Classifications

• • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
  • F17—STORING OR DISTRIBUTING GASES OR LIQUIDS
  • F17D—PIPE-LINE SYSTEMS; PIPE-LINES
  • F17D3/00—Arrangements for supervising or controlling working operations
  • F17D3/01—Arrangements for supervising or controlling working operations for controlling, signalling, or supervising the conveyance of a product
• • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
  • F17—STORING OR DISTRIBUTING GASES OR LIQUIDS
  • F17D—PIPE-LINE SYSTEMS; PIPE-LINES
  • F17D1/00—Pipe-line systems
  • F17D1/02—Pipe-line systems for gases or vapours
  • F17D1/04—Pipe-line systems for gases or vapours for distribution of gas
• • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
  • F17—STORING OR DISTRIBUTING GASES OR LIQUIDS
  • F17D—PIPE-LINE SYSTEMS; PIPE-LINES
  • F17D1/00—Pipe-line systems
  • F17D1/02—Pipe-line systems for gases or vapours
  • F17D1/065—Arrangements for producing propulsion of gases or vapours
  • F17D1/07—Arrangements for producing propulsion of gases or vapours by compression
• • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
  • F17—STORING OR DISTRIBUTING GASES OR LIQUIDS
  • F17D—PIPE-LINE SYSTEMS; PIPE-LINES
  • F17D3/00—Arrangements for supervising or controlling working operations
  • F17D3/10—Arrangements for supervising or controlling working operations for taking out the product in the line

Definitions

• the present invention relates to a connected reverse installation and a method of operating such an installation. It applies, in particular, to gas transport networks to export surplus renewable gas from a distribution network to a transport network with greater capacity, by supplying a more consumption area large, even storage, thanks to the storage facilities connected to it.
• Biogas production is experiencing strong growth in Europe and its development conditions the creation of a long-term methanisation sector.
• biomethane defines the gas produced from raw biogas from anaerobic methanisation of organic waste (biomass) or by high temperature gasification (followed by synthesis by methanation); purified and treated so as to make it interchangeable with natural network gas.
• the countdown station is a work of the transport operator allowing the transfer of gas from the distribution network to the transport network with a large storage capacity, through a gas compression station.
• the countdown station can be located either near the detent station or at another location where the transport and distribution networks intersect.
• the countdown therefore incorporates a gas compression function to adapt it to the constraints imposed by the downstream flow of this compressor, that is to say the transport network.
• the current countdowns are fixed installations in which the compressors are placed in buildings. Each compressor is driven there by an electric motor connected to the electrical network.
• the pressure and flow of gas in the distribution network are very variable, in particular depending on the injection of biogas by a producer or the consumption of gas by consumers, for example industrial sites.
• the simple regulation of gas pressure in the distribution network can thus lead to activating the back-up installation to export gas to the transport network, then a few moments later, relieve gas from the transport network to supply it to the network of distribution.
• the operation of the reverse installation can therefore only be partially effective.
• the present invention aims to remedy all or part of these drawbacks.
• a machine for controlling the operation of at least one compressor, a means of remote communication for receiving at least one instantaneous value of pressure sensed remotely on the network upstream of the reverse installation,
• the controller controlling the shutdown or operation of at least one compressor when the inlet pressure of each compressor is lower, respectively higher, than the determined pressure limit value.
• the prediction means implements dynamic learning and profiles of consumers, suppliers, capacities and response times of the countdown installation.
• the prediction means implements artificial intelligence algorithms and / or neural networks.
• the prediction means uses meteorological data.
• the prediction means uses for each gas consumer and for each gas supplier present on the distribution network:
• the prediction means uses the topology of the distribution network, with its branches and the positions of the sensors.
• the prediction means is configured to predict pressures, within a horizon of a few minutes or a few hours.
• the countdown installation further comprises a means of determining a charge rate of each compressor as a function of the prediction of pressure evolution, the automaton controlling the operation of each compressor to reach the determined charge rate.
• the countdown installation further comprises,
• the automatic device controlling the stopping of at least one compressor when the input quality of each compressor is lower than the determined quality limit value.
• the countdown installation further comprises a means of determining a charge rate of each compressor as a function of the prediction of quality development, the automatic device controlling the operation of each compressor. to reach the determined charge rate.
• a machine for controlling the operation of at least one compressor comprises the following stages: a step of receiving, from a remote sensor, at least one instantaneous pressure value sensed at a distance from the countdown installation,
• the method further comprises:
• the method further comprises:
• the method further comprises:
• FIG. 1 represents, in the form of a block diagram, a reverse installation object of the invention
• FIG. 2 represents, partially and in the form of a block diagram, a transport network and a distribution network provided with means of communication with the reverse installation object of the invention
• FIG. 3 represents, partially and in the form of a diagram, a transport and distribution network with positioning of measurement equipment and calculation results
• FIG. 8 illustrates, in the form of curves, changes in pressure prediction and triggering limit value of at least one compressor
• FIG. 1 diagrammatically represents a countdown installation which is the subject of the invention.
• the back-up installation has a set of technical functions allowing the creation of a gas flow by controlling the operating conditions specific to a transport network 10 and to a distribution network 15. These functions include:
• the first must be between 30 and 60 bars on the regional network and can reach 85 bars on the main network.
• the second is of the order of 4 to 19 bars on MPC networks (Medium Pressure Network type C, i.e. a pressure between 4 and 25 bars) and less than 4 bars on MPB networks (Medium Pressure Network type B, either a pressure between 50 millibars and 4 bars),
• a dehydration unit 29 upstream of the compression 21, to reduce the risk of condensation on the high pressure transport network, formation of hydrates and corrosion,
• a combustion parameters analysis laboratory (Wobbe index, calorific value and gas density) to inject the injected readings into the energy operator's system for determining the energies.
• the analysis of other contents of compounds is optional and is only carried out if there is a proven risk of contamination of the transport network 10 (example: reverse of a biomethane with a high CO2 content without the possibility of dilution on the distribution networks 15 and transport 10, or operated at a very high pressure).
• the configuration is chosen by studying the various advantages and disadvantages in terms of cost, availability, size, and the possibility of upgrading the compression unit.
• the suction pressure to be considered is the operating pressure of the distribution network 15, which depends in particular on the injection pressures of the biomethane producers 17.
• the construction pressure at the discharge to be considered is the maximum operating pressure ("PMS") ) of the transport network, for example 67.7 bars.
• PMS maximum operating pressure
• a recycling circuit 27 provided with a valve 28 can be provided. The recycling circuit expands gas at the second pressure and injects it upstream of the compressor when at least one compressor is put into operation, under the control of a controller 25.
• Each compressor 21 can be sealed with oil or with dry packing. In the first case, certain filtration arrangements are put in place (see below).
• the automaton 25 performs the control functions 24, operation control, load rate and stop of each compressor 21 and regulation and stability 18 of the network 15. It is noted that, throughout the description, the term "The automaton” means an automaton or a computer system or a set of automatons and / or computer systems (for example one automaton by function).
• a cooling system 23 cools all or part of the compressed gas to maintain the downstream temperature, towards the transport network 10, at a value below 55 ° C (equipment certification temperature). To ensure the operation of the cooling system 23, it is dimensioned from relevant ambient temperature values according to meteorological history.
• a control and supervision function performed by the controller 25 makes it possible to obtain:
• Data logging is performed to certify operating conditions.
• the back-up installation In the event of an emergency, the back-up installation is isolated from the distribution network 15, by closing the valve 14. An "emergency stop” function makes it possible to stop and secure the back-up installation.
• the reverse installation is also fitted with safety devices for pressure and temperature 26. There is no automatic venting unless safety studies contraindicate it.
• the back-up installation is equipped with fire and gas detection systems 26. A means of protection against overflow is provided to protect the devices, in the form of a physical organ such as a restriction orifice or by the 'through an automation.
• the flow rate of a reverse can vary from a few hundred to a few thousand Nm 3 / h depending on the case.
• a remote communication means 9 configured to receive at least one instantaneous value of pressure and at least one instantaneous value of quality of gas captured remotely on the network upstream of the reverse installation,
• a means 2 for automatic selection of a regulation mode either in flow or in pressure (for example, between two limit values (SH and SB), the regulation mode is regulation in flow and, outside of l 'interval between these two limit values, the regulation mode is a pressure regulation.
• the transport network 10 is provided with a communicating pressure sensor 31 and a communicating flow sensor 32.
• the distribution network 15 is provided with a communicating pressure sensor 33 and a communicating flow sensor 34.
• a communicating meteorological information source 35 provides geolocated meteorological data.
• the biomethane producers 17 are connected to the distribution network 15 by injection points provided with communicating flow sensors 36.
• the storage and prediction means 8 analyzes the data received from the various sensors and from the source 35, in particular the pressure 33 and flow rate sensors 34 and supplies, as a function of the meteorological data and of the days and hours of the week (taking account for public holidays and summer and winter hours), a consumption forecast on the distribution network 15.
• the invention therefore makes available to the reverse installation the collection and transmission of data. It therefore offers an exchange of data on three distinct components: - data sharing between the distribution network manager, upstream of the countdown installation, and the transmission network manager, downstream of the countdown,
• the transmission system operator 10 As operator of the back-up installation, has quality data for incoming gas and pressure and flow data for the distribution network. .
• the parameters of the mathematical model are the data describing the network (roughness, diameter, length, then possibly, second order data such as, linearity, heat exchange coefficients of the pipe and the soil, the burial depth , or any other value used to refine the description of the structure in the model), the model being supplied by the temporal data of gas quality, flow and pressure available to the upstream network,
• a gas circulating without hydrogen (H 2 ) on the network downstream of the compression may accept a gas upstream of the compression in molar proportion of the mixture of the two gases up to the admissible limit on the network.
• the pressure and flow rates are shared in real time from the distribution network 15 connected to the reverse installation 30 is achieved by pressure sensors connected and positioned at certain critical points of the distribution network 15 highlighted by static studies and dynamic. This data sharing makes it possible to optimize the management of the reverse installation (in particular on stops / start-up and load) and to secure the process by anticipating the risks and impacts on the distribution network 15.
• FIGS. 3 and 4 describe transport and distribution networks and a control algorithm that can be implemented, this one making it possible to define the load level, the need to start a compressor (case where the load rate equals 100%). Identically, a low threshold can be defined to define the shutdown of a compressor.
• a transport network 10 and a distribution network 15 are interfaced by a countdown installation 30 and an expansion and distribution station 42. It is noted that the countdown installation 30 can be fixed, mobile (for example made up of transportable modules on trucks) or upgradeable (the installation comprising locations and connectors for adding compressors).
• Figure 4 is an example of a mathematical function used to define the compression load ratio.
• the coefficients k are determined by simulation or by measurements on the network which may require tests, they can also be derived from artificial intelligence by learning.
• the coefficients k express the importance (in other words, the weight or the criticality) of the measurement point in relation to the piloting constraint. If the information from simulation or prior measurement analysis only designates a binding measurement point for piloting, then this is called critical point (this is the point used for piloting). In the proposed algorithm, the coefficient k makes it possible to change the critical point as a function of the changes in pressure changes.
• PXmaxj maximum pressure that can be reached at this point, all PXmaxj are identical in the case of figure 3
• step 61 it is determined whether the minimum, for any value of i, of k pX _ hi
• the acceleration and deceleration speeds can be calculated by PID (Proportional / Integral / Derivative).
• the operational optimization component aims to provide the operating teams of the transport network 10 with network pressure and flow data, both in real time and over a history of several months. This allows the operator to view in the form of a functional diagram the network pressure and flow data. He can thus analyze a situation more quickly and better understand his intervention by knowing all the parameters of the network, something that is not the case today. This also makes it possible to raise alarms when the reverse installation 30 is operating simultaneously and the injection station 12 delivers. This feedback to the operator is based on the technology used for the “@home” applications of the National Dispatching and Regional Monitoring Centers (CSR), in retrieving information from the remote management system and presenting it in a form that can be used directly by the intervention teams.
• CSR National Dispatching and Regional Monitoring Centers
• the data made available to the operating teams are the source data resulting from the acquisition, as well as all the data (intermediate and final) calculated by the algorithms proposed for the implementation of the invention, these calculated data being time-stamped .
• This data allows intervention teams to make their own analyzes, for example simple pro-rata calculations or by comparison with similar situations already encountered.
• the data collected allow, thanks to their time stamp, the operating teams to assess the time they have before an intervention need, to assess the consequences of a reduction in the load rate on a possible postponement of the intervention, or even a capacity for non-intervention.
• the computer network for the installation of countdowns also includes remote diagnostics and remote maintenance functionalities intended for the internal operational teams of the transport network manager 10 and the contractors in charge of part of the maintenance.
• the innovation lies in the possibility of remotely viewing the supervision / man-machine interface views of the countdown installation and of being able to configure the analyzers remotely and not only face-to-face.
• a first pressure limit value used to trigger the operation of each compressor 21 of the back-up installation 30 and, optionally, for the recycling circuit 27 and the valve 28,
• the automaton 25 triggers the operation of at least one compressor 21 and, optionally, of the valve 28. Conversely, when the pressure of the distribution network 15 crosses, decreasing, the second limit value thus fixed, the automaton 25 stops the operation of each compressor 21.
• FIG. 5 details steps of a method 70 of operation of the automaton 25 controlling the reverse counting installation 30. It is assumed in FIG. 5 that each compressor 21 of the installation 30 is stopped and that the detent and delivery station 12 is also stopped.
• the automatic device 25 receives and stores instantaneous values of pressure and flow coming from the various sensors, in particular the remote pressure 33 and flow 34 sensors.
• the automatic device 25 receives and puts also in memory, preferably, instantaneous gas quality values captured at a distance from the countdown installation 30.
• the controller 25 receives and stores meteorological data, in particular the air temperature and the wind.
• step 73 the evolution of the pressure in the network upstream of the back-up installation is predicted, and the evolution of the quality of gas upstream of the back-up installation is predicted.
• the automaton determines:
• a first pressure limit value used for stopping the operation of each compressor 21 of the reverse installation 30 and, optionally, for the recycling circuit 27 and the valve 28,
• the prediction 93 shows, in the absence of delivery or compression, the next occurrence of a temporary maximum 94 of the pressure at a level lower than the pressure 90 temporarily tolerated by the network 15
• the first limit value 91 is raised to a value 92 greater than or equal to this maximum 93.
• This case occurs, for example, when producers inject biomethane into the distribution network a few moments before the probable start of professional, industrial or commercial installations consuming gas at times 95 and 96. This avoids triggering gas compression by the compressor 21, followed, a few moments later, by the stopping of this compressor 21 and the stopping expansion and delivery station 12.
• the third limit value 98 is fixed at a value 99 less or equal to this minimum 97.
• This case occurs, for example, a few moments before the probable shutdown 101 of professional, industrial or commercial installations consuming gas while producers of biomethane begin, at an instant 100, an injection of biomethane which is knows, by declaration or by learning, that the duration will extend beyond the reduction in consumption predicted. This avoids triggering the expansion and delivery station 12 followed, a few moments later, by stopping the expansion and delivery station and stopping the gas compression by the compressor 21.
• the four limit values are thus optimized to limit the number of start and stop cycles of each compressor 21 and the number of start and stop cycles of the expansion and delivery station 12.
• the automaton 25 determines whether the gas pressure in the distribution network 15 crosses the first or fourth limit values upward or decreases the second or third limit value. If so, the automatic device 25 triggers, respectively, the stopping of at least one compressor 21, the stopping of the expansion and delivery station 12, the stopping of each compressor 21 or the putting into operation of the expansion station and delivery 12. During step 75, the automaton 25 stops the operation of each compressor 21 when the gas quality at the input of each compressor 21 is lower, at the determined quality limit value.
• step 77 the controller 25 determines the compression load values to be applied as a function of the prediction of pressure development.
• step 78 the controller 25 regulates the operation of each compressor 21 to reach the charge rate thus determined.
• the controller 25 also determines, during step 77, compression load values to be applied as a function of the prediction of evolution of the gas quality. In this case, during step 78, the controller 25 regulates the operation of each compressor 21 to reach the charge rate thus determined.
• the predictions are made by conventional statistical calculations. Of course, these can be replaced by artificial intelligence in order to increase performance.
• the statistical establishment data that can be used are, in a non-exhaustive manner, the pressures of the upstream network, the gas flow rates, calendar data such as weekends, holidays and holidays, meteorological data (for example , measured temperature, felt, hydrometry, wind), the flow of consumers and the flow of counters.
• the output data is the inlet pressure of each compressor.
• the standard deviations obtained make it possible to select the best correlations and to assign margins of error to the chosen correlation.
• the correlation results are used as follows:
• the flow regulation means that the flow which passes through the compressor is constant when the station is operating. On the other hand, it is indeed the suction pressure (for example in a medium pressure network) which triggers the starting and stopping of the compressor when this pressure reaches limit values fixed during step 74.
• FIG. 6 represents a example of the evolution of the pressure 80 upstream of the compressor and of the flow rate 81 of the compressor, in a case where the limit value of the compressor start pressure is 4.2 bars and where the limit value of the compressor stop pressure is 2.5 bars.
• the controller regulates compressor operation to have a constant flow of 700 Nm 3 / h.
• FIG. 7 illustrates an example of evolution of the pressure 80 upstream of the compressor and of the flow rate 81 of the compressor with a set pressure value upstream of the compressor of 4 bars, as a function of the flow rate 82 of gas consumed by consumers on the distribution network, the flow 83 of gas injected by biomethane producers on the distribution network.
• the flow rate 84 of gas supplied by the transport network was also observed.
• a first compressor ensures the operation of the reverse installation up to its operating limit. If necessary, the controller controls the operation of a second compressor to complete the gas flow through the back-up installation.
• the two types of regulation have the same objectives, namely to maintain the situation in a stable state as long as possible, and thus limit the frequent accelerations and declarations of compressors and or the successive stops and starts of compressors, or even delivery.
• the choice of mode of piloting is done manually by an operator according to the histories and his analysis of future events.
• the algorithmic transcription of the choice for a countdown station is the proportionality ratio between pressure and flow, that is to say, the importance of a variation of flow compared to a variation of pressure at the suction of the compression.
• the control mode is under pressure, all the more if there is very little flexibility between the minimum and maximum pressures possible at the compression aspiration.
• the present invention allows an automatic choice of the regulation mode. If a possible flow control is selected, three control zones are defined. In the center, the flow mode, and at the ends the pressure control. The choice of switching from one mode to another is done at suction pressure thresholds:
• SB a low threshold "SB" for switching from flow to pressure (adjustable SB), SB near the minimum possible pressure at suction,
• All the flow calculation methods are carried out from the upstream pressure (or / and the downstream pressure) and the upstream / downstream pressure differential of the element on which the flow will be modeled.
• the model is derived from mathematical laws of the trade of the element concerned.
• the flow coefficient "Cv" given as a function of the percentage of opening and the pressure measurements make it possible to recalculate the flow rate passing through the valve.
• centrifugal compressor For a centrifugal compressor, the dimensionless (flow and efficiency coefficients, and the speed of rotation of the compressor or the power consumed by the compressor motorization) and the pressure measurements make it possible to recalculate the flow passing through a compressor.
• Another method for a centrifugal compressor is to take the pressure differential in the inlet volute (usual term “dp-eye” or “eye dp transmitter”), the model being generally supplied by the supplier of the compressor.
• the flow rate is calculated from the dimensions of the piston (compressed volume, dead spaces, rotation speed, and which can take into account the parameter for controlling the valves if they are controlled) and the pressure measurements. allow to recalculate the compressed flow.
• the comparison generates a teletransmitted alarm for a remote diagnosis and
• the present invention also provides:
• the back-up installation is equipped with a flow measurement device passing through it, a means of determining the flow transited through the back-up installation making it possible to automatically replace the counting of the installation in the event of failure of this counting, and making it possible to detect a malfunction of the compressor or the recycling valve (if installed),
• the countdown installation thus comprises:
• a means of remote communication for receiving at least an instantaneous value of gas quality captured remotely upstream or downstream of the back-up installation
• the PLC controls the stopping of at least one compressor when the input quality of each compressor is lower than the determined quality limit value.
• the countdown installation further comprises a means of determining a charge rate of each compressor as a function of the prediction of quality development, the automatic device controlling the operation of each compressor. to reach the determined charge rate.
• the means for determining the limit value preferably comprises a means for determining the absorption capacity of a non-conforming gas (of low quality) downstream of the countdown installation, capacity making it possible to dispense with treatment or to exceed the processing capacities of existing installations.
• a predictive system is the statistical prediction of a subsequent state of a system. Such a system is based on the statistical association of past values of so-called "predictor" input parameters with at least one past output state.
• the impact of predictors on the exit state is not initially known and is the subject of training.
• the training then consists in assigning to each type of predictor a statistical weighting according to the relevance of the past values of the predictor in the estimation of the known past state of the system.
• the predictions implemented are based on dynamic learning and predictors such as profiles of consumers, suppliers, capacities and response times of compressors in the installation of countdown, inertia and safety.
• Dynamic learning based on machine learning algorithms, artificial intelligence and / or neural networks, means that the predictive system uses historical data, in particular, for a large number of predictors such as dates and times, pressures observed at different points in the distribution network and triggers and stops of security, detente, countdown, consumption, injections. In variants, these data are supplemented by meteorological data. The predictive system continues to collect this data when this predictive system is then used to trigger the operation and shutdown of the countdown facility and its organs such as valves.
• the predictive system When the predictive system is initialized, it is provided, for example, for each gas consumer and for each gas supplier present on the distribution network:
• the predictive model is provided for example with the topology of the distribution network, with its branches and the positions of the sensors.
• the predictive model is also provided with the rise curves in operation of the trigger station and the back-up installation, for example.
• the predictive model is supplied, for example, with the initial setpoint and permanent safety limit pressures for each branch of the distribution network.
• the predictive system receives all the values of pressure, flow rate and analysis of the gas (as required, one or more constituents of the molar composition or total sulfur, water content, etc.) on the distribution network, upstream and downstream of the expansion station and the back-up facility.
• the predictive system predicts the evolution of the pressure upstream or downstream of a pressure installation and therefore, depending on a pressure safety value not to be exceeded, the need to start or stop the installation of counters or, on the contrary, the expansion point of the transport network.
• the predictive system makes it possible to regulate the operation of the rebounder installation and the expansion stations so as not to have to stop the rebounder or the producer of biomethane whose gas quality does not allow it to be routed downstream of the rebound.
• the predictive system thus characterizes time constants and safety constants and predicts pressure values and / or pressure setpoint values, for different regimes (injection, consumption, reverse and / or rebound, simultaneous or not) and different moments (in the year, in the week and / or in the day).
• the predictive system determines preferential times for maintenance or inspection stops, on the same bases. These preferential moments are those which minimize a cost function of these stops.
• the predictive system can, according to the embodiments, perform two types of prediction: - gas pressure or quality predictions, within a few minutes or a few hours horizon and / or
• the pressure or gas quality prediction is used to determine if a setpoint will be exceeded without modifying the operating mode of the pressure regulator and the installation of countdowns and, if so, whether this excess will be temporary. If this overshoot is not going to be temporary, the operating regime of the trigger station and the back-up installation is modified. Likewise, the pressure or gas quality prediction is used to determine if a safety value will be exceeded without modifying the operating regime of the expansion station and the back-up installation and, if so, the operating regime of the detent post and the reverse installation is modified.
• the predicted set values are implemented for the automatic operation of the organs of the expansion station and of the reverse installation. For example, as soon as the pressure of the distribution network becomes less than the predicted minimum setpoint at the expansion station and the back-up installation, the expansion station is put into operation. On the contrary, as soon as the pressure of the distribution network becomes, at the expansion station and the back-up installation, greater than the maximum predicted setpoint, the back-up installation is put into operation.
• setpoint and safety can be uniform on the distribution network or, on the contrary, different depending on the portions and branches of the network, these portions and branches being provided with at least one pressure and / or flow sensor .
• the means 7 for determining pressure limit set values comprises, for this purpose, a gain and cost calculator, energy and / or economic.

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• Chemical & Material Sciences (AREA)
• Combustion & Propulsion (AREA)
• Feedback Control In General (AREA)
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• 2018
  • 2018-07-30 FR FR1857112A patent/FR3082600B1/fr active Active
• 2019
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