Update draft

data/compare-data.csv

@@ -0,0 +1,12 @@
+Name,Weather data handling,Further data extraction,SQL-based structural output,Post-processing capabilities
+IESVE (ref:iesve),X,X,,XXX
+IDA ICE (ref:idaice),,X,,XX
+eQUEST (ref:equest),,X,,X
+DesignBuilder (ref:designbuilder),,X,X,XX
+OpenStudio PAT (ref:pat) , X ,X,X ,XXX
+Ladybug \& Honeybee (ref:ladybug), X ,X,   ,XX
+jEplus (ref:jeplus),   ,X,X,XXX
+Modelkit (ref:modelkit),   ,   ,   ,X
+MLE+ (ref:mle),   ,   ,   ,X
+EpXL (ref:epxl),   ,X,   ,XX
+eppy (ref:eppy),   ,X,   ,XXX

data/compare-sim.csv

@@ -0,0 +1,12 @@
+Name,Simulation engine,Cross-platform,Free,GUI,Open-source,API language,Semantic API,Supports optimization,Supports calibration,BIM interoperability
+IESVE (ref:iesve),IESVE,,,X,,Python,X,X,X,X
+IDA ICE (ref:idaice),IDA ICE,,,X,,,,X,,X
+eQUEST (ref:equest),DOE-2,,X,X,,,,,,
+DesignBuilder (ref:designbuilder),EnergyPlus,,,X,,"C\#, Python",,X,,X
+OpenStudio PAT (ref:pat) ,EnergyPlus,X,X,X ,X,Ruby   ,X,X,X,X
+Ladybug \& Honeybee (ref:ladybug),EnergyPlus,   ,X,X,X,Python ,X,   ,   ,X
+jEplus (ref:jeplus),EnergyPlus,X,X,X,X,,   ,X,   ,
+Modelkit (ref:modelkit),EnergyPlus,   ,X,,   ,Ruby   ,   ,   ,   ,
+MLE+ (ref:mle),EnergyPlus,   ,X,X,X,Matlab ,   ,X,   ,
+EpXL (ref:epxl),EnergyPlus,   ,X,X,X,VBA    ,   ,X,   ,
+eppy (ref:eppy),EnergyPlus,X,X,   ,X,Python ,   ,   ,   ,

vignettes/references.bib

@@ -52,6 +52,24 @@ @article{Baker2016a
   number = {7604}
 }
 
+@article{Beckman1994,
+  title = {{{TRNSYS The}} Most Complete Solar Energy System Modeling and Simulation Software},
+  author = {Beckman, William A. and Broman, Lars and Fiksel, Alex and Klein, Sanford A. and Lindberg, Eva and Schuler, Mattias and Thornton, Jeff},
+  year = {1994},
+  month = aug,
+  volume = {5},
+  pages = {486--488},
+  issn = {0960-1481},
+  doi = {10.1016/0960-1481(94)90420-0},
+  abstract = {The five computer programs TRNSYS, PRESIM, TRNSED, ONLINE and PREBID have been put together into a program package which is the most complete solar energy system modeling and simulation software that is available today.},
+  file = {C\:\\Users\\hongy\\Dropbox\\literatures\\attachments\\Beckman et al_1994_TRNSYS The most complete solar energy system modeling and simulation software.pdf},
+  journal = {Renewable Energy},
+  keywords = {computer simulation,modeling,ONLINE,PREBID,PRESIM,Solar energy,TRNSED,TRNSYS},
+  language = {en},
+  number = {1},
+  series = {Climate Change {{Energy}} and the Environment}
+}
+
 @inproceedings{Bernal2012,
   title = {{{MLE}}+: A Tool for Integrated Design and Deployment of Energy Efficient Building Controls},
   shorttitle = {{{MLE}}+},
@@ -227,6 +245,15 @@ @misc{DesignBuilderSoftwareLtd2020
   urldate = {2020-05-19}
 }
 
+@misc{DesignBuilderSoftwareLtd2020a,
+  title = {{{DesignBuilder}}},
+  author = {{DesignBuilder Software Ltd}},
+  year = {2020},
+  month = jul,
+  url = {https://designbuilder.co.uk/},
+  urldate = {2020-07-01}
+}
+
 @misc{Dowle2019,
   title = {Data.Table: {{Extension}} of 'Data.Frame'},
   shorttitle = {Data.Table},
@@ -298,6 +325,25 @@ @techreport{Guglielmetti2011
   number = {NREL/CP-5500-51836}
 }
 
+@book{Hand2018,
+  title = {The {{ESP}}-r Cookbook},
+  author = {Hand, Jon William},
+  year = {2018},
+  publisher = {{Energy Systems Research Unit, Department of Mechanical and Aerospace Engineering University of Strathclyde}},
+  address = {{Glasgow, UK}},
+  file = {C\:\\Users\\hongy\\Dropbox\\literatures\\attachments\\Hand_2018_The ESP-r cookbook.pdf},
+  keywords = {⛔ No DOI found}
+}
+
+@misc{Hirsch2020,
+  title = {{{eQUEST}}: The {{QUick Energy Simulation Tool}}},
+  author = {Hirsch, James J.},
+  year = {2020},
+  month = jul,
+  url = {http://www.doe2.com/equest/},
+  urldate = {2020-07-01}
+}
+
 @article{Hong2000,
   title = {Building Simulation: An Overview of Developments and Information Sources},
   shorttitle = {Building Simulation},
@@ -332,6 +378,15 @@ @article{Hong2018
   number = {5}
 }
 
+@misc{IntegratedEnvironmentalSolutionsLimited2020,
+  title = {{{IES Virtual Environment}}},
+  author = {{Integrated Environmental Solutions Limited}},
+  year = {2020},
+  month = jun,
+  url = {https://www.iesve.com/software/virtual-environment},
+  urldate = {2020-06-30}
+}
+
 @misc{Jia2020,
   title = {Eplusr: {{A}} Toolkit for Using {{EnergyPlus}} in {{R}}},
   author = {Jia, Hongyuan},
@@ -350,6 +405,20 @@ @misc{Jia2020a
   abstract = {A toolkit for conducting parametric analysis on 'EnergyPlus'({$<$}https://energyplus.net{$>$}) models in R, including sensitivity analysis using Morris method and Bayesian calibration using using 'Stan'({$<$}https://mc-stan.org{$>$})}
 }
 
+@inproceedings{Kalamees2004,
+  title = {{{IDA ICE}}: The Simulation Tool for Making the Whole Building Energy- and {{HAM}} Analysis.},
+  booktitle = {Working Meeting of {{Annex}} 41 {{MOIST}}-{{ENG}}},
+  author = {Kalamees, Targo},
+  year = {2004},
+  month = may,
+  pages = {6},
+  address = {{Zurich, Switzerland}},
+  abstract = {This paper gives a short overview of the building simulation program IDA Indoor Climate and Energy (IDA ICE). IDA ICE primarily has been developed to study energy and indoor climate performance. With the additional of the one-dimensional heat, moisture, and air (HAM) simultaneous model, HAMWall, it also becomes possible to analyse the moisture conditions of the indoor climate and those in the building envelope.},
+  file = {C\:\\Users\\hongy\\Dropbox\\literatures\\attachments\\Kalamees_2004_IDA ICE.pdf},
+  keywords = {⛔ No DOI found},
+  language = {en}
+}
+
 @article{Kim2011,
   title = {Analysis of an Energy Efficient Building Design through Data Mining Approach},
   author = {Kim, Hyunjoo and Stumpf, Annette and Kim, Wooyoung},
@@ -572,6 +641,22 @@ @article{Oliphant2007
   number = {3}
 }
 
+@article{Ostergard2016,
+  title = {Building Simulations Supporting Decision Making in Early Design \textendash{} {{A}} Review},
+  author = {{\O}sterg{\aa}rd, Torben and Jensen, Rasmus L. and Maagaard, Steffen E.},
+  year = {2016},
+  month = aug,
+  volume = {61},
+  pages = {187--201},
+  issn = {1364-0321},
+  doi = {10.1016/j.rser.2016.03.045},
+  abstract = {The building design community is challenged by continuously increasing energy demands, which are often combined with ambitious goals for indoor environment, for environmental impact, and for building costs. To aid decision-making, building simulation is widely used in the late design stages, but its application is still limited in the early stages in which design decisions have a major impact on final building performance and costs. The early integration of simulation software faces several challenges, which include time-consuming modeling, rapid change of the design, conflicting requirements, input uncertainties, and large design variability. In addition, building design is a multi-collaborator discipline, where design decisions are influenced by architects, engineers, contractors, and building owners. This review covers developments in both academia and in commercial software industry that target these challenges. Identified research areas include statistical methods, optimisation, proactive simulations, knowledge based input generation, and interoperability between CAD-software and building performance software. Based on promising developments in literature, we propose a simulation framework that facilitates proactive, intelligent, and experience based building simulation which aid decision making in early design. To find software candidates accommodating this framework, we compare existing software with regard to intended usage, interoperability, complexity, objectives, and ability to perform various parametric simulations.},
+  file = {C\:\\Users\\hongy\\Dropbox\\literatures\\attachments\\Østergård et al_2016_Building simulations supporting decision making in early design – A review.pdf},
+  journal = {Renewable and Sustainable Energy Reviews},
+  keywords = {Building performance,Interoperability,Knowledge based input generation,Optimisation,Sensitivity analysis,Uncertainty analysis},
+  language = {en}
+}
+
 @book{Owens2006,
   title = {The Definitive Guide to {{SQLite}}},
   author = {Owens, Michael},
@@ -788,6 +873,37 @@ @article{Wickham2019
   number = {43}
 }
 
+@misc{Wikipedia2020,
+  title = {Object-Oriented Programming},
+  author = {{Wikipedia}},
+  year = {2020},
+  month = feb,
+  url = {https://en.wikipedia.org/w/index.php?title=Object-oriented_programming},
+  urldate = {2020-03-07},
+  abstract = {Object-oriented programming (OOP) is a programming paradigm based on the concept of "objects", which can contain data, in the form of fields (often known as attributes or properties), and code, in the form of procedures (often known as methods). A feature of objects is an object's procedures that can access and often modify the data fields of the object with which they are associated (objects have a notion of "this" or "self"). In OOP, computer programs are designed by making them out of objects that interact with one another. OOP languages are diverse, but the most popular ones are class-based, meaning that objects are instances of classes, which also determine their types.
+Many of the most widely used programming languages (such as C++, Java, Python, etc.) are multi-paradigm and they support object-oriented programming to a greater or lesser degree, typically in combination with imperative, procedural programming. Significant object-oriented languages include
+Java,
+C++,
+C\#,
+Python,
+PHP,
+JavaScript,
+Ruby,
+Perl,
+Object Pascal,
+Objective-C,
+Dart,
+Swift,
+Scala,
+Common Lisp,
+MATLAB,
+and
+Smalltalk.},
+  copyright = {Creative Commons Attribution-ShareAlike License},
+  journal = {Wikipedia},
+  language = {en}
+}
+
 @book{Xie2015,
   title = {Dynamic {{Documents}} with {{R}} and Knitr, {{Second Edition}}},
   author = {Xie, Yihui},
@@ -813,6 +929,38 @@ @article{Xie2019
   volumne = {40}
 }
 
+@article{Yan2008,
+  title = {{{DeST}} \textemdash{} {{An}} Integrated Building Simulation Toolkit {{Part I}}: {{Fundamentals}}},
+  shorttitle = {{{DeST}} \textemdash{} {{An}} Integrated Building Simulation Toolkit {{Part I}}},
+  author = {Yan, Da and Xia, Jianjun and Tang, Waiyin and Song, Fangting and Zhang, Xiaoliang and Jiang, Yi},
+  year = {2008},
+  month = jun,
+  volume = {1},
+  pages = {95--110},
+  issn = {1996-8744},
+  doi = {10.1007/s12273-008-8118-8},
+  abstract = {Many building simulation programs have been developed all over the world since the computer-aided simulation technology was first applied in the 1960s. In early 1980s, Tsinghua University has started to develop a new building simulation tool DeST with the aims to benefit for practical and research use of building simulation related applications in China. DeST can be used to simulate and analyze both building energy consumption and HVAC (heating, ventilation and air-conditioning) system. It has been designed to aim improving the reliability of system design, to ensure the quality of the system performance, and to reduce energy consumption of buildings. This paper reviews the development history, state-of-the-art on the development of building simulation technology and introduces the main objective, structure, and core programs of DeST. The analytical verifications, inter-program comparisons, and empirical validations of DeST are also presented in this paper. The application of DeST will be introduced in part II of the companion paper.},
+  file = {C\:\\Users\\hongy\\Dropbox\\literatures\\attachments\\Yan et al_2008_DeST — An integrated building simulation toolkit Part I.pdf},
+  journal = {Building Simulation},
+  language = {en},
+  number = {2}
+}
+
+@article{Yang2015c,
+  title = {A Model Calibration Framework for Simultaneous Multi-Level Building Energy Simulation},
+  author = {Yang, Zheng and {Becerik-Gerber}, Burcin},
+  year = {2015},
+  month = jul,
+  volume = {149},
+  pages = {415--431},
+  issn = {0306-2619},
+  doi = {10/f7fnf7},
+  abstract = {Energy simulation, the virtual representation and reproduction of energy processes for an entire building or a specific space, could assist building professionals with identifying relatively optimal energy conservation measures (ECMs). A review of current work revealed that methods for achieving simultaneous high accuracies in different levels of simulations, such as building level and zone level, have not been systematically explored, especially when there are several zones and multiple HVAC units in a building. Therefore, the objective of this paper is to introduce and validate a novel framework that can calibrate a model with high accuracies at multiple levels. In order to evaluate the performance of the calibration framework, we simulated HVAC-related energy consumption at the building level, at the ECM level and at the zone level. The simulation results were compared with the measured HVAC-related energy consumption. Our findings showed that MBE and CV (RMSE) were below 8.5\% and 13.5\%, respectively, for all three levels of energy simulation, demonstrating that the proposed framework could accurately simulate the building energy process at multiple levels. In addition, in order to estimate the potential energy efficiency improvements when different ECMs are implemented, the model has to be robust to the changes resulting from the building being operated under different control strategies. Mixed energy ground truths from two ECMs were used to calibrate the energy model. The results demonstrated that the model performed consistently well for both ECMs. Specific contributions of the study presented in this paper are the introduction of a novel calibration framework for multi-level simulation calibration, and improvements to the robustness of the calibrated model for different ECMs.},
+  file = {C\:\\Users\\hongy\\Dropbox\\literatures\\attachments\\Yang_Becerik-Gerber_2015_A model calibration framework for simultaneous multi-level building energy.pdf},
+  journal = {Applied Energy},
+  keywords = {Building energy simulation,Energy conservation measures,Model calibration,Multi-level}
+}
+
 @misc{Yi2020,
   title = {{{jEplus}}},
   author = {Yi, Zhang},