffer, Michael; Witzig, Andreas; Guzzella, Lino

doi:10.1016/j.energy.2011.05.026

Cited by 80 publications

(27 citation statements)

References 7 publications

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“…through experiment evaluation [97]. Bornatico et al (2012) developed a model that could represent the optimal capacity of the solar thermal system through the particle swarm optimization algorithm and genetic algorithm by considering the meteorological data, collector area, tank volume, and size of the auxiliary power unit [99]. Chialastri and Isaacson (2017) conducted tests for a prototype of a building-integrated PV/thermal air collector which can generate thermal and electrical energy based on experiments and two-dimensional models in COMSOL Multiphysics.…”

Section: Part B-1: Renewable Energy (Re)mentioning

confidence: 99%

“…In addition, the economic analysis of BIPB was conducted focusing on the residential progressive electricity tariffs [95]. (2) Solar thermal system: There have been various studies that utilize solar heat by absorbing, storing, and converting it for the heating and cooling of a building based on infinite solar energy (refer to Table 8) [96][97][98][99][100][101][102][103][104][105][106][107]. Anderson et al (2010) analyzed the effect of the color (ranging from white to black) of the solar collector both theoretically and experimentally on the thermal performance of the building-integrated solar thermal system [96].…”

Section: Part B-1: Renewable Energy (Re)mentioning

confidence: 99%

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Advanced Strategies for Net-Zero Energy Building: Focused on the Early Phase and Usage Phase of a Building’s Life Cycle

Hong

Kim

et al. 2017

Sustainability

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Abstract:To cope with 'Post-2020', each country set its national greenhouse gas (GHG) emissions reduction target (e.g., South Korea: 37%) below its business-as-usual level by 2030. Toward this end, it is necessary to implement the net-zero energy building (nZEB) in the building sector, which accounts for more than 25% of the national GHG emissions and has a great potential to reduce GHG emissions. In this context, this study conducted a state-of-the-art review of nZEB implementation strategies in terms of passive strategies (i.e., passive sustainable design and energy-saving technique) and active strategies (i.e., renewable energy (RE) and back-up system for RE). Additionally, this study proposed the following advanced strategies for nZEB implementation according to a building's life cycle: (i) integration and optimization of the passive and active strategies in the early phase of a building's life cycle; (ii) real-time monitoring of the energy performance during the usage phase of a building's life cycle. It is expected that this study can help researchers, practitioners, and policymakers understand the overall implementation strategies for realizing nZEB.

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Section: Part B-1: Renewable Energy (Re)mentioning

confidence: 99%

Section: Part B-1: Renewable Energy (Re)mentioning

confidence: 99%

Advanced Strategies for Net-Zero Energy Building: Focused on the Early Phase and Usage Phase of a Building’s Life Cycle

Hong

Kim

et al. 2017

Sustainability

View full text Add to dashboard Cite

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“…These parameters include the dimensions (which would determine the volume) as well as the thermal properties of the tank. In [22], a methodology is presented for determining the optimal sizing of the main components (solar collector and storage tank) of a SWHS in order to minimize energy consumption and cost, whilst maximizing the solar fraction. The results of this study show that there is an optimal value for the tank dimensions, though this value may be dependent on the SWHS and the water heating requirement, if given.…”

Section: Storage Tank Parametersmentioning

confidence: 99%

Optimal flow control of a forced circulation solar water heating system with energy storage units and connecting pipes

2016

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Degree:Master of Engineering (Electrical Engineering)Keywords: Flat plate solar collector, flow rate optimization, maximum energy extraction, system thermal losses, thermal comfort.Solar water heating systems (SWHS) have fast become a suitable alternative to conventional water heating systems due to growing energy demands. A SWHS generally consists of a solar collector (which is used to convert solar radiation to heat), a water storage tank, and a flow control device such as a pump in the case of forced circulation SWHS. Extensive research and analysis on the operation and performance of these systems has been conducted, and results show that optimal flow control is an important factor that can be used to improve the performance and efficiency of SWHS.This study focuses on pump flow rate optimization for forced circulation SWHS with pipes.The system analyzed consists of an array of flat plate solar collectors, two storage tanks (one for the circulation fluid and one for the water), a heat exchanger, two pumps, and connecting pipes which are considered as one of the components of the SWHS so as to account for their thermal effects. The proposed model is developed using mainly the first and second laws of thermodynamics. The model is used to maximize the difference between the energy extracted from the solar collector and the combined sum of the energy extracted by the heat exchanger and corresponding energies used by the pumps in the primary and secondary loops. The objective function maximizes the overall system energy gain whilst minimizing the sum of the energy extracted by the heat exchanger and energy used by the corresponding pumps in the secondary loop to conserve the stored energy and meet the user requirement of water tank temperatures.The model is solved using the fmincon solver in MATLAB's optimization toolbox. When compared to other flow control techniques, in particular the most suitable energy efficient control strategy, the results of this study show a significant increase in the system's overall energy gain. The results also illustrate the effects of system pipe thermal losses for the different control strategies, hence highlighting the importance of developing a model that takes such losses into account so as to improve the overall accuracy of the model. Sonenergie-waterverwarmingstelsels (SWV) het vinnig 'n geskikte alternatief vir konvensionele waterverwarmingstelsels geword, weens die groeiende vraag na energie. 'n SWV bestaan gewoonlik uit 'n sonkollektor wat gebruik word om sonstraling om te skakel na hitte, 'n opgaartenk vir water, en 'n vloeibeheertoestel soos 'n pomp, in die geval van geforseerde sirkulasie SWV. Uitgebreide navorsing en ontleding op die werking en prestasie van hierdie stelsels is uitgevoer en die resultate toon dat die optimale vloeibeheer 'n belangrike faktor is wat gebruik kan word om die prestasie en doeltreffendheid van SWV verbeter. OPSOMMINGHierdie studie fokus op die optimering van die vloeitempo van 'n pomp vir geforseerde sirkulasie sonenergie-waterverwarmingste...

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“…Most of them are based on certain characteristics and behavior of biological and molecular systems, swarms of insects, or neurobiological systems [7]. For instance, to optimize the design variables of an SWH system, linear and nonlinear optimization methods [8,9], genetic algorithms (GAs) [7,[10][11][12][13][14][15], and particle swarm optimization (PSO) [16,17] have been applied. Furthermore, hybrid optimization techniques such as the combination of PSO with the Hooke-Jeeves method [18] and the combination of a GA with the binary search method [19] have also been utilized in recent years.…”

Section: Introductionmentioning

confidence: 99%

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

2015

Energies

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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.

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Optimal sizing of a solar thermal building installation using particle swarm optimization

Cited by 80 publications

References 7 publications

Advanced Strategies for Net-Zero Energy Building: Focused on the Early Phase and Usage Phase of a Building’s Life Cycle

Advanced Strategies for Net-Zero Energy Building: Focused on the Early Phase and Usage Phase of a Building’s Life Cycle

Optimal flow control of a forced circulation solar water heating system with energy storage units and connecting pipes

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

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