Generic Optimization Program User Manual Version 3.0.0

Wetter, Michael

doi:10.2172/962948

Cited by 109 publications

(152 citation statements)

References 20 publications

Supporting

Mentioning

148

Contrasting

Unclassified

Order By: Relevance

“…The optimization results have tiny differences in different particle update equation algorithm. Hybrid GPS algorithm with PSO algorithm combines the GPS algorithm with PSO algorithm [36]. It has the features of global superiority in PSO and visible convergence property in GPS.…”

Section: Multi-dimensional Optimizationmentioning

confidence: 99%

Research on Energy-Saving Optimization for the Performance Parameters of Rural-Building Shape and Envelope by TRNSYS-GenOpt in Hot Summer and Cold Winter Zone of China

Tang

et al. 2017

Sustainability

View full text Add to dashboard Cite

Abstract:The aim of this paper is to optimize the building shape parameters and envelope parameters influencing the rural building energy consumption in cold winter and hot summer climate. Several typical models are established and optimized by integrated TRNSYS and GenOpt. Single-objective optimization has provided guidance to the multi-dimensional optimization. Building shape and envelope parameters are considered simultaneously by multi-dimensional optimization. Results of the optimization showed significant reduction in terms of EC (energy consumption). When O (building orientation) was SW (south by west) 10 • , LWR (length-width ratio) was 1.1, WWRS (window-wall ratio in south) with the range of 0.6-0.8, ITE (insulation thickness of exterior wall) and ITR (insulation thickness of roof) was 0.05 m and 0.08 m respectively, the building had minimal energy consumption. The results also indicated that the optimal EWT (exterior window type) was plastic single-frame Low-E insulating glazing filled with inert gas, and the optimal shape of building is Re (rectangle). An effective method was provided to optimize the design of the rural building for the purpose of reducing building energy consumption in cold winter and hot summer climate.

show abstract

Section: Multi-dimensional Optimizationmentioning

confidence: 99%

Research on Energy-Saving Optimization for the Performance Parameters of Rural-Building Shape and Envelope by TRNSYS-GenOpt in Hot Summer and Cold Winter Zone of China

Tang

et al. 2017

Sustainability

View full text Add to dashboard Cite

show abstract

“…In this way, he has increased the number of considered building variants compared to other studies. With this aim also, Ferrara et al (2014) applied a simulation-based optimization process, combining the use of TRNSYS (Solar Energy Laboratory 2012) with GenOpt (Wetter 2008). Brandão de Vasconcelos et al (2016), who considers only the envelope technologies, adopted a two-step approach which consists in (i) preliminarily discarding of measures with the same or worse thermal transmission coefficient and higher global costs comparatively with other measures and (ii) combination of all resulting measures with each other, creating 35,000 packages of measures.…”

Section: Literature Reviewmentioning

confidence: 99%

Identification of cost-optimal and NZEB refurbishment levels for representative climates and building typologies across Europe

et al. 2017

View full text Add to dashboard Cite

The energy consumptions of the building stock are playing a central role in the energy policy of the European Union. While the Member States are applying the Directives in force, the European Commission is working to update the regulatory framework. Specifically, it is necessary to achieve the great unrealized potential for energy savings in existing buildings. With this aim, the nearly zero-energy building (NZEB) target was introduced, and a comparative methodology framework to calculate cost-optimal levels of minimum energy performance requirements was proposed. This study focuses on the issue of building renovation, and it presents the results obtained with the application of a cost-optimal calculation method for identifying proper retrofit measures to reach costoptimal levels and NZEB levels. The assessment takes into account an exhaustive set of passive and active renovation options and it was extended to various building types of 60s-70s (residential and non-residential) in a wide range of representative European climatic conditions. A very relevant energy-saving potential was found for all cost-optimal benchmarks, and in many cases, the obtained NZEB refurbishments have resulted interesting also from an economic point of view.

show abstract

“…Performances of other algorithms were not stable and the use of simplex algorithm and discrete Armijo gradient algorithm were not recommended. In GenOpt [10], Wetter introduced an improved hybrid algorithm PSO -Hooke-Jeeves in which the PSO performs the search on a mesh, significantly reducing the number of function evaluations called by the algorithm. Kampf et al [11] examined the performance of two hybrid algorithms (PSO -Hooke-Jeeves and CMA-ES/HDE) in optimizing five standard benchmark functions (Ackley, Rastrigin, Rosenbrock, sphere functions and a highly-constrained function) and real-world problems using EnergyPlus simulation program.…”

Section: Performance Comparison Of Single Objective Optimization Algomentioning

confidence: 99%

A performance comparison of multi-objective optimization algorithms for solving nearly-zero-energy-building design problems

Hamdy

Nguyen

Hensen

2016

Energy and Buildings

263

View full text Add to dashboard Cite

• A submitted manuscript is the version of the article upon submission and before peer-review. There can be important differences between the submitted version and the official published version of record. People interested in the research are advised to contact the author for the final version of the publication, or visit the DOI to the publisher's website.• The final author version and the galley proof are versions of the publication after peer review.• The final published version features the final layout of the paper including the volume, issue and page numbers. Link to publication General rightsCopyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners and it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights.• Users may download and print one copy of any publication from the public portal for the purpose of private study or research.• You may not further distribute the material or use it for any profit-making activity or commercial gain • You may freely distribute the URL identifying the publication in the public portal.If the publication is distributed under the terms of Article 25fa of the Dutch Copyright Act, indicated by the "Taverne" license above, please follow below link for the End User Agreement: ABSTRACTIntegrated building design is inherently a multi-objective optimization problem where two or more conflicting objectives must be minimized and/or maximized concurrently. Many multiobjective optimization algorithms have been developed; however few of them are tested in solving building design problems. This paper compares performance of seven commonly-used multi-objective evolutionary optimization algorithms in solving the design problem of a nearly zero energy building (nZEB) where more than 1.6 10 solutions would be possible. The compared algorithms include a controlled non-dominated sorting genetic algorithm with a passive archive (pNSGA-II), a multi-objective particle swarm optimization (MOPSO), a two-phase optimization using the genetic algorithm (PR_GA), an elitist non-dominated sorting evolution strategy (ENSES), a multi-objective evolutionary algorithm based on the concept of epsilon dominance (evMOGA), a multi-objective differential evolution algorithm (spMODE-II), and a multi-objective dragonfly algorithm (MODA). Several criteria was used to compare performance of these algorithms.In most cases, the quality of the obtained solutions was improved when the number of generations was increased. The optimization results of running each algorithm 20 times with gradually increasing number of evaluations indicated that the PR_GA algorithm had a high repeatability to explore a large area of the solution-space and achieved close-to-optimal solutions with a good diversity, followed by the pNSGA-II, evMOGA and spMODE-II. Uncompetitive results were achieved by the ENSES, MOPSO and MODA in most running cases. The study also found that 1400 -180...

show abstract

Generic Optimization Program User Manual Version 3.0.0

Cited by 109 publications

References 20 publications

Research on Energy-Saving Optimization for the Performance Parameters of Rural-Building Shape and Envelope by TRNSYS-GenOpt in Hot Summer and Cold Winter Zone of China

Research on Energy-Saving Optimization for the Performance Parameters of Rural-Building Shape and Envelope by TRNSYS-GenOpt in Hot Summer and Cold Winter Zone of China

Identification of cost-optimal and NZEB refurbishment levels for representative climates and building typologies across Europe

A performance comparison of multi-objective optimization algorithms for solving nearly-zero-energy-building design problems

Contact Info

Product

Resources

About