Self-adaptive whole station energy-saving control method for hydrogen refueling station

Abstract

The invention discloses a self-adaptive whole station energy-saving control method for a hydrogen refueling station, which comprises the following steps of: S1, acquiring the current state parameters of a vehicle-mounted gas storage cylinder of a refueling vehicle, and reading the current state parameters of a gas storage cylinder group and a tank car of the hydrogen refueling station; s2, calculating the mass of hydrogen to be consumed when the required filling amount of the vehicle is filled, taking the mass as the target hydrogen mass, taking the minimum total energy consumption in the process of completing the target hydrogen mass as an optimization target, and taking the current state parameters of a gas storage cylinder group and a tank car of the hydrogen refueling station as input; calculating final state parameters of the hydrogen storage cylinder set, the compressor set, the compressor water chilling unit and the pre-cooling water chilling unit by utilizing an optimization algorithm when filling is finished; and S3, taking the optimized final state parameter as a target state parameter, and executing pressurization and hydrogenation processes until the next vehicle is filled or the target state parameter is reached. According to the method, the parameters of the compressor unit pressurization and hydrogenation machine filling process are optimized through the optimization algorithm, and the total energy consumption in the operation process is effectively reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of hydrogen refueling in hydrogen refueling stations. More specifically, the present invention relates to an adaptive whole-station energy-saving control method for hydrogen refueling stations. Background Art

[0002] The overall operating energy consumption of a hydrogen refueling station is an important part of the operating cost of the hydrogen refueling station and is the key to affecting the profitability of the hydrogen refueling station. The operating energy consumption of a hydrogen refueling station mainly consists of compressor boosting, compressor cooling, hydrogen pre-cooling, as well as extended losses and other losses. Among them, the power consumption of compressor boosting, cooling, and hydrogen pre-cooling accounts for more than 95% of the losses. Controlling and optimizing the process parameters of boosting and filling is the key to achieving energy conservation and consumption reduction. Existing technologies usually analyze the high, medium, and low pressures of storage tanks, and the station control system or hydrogen dispenser issues a tank switching command by monitoring the filling pressure difference and flow rate. The station control system monitors the pressures of high, medium, and low storage tanks, sets upper and lower limits, automatically starts the boosting command when the pressure is lower than the lower limit, boosts the storage tanks in the order of high, medium, and low priorities, and stops when the upper limit is reached. However, they all focus on optimizing the hydrogen refueling efficiency and do not consider the actual energy consumption. In particular, they lack the utilization of the initial pressure of the tanker and do not match the changes in the initial parameters of the incoming vehicle. Summary of the Invention

[0003] An object of the present invention is to solve at least the above problems and provide at least the advantages described hereinafter.

[0004] To achieve these and other advantages in accordance with the present invention, there is provided an adaptive whole-station energy-saving control method for a hydrogen refueling station, comprising the following steps:

[0005] S1. Collect the current state parameters of the on-vehicle gas cylinders of the vehicle to be refueled, and read the current state parameters of the gas cylinder group and the tanker of the hydrogen refueling station;

[0006] S2. Calculate the mass of hydrogen required to be consumed when the required filling volume of the vehicle to be refueled is completed and use it as the target hydrogen mass. Taking the lowest total energy consumption in the process of completing the target hydrogen mass as the optimization goal, with the current state parameters of the gas cylinder group and the tanker of the hydrogen refueling station as the input, use an optimization algorithm to calculate the final state parameters of the hydrogen storage cylinder group, the compressor unit, the compressor chilled water unit, and the pre-cooling chilled water unit at the end of filling;

[0007] S3. Taking the optimized final state parameters as the target state parameters, execute the boosting and hydrogen refueling processes until the next vehicle to be refueled arrives or the target state parameters are reached.

[0008] Preferably, it further comprises: S4. Iteratively calculate according to the real-time hydrogen refueling demand, continuously update the real-time state parameters of the hydrogen storage cylinder group, the compressor unit, the compressor chilled water unit, and the pre-cooling chilled water unit, and achieve adaptive control.

[0009] Preferably, in step S1, the current state parameters of the on-vehicle gas storage cylinders of the vehicle to be refueled include the pressure, temperature, and water volume of the current on-vehicle hydrogen storage cylinders; the current state parameters of the gas storage cylinder group and the tanker at the hydrogen refueling station include the temperature and pressure of the high-pressure storage tanks, medium-pressure storage tanks, low-pressure storage tanks, and the tanker in the current hydrogen storage cylinder group.

[0010] Preferably, step S2 specifically includes the following steps:

[0011] S21. Use n times the refueling amount required for the vehicle to be refueled as the target hydrogen mass, where n ≥ 1.5;

[0012] S22. Use the multi-objective differential evolution algorithm, with the minimum total process energy consumption as the optimization objective and the hydrogen refueling rate, filling rate, and single refueling time as the constraint conditions, to calculate the final state parameters of the hydrogen storage cylinder group, compressor unit, compressor chiller, and precooling chiller at the end of refueling.

[0013] Preferably, the total process energy consumption includes the flow loss of the pipeline, the pressurization energy consumption of the compressor unit, and the cooling energy consumption of the compressor chiller and the precooling chiller;

[0014] The flow loss of the pipeline includes the flow loss of the pipe sections through which the hydrogen gas flows during the hydrogen refueling process, which consists of the extended loss and the local pressure loss;

[0015] The pressurization energy consumption of the compressor unit is the single pressurization energy consumption of the compressor from the starting parameters to the target parameters, including the pressurization energy consumption to the high-pressure storage tanks, medium-pressure storage tanks, and low-pressure storage tanks in the hydrogen storage cylinder group, as well as the pressurization energy consumption of the compressor to the hydrogen storage cylinder group;

[0016] The cooling energy consumption of the chiller and the precooling chiller includes the energy consumption for providing equal cooling for the compressor pressurization and precooling for each hydrogen refueling machine.

[0017] Preferably, the parameters required for calculating the flow loss of the pipeline, the pressurization energy consumption of the compressor, and the cooling energy consumption of the compressor chiller and the precooling chiller are obtained according to the real gas model, and the real gas model is interpolated and simulated based on the relevant data in the NIST database.

[0018] Preferably, use the full operating condition parameters of the compressor collected during the hydrogen debugging process of the hydrogen refueling station to form a numerical calculation model, and according to the target hydrogen mass, input the current state parameters of the gas storage cylinder group and the tanker at the hydrogen refueling station into the numerical calculation model to obtain the control parameters of the compressor, so as to calculate the pressurization energy consumption of the compressor unit.

[0019] Preferably, the final state parameters in step S22 are decision variables of the multi-objective differential evolution algorithm, including the target pressure of the high-pressure storage tank, the target pressure of the medium-pressure storage tank, the target pressure of the low-pressure storage tank, the tank switching pressure of the low-pressure storage tank, the tank switching pressure of the medium-pressure storage tank, the tank switching pressure of the high-pressure storage tank, the outlet water temperature and flow rate of the compressor chiller, and the outlet water temperature and flow rate of the pre-cooling chiller.

[0020] The present invention has at least the following beneficial effects:

[0021] 1. The adaptive whole-station energy-saving control method for a hydrogen refueling station provided by the present invention matches the current energy efficiency of the compressors and chillers in the hydrogen refueling station according to the current state parameters of the on-vehicle gas cylinders of the refueling vehicles, the gas cylinder groups in the hydrogen refueling station, and the tank trucks, and optimizes the boosting process parameters of the compressor unit and the refueling process parameters of the hydrogen dispenser through an optimization algorithm, effectively reducing the total energy consumption during the operation process.

[0022] 2. The adaptive whole-station energy-saving control method for a hydrogen refueling station provided by the present invention, based on the energy consumption control of the whole process, adaptively matches the changes in the requirements of the hydrogen refueling station according to the real-time operation parameters of the hydrogen refueling station, has higher control accuracy for the boosting and refueling processes, and stronger adaptability of the optimization strategy.

[0023] Other advantages, objectives, and features of the present invention will be partially reflected by the following description, and partially will also be understood by those skilled in the art through the research and practice of the present invention. Brief Description of the Drawings

[0024] Figure 1 It is the working flow chart of the hydrogen refueling station in the adaptive whole-station energy-saving control method for the hydrogen refueling station described in the present invention;

[0025] Figure 2 It is the schematic diagram of the current state parameters to be collected in step S1 of the adaptive whole-station energy-saving control method for the hydrogen refueling station described in the present invention;

[0026] Figure 3 It is the flow chart of the adaptive whole-station energy-saving control method for the hydrogen refueling station described in the present invention; Detailed Description of the Embodiment

[0027] The following further describes the present invention in detail with reference to the drawings, so that those skilled in the art can implement it according to the description in the specification.

[0028] It should be noted that the experimental methods described in the following embodiments are conventional methods unless otherwise specified, and the reagents and materials are commercially available unless otherwise specified; in the description of the present invention, the terms "lateral", "longitudinal", "upper", "lower", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside" and the like indicate orientations or positional relationships based on the orientations or positional relationships shown in the accompanying drawings, and are only for the convenience of describing the present invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as a limitation on the present invention.

[0029] like Figures 1 to 3 As shown, the present invention provides an adaptive whole-station energy-saving control method for a hydrogen refueling station, comprising the following steps:

[0030] S1. Collect the current status parameters of the on-board gas cylinder of the refueling vehicle, and read the current status parameters of the gas cylinder group and tank truck of the hydrogen refueling station;

[0031] S2. Calculate the mass of hydrogen consumed when the required filling amount of the vehicle is completed and use it as the target hydrogen mass. The optimization goal is to minimize the total energy consumption of the process to achieve the target hydrogen mass. The current state parameters of the gas storage bottle group and tank truck at the hydrogen filling station are used as input. The final state parameters of the hydrogen storage bottle group, compressor group, compressor chiller and pre-cooling chiller are calculated using the optimization algorithm at the end of the filling.

[0032] S3. Taking the optimized final state parameters as the target state parameters, the pressurization and hydrogenation process is performed until the next vehicle is refueled or the target state parameters are reached.

[0033] In this technical solution, Figure 1 As shown, after the tank truck arrives at the hydrogen refueling station, it is compressed by the hydrogen unloading column and the compressor group and distributed to the hydrogen storage bottle group, and then the hydrogen refueling machine is used to refuel the on-board gas cylinder of the refueling vehicle. The hydrogen refueling station uses an adaptive whole-station energy-saving control method to match the current compressor and chiller energy efficiency of the hydrogen refueling station according to the current state parameters of the on-board gas cylinder of the refueling vehicle, the gas cylinder group of the hydrogen refueling station and the tank truck, and optimizes the compressor group pressurization and hydrogen refueling process parameters through the optimization algorithm, so that the high-pressure hydrogen of the tank truck is used for high-pressure part pressurization as much as possible, the medium-pressure hydrogen is used for medium and low-pressure part pressurization, and the low-pressure part is used for low-pressure part pressurization, thereby reducing the total energy consumption of the operation process.

[0034] Further, the adaptive whole-station energy-saving control method for the hydrogen refueling station further includes: Step S4: Iteratively calculate according to the real-time hydrogen refueling demand, continuously update the real-time state parameters of the hydrogen storage bottle group, the compressor unit, the compressor chiller, and the precooling chiller, and achieve adaptive control. After the current refueling is completed or during the refueling process, according to the newly added hydrogen refueling demand, repeat Steps S1 to S3 for iterative calculation to obtain the optimal state parameters of the hydrogen storage bottle group, the compressor unit, the compressor chiller, and the precooling chiller under the current state parameters of the on-vehicle gas cylinders of the newly arriving refueling vehicle and the current state parameters of the hydrogen storage bottle group and the tank truck of the hydrogen refueling station.

[0035] In Step S1, the current state parameters of the on-vehicle gas cylinders of the refueling vehicle include the pressure, temperature, and water volume of the current on-vehicle hydrogen storage bottles; the current state parameters of the hydrogen storage bottle group and the tank truck of the hydrogen refueling station include the temperature and pressure of the high-pressure storage tank, medium-pressure storage tank, low-pressure storage tank, and tank truck in the current hydrogen storage bottle group. The above current state parameters can be obtained through the station control system of the hydrogen refueling station, and the current state parameters to be collected are as Figure 2 shown.

[0036] The premise of the total process energy consumption calculation is to know the state parameters of the compressor unit and the chiller before and after pressurization, that is, the hydrogen refueling station before and after refueling. That is, first preset the state parameters after refueling, then calculate the energy consumption, then compare the difference in energy consumption, and then select the state parameters corresponding to the lowest total process energy consumption as the final state parameters; the above calculation and comparison process is completed through an optimization algorithm. Considering that the final state parameters include multiple ones, a multi-objective optimization algorithm is selected. The present invention further uses a multi-objective differential evolution algorithm for solution. Step S2 specifically includes the following steps:

[0037] S21: Take n times the refueling volume required by the refueling vehicle as the target hydrogen mass, where n ≥ 1.5; consider the hydrogen mass available in the hydrogen storage bottle group according to 1.5 times or more of the refueling volume; preferably consider the hydrogen mass available in the hydrogen storage bottle group according to 2 times or more of the refueling volume.

[0038] S22: Use the multi-objective differential evolution algorithm, with the minimum total process energy consumption W z as the optimization target, and the hydrogen refueling rate, filling rate, single refueling time, and the remaining hydrogen mass available for refueling in the hydrogen storage bottle group not less than the target hydrogen mass as the constraint conditions, and calculate the final state parameters of the hydrogen storage bottle group, the compressor unit, the compressor chiller, and the precooling chiller at the end of refueling.

[0039] The total process energy consumption Wz includes the flow loss p wi (p, T) of the pipeline, the pressurization energy consumption W ci (p, T) of the compressor unit, and the temperature reduction energy consumption W fi (T, Q) of the compressor chiller and the precooling chiller; that is

[0040]

[0041] Flow loss p of the pipeline wi (p, T), boosting energy consumption W of the compressor unit ci (p, T) and temperature reduction energy consumption W of the compressor chiller and pre-cooling chiller fi (T, Q) can be calculated in two specific ways:

[0042] Method 1: Derive the corresponding calculation formula through the composition of each energy consumption and the theoretical calculation formula.

[0043] The flow loss of the pipeline includes the flow loss of the pipe sections through which the hydrogen gas flows during the hydrogenation process, which consists of the frictional loss and the local pressure loss; the local pressure loss mainly includes the throttling loss when flowing through components such as valves, filters, and containers, and the damage when flowing through elbows. Specifically:

[0044]

[0045] In formula (2), i = 1, 2,..., n is the segmentation of the pipeline, γ is the frictional resistance coefficient, l is the pipe section length, d is the pipe section diameter, u is the gas flow velocity, ρ is the gas density, Q is the gas flow rate, and p is the pressure of the pipe section. u is a function of p and ρ, and can be calculated by the following formula:

[0046]

[0047] In formula (3), p1 is the pressure at the input end of the pipe section, p2 is the pressure at the output end of the pipe section, η is the efficiency coefficient for converting pressure energy into kinetic energy, ρ is the gas density at the outlet of the pipe section, u1 is the inlet velocity of the pipe section, and u2 is the outlet velocity of the pipe section.

[0048] The boosting energy consumption of the compressor unit is the single boosting energy consumption of the compressor from the starting parameters to the target parameters, including the boosting energy consumption for the high-pressure storage tank, medium-pressure storage tank, and low-pressure storage tank in the hydrogen storage bottle group, as well as the boosting energy consumption of the compressor for the hydrogen storage bottle group; specifically:

[0049]

[0050] In formula (4), i = 1, 2,..., n is the compression process of each stage of the compressor, δ s is the relative intake pressure loss, p s is the intake pressure, λ v is the volumetric efficiency, V A is the working volume, n T is the process index, ε is the intake and exhaust pressure ratio, δ0 is the relative pressure loss, Z s is the intake compression factor, Z d is the exhaust compression factor.

[0051] The cooling energy consumption of the chiller and the pre-cooling chiller includes the energy consumption for cooling the compressor boost and pre-cooling each hydrogen dispenser; specifically:

[0052]

[0053] In Equation (5), i = 1, 2,..., n are each cooling section, including the cooling of each stage of the compressor and the pre-cooling of each hydrogen dispenser; Cop represents the refrigeration factor of the chiller, Q is the cooling capacity required for hydrogen cooling, and can be calculated according to the following formula:

[0054]

[0055] In Equation (6), T in and T out respectively represent the temperature before and after cooling in the corresponding cooling stage; c p represents the specific heat, and the specific heat value at the temperature value is taken; represents the hydrogen mass flow rate.

[0056] The values of each parameter required for calculating the flow loss of the pipeline, the boost energy consumption of the compressor, and the cooling energy consumption of the compressor chiller and the pre-cooling chiller are obtained according to the real gas model, and the real gas model is interpolated and simulated according to the relevant data in the NIST database. The NIST database is a series of scientific databases developed and maintained by the National Institute of Standards and Technology of the United States, including datasets in multiple fields such as physics, chemistry, engineering, biology, and information technology, and can be queried through the REFPROP software. According to the parameters required for calculating Equations (1) to (6), the corresponding data in the NIST database are selected, and the real gas model is established by the interpolation method, and the current state parameters of the compressor, chiller, hydrogen storage bottle group and tank truck of the hydrogen refueling station are retrieved during the calculation.

[0057] Method 2: Use the compressor full-condition parameters collected during the hydrogen commissioning process of the hydrogen refueling station to fit and form an empirical formula for the total process energy consumption with the current state parameters of the hydrogen storage bottle group and tank truck of the hydrogen refueling station before refueling as the input and the final state parameters of the hydrogen storage bottle group, compressor unit, compressor chiller and pre-cooling chiller at the end of refueling as the output. By monitoring the input and output pressure, temperature, displacement and energy consumption parameters of the hydrogen refueling station during the commissioning process, a large number of test data are fitted by the conventional data fitting method to form an empirical formula for the total energy consumption, and then it can be applied to different hydrogen refueling stations, regardless of the specific form and brand of the compressor and chiller.

[0058] In step S22, using the multi-objective differential evolution algorithm, with the minimum of min(W z ) as the optimization objective, the hydrogenation rate Qj, the filling rate SOC, the single filling time t j , and the remaining hydrogen mass m that can be filled in the hydrogen storage bottle group j as the constraint conditions, and using the final state parameters as the decision variables of the multi-objective differential evolution algorithm for calculation. The final state parameters include the target pressure of the high-pressure storage tank, the target pressure of the medium-pressure storage tank, the target pressure of the low-pressure storage tank, the cut-off pressure of the low-pressure storage tank, the cut-off pressure of the medium-pressure storage tank, the cut-off pressure of the high-pressure storage tank, the outlet water temperature and flow rate of the compressor chiller, the outlet water temperature and flow rate of the pre-cooling chiller. The model of the multi-objective differential evolution algorithm is established as follows:

[0059] min(W z ) = min[P wi , W ci , W fi

[0060]

[0061] where a, b, c, and d are the constraint conditions corresponding to the hydrogenation rate, the filling rate, the single filling time, and the remaining hydrogen mass that can be filled in the hydrogen storage bottle group respectively. The final state parameters are solved using the optimization algorithm and used as the control parameters of the compressor unit, the compressor chiller, the hydrogen storage bottle group, and the pre-cooling chiller to perform the pressurization and hydrogenation processes of the refueling vehicle. In actual calculation, other multi-objective optimization algorithms can also be used, with the minimum total energy consumption of the process as the optimization objective and the hydrogenation rate, the filling rate, the single filling time, and the remaining hydrogen mass that can be filled in the hydrogen storage bottle group as the constraint conditions to solve the final state parameters.

[0062] Although the embodiments of the present invention have been disclosed as above, they are not limited to only the applications listed in the specification and the embodiments. It can be fully applied to various fields suitable for the present invention. For those familiar with the field, additional modifications can be easily made. Therefore, without departing from the general concept defined by the claims and the equivalent scope, the present invention is not limited to the specific details and the illustrated examples here.​

Claims

1. An adaptive energy-saving control method for a hydrogen refueling station, characterized in that It includes the following steps: S1. Collect the current state parameters of the on-vehicle gas storage cylinders of the vehicle to be refueled, and read the current state parameters of the gas storage cylinder group and the tanker at the hydrogen refueling station; S2. Calculate the mass of hydrogen to be consumed when the refueling volume required for the vehicle to be refueled is completed as the target hydrogen mass. With the lowest total energy consumption of the process to complete the target hydrogen mass as the optimization goal, using the current state parameters of the gas storage cylinder group and the tanker at the hydrogen refueling station as the input, use the optimization algorithm to calculate the final state parameters of the hydrogen storage cylinder group, the compressor unit, the compressor chilled water unit and the precooling chilled water unit at the end of refueling; S3. With the optimized final state parameters as the target state parameters, perform the pressurization and hydrogen refueling processes until the next vehicle to be refueled or the target state parameters are reached.

2. The adaptive whole-station energy-saving control method for a hydrogen refueling station according to claim 1, characterized in that, It also includes: S4. Iteratively calculate according to the real-time hydrogen refueling demand, continuously update the real-time state parameters of the hydrogen storage cylinder group, the compressor unit, the compressor chilled water unit and the precooling chilled water unit, and achieve adaptive control.

3. The adaptive whole-station energy-saving control method for a hydrogen refueling station according to claim 1, wherein In step S1, the current state parameters of the on-vehicle gas storage cylinders of the vehicle to be refueled include the pressure, temperature and water volume of the current on-vehicle hydrogen storage cylinders; the current state parameters of the gas storage cylinder group and the tanker at the hydrogen refueling station include the temperature and pressure of the high-pressure storage tank, medium-pressure storage tank, low-pressure storage tank and tanker in the current hydrogen storage cylinder group.

4. The adaptive whole-station energy-saving control method for a hydrogen refueling station according to claim 1, wherein Step S2 specifically includes the following steps: S21. Take n times the refueling volume required for the vehicle to be refueled as the target hydrogen mass, where n≥1.5; S22. Use the multi-objective differential evolution algorithm, with the minimum total energy consumption of the process as the optimization goal, and the hydrogen refueling rate, filling rate, single refueling time and the remaining hydrogen mass that can be refueled in the hydrogen storage cylinder group not less than the target hydrogen mass as the constraint conditions, and calculate the final state parameters of the hydrogen storage cylinder group, the compressor unit, the compressor chilled water unit and the precooling chilled water unit at the end of refueling.

5. The adaptive whole-station energy-saving control method for a hydrogen refueling station according to claim 4, wherein The total energy consumption of the process includes the flow loss of the pipeline, the pressurization energy consumption of the compressor unit, and the cooling energy consumption of the compressor chilled water unit and the precooling chilled water unit; The flow loss of the pipeline includes the flow loss of the pipe sections through which the hydrogen gas flows during the hydrogen refueling process, which consists of the extended loss and the local pressure loss; The pressurization energy consumption of the compressor unit is the single pressurization energy consumption of the compressor from the starting parameters to the target parameters, including the pressurization energy consumption to the high-pressure storage tank, medium-pressure storage tank and low-pressure storage tank in the hydrogen storage cylinder group, and the pressurization energy consumption of the compressor to the hydrogen storage cylinder group; The cooling energy consumption of the chilled water unit and the precooling chilled water unit includes the energy consumption for providing equal cooling for the compressor pressurization and precooling for each hydrogen refueling machine.

6. The adaptive energy-saving control method for the whole hydrogen refueling station according to claim 5, wherein, The parameters required for calculating the flow loss of the pipeline, the pressurization energy consumption of the compressor and the cooling energy consumption of the compressor chilled water unit and the precooling chilled water unit are obtained according to the real gas model, and the real gas model is interpolated and simulated according to the relevant data in the NIST database.

7. The adaptive whole-station energy-saving control method for a hydrogen refueling station according to claim 5, wherein Use the full operating condition parameters of the compressor collected during the hydrogen debugging process of the hydrogen refueling station to fit and form an empirical formula for the total energy consumption of the process with the current state parameters of the gas storage cylinder group and the tanker at the hydrogen refueling station before refueling as the input and the final state parameters of the hydrogen storage cylinder group, the compressor unit, the compressor chilled water unit and the precooling chilled water unit at the end of refueling as the output.

8. The adaptive whole-station energy-saving control method for a hydrogen refueling station according to claim 4, characterized in that, In step S22, the final state parameters are used as the decision variables of the multi-objective differential evolution algorithm. The final state parameters include the target pressure of the high-pressure storage tank, the target pressure of the medium-pressure storage tank, the target pressure of the low-pressure storage tank, the tank switching pressure of the low-pressure storage tank, the tank switching pressure of the medium-pressure storage tank, the tank switching pressure of the high-pressure storage tank, the outlet water temperature and flow rate of the compressor chiller, and the outlet water temperature and flow rate of the precooling chiller.

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