Data processing device and method for providing energy to an energy consuming system

Abstract

Disclosed is a data processing apparatus for providing energy to an energy consuming system, the data processing apparatus comprising a transportable containerization unit configured to couple to the energy consuming system in use, the transportable containerization unit comprising at least one electronic data processing device configured to process data in use, a cryogenic material stream thermally coupled to the at least one electronic data processing device and configured to capture thermal energy generated by the at least one electronic data processing device in use, and a load controller for controlling the at least one electronic data processing device or the cryogenic material stream, the load controller configured to receive current energy demand parameters enabling a required energy demand of the energy consuming system to be determined, generate and transmit instructions causing a change in operation of the at least one data processing device or a change in flow of the cryogenic material stream, the instructions determined to cause a change in temperature of the cryogenic material stream to conform to the current energy demand parameters, and enable output of the cryogenic material stream to the energy consuming system, such that the changed temperature of the cryogenic material stream satisfies at least a portion of the required energy demand of the energy consuming system.

Description

[Technical Field]

[0001] The present invention relates to a system for meeting the energy needs of an energy consuming system, as well as to a data processing device and method for providing energy to an energy consuming system, and more particularly, although not exclusively, to the use of data centers that utilize heat generated by data processing devices to meet the energy needs of an energy consuming system and may also serve to regulate power supply generators. [Background technology]

[0002] Sustainability is becoming an important consideration for all industries, with companies looking for ways to make their operations more energy efficient. A company's sustainability can be improved by using more energy-efficient methods to heat buildings, using more sustainable forms of electricity, and reducing waste wherever possible.

[0003] Data centers are often used by organizations to process large amounts of data, but in recent years, emerging technologies in industries such as finance, scientific research, and artificial intelligence have necessitated the use of even more complex computers, such as crypto-mining servers and high-performance computing computers (HPC).

[0004] However, highly complex computing systems such as those described above use enormous amounts of energy and also generate large amounts of heat during operation, which is usually wasted. There is a strong demand for a system that can capture waste heat and use it for some purpose, as such a system would reduce the waste heat from complex computing systems and data centers, thus improving their sustainability. One use of waste heat is to provide heating and hot water to buildings. Buildings such as offices, factories, and even homes consume enormous amounts of energy, with a large portion of that energy being used for heating. A system that uses computer-generated waste heat (produced by computers performing required processing tasks for an organization) to heat a building would provide a very energy-efficient heating system.

[0005] A heating system using this principle to provide heating / hot water to a building using heat generated by a computer is described in U.S. Patent No. 9,958,882. This system uses cloud computing, where the computational tasks are distributed across multiple computers located in multiple different buildings.

[0006] In this prior art heating system, computers are installed in different buildings and connected to a cloud server via a network. The heat requirements of each building are monitored and provided to the cloud server. The heat requirements determine the number and complexity of the computational tasks to be assigned, and based on the heat requirements, the cloud server then commands the computers at a particular location to perform the computational tasks and generate heat. In this way, the heat generated by each computer can be adjusted to meet the heat demand of the building at that location.

[0007] However, this prior art heating system has several limitations. First, this prior art heating system is not transportable because installation incorporates the heating system into the building. Also, this heating system is specifically designed for each building, and this customization means that the prior art heating system is not reusable. Furthermore, prior art heating systems cannot be expanded to meet increased demand as needed because installation requirements typically limit the heating system to the location of the building's previous heating system and there is typically no additional expansion space available.

[0008] It should also be noted that the prior art heating systems described above are designed and dedicated to meeting and managing one type of building energy demand: heat. Heating systems are not adaptable to meet other types of energy demand, such as electricity or computing power, nor are they adaptable to meet multiple types of energy demand. Similarly, while there are currently systems that utilize heat generated by computers to meet electricity or computing power demands, again, all existing systems are configured to meet only one dedicated type of energy demand.

[0009] Currently available systems are unable to meet the multiple energy demands of external systems (such as buildings), primarily because these demands often result in competing operational requirements for heat-generating computers, and current systems are unable to balance these demands.

[0010] As outlined above, it is clear that current systems and methods for using heat generated by a computer to meet the energy needs, such as thermal needs, of external systems have significant drawbacks. In particular, current systems are not scalable, portable, reusable, or capable of meeting the energy needs of multiple coupled external systems. Summary of the Invention [Problem to be solved by the invention]

[0011] It is therefore an object of the present invention to address at least one of the limitations outlined above. [Means for solving the problem]

[0012] According to one aspect of the present invention, there is provided a data processing device for providing energy to an energy consuming system, the data processing device comprising: a transportable containerized unit configured to couple to the energy consuming system in use, the transportable containerized unit comprising: at least one electronic data processing device configured to process data in use; a cryogenic material stream thermally coupled to the at least one electronic data processing device and configured to capture thermal energy generated by the at least one electronic data processing device in use; and a load controller for controlling the at least one electronic data processing device or the cryogenic material stream, the load controller receiving current energy demand parameters that enable a required energy demand of the energy consuming system to be determined; generating and transmitting instructions that cause a change in operation of the at least one data processing device or a flow of the cryogenic material stream, the instructions determined to cause a change in temperature of the cryogenic material stream to conform to the current energy demand parameters; and enabling output of the cryogenic material stream to the energy consuming system, the changed temperature of the cryogenic material stream satisfying at least a portion of the required energy demand of the energy consuming system.

[0013] Advantageously, the data processing equipment described above allows for modular expansion, as multiple units can be combined in series or parallel configurations as desired to meet required demand. Additionally, by providing a containerized solution, as in some embodiments, the data processing equipment can be customized and / or ruggedized for various climates. This also allows the data processing equipment to be easily transportable due to its small size, and installation requires minimal new infrastructure for edge locations.

[0014] The energy demand parameter, in some embodiments, may be a desired temperature of the cryogenic material stream, and the load controller may be configured to use the difference between the desired temperature and the current temperature of the cryogenic material stream to determine the required energy demand.

[0015] In some embodiments, the load controller is configured to vary the temperature of the cryogen stream by increasing or decreasing a clock speed of the at least one data processing device. The load controller may be configured to vary the temperature of the cryogen stream by pausing or resuming operation of the at least one data processing device.

[0016] The data processing apparatus may further comprise a heating circuit thermally coupled to the cryogen stream in use and configured to, under control of the load controller, increase the temperature of the cryogen stream independently of operation of the at least one electronic data processing device. In certain circumstances, the load controller may be configured to vary the temperature of the cryogen stream by activating or deactivating the heating circuit and controlling the amount of data processing performed by the at least one electronic data processing device.

[0017] In one embodiment, the transportable containerization unit comprises a plurality of modular units, each modular unit comprising at least one instance of an electronic data processing device and a respective thermally coupled cryogenic material stream. The load controller may comprise a plurality of load sub-controllers, each load sub-controller assigned to one of the plurality of modular units, enabling independent operation of each modular unit.

[0018] The power consumption of the data processing device may be varied by activating or deactivating one or more of the modular units by changing the clock speed of the at least one data processing device, or by pausing or resuming operation of the at least one data processing device.

[0019] Advantageously, at least one data processing device may comprise a cryptocurrency mining server. In this way, a useful by-product of the at least one data processing device may be a cryptocurrency, such as Bitcoin. Additionally, cryptocurrency generating devices may easily speed up or slow down their processing tasks, or may be suspended for periods of time without adversely affecting ongoing computations, making them ideal for this embodiment.

[0020] Preferably, the transportable containerized unit is configured, in use, to be electrically coupled to the electric energy generation system, such that the load controller receives current electric energy generation level parameters for the energy generation system, enables the load controller to determine a required energy consumption of the containerized unit, and generates and transmits instructions to cause a change in operation of the transportable containerized unit, the instructions being determined to change the energy consumption of the transportable containerized unit to conform with the current electric energy generation level parameters.

[0021] Advantageously, this allows the demands of energy consumers, such as heating systems, to be met, while also helping to regulate electrical energy (power) generators by varying the energy consumption of data processing devices. This added utility is highly beneficial in that it meets the demands of two different energy systems, reducing potential energy waste. Another consideration regarding the benefit of this combination is that this embodiment minimizes waste in power regulation, in that the computational and heat output of the systems provides a highly useful by-product.

[0022] In the above embodiments, the load controller is configured to vary the amount of power consumption of the at least one data processing device to conform to current electrical energy generation level parameters by varying the operating speed of the at least one data processing device. Alternatively or additionally, the transportable containerized unit is operably coupled to an external controllable energy-consuming resource, and the load controller is configured to vary the power consumption of the containerized unit by operating the external controllable energy-consuming resource. This can serve to regulate the electrical energy generation system in many different ways. In some embodiments, the external controllable energy-consuming resource is a load bank for consuming excess energy, and the load controller is configured to provide electrical energy not required by the electrical energy generation system to the load bank.

[0023] In some embodiments, the data processing device further comprises an energy storage provided in the containerized unit and configured to store electrical energy not currently needed by the at least one data processing device or the cryogenic material stream. This energy storage, such as a battery, provides a buffer that can store excess electrical energy from the electrical energy generation system when the electrical energy system needs to offload power (increase its electrical load) or that can be used to provide energy back to the electrical energy generation system when the electrical energy generation system needs to generate more electrical energy to meet demand (reduce its electrical load).

[0024] In some embodiments, the load controller is configured to vary the amount of electrical energy stored in the electrical energy storage to conform to current electrical energy generation level parameters. Optionally, the containerized unit of some embodiments is configured to be coupled to an external electrical energy generator, and the load controller is configured to operate the external energy generator and provide electrical energy generated by the external generator to conform to current electrical energy generation level parameters.

[0025] The transportable containerization unit may comprise a standard size shipping container, and the standard size shipping container may be ruggedized, which, as previously mentioned, provides a significant advantage over existing custom-built systems.

[0026] The present invention extends to a method of providing energy to an energy consuming system, the method comprising: coupling a transportable containerized unit to the energy consuming system; processing data using at least one electronic data processing device provided on the transportable containerized unit; capturing thermal energy generated by the at least one electronic data processing device using a cryogenic material stream thermally coupled to the at least one electronic data processing device; controlling the at least one electronic data processing device or the cryogenic material stream using a load controller, the controlling step comprising receiving current energy demand parameters from which a required energy demand of the energy consuming system can be determined; generating and transmitting instructions to cause a change in operation of the at least one data processing device or a flow of the cryogenic material stream, the instructions determined to cause a change in temperature of the cryogenic material stream to conform to the current energy demand parameters; and enabling output of the cryogenic material stream to the energy consuming system, wherein the changed temperature of the cryogenic material stream satisfies at least a portion of the required energy demand of the energy consuming system.

[0027] According to another aspect of the present invention, there is provided an energy regulator for providing electric energy to an electric energy generating system or consuming electric energy from the electric energy generating system and for providing thermal energy to a thermal energy consuming system coupled to the energy regulator in use, the energy regulator comprising: at least one electronic data processing device configured to process data in use; a cryogenic material stream thermally coupled to the at least one electronic data processing device and configured to capture thermal energy generated by the at least one electronic data processing device in use; an energy storage configured to store energy; and a load controller for controlling the at least one electronic data processing device, the energy storage, or the cryogenic material stream, wherein the load controller receives electric energy regulation parameters enabling the load controller to determine a required electric energy level of the electric energy generating system; and a cryogenic material stream configured to store energy. An energy regulator is provided that is configured to receive thermal energy demand parameters enabling a required thermal energy demand to be determined; generate and transmit instructions that cause a change in operation of at least one data processing device, energy storage unit, or cryogenic material stream, the instructions being determined to cause a change in temperature of the cryogenic material stream to meet the required thermal energy demand and / or cause a change in electrical energy consumed by or provided to the electrical energy generation system to adjust the electrical energy generation system to meet a required electrical energy level; and enable output of the cryogenic material stream to the thermal energy consuming system to meet at least a portion of the required thermal energy demand and / or enable input of electrical energy from or output of electrical energy to the electrical energy generation system to meet the required electrical energy level.

[0028] The ability to have multiple electrical energy sources to meet multiple different system requirements advantageously allows multiple energy demands to be balanced by an energy regulator.

[0029] The provision of energy storage advantageously allows for decoupling of electrical and thermal energy outputs, so that when there are competing electrical and thermal energy demands, the data processing unit, energy storage, and cryogenic material streams can be controlled to simultaneously meet multiple energy demands.

[0030] In one embodiment, the energy storage comprises an electric battery, and the load controller is configured to provide electrical energy from the battery to the power generation system to regulate the power generation system.

[0031] The load controller may be configured to store excess electrical energy received from the electrical energy generation system in a battery, which further aids in regulating the electrical energy generation system, as the excess electrical energy can be consumed by the energy regulator for later use.

[0032] In some embodiments, the energy storage unit comprises an electric energy generator, and the load controller is configured to provide electric energy from the electric energy generator to the electric energy generation system to regulate the electric energy generation system, and / or to provide electric energy to generate thermal energy and provide the thermal energy to the thermal energy consumption system.

[0033] In some embodiments, the thermal energy demand parameter is a desired temperature of the cryogenic material stream, and the load controller is configured to determine the desired thermal energy demand using the difference between the desired temperature and the current temperature of the cryogenic material stream.

[0034] The load controller may be configured to vary the temperature of the cryogen stream by increasing or decreasing a clock speed of the at least one data processing device, and the load controller may be configured to vary the temperature of the cryogen stream by pausing or resuming operation of the at least one data processing device.

[0035] In some embodiments, the energy regulator further comprises a heating circuit thermally coupled to the cryogen stream in use and configured to increase the temperature of the cryogen stream under control of the load controller independently of operation of the at least one electronic data processing device. The load controller may be configured to vary the temperature of the cryogen stream by activating or deactivating the heating circuit and controlling the amount of data processing performed by the at least one electronic data processing device.

[0036] The energy conditioner may comprise a plurality of modular units, each modular unit comprising at least one instance of an electronic data processing device and a respective thermally coupled cryogen stream. The load controller may in some embodiments comprise a plurality of load sub-controllers, each load sub-controller assigned to one of the plurality of modular units and enabling independent operation of each modular unit.

[0037] The power consumption of the data processing device in some embodiments may be changed by activating or deactivating one or more of the plurality of modular units, by changing the clock speed of the at least one data processing device, or by pausing or resuming operation of the at least one data processing device.

[0038] Advantageously, at least one data processing device may comprise a crypto mining server.

[0039] In some embodiments, the load controller is configured to vary the amount of power consumption of the at least one data processing device to meet the required electrical energy level by varying the operating speed of the at least one data processing device.

[0040] The energy regulator, in some embodiments, is operably coupled to an external controllable energy-consuming resource such as a fan or a heater, and the load controller is configured to vary the power consumption of the containerized unit by operating the external controllable energy-consuming resource. In some embodiments, the external controllable energy-consuming resource is a load bank for consuming excess energy, and the load controller is configured to provide electrical energy not required by the electrical energy generation system to the load bank.

[0041] The present invention also provides a method for providing or consuming electric energy from an electric energy generating system and providing thermal energy to a thermal energy consuming system using an energy regulator, the method comprising: coupling the energy regulator to the electric energy generating system and the thermal energy consuming system; processing data using at least one electronic data processing device of the energy regulator; capturing thermal energy generated by the at least one electronic data processing device using a cryogenic material stream thermally coupled to the at least one electronic data processing device; providing an energy storage configured to store energy; and controlling the at least one electronic data processing device, the energy storage, or the cryogenic material stream, wherein the controlling step receives current electric energy regulation parameters that enable determining a required electric energy level of the electric energy generating system; receiving current thermal energy demand parameters enabling a required thermal energy demand of the energy consuming system to be determined; generating and transmitting instructions to cause a change in operation of at least one data processing device, energy storage unit, or cryogenic material stream, the instructions determined to cause a change in temperature of the cryogenic material stream to meet the required thermal energy demand and / or to cause a change in electrical energy consumed by or provided to the electrical energy generation system to adjust the electrical energy generation system to meet a required electrical energy level; enabling output of the cryogenic material stream to the thermal energy consuming system to meet at least a portion of the required thermal energy demand and / or enabling input of electrical energy from or output of electrical energy to the electrical energy generation system to meet a required electrical energy level.

[0042] These and other features, aspects, and advantages of the present disclosure will be better understood by reading the following detailed description in conjunction with the accompanying drawings, in which like reference numerals represent like parts throughout. [Brief explanation of the drawings]

[0043] [Figure 1] FIG. 1 is a schematic block diagram illustrating a block-based energy unit according to an embodiment of the present invention coupled to an electricity supply parameter platform, a data processing parameter platform, and a heating supply parameter platform. [Figure 2] FIG. 2 is a schematic block diagram showing the block-based energy unit of FIG. 1 in more detail. [Figure 3] FIG. 3 is a schematic block diagram illustrating the load control platform and data store of FIG. 2 in more detail. [Figure 4] FIG. 2 shows a perspective view of the block-based energy unit of FIG. 1. [Figure 5] FIG. 4 is a schematic diagram illustrating example input variables for the decision logic engine of FIG. 3. [Figure 6] 4 is a schematic diagram illustrating an example of actions that can be performed by the control logic engine of FIG. 3. [Figure 7A] 4 is a flowchart illustrating an example of a process performed by the decision logic engine of FIG. 3. [Figure 7B] 7B is a flowchart continuing the example of FIG. 7A. [Figure 8] 4 is a flowchart illustrating an example of a process performed by the decision logic engine of FIG. 3. [Figure 9] 1 is a schematic diagram illustrating an example of a Swedish frequency response program (FCR). [Figure 10] 1 is a flowchart illustrating an example of a process that may be implemented by an embodiment of the present invention to perform an FCR-D down service. DETAILED DESCRIPTION OF THE INVENTION

[0044] A containerized data center with enhanced functionality according to one embodiment of the present invention is presented. FIG. 1 shows a schematic diagram of a system 10 comprising a data center 12 (hereinafter referred to as a “block-based” energy unit) and various parameter platforms. The block-based energy unit connects to the various parameter platforms via a communication network 20, which may be any wide area network, such as the Internet. The parameter platforms include a power generation parameter platform 14, a data processing parameter platform 16, and a heating supply parameter platform 18. The power generation parameter platform 14 provides parameters related to an external source supplying energy to the block-based energy unit 12; for example, the parameters may be the frequency of the power grid or the current power consumption of the block-based energy unit 12. Although not explicitly shown in FIG. 1 , it should be understood that the power generation parameter platform 14 is operably coupled to an external electrical supply source 15 to determine electrical supply parameters. The data processing parameter platform 16 provides parameters related to processed data 19 output from the block-based energy unit 12 and parameters related to external data processing sources to which the processed data may be provided. For example, the parameter may be HPC revenue. Although not explicitly shown in FIG. 1 , it should be understood that the data processing parameter platform 16 may be operatively coupled to other external data processing sources (such as other block-based energy units 12) to determine data processing parameters for this block-based energy unit 12. The heating supply parameter platform 18 provides parameters related to external utility systems that may be connected to the block-based energy unit 12 and the heated substances 32a, 32b produced by the unit 12.The external utility system may be, for example, a district heating system (a system for heating multiple homes in a district), and examples of parameters in the heating supply parameter platform 18 may be the required heat output (units / kWh) or the required heat output (kWh) of the block-based energy unit 12. The block-based energy unit 12 uses parameters obtained from these platforms to control the unit outputs 17, 19, 32a, 32b. Although not explicitly shown in FIG. 1 , it should be understood that the heating supply parameter platform 18 is operatively coupled to the external heating utility system (not shown) to determine the heating supply parameters.

[0045] Possible outputs of the block-based energy unit 12 are shown in FIG. 1 as heated substances (such as heated fluid 32a and / or heated air 32b), electrical energy 17, and processed data 19. As inputs, the block-based energy unit 12 receives cold substances (such as cold fluid 28a and / or cold air 28b) and an electrical energy supply 15. Optionally, the block-based unit 12 can also receive data 21 to be processed as input. The block-based energy unit 12 can control the consumption of energy to increase or decrease the demand on the external electrical system that provides the electrical energy. For example, this can be in the form of an FCR-D up or down response, as described below. The block-based energy unit 12 can also store energy and release it when needed as an output, or use the stored energy to generate other forms of energy. For example, electrical energy can be stored and used at the appropriate time to generate and output thermal energy.

[0046] The block-based energy unit 12 is shown in more detail and schematically in Figure 2. The block-based energy unit comprises a data processor 22, a cooling CCT 28, and optionally a heating CCT 32. The cooling CCTS 28 and the heating CCT 32 communicate with and are controlled by a cooling fluid input control function 26 and a heating fluid / air output control function 30, respectively. These control units 26, 30 and the data processor 22 are connected to a load control platform 24. The block-based energy unit 12 further comprises an energy storage 34 and a data store 36, which are also connected to the load control platform 24.

[0047] The block-based energy unit 12 comprises a heat source, a cooling / heat capture device, and a controller. A data processor 22 is used as the heat source, converting electrical energy 15, which is the input of the block-based energy unit 12, into heat. In one embodiment, the data processor 22, and therefore the heat source, is a cryptocurrency mining server. These may be manufactured by companies such as Bitmain, MicroBT / Whatsminer, etc., in some embodiments. This is a particularly useful embodiment because it allows for the rate at which processing tasks are completed to be varied without affecting the outcome of the processing. However, the operating principles of the block-based unit 12 also work with other data processing devices that generate heat, such as standard computer servers or HPC devices that consume electricity. Processed data 19 may be usefully output from the data processor 22 as a result of its operation.

[0048] The cooling CCT 28 and heating CCT 32 within the block-based energy unit 12 function in conjunction as a heat capture / heat generation device. The cooling CCT 28 receives a cryogenic material as an input under the control of a cooling fluid input control function 26. This cryogenic fluid 28a and cryogenic air 28b capture excess heat from the data processor 22, essentially fluid-cooling the data processor 22. The resulting hot fluid 32a and hot air 32b may then be sent to the heating CCT 32, which is under the control of a heating fluid / air output control function 30. The heating fluid / air output control function 30 controls the output temperature of the fluid to an external heating utility system and can increase the temperature of the output fluid 32a as needed. The heating fluid / air output control function 30 also controls the release of hot fluid / air to an external utility heating system, such as a district heating system, or, if the external utility heating system does not require hot fluid / air, the hot fluid / air is cooled to ensure there is enough refrigerant to capture the heat generated by the data processor 22.

[0049] The load control platform 24 communicates with the cooling fluid input control function 26, the heating fluid / air output control function 30, and the data processor 22 to provide instructions for the operation of each component. The load control platform 24 also communicates with each parameter platform 14, 16, 18 to receive input parameters, as well as with an energy storage unit 34 and a data store 36. The energy storage unit 34, which in some embodiments may be provided by a suitable battery, stores electrical energy provided to the block-based energy unit 12 but not used by the data processor 22 in performing its tasks (the amount consumed by the data processor 22 may be increased or decreased). The stored energy may then be provided as electrical energy output 17 when needed to meet increased electrical energy demands, or may be used as an energy source to increase data processing capacity or generate more heat (using a heater or by increasing data processor operation) to meet increased data computation or heating demands. In this regard, it should be appreciated that the energy storage 34 effectively decouples the electrical energy output 17 from the heating material outputs 32a, 32b, allowing the block base units 12 to operate independently to meet simultaneous, competing power demands. In other words, the provision of the energy storage 34 advantageously enables the independent operation of the block base units 12 to provide multiple simultaneous energy outputs, even if those outputs would normally require incompatible methods of operating the block base units 12.

[0050] As discussed above, the provision of energy storage 34 advantageously allows for simultaneous, and potentially competing, demands of different external utility systems to be addressed. This is because energy source 34 allows for decoupling of the competing simultaneous demands. For example, consider the heat demand of an external heating utility system and the frequency requirements for an external electrical supply system that runs a local / national power grid that provides electrical energy 15 to block-based energy unit 12. If it is determined that the heat demand of the external heating utility system is decreasing, but at the same time that the frequency of the electricity from the external electrical system is too high, data processor 22 must perform two opposing actions. That is, a decrease in heat demand requires a decrease in the power consumption of data processor 22, but a decrease in the frequency of the electricity provided by the external electrical system requires an increase in the power consumption of block-based energy unit 12. To meet both the electrical and thermal requirements, data processor 22 reduces its power consumption (thus reducing the amount of heat generated and provided to the external heating utility system) and energy storage 34 is charged by electrical supply 15. Charging the energy storage 34 increases the power consumption of the block-based energy unit 12, and therefore reduces the frequency of the electrical energy provided by the external electrical energy system. It is only necessary to use the energy storage in this way when there are competing demands. Another way to meet these competing demands is to route excess heat generated by the data processor 22 (but not needed by the external heating utility system) through the cooling circuit 28 within the block-based energy unit 12. Naturally, if the demands are complementary, both can be met using the energy storage 34 minimally (to exactly match the demands) or not at all.For example, in the above example, if energy consumption is to be reduced in order to increase the frequency response of the electrical energy supply system (reducing input electrical energy 15), the reduction in electrical consumption of the block base unit 12 for the data processor 22 can be achieved by consuming less energy from the electrical supply 15.

[0051] Although not shown in FIG. 2 , the block-based energy unit 12 can also be optionally coupled to an external, controllable energy-consuming resource, such as an electric heater, which also serves to decouple potentially competing demands of different external utility systems. This is used when the power consumption of the block-based energy unit 12 should be increased to lower the frequency of the power grid to which the block-based energy unit 12 is connected. Similarly, although not shown in FIG. 2 , the block-based energy unit 12 can also be optionally coupled to an external, controllable energy-generating resource, such as a generator (typically a gen set that generates electricity using a fossil-fuel engine), which also serves to decouple as described above. This is used when the power consumption of the block-based energy unit 12 should be reduced to increase the frequency of the power grid to which the block-based energy unit 12 is connected, and power should be provided back to the power grid.

[0052] A schematic diagram of the load control platform 24 and data store 36 is shown in more detail in Figure 3. The load control platform 24 includes a communications engine 40 connected to a processor 42. The processor includes a decision logic engine 44 and a control logic engine 46. The decision logic engine 44 receives parameters from each of the different parameter platforms 14, 16, 18 via the communications engine 40. These parameters, such as power parameters 48, heating parameters 50, and data processing parameters 52, are stored in the data store 36. The data store 36 also includes control algorithms 54 that are used to configure the operation of the decision logic engine 44 and the control logic engine 46.

[0053] Decisions made by the decision logic engine 44 are executed by the control logic engine 46, which communicates data processing and / or configuration instructions to the data processor 22 (e.g., configuration instructions may include changes to the processor's clock speed). The processor 42 of the load control platform 24 communicates with the energy storage 34 and is also responsible for sending instructions to and receiving feedback from the cooling fluid input control function 26 and the heating fluid / air output control function 30. The load control platform 24 is the central component and functions to control the entire block-based energy unit 12. For example, the load control platform 24 can make decisions about how to increase or decrease the output (heated substances 32a, 32b, electrical energy 17, and processed data 19) in response to received parameters, and how the resulting increase in required input energy will be obtained (from the electrical input supply 15 or from the on-board energy storage 34). Examples of such decisions by the load control platform 24 are described below.

[0054] Figure 4 shows a perspective view of a containerized block-based energy unit 12. A containerized solution has several associated advantages. For example, a containerized solution: (i) Allows for modular expansion as multiple units can be combined in series or parallel configurations as desired to meet required demand; (ii) can be customized / ruggedized for various climates (e.g., the block-based energy unit 12 is a fully containerized system, making it suitable for climates with heavy rain and wind, high and low temperatures, and snowfall); (iii) the size of the unit makes it transportable (the block-based energy unit 12 is constructed using standard shipping container sized units; for example, using the dimensions of the most common 40-foot shipping container, the unit size may be approximately 12.0 x 2.3 x 2.4 meters) and inherently ruggedized. Because the unit 12 is not a custom-built solution for a given facility, this allows the block-based energy unit 12 to be reused and redeployed as needed (e.g., easily transportable by tipping truck); and (iv) Located close to end users, requiring minimal new infrastructure. If the generated heated fluid is used as input to an external utility heating system, location can be important as proximity to the district heating system reduces heat losses and therefore increases efficiency.

[0055] In this embodiment, the block-based energy unit 12 is comprised of two modular operating sides, a left side and a right side, each consuming approximately 1.2 MW of power. Each side replicates the data processor 22, cooling circuit 28 and heating circuit 32, cooling fluid input control function 26, and heating fluid / air output control function 30 shown in FIG. 2. However, each modular operating side operates independently of the others, meaning that different logic and settings can be applied to each side within the block-based energy unit 12, allowing for very precise and responsive control of power consumption. In this embodiment, the load controller (load control platform 24) can be comprised of two sub-controllers, each independently controlling a different modular operating side. Thus, the power consumption of the unit 12 in this embodiment can be precisely varied from 0.02 MW to 2.4 MW almost instantaneously and reliably within the required time limits specified, for example, by frequency response (energy regulation) specifications (only a small amount of power is required for the control electronics). Depending on the configuration of the internal devices, the block-based energy unit 12 may also consume more power, for example, by increasing the clock rate of the data processor 22, storing unused power in the energy storage 34, or activating a heating circuit to generate a hotter heated fluid output 32a.

[0056] It should be appreciated that in this embodiment, a temperature difference (delta) of up to 15°C can occur between the input cold water 28a and the output hot water 32a, resulting in a maximum output temperature of approximately 60°C. The output hot water can be provided, for example, to a district heating system. Depending on the computing hardware used within the container, temperature fluctuations and maximum output temperatures can vary. If a temperature output higher than 60°C is desired, the block-based energy unit 12 can optionally provide an additional external heating device 32 to raise the temperature of the heated water / fluid 32a to approximately 85°C. Examples of additional external heating devices 32 that can be used in other embodiments include heat pumps, electric boilers, and flow heaters. These heating devices 32 can also be used for power control for frequency response applications, if desired, with their degree of activation controlling, for example, the degree of power consumption.

[0057] This embodiment can be used to provide multiple services, such as energy frequency response, hot water provision from waste heat, energy trading, computing power for HPC applications, and / or blockchain workloads. The provision of energy storage 34 decouples the various energy supplies provided by the block-based energy unit 12, thereby allowing the demands of multiple services to be addressed simultaneously, even when the demands are competing, as explained above.

[0058] A load control service is used to manage the services that block-based energy unit 12 can provide and to control unit 12 itself. This is an automated program that consists of two parts: decision logic 44a (implemented by decision logic engine 44) and control logic 46a (implemented by control logic engine 46). Figures 5 and 6 show the variables that can be managed by decision logic 44a and control logic 46a, respectively.

[0059] The decision logic 44a makes decisions based on input parameters, calculations, and specifications. Examples of input parameters are shown in FIG. 5 and include a BTC parameter value, an FCR-D down or FCR-D up value, heat generation, heat amount, power parameter value, and power consumption amount. The decision logic engine 44 reads these parameters via multiple parameter platforms 14, 16, 18. The calculations and specifications taken into account by the decision logic 44a include features available at a particular location, such as whether a waste heat supply is available, whether the hardware is FCR-D compatible, or whether additional external add-ons such as batteries are available.

[0060] The decision logic 44a constantly queries external sources (e.g., electrical supply, district heating system) for changes in input parameter values. Depending on how frequently the source values ​​may change, the decision logic 44a can query the data as frequently as every sub-second to once a day. This is useful for frequency response programs, as different frequency response programs require different response times. The block-based energy unit 12 can be configured to meet the requirements of each program.

[0061] In one non-limiting example, the decision logic 44a for the Swedish frequency response program FCR-D must read frequencies with a resolution of 10 MHz. The response time for FCR-D is 50% of the load within 5 seconds, with the remaining load (50%) having to be responded to within 25 seconds. Therefore, 100% of the load must be responded to within a maximum of 30 seconds.

[0062] There are other frequency response programs, such as FFR, that require a response time of 0.7 to 1.3 seconds, and the block-based energy unit 12 can be configured to meet these response times. In general, certain countries, such as Sweden, have different programs for frequency response, and other countries have other programs and requirements. The values ​​above are examples for the Swedish frequency control program.

[0063] An example of the decision logic 44a is shown in the flowchart in Figures 7A and 7B, which illustrate how changes in the value of a power parameter can result in different outcomes (i.e., instruct the control logic 46a to execute different scenarios). The power parameter may be a power price, a power demand, or any other suitable parameter.

[0064] In this example, the term "hatched" is used to represent parameter values ​​that are "locked" or "fixed," i.e., stable, according to predetermined requirements or agreements. In the absence of such predetermined requirements or agreements, the values ​​of the parameters may change significantly over time (have high variability). This will therefore adversely affect energy output generation decisions that are based on these parameter values.

[0065] The process of decision logic 44a shown in Figure 7A begins when decision logic 44a detects a change in the value of a power parameter at step 102. Decision logic 44a then determines at step 104 whether the power parameter for the current location is hatched.

[0066] If the power parameter is not hatched, the process proceeds to point A and calculates a difference value A at step 120; this path is shown in FIG. 7B and described in more detail below. If the power parameter is hatched, the decision logic 44a determines at step 108 whether the power parameter is higher than the hatched value. If the power parameter is less than or equal to the hatched value, the process proceeds to point B and calculates at step 134 whether a change in efficiency alters the difference value A (this path is also shown in FIG. 7B and described below). If not, the decision logic 44a calculates a difference value A at step 112 from the frequency response parameter, the calculation parameter, and the thermal parameter, and the power consumption value and the power parameter value. The difference value A is the power parameter difference value. In one non-limiting example where the power parameter is price, the difference value A may be profitability (thus calculated as the difference between the revenue generated from the frequency response, the calculation process, and the heat provided to the external utility system and the power consumption cost and the power price).

[0067] The decision logic 44a then calculates a difference value from the offering of the hatch capacity relative to the current power parameter in step 114. In this example, difference value B is also a power parameter difference value. In the non-limiting example above where the power parameter is price, difference value B may also be profitability, which is the profitability gained by selling the hatch capacity relative to the current power price.

[0068] The decision logic 44a then determines, at step 116, whether difference value B is greater than difference value A. If difference value B is less than or equal to difference value A, the process proceeds to point B, where, at step 134, it calculates whether a change in efficiency alters difference value A (FIG. 7B). This path is described below. If difference value B is greater than difference value A, the decision logic 44a, at step 118, commands the control logic 46a to stop the current workload and provide hatched capacity to an external utility system. In this example, where the hatched parameter is power, returning the remaining amount of the hatched parameter to the source of that power is a form of energy trading. This is one consequence of the decision logic 44a identifying a change in the power parameter.

[0069] 7B illustrates alternative paths and resulting actions of the decision logic 44a in response to a change in the power parameter. After the decision logic 44a determines in step 104 that the power parameter is not hatched, a difference value A is calculated in step 120 using the same method as in step 112. The decision logic 44a then determines in step 122 whether the difference value A is greater than a threshold value. The threshold value is a selected value above which a difference value provides an advantage to the block-based energy unit 12. For example, the threshold value may be a threshold value for efficiency, profitability, or any other suitable value depending on the power parameter. If the difference value A is less than or equal to the threshold value, the decision logic 44a then calculates in step 124 whether a change in the efficiency of the computer (data processor 22) would change the difference value A. The decision logic 44a then checks in step 126 whether the difference value A is greater than the threshold value, and if so, the decision logic 44a instructs the control logic 46a to change the efficiency parameter in the data processor 22 in step 140. This is a second possible consequence of the decision logic 44a identifying a change in the power parameter.

[0070] If the difference value A is less than or equal to the threshold value at step 126, the decision logic 44a checks at step 128 whether the computing hardware is FCR-D down compatible. If the hardware is not compatible, the decision logic 44a instructs the control logic 46a at step 130 to pause the current workload. This is a third possible consequence of identifying a change in the power parameter. If the hardware is found to be FCR-D down compatible at step 128, the decision logic 44a instructs the control logic 46a at step 132 to pause the current workload, stop the FCR-D up service, start the FCR-D down service, and signal external energy FCR-D down capacity. This is a further possible consequence of the decision logic 44a identifying a change in the power parameter.

[0071] If, in step 122, difference value A is found to be greater than the threshold for this stage, then the block-based energy unit 12 calculates, in step 134, whether a change in the efficiency of the computer (data processor 22) will change difference value A. If, in step 108, the power parameter was less than or equal to the hatched parameter, and if, in step 116, difference value B was less than or equal to difference value A, then step 134 is also completed. After step 134, the block-based energy unit 12 determines, in step 136, whether a change in the efficiency of the computer will cause difference value A to increase. If difference value A increases, then the decision logic 44a instructs the control logic 46, in step 140, to change the efficiency parameter at the data processing device 22. Otherwise, nothing is done and, in step 142, all operating parameters are maintained. It can therefore be seen that various consequences are possible from the decision logic 44a identifying a change in the value of a power parameter.

[0072] While this example shows a particular implementation of decision logic 44a that occurs when a change in the value of power parameter 48 is observed, a similar decision logic flow is or can be implemented for other changes occurring at the inputs, such as a change in the value of heating parameter 50 or the value of data processing parameter 52.

[0073] As briefly outlined, the decision logic 44a instructs the control logic 46a to perform specific operations on different devices. The control logic 46a interacts and communicates with hardware devices such as computers as well as external devices such as generators or battery add-ons. The control logic 46a can perform various actions, as illustrated in FIG. 6 . For example, the control logic 46a can increase the power consumption of the data processing devices 22 by overclocking them, or decrease the power consumption by instructing the data processing devices 22 to downclock or suspend their workloads. An example of a process implemented by the control logic 46a when the control logic receives an instruction to suspend or reduce a current workload is illustrated by the flowchart in FIG. 8 .

[0074] The process begins in step 202 after receiving an instruction from the decision logic 44a to suspend or reduce the current workload. The control logic 46a then retrieves, in step 204, a list of devices (data processors 22) operating in the facility, along with their technical specifications, from a local library stored in the data store 36. The control logic 46a then determines, in step 206, whether all devices should be suspended, or whether only a partial suspension is required. This depends on how much power consumption needs to be reduced to meet requirements defined by changes in external parameters. If only a partial suspension is required, the control logic 46a calculates, in step 208, the number of devices to suspend as an input of percentage or power usage. Once calculated, the control logic 46a selects, in step 210, the devices to suspend, prioritizing devices with less critical workloads, if possible. The control logic 46a then compiles, in step 212, a list of devices to suspend. If, at step 206, it is determined that all devices should be paused, then the control logic 46a, at step 212, compiles a list containing all devices in the facility. The control logic 46a then, at step 214, retrieves from a local library information specifying how to communicate with each device and the commands necessary to pause the devices on the compiled list. Step 214 is required because different devices may require different commands and communication protocols. Once this information is received, the control logic 46a, at step 216, sends a pause command to the compiled device list. This flowchart shows an example of the control logic 46a after receiving an instruction to pause or reduce the current workload. It will be appreciated that a similar process is possible when the control logic 46a receives a different instruction, for example to increase heat generation or change the efficiency of the data processor 22.

[0075] As discussed, the control logic 46a is responsible for instructing the data processor 22 that is part of the block-based energy unit 12. Various types of data processing may be used, such as cryptocurrency mining. Advantages of using this type of data processing include: Very high power density is possible. This means that high power demands can be utilized in a very small footprint, making cryptocurrency mining ideal for containerized implementations. The mining process can be interrupted at any time without losing state or data, making crypto mining highly suitable for frequency response programs, where devices may need to be paused to balance power grid frequencies. The mining process generates instant revenue without the need for a committed customer / contract or service. The high power density of the machine allows for a wide range of power control. This means that the block-based energy unit 12 can operate a single cryptocurrency miner within the range of 0-10 kW (this is just an example of one type of machine that can be used). This power consumption can vary significantly depending on the machine used. This disclosure covers the use of a variety of different cryptocurrency mining machines.

[0076] Another example of the type of data processing that can be performed is any form of HPC. This type of data processing is ideally suited to providing the frequency response functionality of embodiments of the present disclosure. Advantages include: Very high energy densities are possible that can be varied. This means that the amount of power used can be precisely reduced or increased. Short reaction times. Special software and hardware are provided to enable the fast reaction times necessary to react to frequency changes on the power grid. High geographic flexibility: the block-based unit 12 can therefore be located and operated anywhere. Low cost of ownership, which means HPC can operate periodically depending on the application / workload. High availability. Typically, such computing is operational 24 hours a day. This means that frequency response functions can operate 24 hours a day, which is essential for continuously maintaining the power grid frequency within safe limits.

[0077] While there are many uses for the control logic 46a of the described embodiments of the invention, as outlined above, one application for which HPC is a particularly well-suited type of data processing is to provide power grid frequency response functions. Frequency response programs may vary from country to country and may have different names, but the underlying principle is the same: balancing the power grid and responding to frequency changes. The solution provided by the described embodiments of the invention can be adapted to suit the various requirements of each country.

[0078] Below we discuss an example of a Swedish frequency response program, called FCR, and the requirements of the FCR, which is also shown at a high level in schematic form in Figure 9.

[0079] The electrical output of the electrical supply 400 in this response program must always match the electrical demand 402. When the electrical supply 400 is insufficient, which typically results in a frequency drop of the output AC power supply below the 50 Hz standard for electrical supply (which may be 60 Hz in some countries, such as the United States), the needed excess energy is then obtained by rotating more generators. When there is an excess supply of electricity 402 compared to demand, the frequency of the output AC power supply increases as energy is transferred to the rotating more generators. A frequency that is too high or too low compared to the desired standard level (e.g., 50 Hz) can be harmful to equipment and the power supply system and may cause widespread power outages. Therefore, the operation of the power supply system is a constant balancing act, and a stable frequency is a key indicator of a stable power supply. Various frequency reserves, such as frequency constraint reserves against disturbances (FCR-D), ensure that frequency deviations are contained, minimized, and restored. These reserves play a key role in the stability of the power supply system and are essential to the operation of the power supply system.

[0080] FCR-D is a reserve intended to suppress frequency during any disturbances. FCR-D ensures that frequency drops are limited in the event of significant frequency drops outside normal operating limits (i.e., below 49.9 Hz). This can occur, for example, if a generator unexpectedly fails. In such a situation, participants in the FCR program react to balance generation and load by increasing electricity generation or reducing demand. SVK (Svenska Kraftnaet) operates an FCR-D market, which uses third parties to leverage its technological resources to respond to these emergencies.

[0081] FCR-D up represents up-regulation, which is activated within the frequency range of 49.90 to 49.50 Hz. An increase in frequency requires a decrease in power consumption; for example, in the present embodiment where the block-based energy unit 12 provides the FCR-D functionality, the unit 12 can downclock or turn off devices to reduce power consumption, or discharge stored charge from the energy storage 34 (e.g., a battery) to the power grid to provide more power to the power supply system.

[0082] FCR-D Down stands for down-regulation, which is activated within a frequency range of, for example, 50.1 to 50.5 Hz when the required power level is 50 Hz. A decrease in frequency requires increased power consumption; for example, in this embodiment, the block-based energy unit 12 can overclock the device or charge the energy storage 34 (e.g., a battery). Also, if there is a simultaneous demand for increased heat output, the block-based energy unit 12 can consume more electricity by activating the heating circuit 32.

[0083] An example of how a block-based energy unit 12 of one embodiment of the present invention may be configured by decision logic 44a and control logic 46a to implement FCR-D down services is shown in Figure 10. This process helps stabilize the power grid when the frequency exceeds a certain threshold.

[0084] The process begins when the FCR-D down service is initiated in step 302. The block-based energy unit 12 retrieves a list of compatible FCR-D down devices installed or operably connected to the block-based energy unit 12 from the data store 36 in step 304, and then calculates a controllable power load from the compatible device list in step 306. The block-based energy unit 12 then determines whether there are external controllable resources in addition to the energy storage 34 within the block-based energy unit 12 in step 308. In some embodiments, additional external controllable resources, such as a battery or generator (not shown), may be coupled to the block-based energy unit 12. If there are external controllable resources, the block-based energy unit 12 adds the controllable power load of the external resources to the controllable amounts of the local devices (such as the energy storage 34, the data processor 22, and the heating circuit 32) in step 310, and then the block-based energy unit 12 begins monitoring the frequency of the power grid for changes outside known acceptable limits in step 312 (this information may be provided by the power generation parameter platform 14 and stored in the data store 36). If there are no external controllable resources available in step 308, the block-based energy unit 12 proceeds directly to step 312.

[0085] While monitoring the power grid, the block-based energy unit 12 queries whether the power grid frequency is above acceptable limits in step 314. It should be understood that the rate at which the block-based energy unit 12 queries the power grid may vary and is dependent on the electricity market at the time. For example, in Sweden, for FCR, the maximum query time is 200 milliseconds. If the power grid frequency is not above acceptable limits, the block-based energy unit 12 verifies in step 316 whether active measures have been implemented since the previous check. If not, the block-based energy unit 12 repeats steps 312-316. However, if step 316 determines that active measures have been implemented, the block-based energy unit 12 stops the active measures in step 318. Again, steps 312-318 are repeated in a loop, continuously checking the power grid frequency for variations outside of normal limits.

[0086] If step 314 finds that the frequency exceeds the allowable limit, then block-based energy unit 12 calculates, in step 320, the amount of power usage that needs to be increased to reduce the frequency back to within normal limits. Then, in step 322, block-based energy unit 12 determines whether the capacity of energy storage 34 (e.g., battery) alone can satisfy the request. If the capacity of energy storage 34 is sufficient, then measures are activated in step 324, such as charging the battery without interrupting the computing activity of data processor 22, thereby increasing power consumption. However, if the available capacity of energy storage 34 alone cannot satisfy the request, then energy storage 34 is still activated in step 326, and then block-based energy unit 12 increases the power consumption of the computing device (processor 22) in step 328 until the request is satisfied. This can be done by overclocking the device or by enabling a suspended device. In embodiments where external, controllable resources are also present, the block-based energy unit can instruct the external resources to increase their power consumption. For example, when an additional external battery is available, the block-based energy unit can charge the external battery.

[0087] As briefly mentioned above, a further application of embodiments of the present invention is energy trading. If the current energy demand parameter exceeds a threshold associated with the block-based energy units 12 per unit of power consumption, power capacity can be supplied back to the power grid. This can be enhanced by utilizing energy storage 34 or external batteries to charge during times of low power costs and discharge during times of peak power costs. Alternatively, power generation devices (thermal or renewable) can be utilized to supply electricity to the power grid. The energy trading process is automatically managed by load control services 44a, 46a.

[0088] As briefly mentioned above, in one embodiment, the block-based energy unit includes all of the features described above and shown in Figure 2, and further includes an external energy storage 34 in addition to the internal energy storage 34, which also communicates with the load control platform 24. As mentioned above, the external energy storage allows for increased capacity, which is advantageous in frequency regulation and energy trading applications.

[0089] In some embodiments of the present invention, the block-based energy unit 12 includes all of the features described above and shown in FIG. 2 , except that the internal energy storage 34 is external to the block-based energy unit 12. While the internal energy storage 34 allows the block-based energy unit 12 to be modular, which in itself provides many advantages, an external energy storage 34 (e.g., a battery) may also be advantageous because it allows the external energy source to use an energy storage 34 with a larger size and therefore a larger capacity. Thus, a larger amount of energy can be stored and available to the block-based energy unit 12 when needed to meet increased electrical energy demands, computing demands, or heating demands. Thus, in some embodiments, the block-based energy unit 12 is not modular.

[0090] In some specific use embodiments, the block-based energy unit 12 may not regulate the electrical energy generation supply and may focus solely on providing a transportable and controllable energy unit for providing thermal energy to a thermal energy consuming system. In this case, such specific use embodiments may comprise all of the features shown in Figure 2, except for the energy storage 34. This embodiment of the block-based energy unit 12 can provide a transportable heating means to any location, which in itself offers many advantages over known solutions.

[0091] In a further embodiment, the block-based energy unit 12 includes all of the features shown in FIG. 2 except for the heating circuit 32. In this embodiment, where the heating circuit is absent, the cold material 28 captures the heat generated by the data processor 22, thereby increasing the temperature of the cold material 28. Although there is no option to further increase the temperature of the hot fluid 32a or hot air 32b, the heat generated by the data processor 22 may be sufficient to provide energy to external utility systems in some applications. This embodiment provides a slightly simpler design for the block-based unit 12, which may be appropriate in some situations.

[0092] While the embodiments described in this disclosure are susceptible to various modifications and alternative forms, specific embodiments have been shown by way of example in the drawings and are described in detail herein. It should be understood, however, that the disclosure is not intended to be limited to the particular forms disclosed. The present disclosure is intended to cover all modifications, equivalents, and alternatives falling within the spirit and scope of the disclosure as defined by the following appended claims.

[0093] The techniques presented and claimed herein are applied in connection with objects and specific examples that have practical properties that clearly advance the art, and are not themselves abstract, intangible, or purely theoretical. Furthermore, where the claims appended at the end of this specification contain one or more elements designated as "means for [performing] ... [function]" or "steps for [performing] ... [function]," it is intended that such elements be construed under 35 U.S.C. 112(f). However, for claims containing elements designated in any other manner, it is intended that such elements not be construed under 35 U.S.C. 112(f).

Claims

1. 1. A data processing apparatus for providing energy to an energy consuming system, comprising: a transportable containerisation unit configured, in use, to couple to the energy consuming system, the transportable containerisation unit comprising: at least one electronic data processing device configured to process data in use; a cryogen stream thermally coupled to said at least one electronic data processing device and configured to capture thermal energy generated by said at least one electronic data processing device in use; a load controller for controlling said at least one electronic data processing device or said cryogenic material stream; wherein the load controller receiving current energy demand parameters that enable a required energy demand of the energy consuming system to be determined; generating and transmitting instructions causing operation of said at least one data processing device or a change in flow of said cryogenic material stream, said instructions being determined to cause a change in temperature of said cryogenic material stream to conform to said current energy demand parameters; a data processing device configured to enable outputting the cryogenic material stream to the energy consuming system, the changed temperature of the cryogenic material stream satisfying at least a portion of the required energy demand of the energy consuming system.

2. 2. The data processing apparatus of claim 1, wherein the energy demand parameter is a required temperature of the cryogenic material stream, and the load controller is configured to determine the required energy demand using a difference between the required temperature and a current temperature of the cryogenic material stream.

3. 3. A data processing apparatus according to claim 1 or 2, wherein the load controller is configured to vary the temperature of the cryogen stream by increasing or decreasing a clock speed of the at least one data processing device.

4. 4. Data processing apparatus according to any one of claims 1 to 3, wherein the load controller is configured to vary the temperature of the cryogenic material stream by pausing or resuming operation of the at least one data processing device.

5. 5. A data processing apparatus according to any one of claims 1 to 4, further comprising a heating circuit thermally coupled to the cryogenic material stream in use and configured to, under the control of the load controller, increase the temperature of the cryogenic material stream independently of the operation of the at least one electronic data processing device.

6. 6. The data processing apparatus of claim 5, wherein the load controller is configured to vary the temperature of the cryogenic material stream by activating or deactivating the heating circuit to control the amount of data processing performed by the at least one electronic data processing device.

7. 7. A data processing apparatus according to any one of claims 1 to 6, wherein the transportable containerised unit comprises a plurality of modular units, each modular unit comprising an instance of the at least one electronic data processing device and a respective thermally coupled cryogenic material stream.

8. 8. A data processing apparatus as claimed in claim 7, wherein said load controller comprises a plurality of load sub-controllers, each load sub-controller being assigned to one of said plurality of modular units to enable independent operation of each modular unit.

9. 9. A data processing device as claimed in claim 7 or 8, wherein the power consumption of the data processing device can be varied by activating or deactivating one or more of the plurality of modular units by changing the clock speed of the at least one data processing device, or by pausing or resuming operation of the at least one data processing device.

10. A data processing apparatus according to any preceding claim, wherein said at least one data processing device comprises a crypto mining server.

11. The transportable containerized unit, in use, is electrically coupled to an electrical energy generation system, and the load controller is receiving current electrical energy generation level parameters for the energy generation system to enable determining a required energy consumption of the containerized unit; A data processing device according to any one of claims 1 to 10, configured to generate and transmit instructions that cause a change in the operation of the transportable containerised unit, the instructions being determined to change the energy consumption of the transportable containerised unit to comply with the current electrical energy generation level parameters.

12. 12. The data processing apparatus of claim 11, wherein the load controller is configured to vary the amount of power consumption of the at least one data processing device to conform to the current electrical energy generation level parameter by varying an operating speed of the at least one data processing device.

13. 13. The data processing apparatus of claim 11 or 12, wherein the transportable containerized unit is operably coupled to an external controllable energy-consuming resource, and the load controller is configured to vary the power consumption of the containerized unit by manipulating the external controllable energy-consuming resource.

14. The energy regulator of claim 13 , wherein the external controllable energy-consuming resource is a load bank for consuming excess energy, and the load controller is configured to provide electrical energy not required by the electrical energy generation system to the load bank.

15. 15. Data processing apparatus according to any one of claims 11 to 14, further comprising an energy storage unit provided in the containerisation unit and configured to store electrical energy not currently required by the at least one data processing device or the cryogenic material stream.

16. 16. A data processing apparatus according to claim 15, wherein the load controller is configured to vary the amount of electrical energy stored in the electrical energy storage unit to conform to the current electrical energy generation level parameter.

17. 17. The data processing apparatus of claim 11, wherein the containerization unit is configured to be coupled to an external electric energy generator, and the load controller is configured to operate the external energy generator and provide electric energy generated by the external generator to comply with the current electric energy generation level parameters.

18. A data processing apparatus according to any preceding claim, wherein the transportable containerised unit comprises a standard size shipping container.

19. 20. The data processing device of claim 18, wherein the standard size shipping container is ruggedized.

20. 1. A method of providing energy to an energy consuming system, comprising: coupling a transportable containerized unit to the energy consuming system; processing data using at least one electronic data processing device provided on said transportable containerization unit; capturing thermal energy generated by the at least one electronic data processing device using a cryogenic material stream thermally coupled to the at least one electronic data processing device; using a load controller to control the at least one electronic data processing device or the cryogenic material stream; and wherein the controlling step comprises: receiving current energy demand parameters that enable a required energy demand of the energy consuming system to be determined; generating and transmitting instructions to cause operation of the at least one data processing device or a change in flow of the cryogenic material stream, the instructions being determined to cause a change in temperature of the cryogenic material stream to conform to the current energy demand parameters; and enabling output of the cryogenic material stream to the energy-consuming system, wherein the altered temperature of the cryogenic material stream satisfies at least a portion of the required energy demand of the energy-consuming system. A method comprising:

21. 1. An energy regulator for providing electrical energy to or consuming electrical energy from an electrical energy generation system and for providing thermal energy to a heat consuming system coupled to the energy regulator in use, the energy regulator comprising: at least one electronic data processing device configured to process data in use; a cryogen stream thermally coupled to said at least one electronic data processing device and configured to capture thermal energy generated by said at least one electronic data processing device in use; an energy storage configured to store energy; a load controller for controlling the at least one electronic data processing device, the energy storage unit, or the cryogenic material stream; and wherein the load controller receiving electrical energy adjustment parameters that enable determining a required electrical energy level of the electrical energy generating system; receiving thermal energy demand parameters that enable a required thermal energy demand of the thermal energy consuming system to be determined; generating and transmitting instructions to cause a change in the operation of the at least one data processing device, the energy storage unit, or the cryogenic material stream, the instructions being determined to cause a change in the temperature of the cryogenic material stream to meet the required thermal energy demand and / or to cause a change in the electrical energy consumed by or provided to the electrical energy generation system to adjust the electrical energy generation system to meet the required electrical energy level; an energy regulator configured to enable output of the cryogenic material stream to the thermal energy consuming system to meet at least a portion of the required thermal energy demand, and / or to enable input or output of electrical energy from or to the electrical energy generating system to meet the required electrical energy level.

22. 22. The energy regulator of claim 21, wherein the energy storage comprises an electric battery, and the load controller is configured to provide electric energy from the battery to the power generation system to regulate the power generation system.

23. The energy regulator of claim 22 , wherein the load controller is configured to store excess electrical energy received from the electrical energy generation system in the battery.

24. 24. The energy regulator of claim 21, wherein the energy storage unit comprises an electric energy generator, and the load controller is configured to provide electric energy from the electric energy generator to the electric energy generation system to regulate the electric energy generation system, and / or to provide electric energy to generate thermal energy and provide the thermal energy to the thermal energy consumption system.

25. 25. The energy regulator of claim 21, wherein the thermal energy demand parameter is a required temperature of the cryogenic material stream, and the load controller is configured to determine the required thermal energy demand using a difference between the required temperature and a current temperature of the cryogenic material stream.

26. 26. The energy regulator of claim 21, wherein the load controller is configured to vary the temperature of the cryogenic material stream by increasing or decreasing a clock speed of the at least one data processing device.

27. The energy regulator of any one of claims 21 to 26, wherein the load controller is configured to vary the temperature of the cryogenic material stream by pausing or resuming operation of the at least one data processing device.

28. 28. The energy regulator of any one of claims 21 to 27, further comprising a heating circuit thermally coupled to the cryogenic material stream in use and configured to increase the temperature of the cryogenic material stream under control of the load controller and independently of the operation of the at least one electronic data processing device.

29. 29. The energy regulator of claim 28, wherein the load controller is configured to vary the temperature of the cryogenic material stream by activating or deactivating the heating circuit and controlling the amount of data processing performed by the at least one electronic data processing device.

30. 30. The energy regulator of claim 21, comprising a plurality of modular units, each modular unit comprising an instance of the at least one electronic data processing device and the respective thermally coupled cryogenic material stream.

31. 31. The energy regulator of claim 30, wherein the load controller comprises a plurality of load sub-controllers, each load sub-controller being assigned to one of the plurality of modular units to enable independent operation of each modular unit.

32. 32. The energy regulator of claim 30 or 31, wherein the power consumption of the data processing device can be changed by activating or deactivating one or more of the plurality of modular units by changing the clock speed of the at least one data processing device, or by pausing or resuming operation of the at least one data processing device.

33. The energy regulator of any one of claims 21 to 32, wherein the at least one data processing device comprises a crypto mining server.

34. 31. The energy regulator of claim 21, wherein the load controller is configured to vary the amount of power consumption of the at least one data processing device to meet a required electrical energy level by varying an operating speed of the at least one data processing device.

35. 35. The energy regulator of any one of claims 21 to 34, wherein the energy regulator is operably coupled to an external controllable energy-consuming resource, and the load controller is configured to vary the power consumption of the containerized unit by manipulating the external controllable energy-consuming resource.

36. 36. The energy regulator of claim 35, wherein the external controllable energy-consuming resource is a load bank for consuming excess energy, and the load controller is configured to provide electrical energy not required by the electrical energy generation system to the load bank.

37. 1. A method of providing or consuming electrical energy to an electrical energy generating system and providing thermal energy to a thermal energy consuming system using an energy regulator, comprising: coupling the energy regulator to the electrical energy generating system and the thermal energy consuming system; processing the data using at least one electronic data processing device of the energy regulator; capturing thermal energy generated by the at least one electronic data processing device using a cryogenic material stream thermally coupled to the at least one electronic data processing device; providing an energy storage device configured to store energy; controlling the at least one electronic data processing device, the energy storage unit, or the cryogenic material stream; and wherein the controlling step comprises: receiving current electrical energy regulation parameters that enable determining a required electrical energy level of the electrical energy generation system; receiving current thermal energy demand parameters that enable a required thermal energy demand of the thermal energy consuming system to be determined; generating and transmitting instructions to cause a change in the operation of the at least one data processing device, the energy storage unit, or the cryogenic material stream, the instructions being determined to cause a change in the temperature of the cryogenic material stream to meet the required thermal energy demand and / or to cause a change in the electrical energy consumed by or provided to the electrical energy generation system to adjust the electrical energy generation system to meet the required electrical energy level; enabling output of the cryogenic material stream to the thermal energy consuming system to meet at least a portion of the required thermal energy demand; and / or enabling the input or output of electrical energy from or to the electrical energy generation system to meet the required electrical energy level. A method comprising:

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