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    • 专利摘要:
    A method of controlling a power generation system (8) defined by a set of operational parameters, the system (8) comprising: - a fluid pump section for pressurizing a working fluid; - an evaporator section for evaporating working fluid; - an expansion section in which power is generated; - measuring means (21) for determining the power generated in the expansion section; and - a control device (22) to control a vapor fraction of the working fluid entering the expansion section based on the power determined by the measuring means (21), with the aim of maximizing the power generated in the expansion section, characterized in that the vapor fraction is controlled by varying the values for a subset of said set of operational parameters through repeated switching between a first and second set of optimal control algorithms, the first set comprising one non-deterministically optimal control algorithm, and the second set comprising one deterministically optimal control algorithm.
    公开号:BE1027173B1
    申请号:E20195301
    申请日:2019-05-07
    公开日:2020-11-03
    发明作者:Henrik Öhman；Daniël Walraven
    申请人:Atlas Copco Airpower Nv；
    IPC主号:
    专利说明:

    Method of controlling peeling system for | power generation, comprising such power generation and compressor installation system | such power generation system.
    The present invention relates to a method for controlling a power generation system, such a power generation system, and a compressor installation comprising such a power generation system. More particularly, this invention relates to a method for controlling a power generation system. power generation in which heat from a heat source is converted into power, the heat source being, for example, a compressed gas produced by a compressor installation.
    A power generation or power cycle for converting waste heat to power designed to recover waste heat released from, for example, a compressor and to convert some residual heat into useful mechanical energy to power, for example, a generator to operate electrical generate power. Such power generation systems may consist of a heat engine or steam turbine system in which an expansion engine is used to generate power.
    Closed power circuits for converting residual heat into power are also known and described, such as Fankine-
    cycles, EKalina cycles, TFC cycles (Trilateral Flash Cycle), | etc, 9 Set using a Rankine cycle, and in particular a 9 5 Organic Kankin Cycle (ORC), is particularly known for | recovering residual energy from a heat source with a relatively low temperature such as the heat of compressed gas produced by a compressor installation.
    Such known Rankine cycles include a closed loop with a two-axis working fluid, the cycle further comprising a vine fluid section for circulation of the working fluid in the circuit during a duty cycle, successively through an evaporator section comprising at least one evaporator in thermal contact with the heat source to evaporate working fluid to a gaseous or vaporous phase; an expansion section with at least one expansion machine for converting the thermal energy transferred but the gaseous or vapor working fluid produced in the evaporator section into useful mechanical energy; and - a condenser section with at least one condenser in thermal contact with a refrigerant such as water or ambient air to convert gaseous or vapor working fluid from the expansion section into liquid which is returned to the liquid pump section for another working cycle of the working fluid.
    | In compressor installations, the power cycle can be used for the production of hot gases produced | can be contacted by compression by these hot gases with the at least one evaporator of the evaporator section:> of the power generation system, such that heat | from these hot gases is transferred to the working fluid 9 of the power circuit, and at the same time to convert F of the heat transferred to the working fluid into 9 useful mechanical energy in the ezpanie section. 9 10 # The residual heat in compressed gases from compressor installations is available at relatively high temperatures, typically of 150 ° C or higher.At the same time, when cooling these compressed gases in the evaporator section, the temperature of the compressed gases must be reduced to a very low level , typically less than 10 ° C above the temperature of the cell agent.
    The known power circuits for conversion of waste heat to power, which are designed to operate between the temperature levels of the heat source and the coolant, face a performance dilemma in having to choose between two alternatives.
    Either the power circuit uses all the available heat that is present in the heat source, but with a very Low circuit efficiency, or the power circuit uses only part of the available heat and the heat source is only partially cooled, but with a relatively high efficiency, In the latter case a separate cooler is required to reach the correct heat source temperature, for example an aftercooler | for the compressed gases released in a {compressor installation downstream of the | evaporator section of the power circuit. | The known power circuits are used to be suitable for heat sources such as compressed: gas, where | the difficulty exists that the temperature of the compressed gas entering the evaporator section | 10 varies with time, which means that the available heat 9 from this compressed gas also varies with time, The first approach is to cool the compressed cas to a predefined temperature with a cooling target, often water, to avoid temperature variations from the compressed gas entering the evaporator section of the power circuit, to then cool the compressed gas with the power circuit working fluid in the evaporator section, to finally cool the power circuit working fluid with the refrigerant such as cooling water or ambient air.
    However, with this solution, very large thermodynamic losses are introduced due to heat exchange over large temperature differences, leading to very low system efficiency, Bern's second approach is to work with power cycles with evaporation at varying temperatures, such as Kalina cycles and very critical ORCs, In addition, an ORC which works with zeotropic liquid mixtures as working fluid is a well-known approach to the thermodynamic losses due to
    9 Limit evaporation at varying temperatures.
    These | approach, however, leads to technical complexity and thus | expensive systems, 9 5 A third approach is to work with power cycles that | Be equipped with means to determine the power generated in 9 the expansion section and a control device for 9 regulation of the vapor fraction of the working fluid entering the 9 expansion section, based on the power determined by the measuring means, such that this determined power is optimized, or maximized.
    By "vapor fraction" is meant the ratio between the mass flow rate of gaseous or damping working fluid and the total mass flow rate of the working fluid,
    WO 2017/0411145 describes an ORC for converting residual heat from a heat source into mechanical energy and a compressor installation using such a CRC in which the vapor fraction of the working fluid is controlled with various specific controllable operational parameters of the power circuit, such as the flow rate of the working fluid through the visco-fuel punch section and / or the flow rate of the working fluid through the expansion engine according to a non-deterministically optimal control algorithm,
    By "non-deterministic" it is meant that the values of the specific controllable operational parameters are varied such that the optimal control algorithm can result in different sets of locally optimal values for the specific controllable operational parameters, including the mechanical energy generated in the ezpanie section. is maximized with bcerrek Lot the mechanical energy 9 generated in the expansion section under all | other sets of values for the specific controllable: operational parameters in an infinitesimal small environment 9 5 of the respective set of locally optimal values, 9 A disadvantage of the use of these non-deterministic optimal control algorithms is that they tend to get stuck in a set of locally optimal values for the specific controllable operational parameters, including the mechanical energy generated in the expansion section of the power loop circuit, not becoming global maximized with respect to the mechanical energy generated in the expansion section among all other possible cf known sets of values for the specific controllable operational parameters.
    WO 2011/106174 describes a control system for heat recovery installations including a programmable controller configured to generate feedback signals to vary specific controllable coeralional parameters of a heat recovery installation based on organic Rankine cycles, including control signals for the speed of expansion engine and pump, in response cp an algorithmic optimization cylinder for a substantial mazimization of a capacity or efficiency of the heat recovery installation at setpoints outside the design, such as during mismatched temperature levels of external heat sources, during changing heat loads from the heat sources, and during changing ambient inconstancies and operating fluid properties, is a 9 deterministic control algorithm, such as eon | extremumzoexend algorithm, a reinforcement-learning code 9 or a neural network.
    9 “Deterministic” means that the values of the 9 specific controllable operational parameters are {varied so that the optimal control algorithm results in a set # of globally optimal values for the specific controllable operational parameters, below which the mechanical energy generated in the expansion section is maximized with respect to the mechanical energy generated in the expansion section among all other possible cf known sets of values for the specific controllable operating parameters, a drawback of using deterministic optimal control rhythms is that they can set the specific controllable operational parameters of the power cycle on a suboptimal set of values, since a value is not always immediately known for every thermal parameter of the power cycle. The object of the invention is to provide a solution for one or more of the above and / or other drawbacks. For that purpose, the invention relates to a method for controlling a power generation system, said power generation system defined at the
    ; 8; using a set of operational parameters, the power generation system comprising: | - a fluid nozzle section comprising at least one | fluid pump configured to pressurize a working fluid: 3; $ - an evaporator section comprising at least one evaporator configured to at least partially evaporate working fluid pressurized in the fluid pump section by the application of heat;
    an expansion section comprising at least one expansion machine configured to expand the at least partially evaporated working fluid to generate mechanical energy; and in which expansion section power is generated:
    - measuring means configured to determine the power generated in the expansion section; and
    - a control device configured to control a vapor fraction of the working fluid entering the expansion section based on the power determined by the measuring means, with the aim of maximizing the power generated in the expansion section,
    characterized in that the stated vapor fraction is controlled by varying the values Le for a subset of said set of operational parameters by repeated switching between a first and second set of optimal recel algorithms,
    wherein the first set of optimal recel algorithms includes at least one non-deterministically optimal control algorithm, and wherein the second set of optimal control algorithms includes at least one deterministically optimal control algorithm.
    An advantage of the method according to the invention is that a set of optimal values for the specific 9 controllable operational parameters to maximize the power generated in the expansion section can be achieved, without affecting the values for the above subset F of operational parameters. parameters are set at suboptimal 9 levels, in a preferred embodiment of the invention, 19 the expansion loss section comprises a power generator configured to convert the mechanical energy generated by the least Gen expansion engine into power.
    In this way, the mechanical energy generated in the expansion section can be converted into any useful form of power, such as electrical power. The vapor fraction of the working fluid entering the expansion section is controlled with the aim of maximizing this useful form of power. the aforementioned subset of operational parameters from a flow rate of working fluid through the at least one fluid pump and / or a flow rate of the working fluid through at least one excision machine.
    The flow rate of the working fluid through the at least one liquid pump and / or the at least one expansion machine can be easily and simply controlled by providing a fluid pump or expansion machine, respectively, with a variable capacity.
    In accordance with an embodiment of the invention to be created, the first set of optimal control algorithms comprises at least two non-deterministic optimal control algorithms. 9 This provides the control device with more flexibility and / or possibilities to obtain the set of globally optimal 9 values for the specific controllable 9 operational parameters as quickly as possible. The vapor fraction of the working fluid entering the expansion section can be controlled by either applying simultaneously or repeatedly switching between the at least two non-deterministic optimal control algorithms.
    in the case of repeated switching between the at least two non-deterministic optimal control algorithms, this repeated switching between non-deterministic optimal control algorithms preferably occurs more frequently than the repeated switching between the first set of optimal control rhythms and the second set of optimal control rhythms. The repeated switching between the first and second set of optimal control rhythms is preferably less frequent than the repeated switching between the non-deterministic optimal control algorithms in the first set of optimal control rhythms, in order to enable the power generation system to switch quickly from a power source. suboptimal regimen obtained by means of the at least one deterministically optimal control algorithm from the second set of optimal recel algorithms
    9 il | if not all operational conditions of the compressor installation are known, to an optimal | operational regime obtained through the non-| deterministic optimal control algorithms from the first set of # 5 optimal control algorithms. Preferably, a first of the at least two non-deterministic optimal control algorithms comprises varying a # flow rate of the workflutdum through the at least one fluid pump, while a second of the at least two non-deterministic optimal control algorithms comprises varying a # flow rate of the working fluid through the at least one expansion engine vessel,
    Again, the flow rate of the working fluid through the at least one fluid pump and / or the at least one expansion machine can be controlled in an easy and simple way by providing a vice pump or expansion machine, respectively, of variable capacity.
    The ability to apply a separate and / or specifically appropriate nondeterministically optimal control algorithm Le to control each of these working fluid flow rates provides some degree of flexibility for the control of the power generation system such that this control is so fast. possibly converge to the set of giobal optimal values for the specific controllable operational parameters,
    in a preferred Embodiment of the invention, the at least one deterministic cotimal control algorithm is based on a database; Cited database includes sets of | values for the set of operational parameters and paired with: each one of these sets of values the determined power | under this one set of values. 9 A dataset entry in the database, containing a value for each of the operational parameters and associated value for the determined power in the expansion section, can be used as a training dataset for the deterministic optimal control algorithm.
    Based on the training data sets, the deterministic optimal control algorithm can converge more quickly and systematically to the get giobal optimal values for the subset of the specified set of operational parameters to maximize the power generated in the expansion section Le, Even more preferred is that the database is based on data generated by a power generation installation that is essentially identical to said Power Generation System, and that the database has a dynamic structure, in that way the database does not have to completely start from the deterministic optimal control algorithm of a new power generation system. begin to be rebuilt.
    In addition, the power generation system can be trained by spring learning from the essentially identical power generation plant to more accurately and quickly converge to the set of optimal waxes for the subset of BE2019 / 5301 13 | said set of operational parameters to maximize the energy generated in the expansion section, 9 in case the database has a dynamic structure, the 9 & database can be expanded with news useful data sets 9 during the operation of the power generation system, | and the respective datasets can be used in the future as a training dacaset for the power generation system.
    In this way, controlling the power generation system through the deterministically optimal control algorithm becomes faster and more accurate over time.
    Preferably, the at least one deterministic co-ordinate control rhythm is based on predicted values for the power generated in the expansion section, these predicted values being provided by a simulation of the power generation system based on a mathematical model of the power generation system, and the mathematical model in question describes the power generated in the expansion section as a function of the vapor fraction of the working fluid entering the expansion sensation. Application of the mathematical model can limit or even eliminate training data for the database on which the deterministically optimal control algorithm is based.
    Otherwise, the application of the mathematical model can systematize and accelerate the convergence from the at least one deterministically optimal control algorithm to the set of globally optimal values for the specific controllable
    | 14 operational parameters to maximize the power generated in the ez span section 9,: in a preferred embodiment of the invention, F 5 the vapor fraction of the working fluid entering the ez span section 9 is between 0.1 and 1.0, preferably Loops 0, 4 and 9 1.0, and more preferably between 0.6 and 1.0,
    The invention also relates to a power generation system defined by a set of operational parameters, said power generation system comprising:
    a fluid pump section including at least one fluid pump configured to pressurize a working fluid:
    - an evaporator section comprising at least one evaporator configured to at least partially evaporate the working fluid pressurized in the fluid pump section by the application of heat;
    - an expansion section including at least one expansion machine configured to expand the at least partially evaporated working fluid to generate mechanical energy; and wherein the particular expansion section is configured to generate power;
    - measuring means configured to determine the power generated in the expansion section; and
    a control device configured to control a thenp fraction of the working fluid entering the expansion section based on the measurement with the measuring means
    {BE2019 / 5301
    # fixed power, with the aim of maximizing the {power generated in the expansion section, | characterized in that the control device is configured to control said vapor fraction by the | 3 values to vary for a subset of said set | operational parameters by means of a repeated switching 9 between a first and second set of optimal recel algorithms, wherein the first set of optimal control algorithms comprises at least one non-deterministically optimal control algorithm 9 10, and wherein the second set of optimal control algorithms comprises at least one deterministically optimal control algorithm Furthermore, the invention relates to a compressor installation comprising at least one compressor element for compressing a gas or vapor and a cooler for cooling the compressed gas or the compressed vapor, characterized in that the compressor installation comprises a power generation system according to the invention, wherein the above condenser is integrated into a heat exchanger that also integrates at least one evaporator of the evaporator section of the power generation system for heat transfer of the compressed gas or vapor to the operating fluid,
    With the intention of better illustrating the features of the invention, some preferred embodiments of a power generation system according to the invention, a compressor installation comprising such a power generation system and a method for controlling such a power generation system in the present invention are described as example described, without limitation, | With reference to the accompanying drawings, in which: Figure 1 is a schematic representation 18 of a | 5 single stage compressor installation comprising a power generation system 9 according to the invention; Figure 9 - Figure 2 is a schematic representation of a 9 multi-stage compressor installation including a power generation system according to the invention.
    LÉ The compressor installation 1 as shown in Figure 1 comprises a compressor element 2 with an inlet 3 and an outlet 4 for compressing a gas flow OQ, compressor element Z being driven by a motor 5, and a condenser & for cooling the compressed gas before it is fed on a network 7 of compressed gas consumers. The compressor installation 1 further includes a power generation system 8 in accordance with the invention, in this case a Rankine cycle, in which the upper condenser 6 is integrated in a heat exchanger 9 in which also an evaporator LG of the power generation & recovery system is integrated. of residual heat from the compressed gas used as heat source 11 and for converting said heat into useful mechanical energy by means of an expansion machine 12 of the power generation system 8, for example a turbine driving a power generator 13 as shown in the example of figure 1 .
    {The power generation system 8 includes a closed | circuit 14 containing a working fluid, preferably a | organic working fluid, with a boiling temperature below | temperature of the heat source i, i.e. the compressed gas; the working fluid is continuously circulated in the 9 loop 14 by means of a fluid pump 15 in the 9 direction indicated by arrows F. The working fluid is passed successively through the id evaporator 10 which is in thermal contact with the heat source 11, then through the expansion machine 12 and finally through a condenser 16 before it is compressed again by the pharmaceutical pump 15 for a subsequent cycle in the circuit 14. The condenser 16 is, in this example, in thermal contact with a Kcellclement 17 of a refrigeration circuit 18 which, in the example of figure 1, is represented as a supply of cold water W from a tank 19 to circulate through the condenser 16 by means of a liquid pump 20.
    According to the invention, the power generation system 8 is provided with measuring means 21 which are configured to fix the power generated by the expansion engine 12 Le. These measuring means 21 may be, for example, a power meter or power sensor, the power generation system 8 is further equipped with a control device 22 that can control the vapor fraction of the working fluid entering the expansion section 12,
    | Normal operation of the power generation system 8 9 according to the invention is that the reselap device 22 controls the above mentioned danpiraction based on the power | which is determined by the measuring means 21, such that this power is maximized. | In the example of Figure 1 and according to a preferred feature of the invention, the control apcarate 22 controls the vapor fraction of the working fluid entering the expansion engine 12 by varying the flow rate of the working fluid through the vice fluid pump 15 and the flow rate of the working fluid. It is also possible, of course, that the control device 22 only controls the flow direction of the working fluid through the expansion engine 12 or the liquid pump 15. However, in that case the control device 22 controls the vapor action of the working fluid entering the expansion engine. 12: By repeatedly switching between two sets of optimal control algorithms.
    The first set of optimal control algorithms, comprising non-deterministic control algorithms, comprises varying the flow rate of the working fluid through the liquid pump 15 until the power determined by the measuring means 21 has reached a local maximum and varying the flow rate of the working fluid through the expansion engine. 12 until the power determined by the measuring means 21 has reached a further optimized Ickaal maximum,
    BE2019 / 5301 139 | The control device 22 will vary the working fluid trcom by the 9 expansion machine 12 or pharmaceutical pump 15, i.e. vary the 9 capacity of an expansion machine 12 or vice pump 15 #, and at the same time receive data from the power determined by the measuring means 21, and the capacity 9 of the expansion machine 12 or liquid pump 15: for which the determined power has reached a local maximum.
    After convergence of the first optimal control algorithm into the first set of optimal control algorithms, i.e. the optimal control algorithm based on varying the flow rate of the working fluid through the vice pump 15, the determined power is locally optimized according to the capacity of the liquid pump only. By fitting the second control algorithm Lo from the first set of optimal control algorithms, ie, the optimal control algorithm based on varying the flow rate of the recovery fluid through the expansion engine 12, the determined power is individually optimized in function of the capacity of the expansion engine 12, such that a locally optimized maximum can be reached for the determined power with regard to the capacity of the expansion engine 12. By switching back to the first control algorithm, the determined power is again locally optimized in function of the liquid pump 15, such that account can be taken and changes in the operational conditions of the compressor installation will be taken into account 21.
    Such changes in operational conditions are: changes in the temperature of the cells: compressed air, changes in the flow of the | Compressed Air, changes in the # 5 ambient temperature, changes in the cooling water flow, changes in the Cogeneration water temperature or changes in the efficiency of the heat exchanger. By using such control, the control device 22 controls the vapor fraction of the working fluid leaving the expansion machine. 12 9 10 enters a continuous mode, such that it can react quickly to changes in operational conditions. In this way it can be guaranteed that the determined power is at a local maximum under all operational conditions. It cannot of course be ruled out that the non-deterministic optimum control algorithms from the first set of optimal control algorithms are applied simultaneously.
    A second set of optimal control algorithms comprises at least one deterministically optimal control algorithm that is used to direct the power generation system 8 to an ogerational regime corresponding to a global cemaximized fixed power. Several options are possible for varying the flow rate of the working fluid by the expansion engine
    12.
    The capacity of the expansion engine 12 can be varied by varying the speed of the expansion engine 12, as in the present example, or by bypassing the expansion engine 12, by | by means of slide valves and / or valve valves, by varying the volume of the expansion machine 12 and / or by | & vary the oil injection of the expansion machine 12. 9 Several options are possible for varying the flow rate of the working fluid through the fluid pump 9 15. The capacity of fluid pump 15 can be varied by varying the speed of the fluid pump 15, as in the present example or by bypassing the fluid pump 15, by varying the stroke volume of the vice pump 15 or by varying the on-off frequency of the fluid pump 15. The at least one deterministically optimal control algorithm from the second set of optimal control algorithms is based on a Database, such as a morale network algorithm based on a database of Training datasets.
    Said database comprises sets of values for the set of operational parameters and associated with each of these sets of values the determined power under this one set of values,
    To obtain an accurate and rapidly converging deterministically optimal control algorithm without a very large database, a mathematical model can be developed to describe the power generated in the expansion engine 12 as a function of the vapor action of the working fluid entering the expansion engine 12, and then to be used for predicted values for the {power generated by means of a simulation of the: Power Generation System B based on this mathematical | model, 9 In the context of peer learning, the database can be 9 based on data generated by a power generation plant 9 that is essentially identical to the VOOY power generation system 8, In this way, the database on which the deterministic corimal control algorithm is based can be be expanded with more training datasets to give the deterministic optimal control algorithm more accuracy and faster convergence to a maximized determined power, The database can even be expanded with training datasets For which the power generation system 8 was not initially trained, without the time-consuming work of the generating additional data sets with the power generation system 8 itself. The database preferably has a dynamic structure such that the database can be updated and expanded during operation of the power generation system 8.
    In accordance with a Le preferred embodiment of the invention is the vapor action of the working fluid. that the expansion engine 12 enters between 10% and 100% mass fraction. It is of course also possible that the vapor action of the working fluid entering the excision engine 12 is held between other limits,
    à BE2019 / 5301 23 | for example between 40% and 100% mass fraction or between 60% | and 100% mass fraction. 9 The expansion machine 12 can be any kind of expansion machine 12 9 5 capable of generating mechanical energy | by the expansion of a biphasic fluid, i.e., z. a | mixture of liquid and gaseous working fluid. Preferably, the expansion machine 12 is a volumetric expansion machine 12 such as a scorch expansion machine 12 or a mechanical cylinder or the like which can receive a mixture of viscous and gaseous working fluid. The compressor element 2 can also be of any kind, in particular an oil-free air compressor element 2.
    It is also clear that the cooling of the condenser 16 can also be realized in other ways than in the example of figure 1, for instance by blowing ambient air over the condenser 16 by means of a fan or the like. Preferably, a working fluid is used whose boiling temperature is less than 50 ° C or even less than 60 ° C, depending on the temperature of the available heat source 11, i.e. 5. the temperature of the compressed gas to be cooled. An example of a suitable organic working fluid is 1,1,1,3,3-pentafluocropropane. The working fluid could be mixed with a suitable lubricant to lubricate at least some of the moving parts of the machine.
    Power Generation System 8. Alternatively, the 9 working fluid itself! act as a lubricant, which means that | a working fluid is selected with lubricating properties. [5 In Figure 2, a multistage compressor installation 19 is presented according to the invention, with in this case two compressor elements, a first stage compressor element 2 'and a last stage compressor element 2 ”respectively, these elements being driven 2 ° and 2” by a gearbox 23 by a gearbox 23. single motor 5 and they are connected in series for compressing a gas in two incremental pressure stages. The comparator elements 2 ', 2 "can also be of any kind, especially oil-free air compression elements.
    The installation 1 is provided with a circuit cooler & 'for cooling the gas compressed by the first stage compressor element 2' before it is supplied to the next element 2 ", and an intermediate cooler &" for cooling the gas compressed by the final stage compressor element 2 ”before the wWOrot is supplied to the network 7, Each of the above mentioned coolers 6 'and 6" is integrated in a heat exchanger 3' and 9 "respectively, in which also part of the evaporator 10 of the power generation system is integrated 8 In the example shown, the power generation system & comprises two evaporators 10 'and 10, serially connected in the circuit 14, although it is not excluded to have only one evaporator 10 of which a part is 10 ° in thermal contact with the intermediate cell 6 %, while | another part 210 "is in thermal contact with the intercooler 5".: 5 Also in this case the control device 72 is controlled: according to the same method as in Figure 1, in which case the same advantages apply as in the single-stage compressor element 2 of Figure 1, The present invention is by no means limited to the embodiments described and shown in the drawings by way of example, but a compressor installation according to the invention can be realized in all kinds of variants without departing from the scope of the invention,
    权利要求:
    Claims (1)
    [1]
    | BE2019 / 5301 {26 Conclusions. : L.- Method for controlling a system for FS power generation {8}, named system for 9 power generation (8), defined from a set of 9 operational parameters, the system for power generation (8) comprising the following: 9 - a fluid pump section comprising at least one fluid pump (15) configured to pressurize a working fluid; - an evaporator section comprising at least one evaporator (10; configured to at least partially evaporate working fluid pressurized in the fluid body section by the supply of heat; - an expansion section comprising at least one expansion machine {12} that is configured to expand the at least the required vaporized working fluid to generate mechanical energy; and in which expansion section power is generated; - measuring means (21} configured to determine the power generated in the expansion section; and - a control device (22) that is configured to control a vapor action of the working fluid entering the expansion section based on the power determined by the measuring means (21), with the aim of maximizing the power generated in the expansion section, characterized in that said vapor fraction is controlled by the values to vary for a subset of said set operating
    | parameters by repeated switching between a first | and second set of optimal control rhythms, | wherein the first set of optimal control algorithms comprises at least one non-deterministically optimal control algorithm {5, and wherein the second set of optimal control algorithms comprises at least one deterministically optimal control algorithm, 9 2. The method according to claim 1, characterized in that the expansion section has a power generator {13} includes that 9 30 is configured for use by at least one expansion engine | {12} convert generated mechanical energy Le into 9 power. Zen method according to claim 1 or 2, characterized in that the subset of said set of operational parameters comprises a flow rate of working fluid through the at least one liquid pump (15) and / or a flow rate of working fluid through the at least one expansion machine (12).
    The method according to any of the preceding claims, characterized in that the cersion set of optimal control algorithms comprises at least two non-deterministic optimal control algorithms.
    Method according to the preceding claim, characterized in that the thenp fraction of the working fluid entering the expansion section is controlled by applying the at least two non-deterministic optimal control algorithms simultaneously.
    | Method according to claim 4, characterized in that the vapor fraction of the working fluid entering the expansion section | is controlled by a repeated switching between | the at least two non-deterministic optimal control algorithms, the method according to the preceding claim, characterized in that the repeated switching between the at least two non-deterministic optimal control algorithms id E is more frequent than the repeated switching between the first set of optimal recel algorithms and the second set of optimal control rhythms. B. A method according to any one of claims 4 to 7, characterized in that a first of said at least two non-deterministic optimal control algorithms comprises varying a flow rate of the working fluid through the at least one fluid punch (15), and that a second of said at least two non-deterministic ultimate control algorithms varying a flow rate of the working fluid comprised by the at least one expansion engine {12}.
    Method according to claims 3 or B, characterized in that varying the flow velocity of the working Zillum through the at least one expansion machine (12) is realized with one or more of the following means: - a bypass along the at least one expansion machine ( 123: - means configured to vary the speed of the 39 at least one expansion machine (17), - a set of slide valves:
    | BE2019 / 5301 9 25 9 - a set of tilt valves; 9 - means configured to vary the stroke volume of # the at least one expansion engine {12}; and - means configured to vary the cell injection of the at least one expansion engine {12}. LC. A method according to any one of the preceding claims 3, 8 or 9, characterized in that varying the flow rate of the working fluid through the at least one vice pump {15} is realized with one or more of the following means: a bypass along the at least one fluid pump {15}; - means configured to vary the speed of the at least San liquid pump {15}; Lis - means configured to vary the stroke volume of the at least one liquid pump (15); and - means configured to vary the on-off frequency of the at least one pharmacy source (15) Le.
    Method according to any of the preceding claims, characterized in that the at least one deterministically optimal control algorithm is based on a database; The database contains sets of values for the set of operational parameters and, associated with each of these sets of values, the determined power under this one set of values,
    Method according to any of the preceding claims, characterized in that the database is based on data generated by a power generation installation that
    {30 is essentially identical to the mentioned system for power generation (83.
    13. Method according to claim 11 or 12, characterized in that the database has a dynamic structure.
    - Method according to any one of the preceding claims, | characterized in that the at least one deterministic optimal control algorithm is based on predicted values for the power generated in the expansion section, these predicted values being provided by a simulation of the power generation system (8) based on a mathematical model of the system for power generation {8}, and the particular mathematical model describes the power generated in the expansion section as a function of the vapor fraction of the working fluid entering the expansion section. 15. Method according to any one of the preceding claims, characterized in that the vapor fraction of the working fluid entering the expansion section is between 0.1 and 1.0, preferably between 0.4 and 1.0, and more preferably between 0 , 6 and 1.0 by weight percentage.
    16.- Power generation system defined by a set of operational parameters, said power generation system (8) comprising: - a fluid pump section comprising at least one fluid pump (15) configured to pressurize a working fluid;
    9 - sen = evaporator section = comprising at least one 9 evaporator {10} configured for the at least 9 part requirement to vaporize the pressurized working fluid | in the fish pump section by the application of heat: 5. - an expansion section comprising at least one expansion machine (12) configured to expand the at least one vaporized working fluid to generate mechanical energy Le; and where the respective expansion section is configured to generate power; - measuring means {21} configured to determine the power generated in the expansion section; and - a control device (22) configured to control a damping fraction of the working fluid entering the expansion section based on the power determined with the multipurpose means {21}, with the aim of maximizing the power generated in the expansion section, characterized in that it control device (22) is configured to control said vapor fraction by varying the values for a subset of said set of operational parameters by repeatedly switching between a first and second set of optimal control algorithms according to any one of the preceding claims, wherein the first set of optimal control algorithms includes at least one non-deterministically optimal control algorithm, and wherein the second set of optimal control algorithms includes at least one deterministically optimal control algorithm,
    Power generation system according to the preceding claim, characterized in that the expansion section comprises a power generator (13) which is configured to
    | BE2019 / 5301 32 î generated by the least one expansion machine (12) | mechanical energy to convert into power.
    18, Power generation system according to the preceding claim, characterized in that the power generator {133 9 is an electrical power generator (13) configured for converting the mechanical energy into electrical | power, 19. Power co-generation system according to any one of the preceding claims 16 to 18, characterized in that the at least one expansion machine (17) is from scort suitable for a mixture of liquid and gaseous or vaporous working fluid.
    20. Power generation system according to any one of the preceding claims 16 to 19, characterized in that the power generation system (8) is a Rankiner cycle, preferably an organic Rankine cycle.
    2i. Compressor installation comprising at least the compressor element {2} for compressing a gas or vapor and a kveler (6) for cooling the compressed gas or the compressed vapor, characterized in that the compressor installation {13 is a power generation system { 8} according to claims 16 to 20, wherein said cooler {6} is integrated in a heat exchanger {9} in which Levens is integrated at least one evaporator (10} of the evaporator section of the power generation system 36 {8} for heat transfer from it
    {BE2019 / 5301 33 {compressed gas or the compressed vapor to the | working fluid, 9 24. Compressor installation according to the preceding claim, characterized in that it is a 9 multi-stage compressor installation (1) with at least two 9 serially connected compressor elements for compressing a gas and at least two coolers (6, 6 ") acting as either an intercooler {6 ') between the at least two 130 concressor elements or as an aftercooler (6 "}) for cooling the gas compressed by a last stage compressor element {253", the compressor plant (1} having a power generation system { 8} with sean evaporator section, wherein each of the above mentioned cells {6 ', 6 ") is integrated in a heat exchanger {92} in which at least part of the at least one evaporator (10) is integrated of the evaporator section of the power generation system {8}.
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    BE1027173A1|2020-10-27|
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    法律状态:
    2020-12-04| FG| Patent granted|Effective date: 20201103 |
    优先权:
    申请号 | 申请日 | 专利标题
    US201962829744P| true| 2019-04-05|2019-04-05|
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