CO-SIMULATION BETWEEN ESP-R AND TRNSYS:MORE HIGHLY RESOLVED MODELLING OF INTEGRATED

BUILDING AND ENERGY SYSTEMS

Ian Beausoleil-Morrison1, Francesca Macdonald1, Michael Kummert2,Romain Jost2, and Tim McDowell3

1Carleton University, Ottawa Canada2Ecole Polytechnique de Montreal, Montreal Canada

3Thermal Energy System Specialists, LLC, Madison USA

ABSTRACTThe analysis of innovative designs that tightly inte-grate architectural and energy systems presents a chal-lenge for existing building performance simulation(BPS) tools. No single BPS tool offers sufficient ca-pabilities and the flexibility to resolve all the possi-ble design variants of interest. The development of aco-simulation between the ESP-r and TRNSYS sim-ulation tools has been accomplished to address thisneed by enabling an integrated simulation approachthat rigorously treats both building physics and energysystems. The application and capabilities of this newmodelling environment are demonstrated in this paper.

INTRODUCTIONThe need for integrated modellingFuture buildings must become less energy intensiveto address the pressing issues of energy security andthe environmental consequences of energy consump-tion. In the past, reductions in building energy in-tensity have been achieved through improvements tocomponents: increasing fabric insulation, reducing airleakage through the envelope, employing fill gases inglazings, increasing combustion efficiencies, etc. Witha few exceptions, solutions which integrate the build-ing structure and active energy systems have not beensought. Further improvements will be more difficultto achieve using such strategies—e.g. the diminish-ing returns that can be realized from additional insula-tion and the cost of lost floor area due to thicker wallsare limiting factors; combustion efficiencies are near-ing achievable limits; the risk of overheating inhibitsgreater exploitation of passive solar gains.Consequently, more complex designs are increasinglybeing sought, ones which more tightly integrate archi-tecture and active energy systems. Examples include:building-integrated photovoltaic systems with thermalrecovery (PV/t); hydronic-floor systems recoveringexcess passive solar gains and coupled to active stores;automated blinds controlled by central systems to con-trol overheating; thermal storage in the building struc-ture that is charged and discharged through HVAC sys-tems; buried seasonal stores that thermally influencethe house through the ground. With such conceptsthere is a tight coupling between the building fabric,occupant behaviour, energy systems, and controls.

Some of the earlier building performance simula-tion (BPS) tools (starting from the 1960s) subdividedthe problem domain, mainly because computing re-sources were limited, slow, and extremely expensive(see, for example, Sowell and Hittle, 1995). Theso-called Loads-Systems-Plant modelling strategy wascommonly employed in these early approaches, it sub-dividing the simulation of the building into three se-quential steps which essentially decouples the treat-ment of the architecture and energy systems. Althoughsuch sequential approaches can lo longer be justifiedfor reasons of computational efficiency, the ethos ofsegregating the treatment of building physics from en-ergy systems persists in the BPS field. For example, itis not uncommon for users to calculate building loadswith one tool for some assumed indoor environmen-tal conditions and set of occupant interventions, andthen to sequentially predict the performance of en-ergy conversion and storage equipment with anothertool through an imposition of these loads. For thereasons argued above, however, integrated approachesmust be advanced in order to accurately appraise themulti-variate state of buildings and their systems, anargument eloquently expressed by Clarke (1999).

The benefits of coupling

As argued by Trcka et al. (2009), no single BPS tooloffers sufficient capabilities and the flexibility to en-able the treatment of the types of integrated systemsmentioned above in an accurate and time-efficientmanner. State-of-the-art building performance (BPS)simulation tools such as ESP-r possess strengths inmodelling building physics. ESP-r possesses highlyresolved and well validated methods for modelling theinteractions between the indoor and outdoor environ-ments and the building fabric. Although it possessesdomains for treating HVAC and electrical systems ina dynamic and integrated fashion, ESP-r’s librariesof component models for these domains is wantingand the development of new components requires con-siderable expertise and knowledge of the program’ssource-code structure. In contrast, TRNSYS, whichwas originally developed for modelling renewable en-ergy systems, possess a structure and suite of compo-nent models that facilitate the simulation of renewableand other energy systems. Although components ex-

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ist for modelling building physics, TRNSYS currentlylacks the rigour and detail found in state-of-the-artBPS tools in this regard.One option for more integrated and highly resolvedsimulation is to add further capabilities to existingtools. This approach requires considerable expertiseand resources, and, unfortunately, a duplication of ef-fort as code is rarely reused from one code base to an-other, many times due to copyright and licensing re-strictions. A second option is to integrate the sourcecode of one tool into another, and many such exam-ples exist (e.g. Aasem, 1993; Dorer and Weber, 1999;Huang et al., 1999). A more ambitious approach is todevelop new BPS tools drawing upon new simulationparadigms. This is a hugely complex and resource-intensive undertaking, and furthermore it fails to cap-italize upon the decades of effort that have been in-vested in code development, testing, and validation.More recently, initiatives have been taken to couplecomplementary tools at run-time, enabling them to ex-change data as they march together through time. Thisoffers the possibility of a more highly resolved and ac-curate treatment of complex systems. This technique,commonly referred to as co-simulation in the litera-ture (Trcka et al., 2009), allows practitioners to drawupon the tremendous strengths of existing tools. Var-ious co-simulation techniques have been assessed anddemonstrated in the buildings domain (Janak, 1997;Djunaedy, 2005; Trcka et al., 2009; Wetter, 2011).

Figure 1: Co-simulation program and data flow

Co-simulation between ESP-r and TRNSYSA co-simulation has been effected between ESP-r andTRNSYS using methods that have been inspired bythe aforementioned authors, yet in a unique fashion.With this, ESP-r treats the building domain, and po-tentially a portion of the mechanical and electrical en-ergy systems; and TRNSYS resolves most or a por-tion of the mechanical and electrical energy systems.The design is both general and extensible and exploitsthe substantial capabilities of both ESP-r and TRN-SYS. Importantly, the design enables what is termeda strong or onion coupling involving the exchange ofdata during the time-step for the treatment of mechan-ical systems. This is illustrated conceptually in Figure

1, which shows how a newly developed middleware—called the Harmonizer—manages the co-simulation.Importantly, this is not a prototype or proof-of-concept. Rather, the co-simulation capabilities aresupported in the release versions of ESP-r and TRN-SYS1. An important aspect of the design is that thetwo simulation tools can continue to evolve their ca-pabilities independently without disrupting the co-simulation functionality. A detailed description ofthe methodologies employed by the ESP-r / TRNSYSco-simulator and a situation of its approaches rela-tive to those adopted by others is provided elsewhere(Beausoleil-Morrison et al., 2013).

Outline of paperThis paper describes the operation of the ESP-r / TRN-SYS co-simulator from the user’s perspective. Thenext section briefly discusses how the two simulatorsexchange information as they march forward throughtime to co-simulate a complete building and energysystem concurrently. It then describes how the userconfigures both ESP-r and TRNSYS for co-simulationby focusing upon a case study. This includes a de-tailing of the application of the new ESP-r and TRN-SYS components that were created to support co-simulation. It then demonstrates the types of analyzesthat have been enabled by the co-simulator by exam-ining the performance of a number of design variantsaimed at improving the performance of the case studyhouse and systems.

CO-SIMULATION APPROACHThere are significant differences in the simulationmethodologies employed by ESP-r and TRNSYS, andthis informed the design of the co-simulator.Referring to Figure 1, the Harmonizer controls theoverall co-simulation, instructing each BPS programto march through time in a synchronous fashion. ESP-r employs a partitioned solution approach wherein cus-tomized solvers treat each modelling domain (buildingthermal, nodal air flow, HVAC plant, electrical, etc).Once ESP-r’s HVAC plant domain has converged a so-lution for the current time-step, it communicates datato the Harmonizer through new plant components thathave been designed for this purpose. The Harmonizerthen passes these data to TRNSYS, where they are re-ceived by a new type, Type 130. Through TRNSYS’sstandard input-output mapping approach, these dataare then communicated to the normal TRNSYS typesand the TRNSYS simulation proceeds as usual for thegiven time-step. However, before the Harmonizer al-lows ESP-r and TRNSYS to march forward in time, itassess the state of data passed between the two simula-tors. If it concludes that these data have not stabilized,it imposes further invocations2 within the time-step.

1The co-simulation capabilities require ESP-r version 12.0 or higher and TRNSYS version 17.1 or higher. The Harmonizer is freely avail-able under an OpenSource license.

2Each simulator is forced to rewind its solution to the beginning of the time-step and repeat its solution process with the newly passed datafrom the other simulator.

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Figure 2: Co-simulation session: model inputs created through TRNSYS (top) and ESP-r (bottom right) interfaceswith a co-simulation running in a Cygwin xterm (bottom left)

With this design, the user creates models using boththe ESP-r and TRNSYS interfaces and then invokesthe co-simulation using the Harmonizer. This processis illustrated in Figure 2. As such, the user does not in-teract with the graphical interfaces of ESP-r and TRN-SYS in the usual fashion to launch the simulations.Consequently, the user cannot examine the progressof the simulation through the monitoring functionof ESP-r’s Building and Plant Simulator module, orthrough TRNSYS’s online plotter types. Rather, theHarmonizer invokes each simulator through a com-mand window such as the Windows CMD prompt or aCygwin xterm (see Figure 2).

CONFIGURING A CO-SIMULATIONThe process employed by the user to effect the cou-plings between ESP-r and TRNSYS is demonstratedthrough a case study that is described in detail else-where (Beausoleil-Morrison et al., 2013). This in-volves a low-energy house that is heated with asolar-thermal combination space heating and hot wa-ter system (solar combi-system), and by a photo-voltaic/thermal (PV/t) system.With the co-simulator, ESP-r treats the building do-main. Consequently, an ESP-r model was configuredto represent the building’s geometry and the thermal

characteristics of the building envelope, including airinfiltration, air flow through opened windows (an algo-rithm controls window openings in response to indoorand outdoor conditions to control overheating), con-tact with the ground, and the shading due to externalblinds (actuated in response to indoor conditions).

A schematic representation of the mechanical andelectrical systems is shown in Figure 3. The co-simulator design allows ESP-r and TRNSYS to col-laboratively model these systems using an approachthat is tightly coupled at the time-step level. With this,some components are treated in ESP-r while others byTRNSYS and data is exchanged between the simula-tors to predict the performance of the complete systemand its interaction with the building. In this case ESP-rtreats the PV collector and its thermal interactions withthe enclosure through which air is ducted. ESP-r alsomodelled the two fans, the water-air heat exchanger,and the fresh-air heat-recovery ventilator. These com-ponents are coloured light organge in Figure 3.

The air-air heat exchanger between the PV/t loop andthe conditioned air loop was modelled in TRNSYS aswere the dampers to allow the warmed air exiting thePV/t collector (from ESP-r) to bypass the the air-airheat exchanger. A user-defined equation was config-

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Figure 3: Collaborative simulation of solar and mechanical systems by ESP-r (components shown in light orange)and TRNSYS (components shown in dark blue)

ured in TRNSYS to take a control decision on the po-sition of these dampers. Based upon the sensed con-ditions of the house’s indoor air (from ESP-r) and thetemperature of the ducted air exiting the PV/t collec-tor (also from ESP-r), this controller would actuatethe dampers in TRNSYS to ensure that heat was onlytransferred from the PV/t loop to the house (and notthe reverse) and only when the house had a need forthis thermal energy.

The solar collectors and associated pump and con-troller were represented in TRNSYS. This pump andthe mixing valves on the hydronic space heating andDHW loops were controlled by components withinTRNSYS that received sensed inputs from other TRN-SYS components. The pump circulating water throughthe hydronic space-heating loop was controlled by aTRNSYS type based upon the house’s air temperaturepredicted by ESP-r. An ESP-r controller was used tomodulate the variable-speed fan that circulated returnair through the air-air and water-air heat exchangers.This fan was cycled to high speed when the house de-manded heat from the hydronic space-heating loop.Otherwise, it continuously circulated air at a lowerrate (and thus at a lower power draw) from October1 through April 30 in order to pick up heat from thePV/t system, when available.

From the user’s perspective, the co-simulation is firstconfigured by creating separate models in ESP-r and

TRNSYS (see Figure 2). A TRNSYS network wascreated using the Studio; types corresponding to thedark blue components in Figure 3 were added and con-nected in the usual manner. The new Type 130 wasalso added to the network to support the coupling toESP-r and this type was connected to the other types,as can be seen in Figure 4. For example, consider thepump that circulates hot water from the tank and auxil-iary heater to the water-air heat exchanger in Figure 3.This is represented in TRNSYS by a connection frompump-SH to Type 130 in Figure 4. And the cooledwater returning from the water-air heat exchanger isrepresented in TRNSYS by a connection from Type130 to pipe-SH.

The model of the house was constructed with ESP-r’s Project Manager interface in the usual manner, anda plant network configured to represent the light or-ange components in Figure 3. The new plant compo-nents designed for coupling with TRNSYS were theninserted and connected to the other components. Con-sider again the pump that circulates hot water fromthe tank and auxiliary heater to the water-air heat ex-changer. From ESP-r’s perspective, this is seen as astream of hot water that is received from TRNSYS.The new hydronic coupling component was added tothe ESP-r plant network to represent this stream of hotwater and it was connected to ESP-r’s water-air heatexchanger. This can be seen in Figure 5, where the

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Figure 4: TRNSYS network including Type 130 for coupling to ESP-r

Figure 5: ESP-r plant network connections including couplings to TRNSYS

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coupling component has been labelled HCC-R-1 (anylabel can be provided by the user) and the heat ex-changer has been labelled water-air-HX (see connec-tion A in the figure). Once the energy is transferred tothe air in ESP-r’s water-air heat exchanger, the cooledwater stream is returned from ESP-r to TRNSYS (seeconnection B in Figure 5).The PV/t system is handled in a similar manner. Recallthat ESP-r is sending two streams of air to TRNSYS(see Figure 3): return air from the building’s convec-tive heating system and warm air from the PV/t heatrecovery system. These streams originate from ther-mal zones in ESP-r and are communicated to TRN-SYS through two instances of ESP-r’s new air cou-pling component (see connections C and D in Figure5). These streams are received in TRNSYS by Type130 where they are directed to the cold and hot sidesof the air-air heat exchanger (see the red loop in Figure4), respectively. A user-defined equation (labelled By-pass in Figure 4) receives the temperatures of these airstreams and the temperature of the house from ESP-r and takes a control decision for the bypass valveto determine whether or not the PV/t system can andshould supply heating at the current time-step. Oncethe heat exchange between the air streams has takenplace, TRNSYS returns the two streams to ESP-r viaType 130 and the Harmonizer, where they supply twomore instances of ESP-r’s air coupling component.

EXECUTING A CO-SIMULATIONAND APPRAISING RESULTSOnce prepared in the manner outlined above, the ESP-r and TRNSYS models are ready for co-simulation. ATRNSYS deck file is created from the Studio and thelocation of this file is identified in a Harmonizer in-put file that is created with a text editor. This likewisespecifies the location of the ESP-r configuration file.A co-simulation is then commissioned by launchingthe Harmonizer program from a command line (seebottom left of Figure 2) and by specifying the Harmo-nizer input file. As mentioned, the Harmonizer man-ages the interactions between ESP-r and TRNSYS toenable them to collaboratively model the building andits energy systems. At each time-step of the simula-tion, data are passed back and forth between ESP-rand TRNSYS via the Harmonizer multiple times un-til system-wide convergence is achieved. (The com-putational burden of this has been found to be modest(Beausoleil-Morrison et al., 2013)).ESP-r and TRNSYS each create results files from thesimulation. Each program’s internal reporting toolsare aware of the data that are passed through the fluidcouplings, but otherwise are ignorant of variables cal-culated by the other. For example, referring to Figures4 and 5, ESP-r is cognizant of the flow rate and tem-perature of water that is passed from pump-SH into itsHCC-R-1 coupling component, but has no knowledgeof the operational state of the solar collector and tank

that are treated by TRNSYS. Similarly, Type 130 canbe linked to a TRNSYS printer to create a results filethat includes the flow rates and temperatures of the onewater and the two air streams received from ESP-r, butTRNSYS has no knowledge of the electrical energydrawn by the fans or the heat losses from the water-airheat exchanger to the containing zone. Consequently,an appraisal of the co-simulation requires an analysisof results files emanating from both simulation tools.This is achieved by synchronizing the ESP-r and TRN-SYS results files using their time stamps to develop acoherent view of overall system performance.Figure 6 provides an example of the results that canbe attained. By combining data from the ESP-r andTRNSYS results files, it plots for a two-day period thepassive solar gains through windows, the thermal con-tribution of the PV/t loop, and the thermal input fromthe solar thermal loop.

Figure 6: Solar thermal, PV/t, and passive solar inputto house over two days in February

APPRAISING PERFORMANCETHROUGH CO-SIMULATIONFor the case study introduced in the previous sectionthe house’s net space-heating load amounts to 33.1GJ over the course of the heating season (October 1through April 30). This is the net load imposed uponthe active energy systems after accounting for 7.9 GJof passive solar gains and 14.1 GJ of internal gains(some of which come from the tank’s skin losses).The PV/t system contributes 1.6 GJ of thermal energyand the solar thermal system contributes another 4.6GJ, resulting in almost 19% of the space-heating loadbeing met by the active solar systems. Furthermore,the solar thermal system meets 92% of the DHW load.1.6 GJ of electrical energy are required to operatethe systems’ fans and pumps, which amounts to 31%of the production from the PV/t system. The solar-generated electricity responds to 13.5% of the total

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demands generated by the non-HVAC loads, auxiliaryheaters, and pumps and fans.Possible measures aimed at improving this perfor-mance include the following (labels are used to iden-tify each):

• Adding additional insulation to the tank. (+ tankinsulation)

• Altering the control on the space heating hy-dronic loop to delay activating heater-SH for aperiod of time to preferentially supply the loadfrom the solar-charged tank. (delay heater-SH)

• Adding insulation to the house’s above-gradewalls. (+ wall insulation)

• Rather than conditioning the house to a con-stant temperature throughout the heating season,reducing the setpoint temperature of the spaceheating loop at night. (night setback)

• Increasing the flow rate of air through the PV/tcavity to increase the heat transfer rate in the air-air heat exchanger. (+ PV/t air flow)

• In addition to delaying the activation of heater-SH (refer to measure delay heater-SH), recon-figuring the space heating hydronic loop so thatthe tank and heater-SH are arranged in parallel.(parallel SH-loop)

• Increasing the airtightness of the house’s enve-lope. (+ airtight)

• Adding a triple glaze to the windows and apply-ing an on/off shading control to avoid overheat-ing rather than controlling the slat angle of theblinds. (triple-glazed)

Some of these measures alter the building envelopewhile others affect the energy systems. However,due to the strong interdependencies between these do-mains, a realistic appraisal of the impact of each mea-sure requires an integrated simulation. This need canbe demonstrated by considering the + PV/t air flowmeasure. Referring to Figure 7, it can be seen that theenhanced thermal gain from the PV/t system causesthe house’s air temperature to rise to 24oC on a coldwinter day. This is the setpoint temperature that trig-gers the deployment of the external blinds. The impactof this can be seen in the figure, which shows the sud-den reduction in passive solar gains shortly after 12h.Essentially, some of the additional thermal gains fromthe PV/t system are offset by a reduction in passivesolar gains, an effect that would go undetected if thetreatment of the energy systems were segregated fromthe simulation of the building physics. This effect wasrepeated on many days. When these results are inte-grated over the heating season, it is found that almostone quarter of the gains achieved by increasing the airflow rate through the PV/t cavity are offset by a reduc-tion in passive solar gains as a result of blind actuation.

Figure 7: Performance of measure + PV/t air flow ona single winter day

These heating-season-integrated results from the +PV/t air flow co-simulation as well as those from theother measures are given in Figure 8. Each measureis identified by its label. This figure also shows theperformance when a number of the effective individ-ual measures are combined (label combined). Withthis, the 35% of the space-heating load and 92% ofthe DHW load are met by the active solar systems,while the solar-generated electricity responds to al-most 22% of the total demands generated by the non-HVAC loads, auxiliary heaters, and pumps and fans.

CONCLUSIONSThis paper has demonstrated the application of theESP-r / TRNSYS co-simulator. It briefly described theco-simulation approaches employed and then focusedon how co-simulations are configured from the user’sperspective. By focusing on a case study, it demon-strated how the new TRNSYS type and the new ESP-rcoupling components are configured to enable the twoBPS tools to collaboratively simulate the behaviour ofa building with an integrated energy system. It thendescribed how results are attained, and illustrated howthese can be used to develop an appraisal of overallperformance.The design of the co-simulator exploits the strengthsof both simulation tools to enable the modelling ofinnovative building and energy system configurationsmore accurately than either simulation program couldachieve on its own. ESP-r treats the building domain,and potentially a portion of the mechanical and elec-trical energy systems; and TRNSYS resolves most ora portion of the mechanical and electrical energy sys-tems. Importantly, the design enables the collabora-tion between ESP-r and TRNSYS in modelling HVACsystems through the exchange of data within the time-step, an approach that is referred to as strong or onioncoupling in the literature. This is an important contri-

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Figure 8: Impact of individual measures on solar energy gains and auxiliary heating consumption integrated overheating season

bution because co-simulation methods that rely on aloose or ping-pong coupling approach could not ade-quately resolve tightly integrated architectural and en-ergy systems, such as were treated in this paper.The co-simulation is managed by a new middlewareprogram called the Harmonizer. The ESP-r / TRNSYSco-simulator is not a prototype or proof-of-concept.Rather, the co-simulation capabilities are supported inthe release versions of ESP-r and TRNSYS, while theHarmonizer is freely available under an OpenSourcelicense.

ACKNOWLEDGEMENTSThe authors would like to thank Natural ResourcesCanada for their financial support and for the guidanceprovided by Mr. Alex Ferguson.

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