WO2022185110A1 - Procédé et système de commande d'un système de fluide - Google Patents

Procédé et système de commande d'un système de fluide Download PDF

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Publication number
WO2022185110A1
WO2022185110A1 PCT/IB2021/056555 IB2021056555W WO2022185110A1 WO 2022185110 A1 WO2022185110 A1 WO 2022185110A1 IB 2021056555 W IB2021056555 W IB 2021056555W WO 2022185110 A1 WO2022185110 A1 WO 2022185110A1
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WO
WIPO (PCT)
Prior art keywords
inertia
fluid
model
fluid plant
plant
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Application number
PCT/IB2021/056555
Other languages
English (en)
Inventor
Noemi BARRERA
Antoine Frein
Emanuele MASON
Original Assignee
Enersem S.R.L.
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Publication date
Application filed by Enersem S.R.L. filed Critical Enersem S.R.L.
Publication of WO2022185110A1 publication Critical patent/WO2022185110A1/fr

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Classifications

    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F24—HEATING; RANGES; VENTILATING
    • F24D—DOMESTIC- OR SPACE-HEATING SYSTEMS, e.g. CENTRAL HEATING SYSTEMS; DOMESTIC HOT-WATER SUPPLY SYSTEMS; ELEMENTS OR COMPONENTS THEREFOR
    • F24D19/00—Details
    • F24D19/10—Arrangement or mounting of control or safety devices
    • F24D19/1006—Arrangement or mounting of control or safety devices for water heating systems
    • F24D19/1009—Arrangement or mounting of control or safety devices for water heating systems for central heating
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B13/00—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion
    • G05B13/02—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
    • G05B13/04—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric involving the use of models or simulators
    • G05B13/042—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric involving the use of models or simulators in which a parameter or coefficient is automatically adjusted to optimise the performance
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B15/00—Systems controlled by a computer
    • G05B15/02—Systems controlled by a computer electric
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D23/00—Control of temperature
    • G05D23/19—Control of temperature characterised by the use of electric means
    • G05D23/1917—Control of temperature characterised by the use of electric means using digital means
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
    • G05D23/00—Control of temperature
    • G05D23/19—Control of temperature characterised by the use of electric means
    • G05D23/1927—Control of temperature characterised by the use of electric means using a plurality of sensors
    • G05D23/193—Control of temperature characterised by the use of electric means using a plurality of sensors sensing the temperaure in different places in thermal relationship with one or more spaces
    • G05D23/1932—Control of temperature characterised by the use of electric means using a plurality of sensors sensing the temperaure in different places in thermal relationship with one or more spaces to control the temperature of a plurality of spaces
    • G05D23/1934—Control of temperature characterised by the use of electric means using a plurality of sensors sensing the temperaure in different places in thermal relationship with one or more spaces to control the temperature of a plurality of spaces each space being provided with one sensor acting on one or more control means
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B2219/00—Program-control systems
    • G05B2219/20—Pc systems
    • G05B2219/26—Pc applications
    • G05B2219/2614—HVAC, heating, ventillation, climate control

Definitions

  • the object of the present invention is a control method for controlling a fluid plant comprising a central device, a distribution network in fluid connection with one or more diffuse utilities that are characterized by a variable load over time.
  • the proposed invention falls within the scope of the adjustment of centralized fluid plants.
  • Adjusting prior art centralized fluid plants is based on sensors installed in the central device that measure an averaged value associated with all the utilities. For example, the return temperature sensor from the utilities indicates how much energy the generator needs to reach the delivery set- point value.
  • the pump (or fan) is often adjusted with the use a constant pressure jump of the pump (or fan) and enables the flowrate to be modulated in function of the number of active utilities (and thus of the loss of load on the hydraulic system).
  • HVAC heating, ventilation and air conditioning systems
  • climatic curve a climatic compensation curve
  • Adjusting the pump (or the fan) and the generator with an averaged value in the central heating unit and not with the more critical utility, as occurs in the prior art, is limiting because not all the utilities require the same temperature and head needs, thus, with utilities that are variable over time, the ideal operation conditions vary over time.
  • a first utility 1 is always active and requires an operating function that is hardly constraining (required temperature of 7°C and a low head 5 mCE), on the other hand, a second utility 2 is more constraining (required temperature of 2°C and 10 mCE head) but operates only for a few hours a day. If we do not look at the operating status of the utilities, the centralized system must always work at 2°C and 10 mCE, on the other hand if we control the system with the disadvantaged utility we can for some hours of the day use operating conditions that are less strict and improve the total consumption energy efficiency: 7°C and 5 mCE.
  • a further example of the management of the central device with a critical utility can consist of the case of heat storage (e.g. an ice tank), in which the requested temperature is a function of the loading level of the utility (e.g. ice level).
  • the model of the utility gives us information on the need of the utility, which will be met by the adjusted central device.
  • the storage model is missing, the necessary information on the need to be met will be missing.
  • a further advantage of looking at the utility and not the centralized conditions consists of the possibility of optimizing the anticipated switch-on or switch-off in function of the actual need of the utility and not in function of an averaged value of all the utilities.
  • the need of the critical utility is “hidden” inside the averaged value so that in the central device it will be necessary to consider a safety margin to avoid misunderstandings and manage the absence of exact information.
  • the technical task on which the present invention is based is to propose a control method for controlling a fluid plant comprising a central device, a distribution network in fluid connection with one or more diffuse utilities that overcomes the aforesaid drawbacks of the prior art.
  • the object of the present invention is to provide a control method for controlling a fluid plant that enables the energy consumption to be reduced and the service provided by the various utilities to be improved.
  • a further object of the present invention is to provide a control method for controlling a fluid plant that permits monitoring of the variables and parameters, adjusting and optimisation of the energy that is simple and efficient.
  • a control method for controlling a fluid plant comprising a central device, a distribution network in fluid connection with one or more diffuse utilities that are characterized by a variable load over time; the method comprising:
  • - a first step of characterization of a model configured to identify the variables and estimate the parameters of the model necessary to predict a use profile in a reduced temporal horizon by using a numeric prediction model (MNP); - a second step of characterization of the inertia of the fluid plant;
  • MNP numeric prediction model
  • a prediction step for predicting the needs of the heat transfer fluid performed by means of the numeric prediction model (MNP) defined in the first characterization step, said prediction step being configured to estimate an optimum use profile (PUO);
  • MNP numeric prediction model
  • PEO optimum use profile
  • step of adjusting said fluid plant comprising the substeps of: o processing the need of the central device assuming the absence of inertia of the fluid plant; o comparison between the results of the inertia characterization step with the inertia acceptability parameters defined in the configuration step; o if the inertia of the fluid plant is significant:
  • One or more steps of the method can be implemented by means of a computer.
  • a control system for controlling a fluid plant comprising:
  • a central device in fluid connection with one or more diffuse utilities that are characterized by a variable load over time;
  • processing unit comprising:
  • a first characterization module configured to identify the variables and estimate the model parameters that are necessary to predict a use profile in a reduced temporal horizon, by using a numeric prediction model (MNP); • a second characterization module configured to determine the inertia of the fluid plant;
  • MNP numeric prediction model
  • a prediction module configured make a prediction the needs of the heat transfer fluid using the numeric prediction model (MNP) defined by the first characterization module, said prediction module being configured to estimate an optimum use profile (PUO);
  • an adjusting module for adjusting the fluid plant configured to: o process the need of the central device, assuming the absence of inertia of the fluid plant; o compare the inertia of the fluid plant, determined by the second characterization module, with the inertia acceptability parameters defined by the configuration module; o if the inertia of the system is significant:
  • an adjusting module for adjusting the central device configured to send an adjusting signal of the central device.
  • the aforesaid objects are achieved by a computer programme that actuates one or more of the steps of the method.
  • figure 1 illustrates schematically the block diagram of the control system for controlling a fluid plant, in accordance with the present invention
  • figure 2 illustrates a first embodiment of a fluid plant, according to the present invention
  • figure 3 illustrates a second embodiment of a fluid plant with a closed loop circuit, according to the present invention.
  • fluid plant means medium or large dimension circuits that exploit a technical fluid for conveying heat.
  • technical fluids technical water, chilled water, glycol water, diathermic oil, steam, air, compressed air.
  • a central device means a central heating unit consisting of at least one generator (for example, a boiler, a refrigerator unit, a cooling tower or heat exchanger, batteries), at least one distribution pump or fan and a system for adjusting the generator (for example set-point temperature) and/or adjusting the pump or fans (for example, the number of revolutions).
  • Distribution network means a network that distributes a fluid from one point to several utilities. Via the carrier fluid, the distribution network takes the heat to the various utilities (in heating mode) or extracts heat from the various utilities (in cooling or heat recovery mode).
  • diffuse utilities we mean at least two distinct points of use of the service generated by the central device.
  • the diffuse utilities have an adjustment at the utility level intended to reach the local adjustment set- point value.
  • Some examples of adjustment of the diffuse utilities comprise reaching the environmental set-point conditions, reaching the set-point temperature conditions of the storage, the ice level, or the emission power or the temperature value of the utility side set-point.
  • the present invention describes a control method for controlling a fluid plant 1 comprising a central device 10, a distribution network 20 in fluid connection with one or more diffuse utilities 30 that are characterized by a variable load over time.
  • the central device 10 can, for example, consist of at least one heating generator or of at least one refrigerator unit and/or of both. Further, the central device 10 also comprises at least one distribution pump or fan, an adjustment system for adjusting said at least one generator 10a, 10b (for example, adjusting the set-point value of the delivery temperature) and/or adjusting the pump or fan.
  • the distribution network 20 can have a tree topology.
  • the distribution network 20 consists of a closed loop.
  • the control method 100 for controlling a fluid plant 1 according to the present invention is shown by the flow diagram of figure 1.
  • the method 100 comprises initially a step 101 of configuration of a plurality of inertia acceptability parameters of each utility 30 present in the fluid plant 1.
  • the configuration step can comprise defining a plurality of inertia acceptability parameters and defining other parameters associated with the fluid plant and with the control system.
  • Some parameter embodiments comprise the time step, the distinction of comfort and/or saving periods, weights for the terms of the cost function described below, etc.
  • a characterization step 111 follows that in turn comprises two substeps 102 and 103.
  • a first step of characterization 102 of a numeric model configured to identify the variables and estimate the parameters (involved in the process) of the model that are necessary to predict a use profile in a reduced temporal horizon by using a numeric prediction model (MNP);
  • the object of step 102 is to identify which information is necessary to predict the use profile (e.g. power, temperature, flowrate or any other operating indicator like valve position or pump revolutions) in a use profile in a reduced temporal horizon and to construct a calculation instrument to make the prediction.
  • the numeric prediction models MNP of the variables of interest used by the method 100 can be of the grey box or conceptual type, based on knowledge of the physics of the system (white part of the method).
  • the grey box model means a model consisting of two parts, an explicit first part, that is based on knowledge of the physics of the fluid plant 1 , and a second “black” part that exploits the historic data for estimating the trend.
  • the first characterization step 102 comprises a first substep that consists of selecting a numeric model of the response of an interest variable in function of the variables and of the parameters by numeric prediction models MNP of the variables of interest of grey box or conceptual type, based on a knowledge of the physics of the system and comprises a second substep that consists of identifying the parameters Pi of each numeric prediction model MNP by regressive methods without supervision of training and testing on historic data (i.e. black part of the method).
  • the inertia of the fluid plant 1 is determined.
  • the sequence of execution of the substeps 102 and 103 is performed parallel as illustrated in the diagram of figure 1 , i.e. by first performing the characterization substep 103 and then the substep 102.
  • the prediction step 104 is performed by the numeric prediction model MNP defined in the first characterization step 102 (which could also be performed after the step 103).
  • the prediction step 104 is performed to estimate an optimum use profile PUO.
  • the step 105 of adjusting the fluid plant 1 follows. As illustrated in figure 1 , the step 105 of adjusting the fluid plant 1 comprises the substeps 106, 107, 108, 109 and 110.
  • the processing substep 106 comprises calculating the need of the central device 10 assuming the absence of inertia of the fluid plant 1 (i.e. ideal case).
  • the comparison substep 107 the results of the substep 103 of characterizing the inertia are compared with the inertia acceptability parameters defined in the initial configuration step 101. if the inertia of the system is significant, the method 100 proceeds from the step 107 to the steps 108 and 109.
  • a model is constructed that comprises the inertia of the fluid plant 1 and in the step 109 the need of the central device 10 is processed, by taking account of the inertia of the fluid plant 1 and the future variation of the need.
  • the method 100 concludes with a step 110 of adjusting the central device 10.
  • the adjusting step 110 follows directly.
  • the first characterization step 102 comprises a processing step for processing a quality indicator of characterization by a step of simulation of the behaviour of the fluid plant 1 in a given period of time using only the numeric prediction model MNP with the identified parameters Pi and a step of comparison of the results of the simulation with real data, calculating a measurement of the difference between the reality and the simulation.
  • the prediction step 104 comprises processing said optimum use profile PUO to resolve an optimum problem using a method known as a Model Predictive Control (MPC), starting from a model and an FC cost function.
  • MPC Model Predictive Control
  • the cost function FC consists of a first term that forces the vicinity between the objective variable and the set-point value thereof and of a second term that forces the operation with the objective of minimizing energy consumption.
  • the first and second term have different weights configured to check how much importance to give to the service provided with respect to the reduction of energy consumption and which can be adjusted and balanced periodically or according to settings defined in the configuration step 101. For example, in order to balance the two needs at various moments of the day.
  • the first term is a distance between the objective variable and the set- point value thereof in a differentiable metric.
  • the first term is the squared difference between the objective variable and the set-point thereof. If the service provided was comfort in terms of maintenance of a certain temperature it could be the squared difference between the ambient temperature and the desired temperature.
  • the second term is a standardized measurement of energy quantities to be checked, also in a differentiable metric.
  • the second term could be the squared absolute value of the energy.
  • the numeric prediction model MPN comprises parameters and/or variables measured during the step of use of the MPN model that can be, for example, parameters describing the current status (for example, temperature, flowrate, power, level or any operating indicator like valve position or pump revolutions) or parameters of future operation in a reduced temporal horizon (for example, on the basis of the environment set-point - time schedule -, process set-point, activation times) and parameters and/or variables outside the fluid plant in a reduced temporal horizon (for example, weather forecast - e.g. temperature and outside humidity -, production plan).
  • the step of reading the data corresponding to the variables occurs during the use of the prediction model.
  • the numeric prediction model MPN uses current status variables (e.g. objective variable and current set-point value thereof) and set-point values in the future (e.g., following activation of a specific utility in a set period of time in the future, for example in X hours, change of the set-point value in X hours from 16°C to 20°C).
  • current status variables e.g. objective variable and current set-point value thereof
  • set-point values in the future e.g., following activation of a specific utility in a set period of time in the future, for example in X hours, change of the set-point value in X hours from 16°C to 20°C.
  • the adjusting step 105 further comprises the step of defining, given the profiles of the delivery temperature or flowrate for each utility (for example terminal) 30a, 30b, 30c, 30d, a critical profile that has to be reached at each step at the level of the central device.
  • the construction step 108 performed only in the case of significant inertia of the plant 1 , comprises the step of determining one or more of the following parameters of the fluid plant 1 : o heat dissipation DT between the central device and the various utilities; o inertia of the fluid plant 1 ; o sudden variations in the operating conditions in function of the capacity of the generator and/or of the pump or fan; o minimum and maximum operating limit on the control variable.
  • the sudden variation substep of the operating conditions is determined by defining a limit value for the variation of the control variable, for example the temperature, which depends on the capacity of the generator, for example, on the maximum power of the generator, on the dissipation and applying smoothing to the use profile so as to distribute the sudden variation in a set period of time preceding the variation.
  • a limit value for the variation of the control variable for example the temperature, which depends on the capacity of the generator, for example, on the maximum power of the generator, on the dissipation and applying smoothing to the use profile so as to distribute the sudden variation in a set period of time preceding the variation.
  • the method according to the invention will start to heat in advance, moving gradually from 40°C to 60°C, from 8 am less 2X minutes at 8 am minus X minutes and subsequently going to 80°C (from 8 am less X minutes to 8 am).
  • the present invention discloses a control system for controlling a fluid plant 1 comprising a central device 10, a distribution network 20 in fluid connection with diffuse utilities 30 that are characterized by a variable load over time.
  • diffuse utilities 30 we mean at least two distinct points of use of the service generated by the central device 10.
  • the system according to the present invention further comprises a processing unit.
  • the processing unit is in data communication with the central device 10 and with the utilities 30 of the distribution network 20.
  • the processing unit comprises a configuration module for configuring the fluid plant 1 , configured to configure parameters associated with the fluid plant 1 and with the control system, a first characterization module configured to identify the variables and estimate the model parameters that are necessary to predict a use profile in a use profile in a reduced temporal horizon, by using a numeric prediction model MNP, a second characterization module configured to determine the inertia of the circuit of the fluid plant 1 , a prediction module configured to predict the needs of the heat transfer fluid using the numeric prediction model MNP defined by the first characterization module, configured to estimate an optimum use profile PUO, an adjusting module of the fluid plant and an adjusting module for adjusting the central device 10 configured to send an adjusting signal to the central device 10.
  • a configuration module for configuring the fluid plant 1 configured to configure parameters associated with the fluid plant 1 and with the control system
  • a first characterization module configured to identify the variables and estimate the model parameters that are necessary to predict a use profile in a use profile in a reduced temporal horizon, by using
  • the adjusting module for adjusting the fluid plant 1 is configured to: o process the need of the central device 10, assuming the absence of inertia of the fluid plant 1 ; o compare the inertia of the fluid plant 1 , determined by the second characterization module, with the inertia acceptability parameters defined by the configuration module; o if the inertia of the system is significant:
  • processing unit is considered to be divided into distinct functional modules (memory modules or operating modules) for the sole purpose of describing the functionalities thereof clearly and completely.
  • This processing unit can consist of a single electronic device, appropriately programmed to perform the functionalities described, and the different modules can correspond to hardware entities and/or routine software that are part of the programmed device.
  • these functions can be performed by a plurality of electronic devices over which the aforesaid functional modules can be distributed.
  • the processing unit can moreover rely on one or more processors to execute the instructions contained in the memory modules.
  • the fluid plant 1 comprises a circuit of medium and large dimensions that exploits a technical fluid between at least technical water, chilled water, glycol water, diathermic oil, technical steam, air, compressed air.
  • the central device 10 comprises a central heating unit consisting of at least: a generator, at least one distribution pump, a system for adjusting the generator (for example the set point of the delivery temperature) and/or adjusting the pump.
  • the present invention relates to a programme for a computer that actuates one or more steps of the method and a method according any one of claims 1 and 10, characterized in that it is actuated by a calculator.
  • the present invention enables energy consumption to be reduced and the service to be improved that is provided by the various utilities of the centralized fluid plants. It is clear that the specific features are described in relation to different embodiments of the invention with an exemplary and non-limiting intent. Obviously a person skilled in the art can make further modifications and variants to the present invention, in order to satisfy contingent and specific needs. For example, the technical features described in relation to an embodiment of the invention can be extrapolated therefrom and applied to other embodiments of the invention. Such modifications and variations are moreover embraced within the scope of the invention as defined by the following claims.

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Abstract

La présente invention concerne un procédé de commande (100) permettant de commander une installation de fluide (1) comprenant un dispositif central (10), un réseau de distribution (20) en liaison fluidique avec un ou plusieurs utilitaires de diffusion (30) qui sont caractérisés par une charge variable dans le temps ; le procédé comprenant : - une étape de configuration (101) d'une pluralité de paramètres d'acceptabilité par inertie de chaque utilitaire (30) présent dans l'installation de fluide (1) ; une première étape de caractérisation (102) d'un modèle configuré pour identifier les variables et estimer les paramètres de modèle qui sont nécessaires pour prédire un profil d'utilisation dans un horizon temporel réduit, à l'aide d'un modèle de prédiction numérique (MNP) ; - une seconde étape de caractérisation (103) de l'inertie de l'installation fluidique (1) ; - une étape de prédiction (104) permettant de prédire les besoins du fluide de transfert de chaleur à l'aide du modèle de prédiction numérique (MNP) défini dans la première étape de caractérisation (102), ladite étape de prédiction (104) étant configurée pour estimer un profil d'utilisation optimal (PUO) ; et - une étape (110) de réglage du dispositif central (10). L'invention concerne également un système de commande permettant de commander une installation de fluide (1).
PCT/IB2021/056555 2021-03-03 2021-07-20 Procédé et système de commande d'un système de fluide WO2022185110A1 (fr)

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IT102021000004994 2021-03-03
IT102021000004994A IT202100004994A1 (it) 2021-03-03 2021-03-03 Metodo e sistema di controllo di un impianto fluidico

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US20180313557A1 (en) * 2017-04-28 2018-11-01 Johnson Controls Technology Company Smart thermostat with model predictive control
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US20170250539A1 (en) * 2016-02-26 2017-08-31 Abb Schweiz Ag Cloud-based control for power distribution system
US20180313557A1 (en) * 2017-04-28 2018-11-01 Johnson Controls Technology Company Smart thermostat with model predictive control
US20180357730A1 (en) * 2017-06-12 2018-12-13 Tata Consultancy Services Limited Systems and methods for optimizing incentives for demand response

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Title
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