Parametric & Hone User Guide

Transcription

1 Parametric & Hone User Guide IES Virtual Environment Copyright 2017 Integrated Environmental Solutions Limited. All rights reserved. No part of the manual is to be copied or reproduced in any

2 Contents 1 Introduction Elements Parametric User Interface Simulations Result Viewer Workflow Defining Simulation File Set from VE Elements - Defining Parameter Rules and Variables Importing Parameter Rules and Variables into Parametric Performing a Parametric Analysis Single Parameter Grouping Parameters Example Example Example Parametric - Results Exporting and Displaying Results Using Simulation Results Opening Template Rule Files Parametric - Templates Tutorial Model Utilising the Templates Opening Templates and Undertaking a Sensitivity Analysis Study Template 1 - Weather Files Template 2 - Heating System Performance Template 3 - Cooling Comfort Option Template 4 - Humidity Control Template 5 - DHW Performance Template 6 Solar DHW Performance Hone User Interface Workflow Defining Simulation File Set from VE Elements - Defining Rules and Variables Importing Parameter Rules and Variables into Hone Configuring the Hone Worksheet VE 2017 Parametric and Hone User Guide 2

3 4.8.1 Specifying the Objective Configure Simulation and Optimisation Options Configuring Actions Running an Optimisation Study Hone Worksheets Tutorial Model Utilising the Worksheets for Optimisation Studies Hone Templates Minimising Energy and Maximising Comfort with Heating Set-points Minimising Energy and Maximising Comfort with Humidity Control Glossary VE 2017 Parametric and Hone User Guide 3

4 1 Introduction This guide will describe two analysis tools which allow parameterisation of VE models: Parametric this enables users to create and batch run a series of Apache simulations. It provides a mechanism for making individual parameter changes prior to simulation. Typical Use: Sensitivity Analysis, Uncertainty Analysis & Design Options Hone this uses a genetic optimisation process for the minimization of an objective function (e.g. comfort, energy consumption, etc.). Typical Use: Design Optimisation, Model Calibration & Control Optimisation (LT Strategy / Real-time) The guide describes the workflow for Parametric and Hone. Both tools have a layered structure such that users are provided with a simple top-level interface to make high-level changes but access is also available to edit the underlying script and source code if added functionality is required. As a simple guide, the hierarchy can be viewed as follows: GUI Simulation Configuration / Target / Output Parameters Source Code

5 2 Elements The first step is to understand the Elements tool which facilitates the parameterisation of the VE model by defining the target parameters and output variables. The Elements tool requires the user to input data into two sections of the tool: The Rules which are the target parameters being changed during the simulations. The Variables which define the results outputs used to review model performance. Elements is presented in a simple UI, the view below illustrates the layout of the tool.. VE 2017 Parametric and Hone User Guide 5

6 Allows user to create a New Project Allows user to Add (+) a Rule or Remove (-) a rule Rule tab where the Target Parameters can be defined Output of the process that yields the definition of either the Target Parameters or Output Variables for the parametric tool Variables Tab where the Output Variables can be defined VE 2017 Parametric and Hone User Guide 6

7 3 Parametric Parametric - enables users to create and batch run a series of Apache simulations. Provides a mechanism for making individual parameter changes prior to simulation. Typical Use Cases: Sensitivity Analysis, Uncertainty Analysis & Design Options This document provides an overview of the ApacheSim based tool Parametric which enables users to create and batch run a series of Apache simulations, without the need for manual parameter changes (e.g. weather files, HVAC or constructions etc.). In addition to providing a simple batch queue mode, the tool allows a single parameter to be changed before running the Apache simulation. This extra mechanism enables the user to perform simple parametric studies on the same base model. This guide will enhance the user s capability to exploit the parametric tool by detailing the functionality through a series of steps. VE 2017 Parametric and Hone User Guide 7

8 3.1 User Interface The Parametric UI comprises of three sections: B A C A. Simulations o The data input in the Simulations section dictates the output of information in Results Viewer and Output Log. o The Simulations section requires the input of information into 3 fields, the Target File, Target Parameters and Output Variables. Detailed steps will be provided below. B. Results Viewer o The Result Viewer section produces live time results of the batch simulation. C. Output Log o The Output Log provides a time stamped log of the processes executed within the tool. VE 2017 Parametric and Hone User Guide 8

9 The toolbar consists of 4 tabs: File Provides the generic options to save your progress, open projects and create new projects. The latest version of the tool allows the users to import and export parameters and variables when the Parametric Tool is associated with the Elements tool. Project Provided 5 options which functionality will be explained below. View Presents to option to view or hide the Target file. Help VE 2017 Parametric and Hone User Guide 9

10 3.1.1 Simulations Under Parameter Range within the Elements tool: Lower: Lowest threshold value for sampling Upper: Highest threshold value for sampling Number of Steps: Number of samples to be selected within the given range This is where the definition for the Parameters (Model Inputs) and Variables (Vista Outputs) are reserved. Presents the option to Combine or Link variables The Parameters (Model Inputs) defined. VE 2017 Parametric and Hone User Guide 10

11 3.1.2 Result Viewer Variables (Vista Outputs) Live View of Results of Study during the simulation VE 2017 Parametric and Hone User Guide 11

12 3.2 Workflow The following steps are required to run a parametric analysis: 1. Define simulation file set from VE: Create Apache simulation file (APR File) to be used as base model for parametric batch study; 2. Open Elements and access model APR file: Create Model Inputs and Outputs and create parameters and variables files 3. Open Parametric and access model APR file: Import parameter and variables and then run simulation 4. Export Results to continue with analysis tools. VE 2017 Parametric and Hone User Guide 12

13 3.4 Defining Simulation File Set from VE To initiate an Apache simulation in a Parametric analysis requires firstly the creation of an Apache input file (APR). This input files contains all the model data necessary for simulations to be run at a later time. The Apache input files can be created within the VE s ApacheSim view as illustrated below Access the Apache view. 2. Click on ApacheSim (Dynamic Simulation) to load the simulation dialogue. 3. To create the APR file, click on Add to Queue. This will load a prompt stating that the APR file has been created and saved in the root directory of the model. VE 2017 Parametric and Hone User Guide 13

14 3.5 Elements - Defining Parameter Rules and Variables As stated earlier, the definition of the target rules (input parameters) and variables (results outputs) can be facilitated through Elements using the following steps: Part 1: Defining Rules within Elements Select the Apache Input file (APR) of the model under analysis. To define a Target Parameter, the user should work within the Rule tab. To add a target parameter, click on the Add symbol as illustrated. Once a rule has been added, the rule type can be defined. For illustration, Room Heating Set point will be selected. Once the rule type has been defined, the user will be required to state the parameter range of the rule such as the lower and upper bounds as well as the number of steps. The user will also have the option to either group the rooms and combine them into one parameter or generate one parameter for each room. VE 2017 Parametric and Hone User Guide 14

15 Part 2: Defining Variables within Elements Once the target parameters have been defined, the output variables can be selected within the Variables tab. Model and Room Level variables are available for selection By clicking on a variable, the user is presented with set of output options available for selection etc. Total, Maximum. Once the Rules and Variables have been defined, the user is required to Start the facilitation process and then Save the project to import it into the batch tool. Note that the project file containing the parameters and parameters is saved automatically in the Apache input file root directory. VE 2017 Parametric and Hone User Guide 15

16 3.7 Importing Parameter Rules and Variables into Parametric Part 1: Importing Parameter Rules and Variables into Parametric Import the Apache Simulation under analysis Within the Parametric Tool, the user can import the parameters and variables by Clicking on File -> Import Parameters and Variables. The parameters and variables will be imported without any further dialogue prompting. Note that the selected imported files must be the ones created for the current APR file. VE 2017 Parametric and Hone User Guide 16

17 Part 2: Running simulations within Parametric Once the parameter and variables have been imported, a list of simulation to be executed will be displayed under the Simulation dialogue. The Lower, Upper and Steps values are predefined in the Elements tool whilst Simulation states the number of simulation that will be performed for the parameter. Clicking on Start will initiate the simulation. The simulation can be cancelled at any moment by clicking on Cancel. Once the simulation have been completed, the results can be viewed under the Results dialogue. The results can be exported into an excel sheet by clicking on Export VE 2017 Parametric and Hone User Guide 17

18 3.8 Performing a Parametric Analysis Single Parameter For typical use cases such as sensitivity analysis, the user will have the opportunity to investigate how single parameters will impact the building s systems and operation, and correspondingly the internal environment. The parameters will be imported into Parametric from Elements as single parameters, hence the parameters are not grouped as shown below. Each permutation in the single parameters will be indepented and will not effect the output of additional simulation parameters. The total number of simulation of a study consisting of only single parameters will be the sum of the simulations to be completed for each parameter as highlighted. Therefore, the total number of simulations highlighted previously will equate to 13. Example 1 compromises four simulation parameters: 1. Independent parameter: Room Occupancy Sensible Gain 2. Independent parameter: Room Fluorescent Lighting Gain 3. Independent parameter: Room Computer Gain 4. Independent parameter: Apache System Cooling SSEER Parameter 01 Room Occupancy Sensible Gain W/m The independent parameter Room Occupancy Sensible Gain will run a total of 5 permutations between 55 W/m 2 and 75 W/m 2. Parameter 02 Room Fluorescent Lighting Gain W/m The independent parameter Room Fluorescent Lighting Gain will run a total of 3 permutations between 6 W/m 2 and 18 W/m 2. Parameter 03 Room Computer Gain W/m VE 2017 Parametric and Hone User Guide 18

19 The independent parameter Room Computer Gain will run a total of 3 permutations between 5 W/m 2 and 15 W/m 2. Parameter 04 Apache System Cooling SSEER The independent parameter Apache System Cooling SSEER will run a total of 2 permutations between 0.65 and Total number of simulations: = 13 VE 2017 Parametric and Hone User Guide 19

20 3.8.3 Grouping Parameters Within Parametric the user will also have the option to Combine or Link parameters which allows for multiple parameter changes within a single simulation. When added up across a range of parameter steps this leads on huge number of simulation permutations which can be quickly defined: o o Combining two or more parameters will result in running a simulation for each change of the combination of parameters. Meaning, a series of simulations will run to log all of the possible outputs of the combined parameters. Linked parameters must be associated to a parent Combined parameter, this will result in the addition of an extra set of simulations to each of the combined parameters. The grouping functionality has the power to significantly enhance the scope of a study and will therefore increase the total number of simulations performed. Four examples follow providing an insight to the grouping capability. VE 2017 Parametric and Hone User Guide 20

21 3.8.4 Example 1 If two of the parameters were combined as illustrated, a simulation will be performed for each permutation of the parameters combination and therefore the total number of simulation will be: Example 2 compromises four simulation parameters: (5x3) = Combined parameters: Room Occupancy Sensible Gain and Room Fluorescent Lighting Gain 2. Independent parameter: Room Computer Gain 3. Independent parameter: Apache System Cooling SSEER Parameter 01 Room Occupancy Sensible Gain (W/m 2 ) Room Fluorescent Lighting Gain (W/m 2 ) The combined Room Occupancy Sensible Gain parameter will run a total of 5 permutations between 55 W/m 2 and 75 W/m 2 with the other combined parameter Room Fluorescent Lighting Gain running a total of 3 permutations between 6 W/m 2 and 18 W/m 2. Each combination of the two parameters accounts for a single simulation, resulting in a set of 15 simulations. VE 2017 Parametric and Hone User Guide 21

22 Parameter 02 Room Computer Gain (W/m 2 ) The independent parameter Room Computer Gain will run a total of 3 permutations between 5 W/m 2 and 15 W/m 2. Parameter 03 Apache System Cooling SSEER The independent parameter Apache System Cooling SSEER will run a total of 2 permutations between 0.65 and Total Number of Simulations for Study: = 20 VE 2017 Parametric and Hone User Guide 22

23 3.8.6 Example 2 If the following grouping is applied where the Weather parameter is the parent parameter to the linked parameters. The weather parameter will first run seven times as an independent parameter. For each weather parameter, the Apache System Cooling SSEER parameter will be applied to it twice as well as the Room Cooling Set-point parameter. As a result the total number of simulations will be: Example C will compromise of three parameters: 7+ (7x2) + (7x2) = Combine weather parameter will run as an independent parameter. 2. Combine weather parameter will be linked to Apache System Cooling SSEER parameter. 3. Combine weather parameter will be linked to Room Cooling Set-point parameter. Parameter 01 Weather Variable Weather File 1 Weather File 2 Weather File 3 Weather File 4 Weather File 5 Weather File 6 Weather File 7 The weather parameter will run a total of 7 permutations by changing the weather file. Since only one variable was grouped as Combine, the first set of simulations will perform like an independent variable. VE 2017 Parametric and Hone User Guide 23

24 Parameter 02 Weather Variable Weather File 1 Weather File 2 Weather File 3 Weather File 4 Weather File 5 Weather File 6 Weather File 7 Ap. Sys. Cooling SSEER The combine weather parameter will run a total of 7 permutations while the linked parameter will run a total of 2 permutations between 0.45 and The linked Apache System Cooling SSEER parameter will act like a combined parameter for only this simulation set. Each combination of the two parameters accounts for a single simulation therefore resulting in a set of 14 simulations. Parameter 03 Weather Variable Weather File 1 Weather File 2 Weather File 3 Weather File 4 Weather File 5 Weather File 6 Weather File 7 Room Cooling Set-point ( o C) Again, the combine weather parameter will run a total of 7 permutations while the linked parameter will run a total of 2 permutations between 20 o C and 26 o C. Each combination of the two parameters accounts for a single simulation therefore resulting in a set of 14 simulations. Total Number of Simulations for Study: = 35 VE 2017 Parametric and Hone User Guide 24

25 3.8.7 Example 3 If the following grouping is applied where two parameters are grouped as Combine and two additional parameters grouped as Link : A simulation is performed for each permutation of the combined parameters and then for each of the linked parameters, the Room Computer Gain parameter will be applied three times and the Apache System Cooling SSEER will applied two times. As a result, the total number of simulations will be: Example 4 compromises four parameters: 5x2) + (5x2x2) + (5x2x2) = 50 - Two combined parameters: Room Occupancy Sensible Gain and Room Fluorescent Lighting Gain. - Combined parameters will be linked to Room Computer Gain. - Combined parameters will be linked to Apache System Cooling SSEER. Parameter 01 Room Occupancy Sensible Gain (W/m 2 ) Room Fluorescent Lighting Gain (W/m 2 ) The combined Room Occupancy Sensible Gain parameter will run a total of 5 permutations between 55 W/m 2 and 75 W/m 2 whilst the other combined parameter Room Fluorescent Lighting Gain will run a total of 2 permutations between 6 W/m 2 and 12 W/m 2. Each combination of the two parameters account for a single simulation, resulting in a set of 10 simulations. This can now be considered as the base set for the linked variables. VE 2017 Parametric and Hone User Guide 25

26 Parameter 02 Room Occupancy Sensible Gain (W/m 2 ) Room Fluorescent Lighting Gain (W/m 2 ) Room Computer Gain (W/m 2 ) The Room Computer parameter will run a total of 2 permutations between 5 W/m 2 and 15 W/m 2. By linking the Room Computer Gain parameter to the combined parameters or the base set (Room Occupancy Sensible Gain and Room Fluorescent Lighting Gain) will result in a total of 20 simulations. Parameter 03 Room Occupancy Sensible Gain (W/m 2 ) Room Fluorescent Lighting Gain (W/m 2 ) Ap. Sys. Cooling SSEER The Apache System Cooling SSEER parameter will run a total of 2 permutations between 0.6 and 1.0. As illustrated previously, by linking the Apache System Cooling SSEER parameter to the combined variables or the base set (Room Occupancy Sensible Gain and Room Fluorescent Lighting Gain), will result in a total of 20 simulations. Total Number of Simulations for Study: = 50 VE 2017 Parametric and Hone User Guide 26

27 3.9 Parametric - Results Exporting and Displaying Results Once the required results have been obtained, and these are visible under the Results Viewer, click on the Export icon on the top left of the tool. The results will be exported in XLS format and placed in the parametric_batch folder of the project directory. Note: Results can be exported and viewed even if the simulations are cancelled. Once the desired results have been obtained, make sure that all simulations are inactive and press Export The results documents will be located in the parametric_batch folder within the project directory. An example of the result document. An endless number of results can be created without having to worry about the tool overwriting previous results. VE 2017 Parametric and Hone User Guide 27

28 3.9.2 Using Simulation Results Since Parametric enables the user to run a multitude of dynamic simulations then managing the results output is the next logical step. The results are best used by importing the CSV output file into an Excel spreadsheet, then formatting where appropriate. The example below demonstrates applying conditional formatting to the results. VE 2017 Parametric and Hone User Guide 28

29 3.10 Opening Template Rule Files Opening the template file in Elements is as follows: It should be noted that Elements files are organised in the.rule format. The rule file can be loaded into Elements by clicking on Open Project (1) and proceeding to select the rule file (2). The Solar Panel DHW template will be selected for demonstration purposes. 1 Within Elements the user should select the target APR file. The Tutorial Mode APR will be used for demonstration. 2 Once the template file has been loaded, the predefined Rules and Variables will be produced. The user will have the option to redefine the parameter range if desired. Once the Rules and Variables have been defined, the user is required to click on Start the create the files needed to define the model inputs and outputs for use in either the Parametric or Hone tools. Note that the parameters and variables files are saved automatically in the Apache input file root directory. VE 2017 Parametric and Hone User Guide 29

30 3.12 Parametric - Templates Six Parametric templates exist providing a starter set of sensitivity studies and are as follows: 1. Weather Files 2. Heating System Performance 3. Cooling Comfort Option 4. Humidity Control 5. DHW Performance 6. Solar Panel DHW (Solar Heating System) Tutorial Model The selected tutorial model is a generic multi-storey office building compromised of open plan offices, meeting rooms, circulation and toilets Utilising the Templates The process of utilising the templates involves first the use of Elements to create the parameters (model inputs) and variables (model outputs) that must be imported into Parametric for the sensitivity study. The templates can be utilised by adhering to the following steps. VE 2017 Parametric and Hone User Guide 30

31 Opening Templates and Undertaking a Sensitivity Analysis Study Start with selecting target APR file of the model under analysis. Once selected, click on Open Project and select the preferred template of the study. The template file is in a.batch format. After selecting the template, the pre-set sensitivity analysis study will be produced. Within the Parametric tool, the user can edit the simulation settings such as the lower and upper bounds, number of simulations, steps and will have the option to group the parameters. The Sensitivity Analysis Study can be initiated by clicking on the Start button. The description of the output of each of the six templates will be illustrated in the following section. VE 2017 Parametric and Hone User Guide 31

32 Template 1 - Weather Files Model Input: Under Parameter Range within the Elements tool: Lower: Lowest threshold value for sampling Upper: Highest threshold value for sampling Number of Steps: Number of samples to be selected within the given range Model Outputs: - Apache System Total Boiler Load (MWh) - Apache System Total Cooler Load (MWh) - Project Local Weather File - Apache System Cooling SSEER - Apache System Heating SCoP Result Viewer Dialogue within the Parametric Tool Using Results for Post Analysis: The benefits of the Result file can be reaped in several ways using Excel. For etc.: The user desires to conduct a study on: 1. Heat pump's true energy consumption (SCoP) effect on the annual energy consumption. 2. Effect of location and climate on building s heating and cooling systems. VE 2017 Parametric and Hone User Guide 32

33 Template 2 - Heating System Performance Model Inputs: Model Outputs: - Room Heating Plan Sensible Load - Boiler s Load - Boiler s Energy - Total Energy - Occupancy Sensible Gain - Miscellaneous Gain - Infiltration Rate - Apache System Heating SCoP - Room Gain Flourescent Lighting VE 2017 Parametric and Hone User Guide 33

34 Template 3 - Cooling Comfort Option Model Inputs: Model Outputs: - Chiller Energy - Total Energy - Fluorescent Lighting Gain - Miscellaneous Sensible Gain - Infiltration Rate - Cooling Set point VE 2017 Parametric and Hone User Guide 34

35 Template 4 - Humidity Control Model Inputs: Model Outputs: - Room Humidifier Plant Load - Room Dehumidifier Plant Load - Room Humidity Control (Lower Limit) - Room Humidity Control (Upper Limit) VE 2017 Parametric and Hone User Guide 35

36 Template 5 - DHW Performance Model Inputs: Model Outputs: - Apache System Boiler s DHW energy - DHW Supply Temperature - DHW Delivery Efficiency - DHW Storage Losses - DHW Storage Volume VE 2017 Parametric and Hone User Guide 36

37 Template 6 Solar DHW Performance Model Inputs: Model Outputs: - Apache System Boiler s DHW energy - Total System Energy - Apache System Solar Panel Area - Apache System Solar Panel First Order Loss Coefficient - Apache System Solar Panel Efficiency VE 2017 Parametric and Hone User Guide 37

38 4 Hone Hone uses genetic optimisation process for the minimization of a cost function (e.g. comfort, energy consumption, etc.). Typical Use-Cases: Design optimisation, model calibration & control optimisation (LT Strategy / Real-time) This document describes the general work-flow for Hone. Both tools have a layered structure such that users are provided with a simple top-level interface to make high-level changes, but access is also available to edit the underlying script and source code if added functionality is required. As a simple guide, the hierarchy can be viewed as follows: GUI Simulation Configuration / Target / Output Parameters Source Code VE 2017 Parametric and Hone User Guide 38

39 4.1 User Interface The Hone Tool is a development environment for defining and working with optimisation worksheets. An optimisation worksheet provides a link between the problem domain and the optimisation algorithm. When the Hone Tool is launched the user can create a blank optimisation worksheet by selecting the Add Optimisation Worksheet option from the Project menu. Components must then be added to the worksheet to define the optimisation problem. An initial, empty, worksheet is shown below. Components need to be added to define the optimisation run. Typically the Hone Tool will be employed to find a solution to a particular class of problem. For example, the application of design options to my current model in order to minimise operational energy. The tool can be thought of as having two roles. The application to design a new optimisation worksheet and the application from which from which an optimisation run can be launched and monitored. VE 2017 Parametric and Hone User Guide 39

40 Model: Defines the IES <VE> model that provides the base for the optimisation Allows user to Create New Projects, Open Previous Projects and Save Projects Starts and Stops Simulations Definition: Objectives: defines the goal or trade-off to be explored. Design Parameter: Defines the parameters that can be changed in the model. Constraints: Can be set-up to limit the design space to be explored Simulation: Simulation Control: User can assign a number of simulation engines. Actions: This group is used to define operations to be performed after each generation is complete or at the end of the optimisation run. Importantly, the user can specify how the optimisation results are exported to other tools. Optimise: Settings: the user has control over some of the parameters to define how the GA operates. For example the user can specify the number of individuals in each generation. Progress: Graphs can be added to this section so that the user can monitor progress of the optimisation run. VE 2017 Parametric and Hone User Guide 40

41 4.2 Workflow The following steps are required to run a Hone study: 1. Define simulation file set: Create Apache simulation file (APR File) to be used as base model for optimisation study. 2. Open Elements and link to APR file: Create Model Inputs and Outputs and create parameters and variables files. 3. Open Hone and link to APR file Start the optimisation program and link to the relevant VE base model file (APR) and Import Parameters and Variables. 4. Specify the objective and complete the Hone worksheet Specify the appropriate objective/target functions (e.g. energy) to be optimised and then start the Optimisation Study. 4.3 Defining Simulation File Set from VE To initiate an Apache simulation in a Parametric analysis requires firstly the creation of an Apache input file (APR). This input files contains all the model data necessary for simulations to be run at a later time. The Apache input files can be created within the VE s ApacheSim view as illustrated below. 1. Ensure that the Apache module is accessed 2. Clicking on ApacheSim (Dynamic Simulation) will produce the Apache Simulation dialogue. 3. To create the APR file, simply click on Add to Queue. This will prompt message stating that the APR file has been created and saved in the root directory of the model. VE 2017 Parametric and Hone User Guide 41

42 4.5 Elements - Defining Rules and Variables As stated earlier, the definition of the target parameters and output variables can be facilitated with the aid of the Elements tool and can be achieved by following these steps. Part 1: Defining Rules within Elements Select the Apache Input file (APR) of the model under analysis. To define a Target Parameter, the user should work within the Rule tab. To add a target parameter, click on the Add symbol as illustrated. Once a rule has been added, the rule type can be defined. For illustration, Room Heating Set point will be selected. Once the rule type has been defined, the user will be required to state the parameter range of the rule such as the lower and upper bounds as well as the number of steps. The user will also have the option to either group the rooms and combine them into one parameter or generate one parameter for each room. VE 2017 Parametric and Hone User Guide 42

43 4.7 Importing Parameter Rules and Variables into Hone Part 2: Importing Parameter Rules and Variables into Hone Add an Optimisation Worksheet by clicking on Project and Add Optimisation Worksheet from the dropdown list. Once an optimisation has been added, select the Apache Input file (APR) of the model under analysis under Model (1). The predefined Parameters and Variables for the model can now be imported into the Hone tool by clicking on Import (2). 1 2 Once the parameter and variables have been imported, Design Parameters will be populated by the changing variables of the study, displayed under the Definition branch. The lower bound and upper bound values are predefined in the Elements tool but can still be redefined within the Hone tool. VE 2017 Parametric and Hone User Guide 43

44 4.8 Configuring the Hone Worksheet Once the parameters and variables have been imported, the user can now begin to configure Hone to run an effective optimisation study Specifying the Objective The definition group defines the optimisation problem. An optimisation problem is defined in terms of: o Objectives the cost functions of the optimisation problem o Design Parameters the quantities or settings in the model that can be changed After importing the parameters and variables, one or more objective can be specified. The objectives defines the goal or trade-off to be explored. The user will have the option to combine one or more of the following design studies: - System Energy Consumptions - Carbon Emissions - Occupant Comfort Under the Definition branch, the user can add one or more objective by clicking the +. Once an Objective is added, the user can specify the objective by selecting the design study. The user will be capable of running a multi-objective study by simply adding another objective. VE 2017 Parametric and Hone User Guide 44

45 4.8.2 Configure Simulation and Optimisation Options The user may now configure the following options relating to the simulation engine and optimisation routine: Simulation Control: Specify the number of Apache simulations to run in parallel (more simulation = more CPU cores and utilisation rate, and quicker convergence time). The example shown in the figure below is using 4 CPU Cores. Optimisation Settings: These setting relates to the optimisation routine: o Generations: The number of evolutionary generations to compute it is advisable to leave this setting as high as possible as the simulation can be stopped at any time during the optimisation process once satisfactory results have been achieved; o Population Size: Specifies the number of samples within each generation. This number should be sufficiently large in order to identify optimal evolutionary trajectory (this will vary depending on the number of objectives/constraints and the complexity of the model, but a setting of 32/64 is recommended here). Progress: Here, the user can specify which charts to display to track progress during the optimisation study: Type Description Example VE 2017 Parametric and Hone User Guide 45

46 Summary Plot is updated after every evaluation of the cost function. Ie after every variant model has been simulated. Plot shows objective values for the first generation and the last two generations. This is useful to see where the optimisation started and how it is progressing. The red dots should the current generation, ie models that will form the next set of results to be considered by the algoihtm. The plot includes the current pareto front (green). Pareto The current Pareto curve. Updated after each genertion is completed. Pareto + All The current Pareto front, plus all model evaluations. VE 2017 Parametric and Hone User Guide 46

47 4.8.4 Configuring Actions Finally, the user may configure what actions to perform at different stages of the optimisation (e.g. Display Pareto objectives, output results to file etc.). The Pareto objective values and Pareto variables will be displayed in the Output Log dialogue of the Hone tool. Hone - Post-processing actions 4.9 Running an Optimisation Study When the Optimisation Worksheet is complete and the objectives have been specified, the user can now run an optimisation study. Click on the Start button. If the user opted to add progress graphs, the user can observe and track the progress of the optimisation study. If the user specified to display tables for Pareto variables or Pareto Objective values, they can be displayed in the Output Log dialogue. VE 2017 Parametric and Hone User Guide 47

48 By referring to the Pareto progress graph, the optimum variable setting is found when the Pareto curve stops varying and the study can be paused by clicking on the Cancel button. The output result file containing the Pareto variables and objective values tables will be saved in the project directory. VE 2017 Parametric and Hone User Guide 48

49 4.10 Hone Worksheets Optimisation worksheets provides a link between the problem domain and the optimisation algorithm. With the aid of prepared worksheets, the user will gain the opportunity to undertake a several optimisation studies. The readily available studies accessible to the user are as follow: 1. Minimising Conditioning Energy and Maximising Comfort 2. Optimising Humidity Levels for Comfort and System s Energy Tutorial Model The selected tutorial model is a generic multi-storey office building compromised of open plan offices, meeting rooms, recirculation areas and toilets. The office building is accurately modelled to effectively illustrate the utilisation of the different preconfigured worksheets for optimisation studies in the physical world. VE 2017 Parametric and Hone User Guide 49

50 Utilising the Worksheets for Optimisation Studies The process of utilising the templates first involves the use of Elements to create the parameter rules and variables. The process of exploiting the worksheets is efficient and only requires the use of the Hone Tool as the objectives and variables are predefined. The preconfigured worksheets can be utilised by adhering to the following steps. Undertaking an Optimisation Study using the Parametric Tool Within Hone, click on Open Optimisation Project and select the worksheet desired for the study. The worksheet will be in a.moop format. Once the optimisation worksheet is selected, the user will be presented with a preconfigured worksheet and the user can now prepare the worksheet to run a study on the desired model: 1. Start with selecting the Apache Input File of the model (APR) 2. The design parameters are pre-set, but if the user desires to alter the bounds of the variables, this can be done at ease by inputting the preferred values. 3. We highly advise to revise the Simulation setting to ensure that the appropriate amount of Apache simulations to run in parallel are suitable for the user s machine. Click on Start to begin the optimisation study. VE 2017 Parametric and Hone User Guide 50

51 4.11 Hone Templates Minimising Energy and Maximising Comfort with Heating Set-points Example of Summary Progress Chart: Objectives: - Maximise Comfort by minimising occupancy weighted PPD - Minimise Total System s Energy Consumption Design Parameters / Variables: - Room Heating Set-point - Room Cooling Set-point Example of Pareto Progress Chart: VE 2017 Parametric and Hone User Guide 51

52 Minimising Energy and Maximising Comfort with Humidity Control Example of Summary Progress Chart: Objectives: - Maximise Comfort by minimising mean PPD - Minimise Total System s Energy Consumption Design Parameters / Variables: - Room Humidity Lower Limit - Room Humidity Upper Limit Example of Pareto Progress Chart: VE 2017 Parametric and Hone User Guide 52

53 5 Glossary - Apache Input File: The APR file encompasses all the input parameters for an Apache simulations and allows simulation to be run at a later time, i.e. at a time governed by the batch simulator. - Elements Rule: Is a description of how a model is to be parameterised. A rule can generate a number of parameters (or none) and aims to be model independent. A set of rules may be represent a particular analysis the user would like to perform. When the rule is applied to a model it creates a set of parameters targeting a model properties. For example a rule can say parameterise the lighting gain in a room. The rule can be set up to generate a parameter for each room, or combine so that all rooms are adjusted together. - Elements: A tool that facilitates the parameterisation of the model by defining the target parameter rules and output variables by creating a defining command in opposed to the user manually inputting the command into the parametric tool. - Generations: Evolutionary algorithms such as the one used by Hone, progress in by performing groups of simulations. The cost function (objectives) are evaluated for each simulation in the group. The algorithm then uses the objectives to determine what simulations to perform in the next iteration or group of simulations. - Hone Worksheet: Optimisation worksheet provides a link between the problem domain and the optimisation algorithm. Worksheets can run Apache simulations with a number of user defined defined parameters. Model Worksheets can be created, saved and transferred and are formatted as.moop files. - Hone: A tool that uses a genetic optimisation process for the minimization of a cost function (e.g. comfort, energy consumption, etc.). - Optimisation Study: A study that aims to find an alternate with either the most cost effective or highest attainable performance under the given constraints, by maximizing desired elements and minimizing undesired ones. - Parameter: A numerical factor that defines a system or the conditions of a system s operation. - Parametric: A tool that enables users to create and batch run a series of Apache simulations. Provides a mechanism for making individual parameter changes prior to simulation. - Pareto: The Pareto front represents the trade-off curve that highlights the balance between the two or more potentially conflicting objectives. - Population Size: The number of samples within each generation in a Hone based optimisation study. - Sensitivity Analysis: A study that aims to determine how different values of an independent variable effects a dependent variable subject to a set of conditions. - Variables: A numerical value that is subject to change. VE 2017 Parametric and Hone User Guide 53