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To cite this article: Shahrestani, Mehdi. Yao, Runming. and Cook, Geoffrey. K. (2013). Developing new components for variable flow distribution system modelling in TRNSYS. Building Simulation, 6 (3), 309-322. To link to this article DOI: 10.1007/s12273-013-0123-x

Developing new components for variable flow distribution system modelling in TRNSYS

Mehdi Shahrestani1, Runming Yao1* and Geoffrey K Cook1 1

School of Construction Management and Engineering, University of Reading, Whiteknights, PO Box 219, Reading, Berkshire, UK,

ABSTRACT This study attempts to fill the existing gap in the simulation of variable flow distribution systems through developing new pressure governing components. These components are able to capture the actual ever-changing system performance curve in variable flow distribution systems together with the prediction of controversial issues such as starving, over-flow and the lack of controllability on the flow rate of different branches in a hydronic system. The performance of the proposed components is verified using a case study under design and off-design circumstances. Full integration of the new components within the TRNSYS simulation package is another advantage of this study, which makes it more applicable for designers in both the design and commissioning of hydronic systems.

Keywords: Hydronic system, Variable flow distribution system, Building simulation, Variable speed pump, TRNSYS

* : Corresponding author

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1. Introduction Heating, ventilation, air conditioning and refrigeration (HVAC&R) systems account for more than 60% of the total building energy consumption in the UK (DECC 2010). Meanwhile, heating and cooling distribution systems are the most common parts of HVAC&R systems, which account for a significant portion of energy used in HVAC&R processes. For instance, in office buildings, the distribution systems account for more than 20% and 30% of the energy consumption and CO2 emissions of HVAC&R systems respectively (ECG-19 2000; CIBSE 2004). Therefore, an accurate design and a precise performance evaluation of distribution systems are essential to achieve energy efficiency in HVAC&R systems. In HVAC&R systems, heating/cooling could be distributed using water or air as a carrier fluid. To narrow down the scope of work, the water distribution system (hydronic system) is the focus of this study. The most challenging issue in the modelling of the variable flow hydronic systems is to find the actual operating point (Petitjean 1994; Parsloe 1999; ASHRAE 2008). This is a unique point, at which the pressure and flow rate of the hydronic system and the circulation pump are exactly identical.

2. Problem statement The literature reveals two dominant approaches for the modelling of hydronic systems (Gamberi et al. 2009; Klein et al. 2009; EnergyPlus 2011; IES 2011). The first approach is based on using a pre-set operation point, whereas the second is to

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find the operating point according to the intersection of predefined system and pump performance curves. Under a constant flow regime using a single speed circulation pump, the first approach is able to simulate the actual performance of hydronic systems as long as an accurate pre-set operating point is defined. Due to the complexity of the process of finding the actual operating point, the second approach automates the process. This is achieved through a successive mathematical operation to find the intersection of pump and hydronic system performance curves (EnergyPlus 2011). However, when the hydronic system performs under a variable flow regime using a variable speed pump, neither of these two methods is able to provide an accurate operating point. This is mainly due to the ever-changing nature of the system performance curve under the variable flow regime. In the real world, the performance of variable flow hydronic systems depends critically on the operation of control valves. Any small alteration in the opening fraction of these flow control devices significantly changes the system performance curve (Parsloe 1999; Klein et al. 2009); which is not considered within the existing simulation tools such as TRNSYS, IES and EnergyPlus (Klein et al. 2009; EnergyPlus 2011; IES 2011). In the IES simulation package, finding the interaction between system and pump performance curves is not considered and the first approach is adopted (IES 2011). Alternatively, in EnergyPlus, both approaches are provided optionally. But, in EnergyPlus, some unrealistic assumptions are considered for the second approach of hydronic system modelling (EnergyPlus 2011):

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

the performance curve of a hydronic system is supposed to be an input function for the model; whereas, identification of the system performance curve is highly unlikely to be accurate, especially in a variable flow regime with an ever-changing opening fraction of the control valves,



for the parallel loops, the pressure drops of branches are not defined based on the flow rate of each branch. Instead, the maximum pressure drop within branches is set for all branches. To compensate for the excessive pressure, an imaginary valve (pressure drop source) is placed within the low pressure branches,



the flow rate of branches are directly controlled by heating and cooling demands, which does not comply with the actual pressure governing approach of hydronic systems (Petitjean 1994).

The above points culminate in a deficiency of the model in prediction of the starving (during off-design conditions) and over-flow (during warm-up period) phenomena in hydronic system balancing and control (Avery 1993; Lau 1996; Lau 1996; Taylor 2002). Similar to EnergyPlus, the TRNSYS simulation package does not provide a pressure governing model for hydronic systems. In the other words, the flow rate of hydronic system is directly controlled by heating and cooling demands (Klein et al. 2009). Like EnergyPlus, TRNSYS, provides two options for modelling the circulation pump within a hydronic system. The first model is based on a predefined operating point and the second is designed to find the operating point (intersection of system and pump performance curves). In the second option, the system performance curves are assumed to be fixed through the modelling (Klein et al.

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2009). This approach produces inaccurate results due to the ever-changing system performance curve found in variable flow hydronic systems. This study is designed to overcome these deficiencies in TRNSYS. To this end, a set of new and modified models is developed to simulate the dynamic performance of the main components of a hydronic system, including; circulation pumps, control valves, heating coils, pipes and fittings. The following sections introduce the HVAC&R system modelling approaches along with the proposed model for simulation of hydronic systems and a comprehensive case study for verification of the proposed model.

3. HVAC&R system modelling and simulation approaches HVAC&R system modelling and simulation approaches that are adopted in Building Performance Simulation (BPS) tools can be categorised by taking into account different aspects of HVAC&R system modelling. In a coarse distinction, HVAC&R system simulation tools are categorised based on their modelling approaches including: steady-state or dynamic, general or domain specific, stand alone or integrated, simultaneous or sequential and conceptual or explicit (Hensen 1996; Trcka and Hensen 2010; Trcka and Hensen 2011). Among these, taking into account the level of abstraction (conceptual or explicit) provides a distinctive notion about the structure of HVAC&R system modelling approaches. Considering the level of abstraction, Hensen (1996) categorised the HVAC&R system modelling approaches into four dominant categories, ranging from purely conceptual towards more explicit which are: 

Purely conceptual

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

System-based

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Component-based

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Component-based multi-domain

Here, it should be noted that the second introduced approach (system-based) is also addressed in the open literature as “template-based” approach for HVAC&R system modelling (Strand et al. 2002). In HVAC&R system simulation tools using “purely conceptual” modelling approach, the representation of the primary and secondary HVAC&R systems is purely conceptual. In the other words, only room processes are considered, while other processes and equations in both primary and secondary systems are assumed ideal and it is only possible to impose a capacity limit upon them. Most of the stateof-the-art BPS tools are equipped with a simplified option to perform in this conceptual simulation level (Hensen 1996; Trcka and Hensen 2010; Trcka and Hensen 2011). In the contrast with purely conceptual models, system-base (template-based) modelling approach includes both the primary and secondary HVAC&R systems and provides a set of pre-configured models for common HVAC&R systems like Constant Air Volume (CAV) and Variable Air Volume (VAV) systems as well as main plant equipment such as boilers and chillers. In the building performance simulation (BPS) tools formed based on this modelling approach, users have the flexibility to specify some parameters of the model such as capacities, flow rates and efficiency of the predefined components, but it is restricted to the system configurations that are pre-defined in the tool. DOE-2 (Bridsall et al. 1990), HAP

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(Carrier 2003; Carrier 2012) and BLAST (Treado et al. 1986) are of the common BPS tools in this category. The third category of HVAC&R system modelling approaches (component-based) was mainly developed to provide flexibility for the configuration of components within HVAC&R systems. In this approach, the user defined arrangement of the components along with the user specified interconnections between the components form the final model of a HVAC&R system (Hensen 1996; Trcka and Hensen 2010; Trcka and Hensen 2011). HVACSIM+ (Clark et al. 1985) and TRNSYS (Klein et al. 2009) are well-known examples for this category of simulation approaches. In the fourth category of HVAC&R system modelling approaches (Componentbased multi-domain), there are additional interconnections between components compared with the original component-based modelling approach (the third category). For instance, to balance an air or water system, apart from the normal connections (representing the physical connections between the components of a real HVAC&R system), the configuration and specifications of the air or water distribution network are defined and interrelated to another domain to provide a platform for simultaneous solving the pressure and mass balance equations of the air or water distribution network (Hensen 1996; Trcka and Hensen 2010; Trcka and Hensen 2011). Likewise, this study has introduced a new approach in TRNSYS for balancing the flow rate and pressure of the hydronic systems that is integrated within the proposed component for circulation pump. The hydronic system network configuration and specifications (as a set of user inputs) are encapsulated within the newly developed component for circulation pumps. In the other words, the proposed model for

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circulation pumps includes both the circulation pump model and specification of hydronic system as a network. Descriptions of the proposed models for simulation of hydronic systems are described in the next section.

4. Model description TRNSYS is a modular simulation package in which all devices and equipment are referred to as "Type" (e.g. Type 1 is a solar collector). In this study, two new components are developed. The first component is called the network-pump (Type 247). As mentioned earlier, this component includes both the hydronic network specifications and the numerical model for the simulation of variable speed circulation pumps. The second new component is a two-port control valves (Type 212) which is developed in this study to simulate the performance of two-port valves within variable flow hydronic systems. Besides, some of the existing TRNSYS components are modified in order to be used for pressure governing modelling of hydronic systems. Pressure drop calculation is amended to the existing pipe component (Type 709) and the existing pipe fitting components such as diverter 'Tee' (Type 11f) and mixer 'Tee' (Type 11d). Consequently, the modified components for pipe, diverter and mixer 'Tee' are introduced as Types 210, 221 and 222 respectively. Also, the existing model of heating coil (Type 733) is improved by adding a pressure drop-flow data file for coil pressure drop calculation during partial load circumstances and is then referred to Type 229. Following the brief introduction of the new and modified components proposed in this study, the detailed modelling descriptions of these components are provided in the next subsections.

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4.1 Circulation pump and hydronic network (network-pump) As it was mentioned in the previous section, the hydronic network arrangement and specifications together with the numerical model for the circulation pump are encapsulated within the newly developed component called network-pump (Type 247). In the other words, this component includes both the pump specifications and hydronic network arrangement and specifications. Inputs and parameters which are considered to be specified by users along with the output of the newly developed network-pump component(Type 247) are demonstrated in Appendix A. Figure 1 shows the flowchart algorithm of the proposed model for the network-pump (Type 247). This model is developed to find the actual operation point of the hydronic system (intersection of circulation pump and hydronic system performance curves).

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Start Inputs: SF, Kv (n), Inlet fluid flow rate, inlet fluid pressure, inlet fluid temperature Parameters: flow min, flow max, n, pipes size (n), fittings size (n), fittings type (n) pump performance curve (pressure, flow, power), coil pressure drop-flow data file x0=( flow min +flow max)/2 Pressure loss (x0, n), n=1 to n Pump head(x0, SF) =pump head(x0, SF=1) ×SF2 Loop for i=1 to n f(x)=pressure loss(x0, i)-pump head(x0,SF) Newton-Raphson Flow branch (i) End loop 'i' n

Total branches flow=Σi=1 flow branch (i) f(x) = total branches flow - x0 x x phead(x,speed) Newton-Raphson Pump flow rate=total branches flow Pump power (pump flow rate, pump head, SF) = pump power (pump flow rate, pump head, SF=1) ×SF3 Pump outlet fluid pressure= pump inlet fluid pressure + pump head (pressure rise)

|pump flow rate- x0|