Abstract:
A system includes a biodiesel production system and an advanced process controller configured to implement a model predictive control algorithm to control one or more aspects of the biodiesel production system.

Description:
BACKGROUND 
       [0001]    The invention relates generally to control systems, and more particularly to process control employing novel techniques for controlling a biodiesel plant. 
         [0002]    A biodiesel plant may include one or more continuous processes to produce biodiesel through chemical reactions, such as transesterification and esterification. The biodiesel plant may use a variety of feedstocks, such as vegetable or animal fats and oils. The feedstock is typically reacted with short-chain alcohols, such as methanol or ethanol, to produce the biodiesel. The biodiesel produced by the biodiesel plant may be used as a fuel in diesel engines. When used in diesel engines, the biodiesel may be used alone or blended with petrodiesel. A process control system may be used to control the biodiesel plant. For example, the process control system may include one or more single loop controllers. However, existing methods for controlling the biodiesel plant may suffer from various disadvantages that may result in decreased biodiesel production, inefficient use of raw materials, and low energy efficiency. 
       BRIEF DESCRIPTION 
       [0003]    The present invention provides novel techniques for controlling a biodiesel production plant. In particular, the present techniques are presented in the context of using a model predictive control algorithm of an advanced process controller to control one or more aspects of the biodiesel production system. However, it should be borne in mind that the invention may be applied in a wide range of contexts, in a variety of plants, and in any desired industrial, commercial, private, or other setting. 
         [0004]    In accordance with one aspect of the present disclosure, a system includes a biodiesel production system and an advanced process controller configured to implement a model predictive control algorithm to control one or more aspects of the biodiesel production system. 
         [0005]    In accordance with another aspect, biodiesel is prepared by a process including the steps of operating a biodiesel production system to produce the biodiesel and implementing a model predictive control algorithm using an advanced process controller to control one or more aspects of the biodiesel production system. 
         [0006]    In accordance with a further aspect, a method includes operating a biodiesel production system to produce the biodiesel and implementing a model predictive control algorithm using an advanced process controller to control one or more aspects of the biodiesel production system. 
     
    
     
       DRAWINGS 
         [0007]    These and other features, aspects, and advantages of the present invention will become better understood when the following detailed description is read with reference to the accompanying drawings in which like characters represent like parts throughout the drawings, wherein: 
           [0008]      FIG. 1  is a diagram of an exemplary biodiesel plant; 
           [0009]      FIG. 2  is a diagram of a control system capable of implementing an exemplary method of controlling a biodiesel production plant; 
           [0010]      FIG. 3  is a diagrammatical representation of a dynamic multivariable predictive module controller capable of implementing an exemplary method of controlling a biodiesel production plant; 
           [0011]      FIG. 4  is a detailed diagram of an exemplary biodiesel production plant; 
           [0012]      FIG. 5  is a diagram of an optimizer of a control system for operating a biodiesel production plant; 
           [0013]      FIG. 6  is a diagram of a glycerin section of an exemplary biodiesel production plant; 
           [0014]      FIG. 7  is a diagram of a biodiesel drying section of an exemplary biodiesel production plant; and 
           [0015]      FIG. 8  is a graphical representation of a level of crude methyl ester in a crude methyl ester tank. 
       
    
    
     DETAILED DESCRIPTION 
       [0016]      FIG. 1  is a diagram of an exemplary biodiesel production plant  10 . For example, the biodiesel production plant  10  may include a catalyst preparation system  12  that produces a catalyst  14 , which may include, but is not limited to, sodium hydroxide, potassium hydroxide, sodium methoxide, potassium methoxide, or any combination thereof. The catalyst  14  is used to speed up the transesterification reaction to produce biodiesel, but is not consumed by the transesterification reaction. The biodiesel production plant  10  may also include a feedstock preparation system  16  that produces a feedstock  18  that is used in the transesterification reaction to produce biodiesel. The feedstock preparation system  16  may receive various raw materials, such as, but not limited to, vegetable oil, animal fat, recycled vegetable oil, tallow, hog fat, or any combination thereof. These raw materials may be composed of triglycerides, which are esters that contain three fatty acids and glycerol (also called glycerine or glycerin). The feedstock preparation system  16  may be used to remove various impurities from the raw materials, such as, dirt, charred food, water, or any combination thereof. The feedstock preparation system  16  may also use degumming to remove phospholipids and other plant matter from the raw material. In addition, the raw material may be neutralized in the feedstock preparation system  16 . 
         [0017]    The biodiesel production plant  10  may also include a transesterification reaction system  20 , in which the feedstock  18  is reacted with methanol  21  in the presence of the catalyst  14  to produce a crude mixture or reactor product  22 . In other embodiments, other short-chain alcohols other than methanol  21  may be used in the transesterification reaction system  20 . In the transesterification reaction system  20 , the triglycerides of the feedstock  18  are reacted with the methanol  21  in the presence of the catalyst  14  to produce a mixture of methyl esters of fatty acids and glycerol (i.e., the reactor product  22 ). The methyl esters, or mono-alkyl esters, are separated from the glycerol to produce biodiesel. Specifically, the reactor product  22  is transferred to a separation system  24  to produce a crude biodiesel  26 , a crude methanol  27 , and a crude glycerin  28 . The crude biodiesel  26  is treated in a biodiesel treatment system  30  to produce biodiesel  32  and a recycle methanol  34  (e.g., purified crude methanol). For example, the biodiesel treatment system  30  may use techniques, such as distillation, to separate the biodiesel  32  from the recycle methanol  34 . The biodiesel  32  may then be transported to various storage and distribution facilities to be used to power diesel engines. 
         [0018]    The crude glycerin  28  from the separation system  24  may be transferred to a glycerin treatment system  36  to produce glycerin  38  and a recycle methanol  40  (e.g., purified crude methanol). The glycerin treatment system  36  may utilize various techniques, such as acidification, neutralization, decanting, drying, or any combination thereof, to separate the glycerin  38  from the recycled methanol  40  and to purify the glycerin  38 . The biodiesel production plant  10  may also include a methanol treatment system  42  for treating one or more of the crude methanol streams  27 ,  34 , and  40  to produce the methanol  21  used in the transesterification reaction system  20 . The methanol treatment system  42  may use various techniques, such as distillation, to produce the methanol  21 . 
         [0019]    A variety of sensors, or process instruments, may be placed throughout the biodiesel production plant  10 . Such sensors may measure process data or operating variables, such as temperatures, flow rates, pressures, and/or levels, of the various processes in the plant  10 . Alternatively, the operating variables may be determined using inferential models, laboratory values, or combinations thereof. Sensor output  62  may be transmitted to a biodiesel control system  60 , which may be a model predictive controller. Plant operators may be able to monitor the sensor output  62  and interact with the control system  60  to provide new set points, for example. Based on sensor output  62 , input from operators, programming, and/or other inputs, the control system  60  transmits output signals  64  to the process. The output signals  64  may be used to manipulate equipment, such as valves, motors, and/or pumps. By using the biodiesel control system  60 , the quality of the biodiesel  32  produced by the biodiesel production plant  10  may be improved compared to biodiesel produced by plants that do not have the biodiesel control system  60 . For example, the biodiesel  32  produced by the controlled biodiesel production plant  10  may be more uniform with a concentration of impurities (e.g., monoglycerides) with a variability of less than approximately ±0.01 weight percent. Thus, the variability of the concentration of impurities of the biodiesel  32  produced using the biodiesel control system  60  may be less than that of biodiesel produced by plants that are not controlled by the biodiesel control system  60 . For example, the concentration of impurities of the biodiesel  32  produced by the biodiesel control system  60  may vary between approximately 3.99 to approximately 4.01 weight percent, between approximately 4.49 to approximately 4.51 weight percent, or between approximately 4.99 to approximately 5.01 weight percent. These values of impurities are non-limiting examples and the biodiesel control system  60  may produce biodiesel  32  with different values of impurities, with a variability of less than approximately ±0.01 weight percent, depending on customer requirements and/or governmental regulations. 
         [0020]    In certain embodiments, the biodiesel control system  60  may include a mass balance module that provides an estimated composition of a flow stream of the biodiesel production plant  10  based on a mass balance calculation. For example, the flow stream may be the catalyst  14 , feedstock  18 , methanol  21 , biodiesel  32 , glycerin  38 , or any combination thereof. In certain embodiments, the biodiesel production plant  10  may not include online analyzers or sample points to provide compositions of all flow streams of interest. Thus, the mass balance module may be used to provide an estimated composition of a particular flow stream or a flow rate of a component of the flow stream based on comparisons with measured flow rates of certain flow streams of the biodiesel production plant  10  and mass balance calculations. For example, the mass balance module may be used to determine the composition of the crude glycerin  28  based on mass balance calculations. Specifically, the mass balance module may provide an estimated flow rate of the crude glycerin  28  or the methanol in the crude glycerin  28 . The biodiesel control system  60  can then use the estimated composition of the crude glycerin  28  as an indication of high methanol, for example. Specifically, the biodiesel control system  60  may compare the estimated flow rate of the crude glycerin  28  with a measured flow rate of the crude glycerin  28  as provided by a flow meter. If the estimated flow rate of the crude glycerin  28  is higher than the measured flow rate, then the crude glycerin  28  stream may contain more methanol than desired. Additionally or alternatively, the biodiesel control system  60  may compare the estimated flow rate of methanol in the crude glycerin  28  with an expected flow rate of methanol in the crude glycerin  28  based on the measured flow rate of the crude glycerin  28  and mass balance calculations. If the estimated flow rate of the methanol in the crude glycerin  28  is higher than the expected flow rate, then the crude glycerin  28  may contain more methanol than desired. High amounts of methanol in the crude glycerin  28  may result in higher energy consumption in the glycerin treatment system  36  to produce the recycle methanol  40  and/or may indicate the approach to a process constraint. Operators of the biodiesel production plant  10  may reduce the flow rate of the feedstock  18  to the transesterification reaction system  20  to reduce the amount of methanol in the crude glycerin  28 . Alternatively, the operators may increase the flow rate of the feedstock  18  and thereby, increase production of the biodiesel  32 , as long as the difference between the estimated and measured flow rates of crude glycerin  28  and/or the difference between the estimated and expected flow rates of methanol in the crude glycerin  28  does not exceed a threshold. Thus, the mass balance module provides data that the operators may use to operate the biodiesel production plant  10  as close to capacity as possible. 
         [0021]    In other embodiments, the biodiesel control system  60  may include a stoichiometry module that provides a desired feed flow rate of a raw material of the biodiesel production plant  10  based on stoichiometric calculations. Stoichiometry refers to a branch of chemistry that deals with relative quantities of reactants and products in chemical reactions, such as the transesterification reaction of the transesterification reaction system  20 . Thus, a desired quantity of one of the catalyst  14 , feedstock  18 , or methanol  21  may be calculated based on quantities of the other materials using stoichiometric calculations. For example, a desired amount of methanol  21  may be determined based on flow rates of the catalyst  14  and the feedstock  18 . Adding more than this desired amount of methanol  21  to the transesterification reaction system  20  results in higher amounts of recycle methanol  34  and  40  from the biodiesel treatment system  30  and the glycerin treatment system  36 , respectively. Thus, more energy is used by the biodiesel treatment system  30  and the glycerin treatment system  36  to process this excess recycle methanol  34  and  40 . By using the stoichiometry module to provide the desired flow rate of methanol  21 , the amounts of recycle methanol  34  and  40  and energy consumption by the biodiesel treatment system  30  and the glycerin treatment system  36  may be reduced, thereby improving the overall efficiency of the biodiesel production plant  10 . In other embodiments, the stoichiometry module may be used to provide desired flow rates of the catalyst  14 , feedstock  18 , acid, caustic, or any combination thereof. 
         [0022]      FIG. 2  shows a diagram of a control system  80  for the biodiesel production plant  10  capable of implementing an exemplary method of controlling the biodiesel production plant  10 . For example, sensor input interface circuitry  82  may organize input from a variety of sensors and configure it into a recognizable form, such as a 4-20 mA signal, for processing circuitry  84 . In addition, the processing circuitry  84  may send queries or adjust settings of the sensors through the interface circuitry  82 . Similarly, actuator interface and/or driver circuitry  86  may organize output from the processing circuitry  84  to ensure transmission to the correct device and/or transform the output into a compatible format. The actuators and/or drivers may also provide status information back to the processing circuitry  84 . Connected to the processing circuitry  84  may be one or more control modules  88 , which may exist as hardware, software, or firmware. The control modules  88  serve to separate the tasks performed by the processing circuitry into smaller programs that may be easier to install, modify, debug, upgrade, and/or replace without disrupting the overall operation of the biodiesel production plant  10 . For example, the biodiesel control system  60  may be one of the control modules  88 . In addition, there may be one or more other control modules  90  depending on the complexity or architecture of the biodiesel production plant  10 . 
         [0023]    The processing circuitry  84  of  FIG. 2  may also communicate with memory circuitry  92  that can store processed data or data to be processed by the processing circuitry  84 . It should be understood that any type of computer accessible memory device capable of storing the desired amount of data and/or code may be utilized in the control system  80 . For example, the memory circuitry  92  may include one or more memory devices, such as magnetic, solid state, or optical devices, of similar or different types, which may be local and/or remote to the control system  80 . The memory circuitry  92  may store data, processing parameters, and/or computer programs having one or more routines for performing the processes described herein. Finally, information may be shared between a remote management and control interface  94  and the processing circuitry  84 . The interface  94  enables operators, engineers, and/or management at a remote location to monitor and/or interact with the processing circuitry  84 . 
         [0024]      FIG. 3  illustrates a dynamic multivariable predictive model controller  110  (e.g., model predictive controller), which may govern the control actions implemented by the processing circuitry  84  of  FIG. 2 . For example, one of the control actions may be the control of the biodiesel production plant  10 . The dynamic predictive model may define mathematical relationships that include not only steady state relationships, but also time varying relationships required for each parameter change to be realized in an output. In other words, a model  112  may not only define how changes in certain process variables affect other process variables, but also rates at which such changes occur. Based on such relationships, the model  112  may derive or predict one or more anticipated trajectories  114  representing desired future values or set points for particular process variables over a time period. The trajectories  114  may be determined based at least partially on certain operating constraints  116  imposed on the controller  110  as well as one or more objective functions  118  associated with the controller  110 . 
         [0025]    Turning to the constraints  116  and objective functions  118  in more detail, the constraints  116  may include controllable constraints (e.g., those that a process has the ability and discretion to change) as well as external constraints (e.g., those outside of the process itself). Examples of constraints include, but are not limited to, process constraints, energy constraints, equipment constraints, legal constraints, operator-imposed constraints, or combinations thereof. Essentially, the constraints  116  imposed on a particular controller  110  may be representative of limits by which a controller  110  may manipulate certain manipulated variables (MV&#39;s) in controlling a process. The objective function  118  may be a mathematical relationship that defines or sets the goal or goals for the overall optimization of the process (or sub-processes within a process). In general, the objective function  118  may provide one or more consistent numerical metrics by which a process or sub-process strives to achieve and over which the performance of the process or sub-process may be measured or evaluated. The objective function  118  may be defined in terms of either objectives to be obtained or maximized or costs to be minimized, or both. Thus, the model  112  may attempt to achieve one or more process results  120  or targets (i.e., controlled variables, or CV&#39;s) based on the control or manipulation of process set points  122  for one or more other process variables (MV&#39;s) in accordance with the aforesaid trajectories  114 , constraints  116 , and/or objective function  118  associated with the controller  110 . 
         [0026]    For example, an exemplary biodiesel control system  60  may perform several different steps to control the biodiesel production plant  10 . In one embodiment, the control system  60  may be configured to consider the purity of the biodiesel  32  as one of the operating variables and configured such that steam pressure or temperature is one of the constraints  116 . In addition, one of the objective functions  118  may be to minimize an economic cost of energy utilized in the biodiesel production plant  10 . An additional objective function  118  may be to maximize an economic value of products of the biodiesel production plant  10 , such as the biodiesel  32 , or to achieve a target or maximum throughput of biodiesel  32 . Combining the two objective functions  118 , an overall optimization objective may be to reduce energy costs per unit mass of biodiesel  32  produced by the production plant  10 . In addition, based on the operating variables, constraints  116 , and objective functions  118 , the control system  60  may determine optimal flow rates of the catalyst  14 , feedstock  18 , and methanol  21 . Further, the control system  60  may control the flow rates based on the optimal flow rate determinations. In certain embodiments, the control system  60  may cyclically repeat the above steps and in further embodiments, the steps may be performed sequentially or simultaneously. 
         [0027]      FIG. 4  is a detailed representation of the biodiesel production plant  10 . As shown in  FIG. 4 , a raw material  140  is transferred to a stripper/refiner  142  of the feedstock preparation system  16 . The stripper/refiner  142  may be a distillation column configured to separate undesirable materials and/or impurities, such as free fatty acids (FFAs), from the raw material  140  to produce an overhead stream  144 . For example, the components of the overhead stream  144  may produce undesirable by-products in the transesterification reaction system  20 , and therefore the stripper/refiner  142  removes the overhead stream  144  from the raw material  140  to produce the feedstock  18 , which may be stored in a feedstock tank  146 . The feedstock  18  is then combined with the methanol  21  and the catalyst  14  to a produce a mixture that is then introduced into a first reactor  150  of the transesterification reaction system  20 . The mixture begins to undergo the transesterification reaction described above to produce crude reactor product  152 , which may then be transferred to a second reactor  154 . In certain embodiments, additional methanol  21  and/or catalyst  14  may be added to the crude reactor product  152  before being transferred to the second reactor  154 . In certain embodiments, a recycle stream  156  may be recycled from the second reactor  154  to the inlet of the first reactor  150  to help adjust the extent of the transesterification reaction in the first reactor  150 . After the mixture continues to undergo the transesterification reaction in the second reactor  154 , crude reactor product  158  may be transferred to one or more of N reactors  160  to produce additional crude reactor product  162 . In the illustrated embodiment, the transesterification reaction may be better adjusted to achieve the desired production of biodiesel by staging the reaction in two or more reactors. In certain embodiments, additional methanol  21  and/or catalyst  14  may be added to the crude reactor product  158  prior to addition to the N reactors  160 . 
         [0028]    As described above, the reactor processes of the transesterification reaction system  20  include continuous reactors in series. In other embodiments, the transesterification reaction system  20  may include batch reactor processes. Specifically, the feedstock  18 , methanol  21 , catalyst  14 , and/or other co-feedstock are added to a batch reactor vessel and the reaction extent is managed by residence time and/or mixing energies (e.g., contact between the feedstocks and catalyst). The previously described control concepts may also be applied to these embodiments. For example, stoichiometric or material balance equations as used to support inferential quality models and control functions may be adjusted to match the batch equipment topology. In addition, residence time is relevant to the reaction extent in both the continuous and batch reactors. In the embodiments that include batch reactors, auxiliary equipment may be operated in a continuous fashion and thus, the separation system  24 , biodiesel treatment system  30 , glycerin treatment system  36 , and/or methanol treatment system  42  may be controlled in a similar manner to that of embodiments that include continuous reactor processes. 
         [0029]    As shown in  FIG. 4 , the crude reactor product  162  from the N reactors  160  may be heated in a reactor product heater  164 . In other embodiments, the N reactors  160  may be omitted and the crude reactor product  158  transferred directly from the second reactor  154  to the reactor product heater  164 . As illustrated, steam  166  may be supplied to the reactor product heater  164  via a steam control valve  168 . The reactor product heater  164  may be used to increase a temperature of the reactor product  162 . Reactor product  22  from the reactor product heater  164  may then be transferred to a methanol flash tank  170 , where the increased temperature of the reactor product  22  may facilitate separation of the crude methanol  27 . Essentially methanol-free crude biodiesel  172  from the methanol flash tank  170  may be transferred to a decanter  174 , to separate the crude biodiesel  26  from the crude glycerin  28 . Specifically, the decanter  174  may take advantage of the difference in densities between the crude biodiesel  26  and the crude glycerin  28  to separate one from the other. The crude biodiesel  26  may be transferred from the decanter  174  to a crude methyl ester tank  180  of the biodiesel treatment system  30 . From the crude methyl ester tank  180 , the crude biodiesel  26  may be transferred to a methyl ester dryer  182  to remove water and other impurities to produce the biodiesel  32 . 
         [0030]    Returning to the decanter  174 , the crude glycerin  28  may be transferred to a crude glycerin tank  190 . In addition, crude glycerin  28  may be recovered from the first and second reactors  150  and  154  and transferred to the crude glycerin tank  190 . From the crude glycerin tank  190 , the crude glycerin  28  may be transferred to a crude glycerin cross exchanger  192  to be heated. Heated crude glycerin  194  from the cross exchanger  192  may be transferred to a crude glycerin heater  196  for further heating to produce heated crude glycerin  198 . Heating the crude glycerin  28  in the cross exchanger  192  and in the crude glycerin heater  196  may facilitate the preparation of the glycerin  38  in the glycerin treatment system  36 . Next, the heated crude glycerin  198  may be transferred to a glycerin flash tank  200  to produce the recycle methanol  40  and a crude glycerin  202 . The essentially methanol-free crude glycerin  202  may be used in the cross exchanger  192  to preheat the crude glycerin  28 . Cooled crude glycerin  204  from the cross exchanger  192  may be transferred to a glycerin neutralization tank  218 . As shown in  FIG. 4 , an acid  208  and/or a caustic  214  may be added to the cooled crude glycerin  204  in the glycerin neutralization tank  218  to produce neutralized glycerin  220 . The neutralized glycerin  220  from the glycerin neutralization tank  218  may then be transferred to a glycerin dryer  226 , which may utilize distillation to separate methanol from the glycerin. In certain embodiments, steam  166  may be used in a glycerin heater  228  to heat the neutralized glycerin  220  circulating through the glycerin dryer  226 . A steam control valve  230  may be used to adjust the flow rate of the steam  166  to the glycerin heater  228 . As water and other impurities are driven off in the glycerin dryer  226 , the glycerin  38  may be produced. 
         [0031]    In the methanol treatment system  42 , a wet methanol tank  240  may receive the crude methanol  27  from the methanol flash tank  170  and the recycle methanol  40  from the glycerin flash tank  200 . Wet methanol  242  from the wet methanol tank  240  may be transferred to a methanol rectifier  244 , which may be a distillation column. The methanol rectifier  244  may include a reboiler  246  to provide heat to drive the distillation of the wet methanol  242 . The methanol  21  from the methanol rectifier  244  may then be transferred to a methanol work tank  248  before being used in the transesterification reaction system  20 , as described above. In other embodiments, the biodiesel production plant  10  may be configured differently from that shown in  FIG. 4 . For example, the biodiesel production plant  10  may use different processes and/or equipment in the production of the biodiesel  32 . 
         [0032]    As shown in  FIG. 4 , several virtual online analyzers (VOAs) may be distributed throughout the biodiesel production plant  10 . The VOAs provide estimates of various parameters, such as compositions, of the biodiesel production plant  10 . In other words, VOAs may be configured to provide an estimated value for certain variables of the biodiesel production plant  10  based on mathematical models of the variables. Specifically, the VOAs may use mathematical models based on mass balances or neural network models that correlate well with actual process measurements. VOAs may be useful when the biodiesel production plant  10  does not include online analyzers or have laboratory facilities for analysis of samples. For example, without the use of VOAs, the biodiesel control system  60  may not have information regarding some controlled variables to provide feedback to the control system  60 . Once a VOA is created and validated, the VOA may provide accurate estimates of composition information without the capital, operating, and maintenance costs associated with online analyzers. In addition, VOAs may provide property estimates at a higher frequency than possible with laboratory analyses. During the execution of VOAs, available results of laboratory analyses may be used to correct (bias) the VOAs to reduce the effect of unmodeled bias and/or unmeasured disturbances. In addition, time shifts between process conditions and laboratory analyses may be accounted for using appropriate process dynamics to allow for accurate biasing of the VOAs, which may provide high model fidelity. 
         [0033]    One of the VOAs of the biodiesel production plant  10  may be an overhead weight percent VOA  143 , which provides an estimate of the amount of the components of the overhead stream  144  in the feedstock  18 . The overhead weight percent VOA  143  may be based on various inputs, such as temperatures, pressures, and flow ratios associated with the stripper/refiner  142 . The biodiesel control system  60  may use the overhead weight percent VOA  143  in controlling the operation of the stripper/refiner  142 . For example, if the amount of the components of the overhead stream  144  in the feedstock  18  is above a threshold, the biodiesel control system  60  may increase the amount of steam to the stripper/refiner  142 , decrease a reflux of the stripper/refiner  142 , decrease an operating pressure of the stripper/refiner  142 , or any combination thereof. In certain embodiments, the biodiesel control system  60  may operate the stripper/refiner  142  such that the overhead weight percent VOA  143  is close to the threshold to reduce steam requirements and/or reduce the possibility of flooding the stripper/refiner  142 . 
         [0034]    The biodiesel production plant  10  may also include a biodiesel VOA  183 . Specifically, the biodiesel VOA  183  may be configured to provide an estimate of the amount (i.e., purity) of biodiesel in the biodiesel  32  and/or an estimate of the amount of impurities (e.g., monoglycerides) in the biodiesel  32 . The biodiesel control system  60  may use the biodiesel VOA  183  in controlling the operation of the methyl ester dryer  182 . For example, if the amount of biodiesel in the biodiesel  32  is below a threshold and/or the amount of monoglycerides in the biodiesel  32  is above a threshold, the biodiesel control system  60  may adjust the operation of the methyl ester dryer  182  such that more water is removed from the biodiesel  32 . 
         [0035]    Another VOA may be a methanol in glycerin VOA  201 , which may be configured to provide an estimate of the amount of methanol in the crude glycerin  202 . The biodiesel control system  60  may use the methanol in glycerin VOA  201  in controlling the operation of the glycerin flash tank  200 . For example, if the amount of methanol in the crude glycerin  202  is above a threshold, the biodiesel control system  60  may increase the amount of steam to the crude glycerin heater  196 , decrease the operating pressure of the glycerin flash tank  200 , or any combination thereof. 
         [0036]    In certain embodiments, the biodiesel production plant  10  may also include a methanol rectifier bottom composition VOA  245  and/or a methanol rectifier top composition VOA  247 , which may provide estimates of the compositions of the bottoms stream from the methanol rectifier  244  and the methanol  21  from the top of the methanol rectifier  244 , respectively. The biodiesel control system  60  may use the methanol rectifier bottom composition VOA  245  and/or the methanol rectifier top composition VOA  247  in controlling the operation of the methanol rectifier  244 . For example, if the amount of impurities in the methanol  21  is above a threshold, the biodiesel control system  60  may decrease the amount of steam to the reboiler  246 , increase the reflux of the methanol rectifier  244 , increase the operating pressure of the methanol rectifier  244 , or any combination thereof. 
         [0037]      FIG. 5  is diagram of an optimization system  256  that may be used to control the biodiesel production plant  10 . Specifically, the optimization system  256  may include an optimizer  258  that receives one or more inputs  260  and generates one or more outputs  262 . For example, one of the inputs  260  may be a feed flow  264 , which may represent a flow rate of the feedstock  18 . Similarly, other inputs  260  may include a methanol flow  266  that represents a flow rate of the methanol  21  and a catalyst flow  268  that represents a flow rate of the catalyst  14 . Another input  260  to the optimizer  258  may be a catalyst cost  270  that represents a unit cost of the catalyst  14 . Similarly, other inputs  260  may include a methanol cost  272  that represents a unit cost of the methanol  21  and a feed cost  274  that represents a unit cost of the feedstock  18 . An energy cost  276  may represent a cost of energy used to run one or more portions of the biodiesel production plant  10 . For example, the energy cost  276  may represent a unit cost of electricity, steam, water, or any combination thereof. Another input  260  to the optimizer  258  may be a biodiesel price  278  that represents a unit price of the biodiesel  32 . Similarly, a glycerin price  280  may represent a unit price of the glycerin  38 . 
         [0038]    One or more of the inputs  260  may be used by the optimizer  258  to generate the one or more outputs  262 . For example, a profit  282  may be one of the outputs  262 . In addition, a biodiesel quality  284  and a glycerin quality  286  may be additional examples of outputs  262 . For example, the biodiesel quality  284  may be a purity or impurity specification of the biodiesel  32 . Similarly, the glycerin quality  286  may represent a purity or impurity specification for the glycerin  38 . In certain embodiments, the optimizer  258  may be used to optimize one or more of the outputs  262 . For example, the optimizer  258  may be used to maximize the profit  282 . In other embodiments, the optimizer  258  may be used to produce biodiesel  32  that is within a threshold of a purity or impurity specification of the biodiesel  32 , as represented by the biodiesel quality  284 . Thus, the optimizer  258  may be used to balance yield verses chemical usage or chemical cost. For example, as one or more of the catalyst, methanol, and/or feed costs  270 ,  272 , and  274  increases, the optimizer  258  may adjust one or more of the feed, methanol, or catalyst flows  264 ,  266 , and  268  to maximize the profit  282 . In another example, increasing the catalyst flow  268  may result in increased soap production, which may be undesirable and negatively affect the profit  282 . Soap may be generated in the transesterification reaction system  20  from the saponification of FFAs in the feedstock  18 . If the feedstock  18  has a high amount of FFAs, excessive soap production and/or catalyst  14  consumption may result. Thus the optimizer  258  may adjust the catalyst flow  268  to achieve a maximum profit  282 . 
         [0039]      FIG. 6  is a diagram of portion  300  of the glycerin treatment system  36  and the methanol treatment system  42 . As shown in  FIG. 6 , the glycerin heater  228  is used to provide heat to the glycerin dryer  226 . Specifically, steam  166  is provided to the glycerin heater  228 , which produces condensate  302 . The glycerin  38  may be stored in one or more refined glycerin tanks  304 . As shown in  FIG. 6 , one or more signals  306  may be provided to the biodiesel control system  60 . Specifically, a pressure compensated temperature (PCT)  308  of the glycerin dryer  226  may be provided to the biodiesel control system  60 . The PCT  308  provides a temperature of the glycerin dryer  226  that is compensated by a pressure of the glycerin dryer  226  provided by a pressure sensor. The PCT  308  of the glycerin dryer  226  may provide an improved indication of the quality of the glycerin than that provided by an actual temperature sensor  310 . In other words, the PCT  308  may be different from the actual temperature provided by the temperature sensor  310  under certain conditions. For example, the pressure of the glycerin dryer  226  may vary with changes in the flow rate of the neutralized glycerin  220 . As the pressure of the glycerin dryer  226  changes, the desired temperature of the glycerin dryer  226  to maintain the quality of the glycerin  38  may also change. If the temperature  310  was used to control the amount of steam  166  instead of the PCT  308 , the amount of steam  166  may be higher than needed to maintain the quality of the glycerin  387 . Thus, by using the PCT  308  to control the operation of the glycerin dryer  226 , the amount of steam  166  may be reduced. In certain embodiments, the wet methanol tank  240  may include a level sensor  312 . 
         [0040]    In response to the received signals  306 , the biodiesel control system  60  may produce one or more output signals  314 . For example, the output signal  314  may be used to control the steam control valve  230  to the glycerin heater  228 . Specifically, the PCT  308  may be used by the biodiesel control system  60  to control the steam control valve  230  instead of using the temperature sensor  310 , as discussed above. One of the quality parameters for the glycerin  38  may be a water composition. The temperature sensor  310  may not provide an accurate indication of the water composition in the glycerin  38 . Instead, the PCT  308  may provide an improved indication of the water composition in the glycerin  38 , especially as the pressure of the glycerin dryer  226  varies. Thus, by using the PCT  308  instead of the temperature  310  by the biodiesel control system  60 , better control of the steam  166  to the glycerin heater  228  may be achieved. Specifically, less steam  166  may be used, thereby increasing the efficiency of the biodiesel production plant  10 . 
         [0041]      FIG. 7  is a diagram of a portion  330  of the biodiesel treatment system  30 . As shown in  FIG. 7 , the crude biodiesel  26  may be transferred from the crude methyl ester tank  180  to the methyl ester dyer  182 , which may be a centrifuge in certain embodiments. A crude biodiesel control valve  332  may be used to adjust a flow rate of the crude biodiesel  26  from the crude methyl ester tank  180  to the centrifuge  182 . In addition, a crude biodiesel isolation valve  334  may be used to block the flow of the crude biodiesel  26  to the centrifuge  182 . By centrifuging the crude biodiesel  26 , the centrifuge  182  may produce water  336  and the methyl ester, or biodiesel  32 . As shown in  FIG. 7 , a level sensor  338  may be coupled to the crude methyl ester tank  180  to provide the signal  306  representing the level of crude biodiesel  26  to the biodiesel control system  60 . The biodiesel control system  60  may provide the output signal  314  to the control valve  332  based on the level in the crude methyl ester tank  180 , as provided by the level sensor  338 . In certain embodiments, the centrifuge  182  may be backwashed on a regular basis to improve operating efficiency and capacity. During the backwashing of the centrifuge  182 , the isolation valve  334  may be manually closed by operators. During this time, the level in the crude methyl ester tank  180  may rise. Without the biodiesel control system  60 , when the isolation valve  334  is reopened by the operators, the control valve  332  may operate in an undesired manner. Specifically, a large flow rate (e.g., slug) of the crude biodiesel  26  may be sent to the centrifuge  182  by the control valve  332 . This may be caused by the flow controller for the control valve  332  winding up. In other words, during the backwashing of the centrifuge  182 , there is no flow through the control valve  332  and the valve  332  may open completely in an attempt to provide the desired flow rate. When the isolation valve  334  is reopened, the completely open control valve  332  provides a flow rate of crude biodiesel  26  much higher than desired and takes time to adjust to provide the desired flow rate. Thus, in certain embodiments, the biodiesel control system  60  may manage the flow rate of the crude biodiesel  26  based on a rate of change in the level  338 , as discussed in detail below. 
         [0042]      FIG. 8  is graph  350  of the level of the crude methyl ester tank  180  provided by the level sensor  338 . Specifically, an x-axis  352  represents time and a y-axis  354  represents the value provided by the level sensor  338 . A curve  356  represents the level  338  during a first period  358  (e.g., normal operation of the centrifuge  182 ). As shown in  FIG. 8 , the curve  356  has a negative slope  360 . In a second period  362 , the centrifuge  182  undergoes backwashing. The second period  362  may be generally defined by dashed lines  364 . As shown in  FIG. 8 , the curve  356  has a positive slope  366  in the second period  362 . In other words, the level  338  rises in the crude methyl ester tank  180  during backwashing of the centrifuge  182  caused by closing the isolation valve  334 . In a third period  368  (e.g., normal operation after backwashing), the curve  356  has a negative slope  370  caused by opening of the isolation valve  334 . As shown in  FIG. 8 , the rapid changes in the level as represented by the curve  356  may result in undesired operation with traditional proportional integral derivative (PID). Specifically, the derivative term of a PID controller is calculated by determining the slope of the error between a measured value and a setpoint over time and multiplying this rate of change by the derivative gain. During the second period  362 , the derivative term may be sensitive to the large change in slope of the curve  356 . Thus, the biodiesel control system  60  may adjust the control valve  332  based the rate of change of the level  338  in the second period  362  instead of the value of the level  338  itself. By utilizing the rate of level change instead of the actual level, the control of the flow rate of the crude biodiesel  26  may be improved. 
         [0043]    While only certain features of the invention have been illustrated and described herein, many modifications and changes will occur to those skilled in the art. It is, therefore, to be understood that the appended claims are intended to cover all such modifications and changes as fall within the true spirit of the invention.