Modules in the developed simulation model

As shown in Figure 4-2, each operation is represented by a module. In addition to the developed modules for logistics operations, a module called Information Management (IM) module was developed. This module is the heart of the simulation model as it is responsible for integrating and coordinating all the modules in the biomass supply chain. The real-time information is sent from each module to IM. Upon the receipt of the information, the IM module analyzes the information and reacts. The reaction process usually involves sending information to other modules. The main purposes of the integration and coordination of the supply chain were to 1) fulfill the daily feedstock demand; 2) provide a smooth flow of biomass in the supply chain; 3) avoid bottlenecks in the supply chain; 4) utilize the equipment efficiently to reduce operating costs; and 5) quickly react to any disturbance and shock in the supply chain to keep the system robust.

Three sources of delay in the supply chain are considered in the IM module: 1) moisture content (Delay-To-Dry); 2) weather condition (Weather-Delay); and 3) machine unavailability (Machine-Delay).

The purpose of Delay-To-Dry is to prepare a stable feedstock. Stability prevents the self- heating of biomass during the densification process such as baling, and also reduces the amount of dry matter loss due to the biological activities while storing (Rentizelas et al., 2009b). In most agricultural biomass logistics scenarios, the cut biomass is left on the field to dry down to a safe moisture level at which it can be collected and densified into different sized packages. Densified biomass may remain in the field for several days prior to its removal from the field. During this time, overall dry matter of biomass would decrease as biomass is exposed to weather. The safe level of moisture content is 15−20% or less for all agricultural resources (Hess et al., 2009). In this study, it is assumed the safe moisture content for baling and storing is 20% (Sokhansanj et al., 2008a). It is noted that moisture content constantly changes depending upon climate conditions. Moisture content of biomass is updated continuously in the simulation model based on the daily weather data.

62 In addition to moisture content, Delay-To-Dry is estimated based on two other parameters including minimum days on field (MinDF) and maximum days on field (MaxDF). MinDF is the minimum number of days the residue is left on the field. After MinDF, the residue may be still kept on the field or baled depending on its moisture content. MaxDF is the maximum number of days the residue can be left on the field. After MaxDF, the residues are baled regardless of their moisture content. This parameter represents the situation in which the moisture content is higher than safe moisture content but residue has been laid on the field for several days and it needs to be removed from the field as the harvest season is short. For instance, Hess et al. (2009) considered seven days the maximum for field drying. MinDF and MaxDF parameters are defined by the user and can be neglected from the Delay-To-Dry logic. In this study, both MinDF and MaxDF are neglected due to low moisture content of wheat straw. Thus, only safe moisture content was considered as the source of Delay-To-Dry.

Weather conditions are another source of delay. Weather-related parameters such as rain, snow, temperature, excessive soil moisture, and other conditions caused by weathering affect the performance of field machinery. Weather conditions may delay harvest and collection operations (Sokhansanj et al., 2008b). In this study, the weather delay is estimated based on the weather data including temperature and the precipitation rate. It is assumed the field operations would stop at temperatures below -20oC until weather gets warmer. Moreover, the operations are delayed by one or two hours for each millimeter (mm) of rain or snow precipitation (Sokhansanj et al., 2008b). The IM module calculates the amount of delay caused by the weather conditions and holds the simulation items until the weather conditions favor the work conditions on the field. Consideration of weather delay is important to assure the suitability of soil condition for machinery traffic.

The last source of delay is machine unavailability. Before releasing a simulation item to the next module, IM module checks whether a machine is available to process the dry biomass. The unavailability of the machine can be due to two factors: 1) The machine is busy processing another item; or 2) The machine is broken down and needs to be repaired. Once the machine is idle or fixed, the item is released. Figure 4-3 depicts the delays and their connection in a flowchart developed in the IM module.

63 Is the minimum

days to dry met?

Is moisture content of biomass less than

the safe level?

Is the machine available?

Delay the item for one more day

Is the maximum days to dry met?

Delay the item until the machine is available

Has the day advanced?

Start the operation

Delay the item until its moisture reaches the safe level or the day advances Is weather favourable to

proceed the operation?

Delay the item until the weather permitted

Has the day advanced? Has the day

advanced? No Yes Yes No Yes No Yes No No Yes Yes No Yes No Yes No Day=Day+1 Day=Day+1

Figure 4-3: Delay logic flowchart in the simulation model

It is noted that the delay logic shown in Figure 4-3 is applied to the field operations. For other operations such as transportation and unloading, only the last condition regarding the availability of machinery is checked as moisture content is not a constraint for these operations. Weather conditions can also impact the loading operations taking place at storage sites- depending upon the type of storage regime. If the loading equipment travels on the ground, the performance of the loader will be affected by the weather conditions. On the other hand, covering the floor of the storage location with material such as crushed gravel pad eases equipment use and vehicle traffic. Thus, equipment can work even during high precipitation.

64 1. Item creation module

In this module, all the farms in the supply area are created at the beginning of the simulation run and their characteristics are assigned to them as attributes. The assigned attributes to each farm include farm size, produced biomass type and its biomass yield, distance from the plant, and the initial moisture content of biomass (harvest moisture content). Hess et al. (2009) reported the harvest moisture content of wheat straw could be in the range of 9-25% (w.b.). This range has been used in the simulation model to estimate the initial moisture content. A discrete uniform distribution function was used to generate the initial moisture content of straw at the beginning of the harvest season. The created farms are first held in a queue. Once the simulation time advances, farms are broken down into small piece of farmlands based on the harvest schedule. Each farmland has a specific area and biomass tonnage.

2. Baling module

Once the moisture content of biomass is at a safe level for baling, the weather conditions are favourable for field operations and the baler is available, the simulation item (portion of a farm) is released to the baling module. In this module, loose biomass laid on the ground is compacted into 1.2 m×1.2 m×2.4 m (4 ft×4 ft×8 ft) large square bales. Then, the baler ties the bale with twine strings to maintain the integrity of the bale and drops it on the field. The cost of twine per bale is assumed to be $0.8 (Sokhansanj et al., 2008b). The density of the created bales is assumed to be 128 kgm-3 wet bulk (8 lbft-3) (Hess et al., 2009). This module also models a tractor utilized to pull the baler. The square baler is drawn behind a 165-kW tractor. It is noted the simulation item changes from farmlands to bales in this module.

In this study, only the large square bale is modeled. The large square bale has distinct handling, transportation and storage footprint benefits over the round bale. Large square bales can be loaded two at a time and quickly stacked on trailers. They can also be picked up by stinger stacker. In contrast, round bales are handled once at a time. Hess et al. (2009) reported that a 16.5 m (53-ft) semi-tractor trailer with square bales can be loaded in less than 30 minutes (80 bales/hr) while loading the same trailer with round bales takes nearly one hour (40 bales/hr). Thus, it is not cost-efficient to ship round bales for long distances due to their handling difficulties. In addition, the square bale has been used for the commercial hay harvest, whereas

65 the round bale has been widely used by cattle farmers. Since the developed simulation model is applied to a commercial-scale ethanol plant, the large square bale was modeled here.

3. In-field hauling module

Immediately or at a later time (depending on moisture content, and schedule and readiness of bale collection machine), bales are hauled to the storage sites by a self-propelled stinger stacker. A self-propelled stinger stacker enables the collection, transportation and stacking of bales at the storage sites. The stinger picks up 8 bales in the field, hauls them to storage and stacks them 4 bales high. Thus, the total operating time is the sum of loading, transporting and unloading (stacking) bales at storage. The loading and unloading of 8 bales takes 2 and 1 minutes, respectively. The transportation time depends on the location of storage and also the distribution of bales on the farm. It is assumed that bales are randomly distributed on the farm. To estimate the transportation time, a similar approach used by Cundiff et al. (2009b), was employed in this module. The module assigns a coordinate to each bale in the farm. Given the number of bales in each farmland from the baling module and the size of farmland, a coordinate is assigned to each single bale. The origin was set as the center of the storage site.

For the first load, it is assumed the first bale is located at 0.16 km away from storage (Sokhansanj et al., 2008a). The module finds the second bale which has the minimum distance from the first bale, and the third one which has the minimum distance from the second one and so on. This process will continue until 8 bales are loaded on the stinger. Given the coordinates of the bales, Euclidean distance is used to estimate the distance of two adjacent bales with a winding factor of 1.2 (Kumar and Sokhansanj, 2007). Although the procedure to load bales on the stinger is not an optimal procedure, it reasonably reflects the impact of the distribution of bales on the farm on the transportation time spent by the stinger.

The same process is applied for the subsequent loads until all of the bales are transported to storage or the harvest season ends. The field speed and highway speed of the stinger are assumed to be 8 kmh-1 (5 mph) and 25 kmh-1 (15 mph) (Brummer et al., 2000).

4. Storage module

This module models the inflow and the outflow of biomass in both roadside and satellite storage sites. Stacked bales are held in storage if one of the following conditions occurs: 1) weather

66 conditions are unfavourable for loading operations; 2) there is no truck available at storage; 3) the loading equipment is broken down and needs to be repaired; or 4) the daily feedstock demand of the conversion facility is met and the capacity of at-plant storage is full. These conditions are continuously checked by the IM module.

In addition to the type of storage system (roadside/satellite), the type of the storage regime and the stack configuration must be identified in this module. Table 4-1 lists different types of storage regimes, their associated construction cost and the average annual dry matter loss percentage. The dry matter loss percentage is based on the assumptions that the moisture content of stored biomass is 15% w.b. and biomass is stored for one year (Brummer et al., 2000). This moisture content is close to the moisture content of wheat straw.

Table 4-1: Construction cost and average dry matter loss of different storage regime (Brummer et al., 2000)

Storage regime Construction cost

($m-2)

Average dry matter loss (%) Enclosed, pole frame building on crushed rock 70.39-107.64 2 Open sides, pole frame building on crushed rock 53.82 4

Reusable tarp on crushed rock 1.471 7

Outside unprotected on crushed rock 2.70 15

Outside and unprotected on ground 0.00 25

1

The cost per m2 is only the cost for the tarp.

The large stack of bales increases the risk of fire, which would cause a biomass supply shock in the system. Fire could also spread to adjacent facilities and farms and cause a large loss of assets (Hess et al., 2009). To prevent fires, the stack configuration of storage is important. In this study, the fire codes recommended by the International Code Council (Hess et al., 2009) are taken into account. According to these fire codes, the size of each stack in storage should not exceed 91 t (100 tons). Similar to Hess et al. (2009), the large square bales are stacked 4 high and 5 wide. The length of the stack depends upon the density of bales. For example, bales are stacked 10 long if each bale weighs 0.5 tons.

In addition, fire lanes are considered between stacks. The fire lanes between two adjacent stacks in a row and in a column are 3 m (10 ft) and 30.5 m (100 ft), respectively in open yards

67 and 6.1 (20 ft) and 30.5 m (100 ft), respectively in closed storage. For closed storage, a fire lane of 23 m (75 ft) is considered between the wall and the nearby stacks (Hess et al., 2009). Figure 4-4 shows a simple schematic of the stack configuration in a closed storage site.

Figure 4-4: Stack configuration in a closed storage site according to the fire codes

5. Loading module

In this module, the stored bales in storage are loaded onto a semi-tractor trailer attached to a tractor truck. This module models both the loader and the trailer. The loading process is carried out by a telehandler. At each trip, a telehandler picks up two large bales and places them on a 12- m (40-ft) flatbed trailer. This process continues until the trailer is fully loaded. The trailer is 3 m (102 in.) wide. The size and weight of the trailer comply with the legal dimensions and weight regulations in the province of Saskatchewan, as explained in section 3.9. The configuration of the trailer allows for a truckload of 30 bales with 5 rows of three-high (3.6 m) and two-wide bale stacks (2.4 m). On average, the loading operation takes 20 minutes for each empty trailer. The reason for modeling the trailer along with the telehandler in this module is to keep track of the

6.1 m

30.5 m

23 m Bale stack

(4 high, 5 wide, 10 long)

Storage wall Row

68 time that the trailer waits in order to be loaded. This time is considered in the associated costs and resource utilization rate.

6. Road transportation module

This module models a truck with its attached trailer between the storage sites and the gate of the plant. A 330-kW tractor is used to carry the trailer. The truck with a semi-tractor trailer is modeled here since this transportation mode can travel to rural areas and has been widely used for moving square bale hay.

7. Weighing module

In order to determine the net weight of loaded bales on a truck, each arriving truck to the plant is weighed twice by a truck scale, once loaded with bales and once after unloading bales (tare weight). This module models a scale unit above the ground with the capacity of 91 t (100 tons).

8. Unloading module

A similar telehandler used in the loading module is also utilized here to unload the bales from the trailer and stack them at the at-plant storage site. On average, the unloading of each trailer takes 15 min. Once the telehandler unloads all the bales, the empty trailer must be dispatched to another roadside/satellite storage location to pick up a new load of bales. The dispatching method in the IBSAL-MC model is based on the shortest travel time first and the longest travel time next. Based on this method, the first empty truck is dispatched to the closest storage site to the plant and the next empty truck is sent to the farthest storage site from the plant. The IM module continuously updates the list of closest and farthest storage sites. Once the inventory of a storage site exhausts, it is removed from the list of storage sites to assign empty trucks to. This dispatching method creates a fair balance in the transportation times of trucks and reduces the maximum number of trucks and also the variation on the number of required trucks in the supply chain (Ravula, 2007).

9. At-plant storage module

This module models storage located at the ethanol plant. This storage acts as a buffer to avoid the starvation of the conversion process in case of unforeseen supply shocks or during the off-shift hours of the transportation system. This storage should be a well-structured area that not only

69 makes it accessible 24/7 but also protects the stored bales from weather as the stored bales at this stage of the supply chain are value-added feedstock. The bales are released from at-plant storage and fed into the grinder by a telehandler. The release of bales is managed by the IM module.

10. Grinding module

The last module of the simulation model is grinding. This module is comprised of four sub- modules: grinder in-feed system, grinder, dust collection system and surge bin. The grinder in- feed system removes the bale strings and conveys the bale into the grinder. The grinder is a hammer mill with a 463-kW electric motor and a base throughput of 16.5 t per hour. The grinder grinds biomass into an average particle size of 2.5 mm (0.1 in.). Depending on the daily feedstock demand, several grinders may operate in parallel. The dust collection system filters and captures the dust created during the grinding process. Finally, the surge bin feeds the small particles of biomass into the conversion process.

All the developed modules contain a block estimating the dry matter loss (DML). The estimated DML for each operation is the aggregate of both physical losses during an operation and chemical losses.

Chemical DMLs take place at any stage of the supply chain in which the biomass waits to be processed, such as loose biomass left on the field to get dry or stored bales at storage. The exact amount of chemical DML as a function of time is not available. The development of such a function would require extensive field experiments.

To estimate the percentage of the chemical DMLs, given the average annual DML percentage, the daily DML percentage was first calculated by dividing the annual percentage by 365. The final amount of DML was then calculated by multiplying the number of days the biomass remained in storage/queue by the daily DML percentage.

The annual DML percentage for different types of storage regime is given in Table 4-1. It is assumed that if loose biomass is left on the field for one year, the whole biomass will be lost (100%). During a short time window, bales may be left on the field until they are transported to storage sites. As these bales rest on the ground, ground moisture which is pulled into the base of the bale by capillary action, can easily double the amount of spoiled material normally expected