Classifications

• • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
  • F04—POSITIVE - DISPLACEMENT MACHINES FOR LIQUIDS; PUMPS FOR LIQUIDS OR ELASTIC FLUIDS
  • F04D—NON-POSITIVE-DISPLACEMENT PUMPS
  • F04D27/00—Control, e.g. regulation, of pumps, pumping installations or pumping systems specially adapted for elastic fluids
  • F04D27/02—Surge control
  • F04D27/0269—Surge control by changing flow path between different stages or between a plurality of compressors; load distribution between compressors

Definitions

• the invention relates to a method for controlling a compression system with at least two separately zu- and / or turn-off compressor units, with a plurality of devices for changing the performance of the compressor units and with a control device.
• the invention relates to a control device for controlling a compression system with at least two separately zu- and / or disconnectable Ver Whyraggrega- and with a plurality of devices for changing the performance of the compressor units.
• Compacting systems such as gen Erdgasverdichtungsanla ⁇ , for transporting gas and / or gas storage are essential facilities according to the national and international energy supply.
• a system for gas transport consists of a plurality of compression systems, which can each consist of several compressor units.
• the task of the compressor units is to add a sufficient amount of mechanical energy to a pumped medium in order to compensate for friction losses and to achieve the required operating pressures or speeds. ensure flows.
• Compressor units often have very different drives and running ⁇ wheels, as they are designed for example for a base load or a NEN peak load operation.
• a compressor unit includes z. B. at least one drive and at least one compressor.
• Plant automation is particularly important for cost-optimal driving.
• the ability of plant automation to guide the process, and the Mieren compressor plant within the production constraints to opti ⁇ provides significant economic advantages.
• compressors of a compression plant are driven by turbines that cover their fuel needs directly from a pipeline.
• compressors are driven by electric motors.
• a cost - optimal driving means, the energy consumption of the turbines or. the electric drives for a given compaction performance, delivery capacity, delivery capacity and / or to minimize the given volume flow.
• a useful operating range of compressors is limited by adverse effects of internal flow processes. This results in operating limits, such. B. a temperature limit, exceeding the local speed of sound (compression shock, sip limit), the umlau ⁇ fende tearing off the flow at the impeller or the surge limit.
• the automation of a compression system has primarily the task of a dispatching center predetermined setpoints, such as either a flow through the station or a final pressure on the output side to realize as actual values. Specified limits for the suction pressures at the inlet side, the final pressures at the outlet side and the final temperature at the system outlet must not be exceeded.
• EP 0 576 238 B1 discloses a method and a device for load distribution. With a compressor designed as a guide compressor, a control signal is generated which is used as a reference for the non-leading compressors.
• the invention is based on the object to provide egg ⁇ ner compressor plant available a method and a device to further optimize the energy consumption for operation of several compressor units.
• This object is characterized st according to the invention gel ö that, for presetting of new setpoints or change the current supply state of the compressor plant by means of an optimization ⁇ bill from a current switching configuration of the compaction teraggregate regard to an optimized Retroenergybe ⁇ needs for supplies of the compression system, a new switching configuration is calculated, and that the new switching configuration is set automatically via the control device.
• An advantage of the invention is that, in the optimization of all compressor units available or operable on the respective compacting system, it can be assumed that they are independent of their respective operating or switching state.
• the invention allows - in contrast to known controls for compression equipment - than results-nis optimizing automatic connection of a previously liges inoperative located compressor unit or a pop u la ⁇ shutdown of a compressor package to be.
• Real time means that the result of a calculation intra ⁇ half of a certain period of time guaranteed This means that the optimization calculation can take place on a separate data processing system which automatically forwards its calculation data to the control device.
• the invention is based on the known sequential concept, i. H . to close after the start of an externally set, additional aggregate until the anti-surge valves and then back ⁇ clear to optimize the operating points of the compressor units of their efficiency decreases.
• the invention is preferably during each optimization calculation ⁇ drying the entire compressor plant considered, and the switching configuration of the compression system d. H . the specification of a switching state of the individual compressor units, be ⁇ calculates.
• the closing of the or all pump preventive valves can be ensured by a minimum flow through the Verêtrag ⁇ gregate in the optimization. Even a first start of the compression system can already with a favorable with regard to an optimized total energy demand switching configuration done.
• switching configuration of a compressor plant is meant a Men ⁇ ge of the respective switching states of the individual Ver Whyrag ⁇ aggregates.
• the switching configuration is represented by the switching states "0" for Off or "1" for On, which is stored bit by bit in ⁇ example in an integer variable.
• switching operation is meant the change from one, in particular electrical, switching state to another.
• a prediction by means of the optimization ⁇ is approximate calculation for at least one, preferably a plurality of future to ⁇ (n) time (s) determined. Since the method Progno ⁇ sen up to a given time permits, it is possible knowledge of a normal mode of operation of the station d. H . for example B, a usual load curve to use to minimize the switching frequency ⁇ speed of compressor units.
• compressor unit-specific sHence ⁇ ze and / or compressor unit-specific characteristic maps evalu- ated and points for the individual compressor units working ⁇ be determined which of predetermined resp.
• the operating points are set in such a way that the total energy consumption of the compaction plant is optimized.
• the data sets and / or maps are specified as a function of a mass flow and a specific production work of the individual compression units.
• a load distribution i. H . a speed Ratio, calculated between the compressor units and changed if necessary.
• Another significant advantage is that side conditions to the optimization, such. B. not to violate the surge limit, can already be taken into account in an optimal efficiency calculation of the speed setpoints for the individual Ver Togetherrstati ⁇ ons.
• optimization calculation is carried out with a control cycle, in particular self-triggering.
• speed setpoint values and / or the new switching configuration for the control device are provided as output variables of the optimization calculation with each control cycle.
• the speed setpoints and / or the switching configuration are kept constant.
• the speed setpoints are scaled with a common factor and used as a setpoint for a compressor unit controller.
• a further increase in the effectiveness of the system operation is achieved by the control device with the new switching configuration already before the end of the control cycle a warm-up phase of the compressor units for the subsequent Zuschal ⁇ th a previously out of service Kompressichteraggre ⁇ gates triggers.
• a load readiness for the next control cycle is communicated with the end of the warm-up phase of the control device. If, for example, the rotational speed of an approaching compressor unit is sufficient is high and the warm-up phase of the turbine is completed, a signal "load ready" is set. This means that the compressor unit participates in the load sharing procedure and is included in the optimization calculation for the best load distribution between those in service.
• a current mass flow through the single compression unit in particular by a single compressor and / or - a current mass flow through the compression plant and / or
• the optimization calculation according to the principle of model-predictive control by means of forecast calculations minimizes the total energy demand expected up to a later point in time.
• an energy consumption of a switching operation is taken into account in the optimization calculation.
• the energy consumption of the switching process from the data sets and / or the maps of the compressor units is calculated.
• Knowledge of a anteili ⁇ gen energy consumption for the switching operation enables an even more accurate determination of the minimum total energy consumption of the compressor plant.
• An alternative advantageous variant of the invention is that the mass flow of the compressor system for the control cycle is assumed to be constant, in particular in a series circuit of the compressor units.
• an active compressor unit is at least ⁇ operated with a predetermined or predetermined minimum flow.
• the optimization calculation is carried out by ei ⁇ nes branch-and-bound algorithm.
• a further increase in the efficiency of the calculation method is achieved by the optimization calculation solves by ei ⁇ ner dynamic programming sub-problems, insbesonde ⁇ re in a series circuit.
• the device-related problem is based on the a ⁇ gangs said controlling means achieved by an optimization module, with the new at preset setpoints or ⁇ nde ⁇ tion of the current state of the compressor plant by means of an optimization calculation from a current switching configuration of the compressor units with regard to an optimized total energy demand of the compressor plant a new switching ⁇ configuration is calculable, and by a control module, with which the new switching configuration is automatically adjustable.
• the optimization module for optimizing energy consumption is in particular designed to distribute the predetermined total load to the individual compressor units in combination with the control device and / or the dispatching center in such a way that the station setpoint values are minimized using as little energy as possible. H . with maximum overall efficiency, be realized. This includes, for example, both the decision which compressor units are active and which are switched inactive, as well as the specification of how much ⁇ each of the active units to contribute to overall performance, so the specification of the load distribution.
• the Op is tim istsmodul in physical distance, in particular several ⁇ re Km, arranged for controlling means.
• the optimization module is prepared for the consideration of an energy consumption of a switching operation.
• Another embodiment is that the optimization module for optimization calculation for a plurality of control devices of several compression systems is prepared.
• the invention also includes a computer program product is one contained tend software for performing a method according to ei ⁇ nem of claims 1 to 21 with a machine readable program code on a data carrier can be advantageously DV systems herhouse to an optimization module.
• FIG 1 is a block diagram of a method for optimizing the operation of a compacting installation
• Figure 2 shows a compressor map of a specific compaction ⁇ teraggregats
• FIG. 3 shows a control device for controlling a compression plant
• the behavior of a single compression unit 3, 4, 5 is modeled by a map 20, the map 20 describes its efficiency and its speed as a function of its operating point 22.
• the operating point 22 by means of a state variable m, which describes a mass flow through the compression unit , and a determinable with Equation 1 specific funding work
• R is a specific gas constant
• Z is a real gas factor
• c E c A is a speed at the entrance resp.
• T E is an input temperature
• the maps 20 are not provided by a closed formula. From a measurement, a delivery characteristic 21 and an efficiency curve 23 are determined. At constant speed, the dependence on the conveying work and an efficiency ⁇ . determined by the volumetric flow V or mass flow m at interpolation points.
• a pumping limit 36 which are caused by the occurrence of certain flow phenomena in the compressor, are absorbed as a function of the speed. From these nodes and the associated values for different speeds can be determined by appropriate approaches, such. B. piecewise polynomial interpolation or B-splines, the maps 20 as a function of mass flow m. and specific promotional work yl. and build their domain of definition.
• Equation 3 For the application of a mathematical programming, Equation 3 is considered as an equation constraint:
• N y Y ys . y min (m) ⁇ y. ⁇ s . y max (m)
• Equation 5 is considered as an equation constraint:
• An active compression unit must, in order not to violate the surge limit, a minimum flow, in particular ⁇ a special minimum mass flow w TM n comply. This minimum flow rate depends on the current production work of the compaction plant. Similarly, the mass flow must remain below a maximum allowable value m max . i, t
• FIG. 1 shows a block diagram of a method for optimizing the operation of a compression plant.
• the compaction is ⁇ treatment plant with three compressor units 3, 4 and 5 shown in a very schematic way. For an interconnection of the compressor units 3, 4 and 5, a parallel connection is assumed.
• the compressor units 3, 4 and 5 are controlled and regulated by a control device 10.
• the control device 10 includes a controller of the control device 12, a first compressor unit controller 13, a second compressor unit controller 14 and a third compressor unit controller 15.
• An optimization module 11 is in bidirectional connection with the control device 10. By means of the optimization module 11 is a non-linear mixed-integer Optimization problem solved.
• a mathematical formulation of the optimization problem is implemented in the optimization module 11.
• the optimization ⁇ extension module will provide 11 with regard to an optimized total energy ⁇ consumption optimized outputs 32 of the control of the control means 12th
• the input variables 33 consist of a model library 26, with a model 24a, 24b, 24c for each compressor unit 3, 4, 5 and Pro ⁇ variables are processed together of the compressor plant.
• Verdichtungsanläge - a current discharge pressure p g A on the output side of
• the setpoints resp. Limits 31 for the control of the control device 12 are based on a maximum temperature 7; , A, max a pressure P g, A (set) and a volume flow V ⁇ ;;) at the
• Sequence which specifies the following new switching configuration:
• Continuous operation means that the compressor units in operation are operated with an optimized load distribution and with an optimized setting of their operating points 22 in the maps 20.
• the output variables 32 of the optimization module 11 thus contain not only the switching states of the compressor units currently to be set, but also a speed setpoint input ⁇ . for the individual compressor units 3, 4 and 5.
• the speed setpoints ⁇ ⁇ From the subordinate station control, which is cyclically higher than the optimization, the speed setpoints ⁇ ⁇ , before being applied to the compressor aggregate controllers, scaled by a common factor ⁇ to regulate the setpoints.
• the optimization calculation is carried out automatically with a control cycle R in the optimization module 11. In the optimization calculation, therefore, in addition to the calculation of a possible switching configuration, the
• the new switching configuration is now operate three dense aggregates of three Ver ⁇ . Since the result of the optimization calculation is known before the end of the control cycle, a warm-up phase is started for the third compressor unit 5 to be approached. At the end of the control cycle R ⁇ the new values of the control device 10 and in particular the compressor unit controllers 13, 14, 15 provided. The previously prepared with a warm-up Ver ⁇ dense aggregate 5 can now be seamlessly switched for the new control ⁇ cycle R and the optimal total energy ⁇ consumption for the required flow rate or the required volume flow Vö "(setpoint) is given again.
• a surge limit 36 is entered.
• Efficiency optimal operating points 22 are close to the pumping limit 36 on an efficiency curve 23 with a high efficiency n.
• the characteristic fields 20 as a mathematical function of a mass flow (or the flow rate) and a specific För ⁇ are derarbeit of the individual compressor units added to the described method with Figure 1.
• the mathematical formulation of the maps 20 as a calculation function is part of the optimization module 11 or. the optimization calculation.
• FIG. 3 shows a control device 10 for controlling a compression system 1.
• Control device 10 via an adjusting module S to the compressor units 3, 4 and 5 set and / or regulated.
• control variable for a control of the control device 10 in particular that variable of flow, suction pressure, discharge pressure and end temperature, which has the smallest positive Re ⁇ gelabweichung used.
• the regulation of the Steue ⁇ inference means 10 provides as output together with the optimization module, the target values for a single encryption compressor unit controllers 13, 14, 15, see Fig. Second
• FIG. 4 shows a flow chart of the method steps 40, 42, 44 and 46.
• the optimization method is triggered cyclically.
• the current state of the compressor station 1 is determined. The following values are detected to: actual values 30, setpoints 31, limits and Randbedin ⁇ conditions 37, and models 24a, 24b, and 24c 26 from the ModellBiblio ⁇ theque
• the current switching state Sj_, t -i the compression system 1 determines
• a third method step 44 represents a decision point. With the third method step 44, the decision is made an optimization calculation 46 is performed in a fourth method step or the method is ended 48.
• the method will continue with the fourth method step 46.
• the mixed integer optimization ⁇ problem is solved.
• Input variables for the fourth process step 46 are actual values 30, setpoints 31, Grenzwer ⁇ te and boundary conditions 37 and the models from a model ⁇ library 26.
• As a result of the fourth process step 46 are speed setpoints .lambda..sub.i and new switching states Si, t outputted.
• the method is ended 48. With the cyclical initiation from the first method step 40, the method is run through again.

Landscapes

• Engineering & Computer Science (AREA)
• Mechanical Engineering (AREA)
• General Engineering & Computer Science (AREA)
• Control Of Positive-Displacement Pumps (AREA)
• Feedback Control In General (AREA)
• Control Of Positive-Displacement Air Blowers (AREA)
• Separation By Low-Temperature Treatments (AREA)
• Compressor (AREA)
• Applications Or Details Of Rotary Compressors (AREA)
• Control Of Multiple Motors (AREA)

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• 2005
  • 2005-02-11 DE DE102005006410A patent/DE102005006410A1/de not_active Withdrawn
• 2006
  • 2006-02-02 AT AT06707973T patent/ATE428055T1/de active
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  • 2006-02-02 RU RU2007133792/06A patent/RU2381386C2/ru active
  • 2006-02-02 CN CNA2006800115189A patent/CN101155995A/zh active Pending
  • 2006-02-02 WO PCT/EP2006/050612 patent/WO2006084817A1/fr active Application Filing
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