Cost-effective operation of other subsystems of total system and facilities of metal industry

Abstract

The overall system comprises an electrical energy store (6) and other subsystems (1, 4, etc.), including a facility (1) of the metal industry. The installation (1) and the energy store (6) are connected to each other and to the power supply network (2) for transmitting electrical energy. Before the start of the first time range (T1), the control device (9) knows an initial state (Z1, Z4, etc.) of the subsystem (1, 4, etc.) that is expected at the start of the first time range (T1). Furthermore, before the start of the first time range (T1), the control device (9) also knows, for the first time range (T1), a planned first time curve (E1) for purchasing electrical energy from the supply network (2) and a planned first operating mode (B1, B4, etc.) of the other subsystems (1, 4, etc. On the basis of the initial state (Z6) of the energy store (6), the planned first time curve (E1) and the planned first operating mode (B1, B4, etc.), the control device (9) determines a final state (Z6 ') of the energy store (6), which is expected for the end of the first time range (T1). The control device (9) determines a second time curve (E2) for purchasing electrical energy for a second time range (T2), starting from the expected final state (Z6 ') and a second operating mode (B1', B4 ', etc.) of the other subsystems (1, 4, etc.), known by the control device, planned for the second time range (T2) directly following the first time range (T1), the second time curves are Pareto optimal in each case with respect to a plurality of cost functions (K1, K2) dependent on the respective second time curve (E2). Before the first time range (T1) starts, the control device (9) defines one of the second time curves (E2) as a second time curve (E2) for purchasing electrical energy. The control device (9), as long as possible, operates the other subsystems (1, 4 etc.) and the electrical energy store (6) during the time range (T1, T2) on the basis of the planned first and second operating modes (B1, B4 etc., B1 ', B4' etc.) in such a way that electrical energy is purchased from the supply network (2) during the time range (T1, T2) on the basis of the planned first time profile and the defined second time profile (E1, E2).

Description

Technical Field

[0001] This invention relates to a method for operating a complete system. -The overall system includes an energy storage system as one subsystem and other subsystems. Other subsystems include facilities for the metal industry. -In this context, the facilities and energy storage devices in the metal industry are directly or indirectly interconnected and connected to the power supply network for the purpose of transmitting electrical energy. - Wherein, prior to the start of the first time range, the control device of the overall control system knows the expected initial state of the subsystem at the start of the first time range.

[0002] The present invention also relates to a control program for a control device of a general system. -The overall system includes an energy storage system as one subsystem and other subsystems. Other subsystems include facilities for the metal industry. -In this context, the facilities and energy storage devices in the metal industry are directly or indirectly interconnected and connected to the power supply network for the purpose of transmitting electrical energy. -The control program includes machine code that can be processed by the control device. - In this process, the control unit's processing of machine code enables it to control the overall system according to this operating method.

[0003] The present invention also relates to a control device for a total system. -The overall system includes an energy storage system as one subsystem and other subsystems. Other subsystems include facilities for the metal industry. -In this context, the facilities and energy storage devices in the metal industry are directly or indirectly interconnected and connected to the power supply network for the purpose of transmitting electrical energy. -The control device is programmed using this control program so that it controls the overall system according to this operating method when processing the machine code of the control program.

[0004] The present invention also relates to an overall system. -The overall system includes an energy storage system as one subsystem and other subsystems. Other subsystems include facilities for the metal industry. -In this context, the facilities and energy storage devices in the metal industry are directly or indirectly interconnected and connected to the power supply network for the purpose of transmitting electrical energy. -The overall system includes such a control device, which controls the overall system according to such an operating method when processing the machine code of such a control program. Background Technology

[0005] For example, the topic is known to be mentioned in the literature “Green Energy Supply for the Steel Industry” (Steel and Iron, August 2022, pp. 22-24).

[0006] Industrial processes equipped with energy storage are known from KR 2019 0136300 A. Industrial processes can be technological processes of varying complexity, comprising multiple interdependent and cooperating subprocesses. Industrial processes have different types of loads: loads that must be continuously supplied with energy, loads that can be shut off, and loads in which energy consumption can be adjusted. The actual energy consumption of each component of the industrial facility is determined. The operation of the industrial facility and the energy storage is adapted to each other to minimize costs.

[0007] A device comprising a household appliance, an energy generator, and an energy storage device is known from US 10354297 B2. The operation of the energy storage device can be determined taking into account the planned energy consumption of the appliance. Weather data can also be used. Price information for obtaining electrical energy from and feeding electrical energy into the supply network can also be considered.

[0008] It is known from TW 201 235 124 A that, given the known operating mode of a metal industrial facility, the energy consumption of the metal industrial facility (specifically a rolling mill) can be predicted with good accuracy.

[0009] The operating method for a total system is known from the technical literature “Two-Stage Discrete and Continuous Multi-Objective Load Optimization: An Application Method for Industrial User Request Response” (authors Ahmed Abdulaal et al., *Applied Energy*, Issue 206 (2017), pp. 206-221), where the total system includes an energy storage device as a subsystem and other subsystems. Subsystems are directly or indirectly connected to each other and to an electricity supply network for the transmission of electrical energy. Other subsystems may also include facilities in the metal industry. Before the start of the first time period, the initial state of the subsystems is known by the control device controlling the total system, wherein this initial state is anticipated for the subsystems at the start of the first time period. Before the start of the first time period, the control device also knows the first time curve for the planned purchase of electrical energy from the supply network for the first time period and the first operating mode planned for the other subsystems. Summary of the Invention

[0010] In the past, the costs (and energy costs) incurred in determining the operation of metal industrial facilities were considered. However, this consideration only took into account the total demand for electricity and the resulting cost of that electricity. With the transition to renewable energy, the availability of electricity (including the fluctuations in its cost over time) must be given greater weight, as the future availability and cost of electricity will fluctuate much more than in the past.

[0011] Within the scope of this invention, the key to the effective use of electrical energy storage lies, on the one hand, in the (expected) future energy consumption of the facilities in the metal industry, and on the other hand, in the (expected) future price of electrical energy obtained from the supply network.

[0012] The aforementioned professional literature describes the control and operation of facilities and energy storage in the metal industry using intelligent energy management systems; however, it does not provide more detailed plans for the implementation of intelligent energy management systems.

[0013] The purpose of this invention is to provide a feasible solution for achieving cost-effective operation of a total system, which includes facilities in the metal industry and electrical energy storage as subsystems.

[0014] This objective is achieved by an operating method having the features of claim 1. An advantageous design of this operating method is the subject of claims 2 to 10.

[0015] According to the present invention, the above-mentioned type of operation method is designed in the following manner: - Prior to the start of the first time period, for that first time period, the control device knows the first time curve of the planned purchase of electrical energy from the supply network and the first operating mode of the planned other subsystems. Based on the initial state of the energy storage device, the first time curve of the energy purchase plan, and the first operating mode of the other subsystems, the control device determines the expected final state of the energy storage device at the end of the first time period. -Starting from the expected final state of the energy storage device and the second operating mode of other subsystems for the second time range, which is known to the control device and planned for the second time range that directly follows the first time range, the control device determines the second time curve for which energy can be purchased. - The control device determines a second time curve for purchasing electrical energy, such that each of the second time curves is Pareto optimal in relation to several corresponding cost functions depending on the respective second time curve for purchasing electrical energy. The correlation between the cost function and the corresponding second-time curve for purchasing electricity differs for different cost functions. -The control device determines one of the second time curves for which electrical energy can be purchased within the second time range as the second time curve for purchasing electrical energy. -The control device executes the limitation of the second time curve for purchasing electrical energy before the first time curve begins. Where feasible, the control device operates other subsystems based on the planned first and second operating modes during the first and second time ranges, and the control device operates the energy storage device to purchase energy from the supply network during the first and second time ranges according to the planned first time curve and the defined second time curve for purchasing energy.

[0016] The term "subsystem," when used without further elaboration, includes all upstream and downstream subsystems, including energy storage and other subsystems. The term "other subsystems," however, includes only additional subsystems, excluding energy storage.

[0017] The facilities of the metal industry are typically those used in the production or direct processing of metals, such as electric arc furnaces, converters, continuous casting facilities, and / or rolling mills.

[0018] The state of a subsystem can be defined as needed. In particular, the state can include a "normal" operating state ("how the subsystem is currently operating"), operating constraints ("what is feasible and what is no longer feasible"), and a wear and tear state.

[0019] Specifically, for an electrical energy storage device (EESD), the corresponding sub-states include, in particular, the degree of charge (percentage and / or absolute value) of the EESD and the temperature of the EESD's storage cells. Furthermore, the corresponding sub-states may also include the state of wear and tear of the EESD or its components. In principle, the corresponding sub-states may also include the maximum feasible operating parameters and the currently maximum feasible operating parameters, such as charging current and discharging current. This also applies to the initial state, the final state, and states before the first time range, during the first time range and the second time range, and after the second time range.

[0020] It is feasible to: before the start of the first time period, define a first time curve for the planned purchase of electrical energy from the supply network for the first time period, and then define a first operating mode for the planned purchase of electrical energy from various other subsystems based on this curve. Alternatively, the reverse process is feasible. It is also feasible to: first know the planned first operating modes of the other subsystems of the control device (e.g., because the first operating mode is preset for the control device, or determined by the control device), and then determine the first time curve for purchasing electrical energy based on the planned first operating modes. However, in any case, the planned operating mode of the energy storage device is derived from the defined first time curve for purchasing electrical energy and the planned first operating modes of the other subsystems. The energy storage device can be a slave to its "master," where the master represents the defined first time curve for purchasing electrical energy from the power supply network and the other subsystems.

[0021] The first and second time ranges typically span several hours. For example, the first time range could be 12 hours. The second time range could be, for example, 24 hours. The values ​​mentioned are typical within the European Union. These values ​​correspond to the typical fact that, up to 12:00 on a particular day, bids for contracts covering the entire following day (i.e., from 0:00 to 24:00 on the following day) must be posted at the energy exchange. However, the invention is not limited to the mentioned values ​​for these two time ranges.

[0022] In the simplest case, the control device applies only two cost functions to determine the corresponding feasible second time curve for purchasing electrical energy. However, it is also readily feasible for the control device to perform Pareto optimization on more than two cost functions. The term "Pareto optimality" itself has a fixed definition; see, for example, the entry for "Pareto optimality" on the German Wikipedia page accessed on June 27, 2023. The term "Pareto optimization" essentially means changing the input variables with the aim of minimizing multiple cost functions. By changing the input variables of the cost functions, Pareto optimality is achieved only when one of the cost functions takes a larger value, thus further minimizing another cost function.

[0023] This invention is based on the fact that large quantities of electrical energy are frequently purchased on the spot market. Therefore (in the EU and, as is currently the case, although this will certainly change in the future and in other parts of the world), the price of electrical energy is determined in an auction on a specific day until 12:00 noon, with the energy being provided or received on subsequent days. Prices apply to specific times on subsequent days. For example, electrical energy has different prices between 8:00 and 9:00 compared to, for example, between 12:00 and 13:00.

[0024] However, the negotiated price applies only when the agreed-upon amount of electricity is actually received. Furthermore, at least within the EU, it is usually additionally agreed that the electricity agreed upon for the entire corresponding hour must be received in the same portion within the four quarter-hour periods of that corresponding hour. If this is not the case, i.e., if the actual purchased electricity during the mentioned quarter-hour period differs from the agreed-upon purchased electricity, then a different price applies. However, this different price is not only not agreed upon beforehand, but is also absolutely not defined. This different price specifically incorporates whether the operator of the supply network needs and is required to obtain the additional electricity at what cost, or whether the operator of the supply network can and is required to otherwise utilize the purchased but not yet obtained electricity at what cost. Therefore, the aforementioned different price can deviate significantly from the originally agreed-upon price.

[0025] This creates significant uncertainty for the overall system operator. It would be significantly more reliable to guarantee that, in subsequent operation of the overall system, the previously purchased electrical energy is actually obtained from the supply network, but not more or less. To reduce uncertainty, energy storage devices are used in both the prior art and this invention. Such energy storage devices can compensate for fluctuations, ensuring that the previously ordered electrical energy is actually obtained from the supply network. This is precisely ensured in an excellent manner and method by the processing method according to the invention. Here, due to Pareto optimization, not only individual optima are determined, but also the possible optima of the total amount (or at least one representative portion of the total amount). This creates the possibility of selecting the preferred optima from the possible optima of that amount. For example, an operator can perform this selection based on their experience.

[0026] In a preferred design, the cost function includes a first cost function, the value of which depends on the operating cost of the energy storage device during a second time period, without considering the cost of purchasing electrical energy. In this case, the first cost function reflects the operating price of the energy storage device itself, i.e., the cost obtained from depreciation or amortization due to wear and tear, maintenance, etc.

[0027] It is feasible for the control device to provide the operator of the overall system with a feasible second time curve for selecting the purchased electrical energy, and to receive from the operator a selection of at least one of the feasible second time curves for the purchase of electrical energy. In this case, the operator's selection determines the limitation of the second time curve for purchasing electrical energy. However, alternatively, in the case of this cost function, it is feasible and often even possible to propose that, in order to limit the second time curve for purchasing electrical energy, the control device...

[0028] - Multiple requests for the purchase of a corresponding amount of electrical energy are submitted to the energy exchange via the Internet for each of the multiple time periods within a second time range, wherein corresponding conditions are assigned to the requests. - Check: Whether the energy exchange confirms requests to purchase electricity if the corresponding allocation conditions are met, and, if necessary, which of the requests to purchase electricity is confirmed, and -Then, considering the request, a second timeline for purchasing electricity is determined, in which the energy exchange confirms the required electricity purchase if the conditions for the corresponding allocation are met.

[0029] These requests can be in particular at prices that the overall system operator is willing to pay. Therefore, for example, the operator can select from multiple Pareto-optimal second time curves for purchasing electricity, each determined by the control unit, and submit corresponding bids on the energy exchange for the respective curve. The final second time curve for purchasing electricity in this case is one whose bid is just met. Therefore, the final constraint is based on the principle: "If electricity X is obtained at price Y, then option A is chosen; if electricity X is obtained at price Z, then option B is chosen."

[0030] Alternatively, the cost function may include a first cost function, the value of which depends on the cost of operating the energy storage device during the second time period and the cost of purchasing energy. In this case, the corresponding second time period must be known or based on a time curve that estimates the expected price for purchasing energy. The price can also be additionally related to the amount of energy acquired during a specific time unit, if necessary. Furthermore, in this case, the control device typically provides the operator of the overall system with a defined feasible second time curve for purchasing energy, and the operator receives a choice of at least one of the feasible second time curves provided for purchasing energy. Here, the operator typically selects only the single Pareto-optimal second time curve.

[0031] In a preferred design, the cost function includes a second cost function, the value of which depends on the time curve of the load state of the energy storage device during a second time period. The second cost function preferably obtains, in principle, the possible reserves of the energy storage device during the second time period. Where necessary, the upper limit reserve (i.e., the energy that the energy storage device can still absorb when needed) and the lower limit reserve (i.e., the energy that the energy storage device can output when needed) can be determined independently of each other, or combined into a combined value with independent weights.

[0032] Preferably, the feasible second time curve for purchasing electrical energy satisfies uniform auxiliary conditions. This ensures that the found solution, i.e., the feasible second time curve, is permissible.

[0033] Ancillary conditions may include, for example, the minimum required load state, the maximum required load state, and / or the maximum charging current of the energy storage device. Ancillary conditions may also include a specific load state that the energy storage device should have at the end of the second time period, or a specific range within a load state that is permissible in principle.

[0034] Preferably, the control device operates in such a manner as to determine the corresponding feasible second time curve for purchasing electrical energy, i.e., the control device...

[0035] - Set a second time curve for purchasing electricity within the second time range, and determine the value and gradient of the cost function for the set second time curve. - Determine based on the overall gradient: whether the established second time curve can be Pareto optimized. - If the established second time curve cannot be Pareto optimized, adapt the established second time curve to a usable second time curve, and - If the established second time curve can be Pareto optimal, use the gradient of the cost function to determine the descent direction, use the descent direction to change the established second time curve, and repeat the determination of the value of the cost function and the gradient of the cost function and this change until the established second time curve is Pareto optimal, and then adapt the established second time curve to a usable second time curve.

[0036] In the simplest case, with only two cost functions, the descent direction can be determined, for example, by using the angle bisector of the two gradients of the cost functions as the ascent direction. If the two gradients point in opposite directions, then the second time curve can be Pareto optimal.

[0037] Regarding the examination of how to achieve Pareto optimization in the case of more than two cost functions and the corresponding procedures for performing such optimization, the professional literature "Stochastic Methods for Solving Unconstrained Vector Optimization Problems" (by S. Schäffler, R. Schulz and K. Weinzierl, published in Optimization Theory & Applications, 114(1), pp. 209-222, January 2002) has described this.

[0038] Specifically, the following approach can typically be used for the descent direction. The descent direction sought is a weighted sum of the gradients of the cost function. The weights are constrained by the following: the weights are non-negative, i.e., greater than or equal to 0, and their sum equals 1. The specific value of the weights is the value that minimizes the square of the L2 norm of the sum of gradients strengthened by the weights. If G represents the descent direction, Gi represents the gradient of the cost function, and wi represents the weights, then the following must hold:

[0039] Among them, the conditions wi≥0 and ∑wi=1 are satisfied.

[0040] A readily feasible approach is to determine the solution using known numerical methods. Consequently, it becomes possible to identify paths leading to at least a locally Pareto optimal solution. This article also outlines pathways to achieving global Pareto optimality.

[0041] Interferences repeatedly occur during the operation of other subsystems, both within the first and second time periods. This necessitates deviations from the planned second operating mode for these subsystems. Therefore, the control device checks during the second time period whether deviations are required. If deviations are not required, the control device operates the other subsystems according to the planned second operating mode and activates the energy storage device to purchase energy from the supply network during the second time period based on the defined second time curve for energy purchase. In cases where deviations are required, various processing methods are feasible.

[0042] In rare cases, such changes in operation may affect electricity demand. In such cases, there is no need to adapt to purchasing electricity from the supply network. The same applies to adapting the operation of energy storage devices. However, such deviations typically have consequences for electricity demand. To compensate for these changes in electricity demand, adaptation to the operation of energy storage devices is provided on one hand, and adaptation to purchasing electricity from the supply network is provided on the other.

[0043] In the simplest case, the control device (obviously within feasible limits) always adapts to the operating mode of the energy storage device. However, more preferably, when a deviated operating mode is required, the control device operates other subsystems according to the deviated operating mode and determines the extent to which this changes the energy demand of other subsystems, defined by a second time curve for energy purchase. Based on this, the control device preferably checks whether the defined second time curve for energy purchase can be maintained by adapting the operation of the energy storage device. If the defined second time curve for energy purchase cannot be maintained, the control device changes the energy purchase, with or without adapting the operation of the energy storage device, to achieve the deviated operating mode of the other subsystems. If the defined second time curve for energy purchase can be maintained, the control device preferably decides whether and to what extent it should change the energy purchase and operate the energy storage device accordingly.

[0044] Therefore, the control device decides, where possible, whether to immediately use the energy reserves in the energy storage device or to reserve them for later use. For example, if, despite a disturbance (requiring more energy due to the disturbance), energy is available at a reasonable or at least expected cost at the time of the disturbance, but is subsequently expected to be significantly more expensive, then reserving for later use would be meaningful. Other situations can also be considered. For example, the opposite approach would be meaningful if lower energy purchases were incurred due to changes in the operation of other subsystems.

[0045] Preferably, the control device makes its decisions based on: the type and extent of changes in the power demand of other subsystems, the current load status of the energy storage, the progress in the second time period, and / or the estimated price of purchasing power during the remainder of the second time period. In practice, this results in cost optimization without compromising the technical situation.

[0046] The operating method according to the invention is typically re-executed iteratively. Here, the second time range of each iteration is at least partially a component of the first time range of the corresponding subsequent iteration. In the simplest case, the same cost function is always used for different iterations. However, preferably, at least one cost function is determined separately for different iterations.

[0047] The determination of the corresponding cost function can be made in particular based on the expected price of electricity and / or the planned operation of the facility during the second time period of the corresponding iteration.

[0048] This objective is also achieved by a control program having the features of claim 11. According to the invention, the processing of machine code by the control device causes the control device to control the overall system according to the operating method of the invention.

[0049] Furthermore, this objective is also achieved by a control device having the features of claim 12. According to the invention, the control device is programmed using a control program according to the invention, such that the control device controls the overall system according to the operating method according to the invention when processing the machine code of the control program.

[0050] Furthermore, this objective is also achieved by a total system having the features of claim 13. According to the invention, the control device is designed as a control device according to the invention, which controls the total system according to the operating method according to the invention when processing the machine code of the control program. Attached Figure Description

[0051] The above-described features, characteristics, and advantages of the present invention, as well as its implementation methods, will become more apparent from the following description of the embodiments, which are explained in more detail in conjunction with the accompanying drawings. The drawings show: Figure 1 Show the overall system, Figure 2 The flowchart is shown. Figure 3 Showing the timeline, Figure 4 The flowchart is shown. Figure 5 Another flowchart is shown. Figure 6 Another flowchart is shown. Figure 7 Another flowchart is shown. Figure 8 Two cost functions are shown. Figure 9 Two cost functions are shown. Figure 10 Show the flowchart, and Figure 11 The communication structure is shown. Detailed Implementation

[0052] according to Figure 1 The overall system includes a metal industry facility 1. Facility 1 can have multiple components. Examples of such facility 1 are components for producing iron (e.g., direct reduction facilities), electric arc furnaces, converters, and ladle facilities. Another possible facility 1 is a hot rolling production line.

[0053] Facility 1 consumes electrical energy during its operation. Facility 1 is able to obtain electrical energy from electrical supply network 2, which is connected directly (not shown) or indirectly (e.g., via converter 3). Supply network 2 is typically a three-phase power grid, and therefore a multi-phase supply network. Three-phase power grids typically operate at medium voltage in the range of 20kV to 30kV or high voltage of 110kV.

[0054] The overall system typically includes an electrolysis facility 4 as another subsystem. The invention will be explained below in conjunction with this design. However, the electrolysis facility 4 is not absolutely necessary.

[0055] Electrolysis facility 4 also consumes electrical energy during its operation. Therefore, electrolysis facility 4 is also connected to supply network 2. Electrolysis facility 4 requires DC voltage for its operation. Therefore, a rectifier 5 is usually arranged upstream of electrolysis facility 4, so that there is only an indirect connection with supply network 2.

[0056] In some cases, facility 1 requires hydrogen for its operation. In such cases, facility 1 and electrolysis facility 4, according to... Figure 1The diagrams in the diagrams are connected directly or indirectly to transfer hydrogen. Figure 1 Possible pumps, valves, etc. are not shown.

[0057] The overall system also includes an energy storage device 6 as a subsystem. The energy storage device 6 is directly or indirectly connected to the supply network 2 to receive electrical energy from and, where feasible, to output electrical energy to the supply network 2. Furthermore, the energy storage device 6 is also connected to facility 1 and electrolysis facility 4 to output electrical energy. If the energy storage device 6 receives electrical energy, the electrical energy is always obtained from the supply network 2. If electrical energy is output from the energy storage device 6, the electrical energy is primarily used to meet the needs of facility 1 and electrolysis facility 4, and only secondarily used to feed power into the supply network 2. Therefore, as a result, depending on whether the electrical energy indicated by the energy storage device 6 is greater or less than the electrical energy consumed by facility 1 and electrolysis facility 4, electrical energy can be temporarily fed into or obtained from the supply network 2.

[0058] The precise manner in which facility 1, electrolysis facility 4, and energy storage facility 6 are electrically connected to each other and to supply network 2 is secondary. Specifically, rectifier 5, inverters, and other converters 3 can be assigned to the respective subsystems 1, 4, and 6 as needed. However, it must be ensured that electrical energy can be transferred from energy storage facility 6 to facility 1 and electrolysis facility 4 without bypassing supply network 2.

[0059] The aforementioned subsystems 1, 4, and 6 represent a small-scale configuration of the overall system, with the metal industry facility 1 and the electrical energy storage device 6 forming a minimal configuration. However, according to... Figure 1 The overall system can also include additional subsystems 7 and 8. Upon request, only one or both of subsystems 7 and 8 may exist.

[0060] For example, the overall system can include a hydrogen storage device 7. The hydrogen storage device 7 can be designed as a storage device in the narrow sense, i.e., a dedicated hydrogen storage device. However, the pipeline network through which hydrogen is transported also has a certain storage capacity and can be used as the hydrogen storage device 7. If the hydrogen storage device 7 is present, it is directly or indirectly connected to the electrolysis facility 4 to receive hydrogen, and directly or indirectly connected to facility 1 to output hydrogen. Due to the hydrogen storage device 7, the operation of facility 1 and electrolysis facility 4 can be designed with greater flexibility.

[0061] Provided that hydrogen storage 7 exists, it is feasible for hydrogen produced by electrolysis facility 4 to be continuously supplied to hydrogen storage 7, and for hydrogen required by facility 1 when necessary to be continuously supplied by hydrogen storage 7, so that hydrogen storage 7 can be used as a transfer station for hydrogen. However, direct connection between facility 1 and electrolysis facility 4 is also feasible.

[0062] Alternatively or additionally, the overall system may include a power generation unit 8, such as a wind power facility or a photovoltaic facility. In this case, the power generation unit 8 is directly or indirectly connected to other subsystems 1, 4, 6, 7 that receive or output electrical energy, as well as to the power supply network 2, to transmit electrical energy. The converters typically required for the power generation unit 8 can be considered as part of the power generation unit 8. The converters in... Figure 1 Not shown in the diagram. Preferably, the power generation device 8 can transmit electrical energy to subsystems 1, 4, 6, and 7 without bypassing the supply network 2.

[0063] The following distinction is made between the energy storage device 6 and all other subsystems 1, 4, and, if necessary, subsystems 7, 8. "Other subsystems" excludes the energy storage device 6 and includes only all other subsystems 1, 4, and, if necessary, subsystems 7, 8. However, if the term "subsystem" is used without "other," it refers to all subsystems 1, 4, 6, and, if necessary, subsystems 7, 8, including the energy storage device 6.

[0064] The overall system also includes a control unit 9. The control unit 9 is programmed using a control program 10. The control program 10 includes machine code 11, which can be processed by the control unit 9. Because it is programmed using the control program 10, the control unit 9 processes the machine code 11. The processing of the machine code 11 by the control unit 9 causes the control unit 9 to control the overall system according to an operating method, which is described below. Figure 2 A more detailed explanation is provided below. However, before explaining the operating method according to the invention, it should be noted that although control device 9 is hereinafter interpreted as a unified control device for the common control of subsystems 1, 4, and 6 of the overall system, and subsystems 7 and 8 if necessary, control device 9 can also have its own sub-control devices to control subsystems 1, 4, and 6, and subsystems 7 and 8 if necessary. In this case, corresponding information exchange and coordination or cooperation must be performed between the sub-control devices. Furthermore, it should be noted that the following assumes the presence of electrolysis facility 4, hydrogen storage device 7, and power generation device 8. However, if subsystems 4, 7, and / or 8 are not present, or if additional subsystems not mentioned herein exist if necessary, the handling principle remains the same.

[0065] according to Figure 2 In step S1, the initial state Z of the overall system is known by the control device 9. The initial state Z includes corresponding substates Z1, Z4, Z6, Z7, and Z8 for each of subsystems 1, 4, 6, 7, and 8. The numbering of the corresponding substates Z1, Z4, Z6, Z7, and Z8 is consistent with the reference numerals of the corresponding subsystems 1, 4, 6, 7, and 8.

[0066] For example, substate Z1 (assuming the existence of the corresponding component of facility 1) can contain the following variables: - Production progress of iron production facilities - Production progress of electric arc furnace -The progress status of the continuous casting machine - Temperature of the furnace upstream of the rolling mill - The wear condition of the work rolls on the rolling mill stand. -Is the mill stand currently performing a rolling pass?

[0067] Sub-state Z1 can also include which materials in facility 1 are currently in which state. For example, (assuming that the corresponding material exists in the corresponding component of facility 1) sub-state Z1 can include the following variables: - The quantity and condition of the batch in the electric arc furnace or crucible. -The rolled material has been in the furnace for the duration of time. - The temperature of the rolled material.

[0068] For example, sub-state Z4 can include the temperature and chemical composition of the electrolyte in electrolysis facility 4 and the wear state of electrolysis facility 4.

[0069] Sub-state Z6 includes at least the load state of the energy storage device 6, i.e., the degree of charging of the energy storage device 6. Sub-state Z6 may also include other variables, such as the temperature of the energy storage device 6 or the maximum possible or permissible charging and discharging current. In addition, sub-state Z6 may include the loss state of the energy storage device 6.

[0070] according to Figure 3 The initial state Z relates to time point t0, and the first time range T1 begins at time point t0. Since step S1 is executed before time point t0, the initial state Z is the expected state. Starting from the state given at the current time point, the expected state can be predicted by the control device 9, for example, based on the operating mode defined by subsystems 1, 4, etc. up to time point t0. Figure 3 The first time range T1 spans a considerable period of time, such as 12 hours. Of course, other time periods are also possible. However, it is usually not less than a few hours (e.g., 2 hours, 3 hours, and further hourly up to, for example, 24 hours) and not more than a few days (i.e., 2 days, 3 days, etc., up to a maximum of 7 days).

[0071] In step S2, the control device 9 knows the planned first operating modes B1, B4, B7, and B8 of other subsystems 1, 4, etc. (i.e., the planned first operating mode not of the energy storage device 6). Furthermore, in step S2, the control device 9 knows the planned first time curve E1 for purchasing electrical energy from the supply network 2. According to... Figure 3The operating modes B1, B4, B7 and B8, as well as the first time curve E1, all involve the first time range T1.

[0072] In step S3, the control device 9 defines the operating mode B6 of the energy storage device 6 for a first time range T1. This definition is made based on the planned first operating modes B1, B4, etc., of other subsystems 1, 4, etc., and the first time curve E1 of the planned purchase of electrical energy from the supply network 2. Specifically, the amount of electrical energy required by the corresponding other subsystems 1, 4, 7, and 8 at a given time point t is defined based on the known operating modes B1, B4, B7, and B8. Thus, by combining the first time curve E1 of the planned purchase of electrical energy from the supply network 2, it is possible to define at which time point t a certain amount of electrical energy must be absorbed or output from the energy storage device 6. Step S3 defines the operating mode of the entire system for the first time range T1.

[0073] In step S4, the control device 9 determines the expected final state Z6' of the energy storage device 6. According to... Figure 3 The expected final state Z6' relates to the end of the first time range T1. Based on the initial state Z6 of the energy storage 6 and the previously determined operating mode B6 of the energy storage 6, and further based on the first time curve E1 of the energy purchase plan, the control device 9 determines the expected final state Z6' and the first operating modes B1, B4, etc. of the planned other subsystems 1, 4, etc. Typically, in step S4, the control device 9 also determines the expected final states Z1', Z4', etc. of other subsystems 1, 4, etc. However, within the scope of this invention, determining the expected final states Z1', Z4', etc. of other subsystems 1, 4, etc. is secondary.

[0074] In step S5, the planned second operating modes B1', B4', etc., of other subsystems 1, 4, etc., are transmitted to the control device 9. The planned second operating modes B1', B4' can be preset by operator 12 for the control device 9 (see [link to relevant documentation]). Figure 1 The planned second operating modes, B1', B4', etc. (see...) Figure 3 This is related to the second time range T2, which directly follows the first time range T1. According to... Figure 3 The second time frame T2 spans a considerably long period, such as 24 hours. Of course, other time frames are possible. However, it is typically no less than a few hours and no more than a few days. The implementation scheme described above regarding the first time frame T1 can be used in a similar manner.

[0075] In step S6, the control device 9 defines a second time curve E2 for purchasing electrical energy from the supply network 2 for the second time range T2. Step S6 will be explained in detail later.

[0076] In step S7, the control device 9 defines the operating mode B6' of the energy storage 6 for the second time range T2. This definition is implemented based on the second operating modes B1', B4', etc., which are planned for purchasing electricity from the supply network 2, and the planned second time curve E1. The above-described implementation scheme of step S3 can be used in a similar manner. By executing step S7, the corresponding operating mode of the overall system is thus defined for the second time range T2.

[0077] Steps S1 to S7 are executed before time point t0, that is, before the start of the first time range T1. Therefore, in step S8, control device 9 waits for the start of the first time range T1. Then, control device 9 transitions to step S9.

[0078] In step S9, whenever feasible, control device 9 operates subsystems 1, 4, 6, etc., according to the previously determined planned first operating modes B1, B4, B6, etc. If necessary, control device 9 also operates converter 3 within the scope of step S9. As a result, the energy storage 6 balances the difference between the energy demand of the other subsystems 1, 4, etc., and the other side of the defined first curve E1 for purchasing energy. This balancing is performed for each time point t, or at least for smaller time periods typically up to 10% of the first time range T1. Typically, these smaller time periods are in the range of a few minutes, for example, 15 minutes each.

[0079] To set whether and to what extent electrical energy is supplied to the energy storage device 6, or to control whether and to what extent electrical energy is output from the energy storage device 6, a bidirectional converter unit can be assigned to the energy storage device 6. The converter unit in... Figure 1 Not shown in the diagram. Instead, the converter unit is considered a component of the energy storage 6.

[0080] Step S9 is repeated until the end of the first time range T1 is reached (t1). This is checked by the control device 9 in step S10.

[0081] If control device 9 does not return from step S10 to step S9, then control device 9 transitions to step S11. In step S11, whenever feasible, control device 9 operates subsystems 1, 4, 6, etc., according to the previously determined planned second operating modes B1', B4', B6', etc. As a result, the energy storage 6 thus balances the difference between the energy demand of the other subsystems 1, 4, etc., and the other side of the defined second time curve E2 for purchasing energy, as before. This balancing is performed for each time point t, or at least for smaller time periods typically up to 10% of the second time range T2. Typically, the smaller time periods are in the range of a few minutes, for example, 15 minutes each.

[0082] The control device 9 continuously executes step S11 until the end of the second time range T2, t2, is reached. This is checked by the control device 9 in step S12.

[0083] If control device 9 does not return from step S12 to step S11, then control device 9 transitions to step S13. In step S13, other actions are taken. For example, in step S13, control device 9 can adapt to two time ranges T1 and T2, and then return to step S1 again. In this case, Figure 2 The entire process is iteratively re-executed, each timeframe T1 and T2 respectively. In any case, during re-execution, the second timeframe T2 of the corresponding iteration is at least partially a component of the first timeframe T1 of each subsequent iteration.

[0084] Figure 2 The simplified processing method is shown. The actual processing method is more complex. In particular, a rolling processing method is used in practice. Therefore, steps S1 to S13 are repeatedly executed, while always adapting and tracking time points t0, t1, and t2 or time ranges T1 and T2. For example, the first time range T1 can be 12 hours, and the second time range T2 can be 24 hours. This corresponds to the typical EU processing method, which requires the purchase of electricity for the following day (0:00 to 24:00) to be restricted before 12:00. Therefore, if (for example) the purchase of electricity for the 16th of the month is restricted before 12:00 on the 15th of the month, then the purchase of electricity for the 17th of the month is restricted before 12:00 on the 16th of the month; however, since the restriction has already been implemented on the 15th of the month, the purchase of electricity for the second half of the month on the 16th is already known.

[0085] The following, combined with Figure 4 The typical treatment of the second time curve E2 used to limit the purchase of electricity is explained. Therefore, Figure 4 Show Figure 2 The implementation of step S6.

[0086] according to Figure 4 In step S21 (preparatory), the control device 9 sets the second time curve E2. In this setting, the control device 9 implements the second operating mode B1', B4', etc., planned for the second time range T2 based on the expected final state B6' of the energy storage 6 and other subsystems 1, 4, etc.

[0087] When setting the corresponding time curve E2, the control device 9 considers auxiliary conditions that must be met by the time curve E2. Specifically, when executing step S21, the operating modes B1' and B4' of other subsystems 1, 4, etc., are already known, making the time curves of the power demand of other subsystems 1, 4, etc., known. Furthermore, the operating limitations of the energy storage device 6 are known, i.e., the maximum possible or permissible charging current, the maximum possible or permissible discharging current, the minimum possible or permissible load state, and the minimum possible or permissible load state are known. Another possible auxiliary condition is that the load state of the energy storage device 6 at the end of the second time range T2 should have a predetermined value, or at least should be within a predetermined value range. Therefore, while the implementation of step S21 is not explicitly limited on the one hand, it is not entirely arbitrary on the other. More precisely, the appropriate implementation is selected such that the second time curve E2 for purchasing power satisfies the auxiliary condition NB.

[0088] In step S22, the control device 9 determines the values ​​of multiple cost functions K1 and K2 for the second time curve E2 formed in step S21. Therefore, the control device 9 determines the values ​​of at least two cost functions K1 and K2. However, it can determine the values ​​of more than two cost functions if necessary. Regardless of the number of cost functions K1 and K2, both cost functions K1 and K2 depend on the second time curve E2 for purchasing electricity. However, the correlation between cost functions K1 and K2 and the second time curve E2 for purchasing electricity differs for different cost functions.

[0089] In step S23, the control device 9 performs Pareto optimization of the set second time curve E2 in terms of cost functions K1 and K2.

[0090] In step S24, control device 9 checks whether the second time curve E2 for the power purchase setting is Pareto optimal. If not, control device 9 transitions to step S25, where it changes the second time curve E2 for Pareto optimality. When changing the second time curve E2, control device 9 also considers the auxiliary condition NB mentioned in step S21. From step S25, control device 9 returns to step S22.

[0091] Conversely, if the second time curve E2 for purchasing electrical energy is Pareto optimal, the control device 9 transitions to step S26, in which the control device stores the set second time curve E2 as a feasible second time curve E2.

[0092] From step S26, control device 9 transitions to step S27. In step S27, control device 9 checks whether it has already executed steps S21 to S26 for all the set second time curves E2. If not, control device 9 returns to step S21. However, upon re-executing step S21, control device 9 sets new, different second time curves E2. Therefore, upon re-executing step S26, in addition to the already found feasible second time curves E2, the newly discovered Pareto optimal feasible second time curve E2 is also stored.

[0093] If the control device 9 has performed steps S21 to S26 for all the second time curves E2 to be set, the control device 9 transitions from step S27 to step S28. In step S28, one of the feasible second time curves E2 found is selected or limited to the second time range T2 as the limited second time curve E2 for purchasing electrical energy.

[0094] Below, in conjunction with Figure 5 explain Figure 4 The design scheme of the processing method enables the determination of the Pareto optimal feasible second time curve E2 for purchasing electricity in a particularly simple way and method.

[0095] Figure 5 This includes steps S31 to S41. Figure 5 Steps S31, S32, S38, S39, S40 and S41 are related to Figure 4 Steps S21, S22, S24, S26, S27, and S28 correspond to each other. Therefore, these steps are only briefly mentioned and not explained in detail.

[0096] according to Figure 5 In step S31, the control device 9 (preparatory) sets the second time curve E2. In step S32, the control device 9 determines the values ​​of cost functions K1 and K2 for the second time curve E2 set in step S31.

[0097] In step S33, the control device 9 determines G1 and G2 of the cost functions K1 and K2 for the second time range T2. The determination of gradients G1 and G2 is straightforward.

[0098] In step S34, the control device 9 determines whether the second time curve E2 formed in step S31 can be Pareto optimized. The control device 9 makes this decision based on the total gradients G1 and G2.

[0099] It is feasible to assume that the second time curve E2 set in arrangement S31 is already Pareto optimal, meaning that no further optimization will be performed and is unnecessary. In this case, control device 9 directly transitions to step S39. Step S39 will be discussed in detail below.

[0100] If Pareto optimization is possible, then in step S35, control device 9 determines the descent direction G using the gradients G1 and G2 of cost functions K1 and K2. In the case of exactly two cost functions K1 and K2, control device 9 determines the angle bisector of gradients G1 and G2 as, for example, the descent direction G.

[0101] In step S36, the control device 9 changes the set second time curve E2 using the descent direction G. Specifically, the control device 9 can change the set second time curve E2 along a direction given by the descent direction G. For example, the control device 9 can multiply the descent direction G by a coefficient k and add it to the previous second time curve E2.

[0102] In step S37, control device 9 re-determines the values ​​of cost functions K1 and K2 and their gradients G1 and G2. In step S38, control device 9 checks whether the (changing) second time curve E2 determined in step S36 is Pareto optimal. Control device 9 makes a decision based on the overall gradients G1 and G2 determined in step S37.

[0103] If the (changing) second time curve E2 determined in step S36 is not Pareto optimal, then the control device 9 returns to step S35. Otherwise, the current second time curve E2 is Pareto optimal, and can be adapted by the control device 9 to a feasible second time curve E2 in step S39.

[0104] In step S40, the control device 9 checks whether steps S31 to S39 have been performed for all the second time curves E2 to be set. Depending on whether this is the case, the control device 9 returns to step S31 or transitions to step S41. In step S41, for the second time range T2, one of the feasible second time curves E2 is selected or limited to a specific second time curve E2 for purchasing electrical energy.

[0105] Figure 5 The process has already been explained above in conjunction with the sequential determination of the feasible second time curve E2. In addition to sequential determination, it can also be determined in parallel, provided that the control device 9 is designed accordingly.

[0106] The planned first operating modes, B1, B4, etc., are as follows: Other subsystems 1, 4, etc., operate within the first time frame T1 based on feasibility according to these operating modes. However, in practice, not all situations are fully considered when defining the planned first operating modes, B1, B4, etc. Certain situations are consistently overlooked. For example, in the case of a rolling mill as facility 1 in the metal industry, the rolled material may be slightly hotter or colder than planned, causing changes in rolling force, rolling tension, and the associated power demand.

[0107] Therefore, according to Figure 6 In step S51, during the first time period T1, control device 9 also checks whether the operating limits (e.g., maximum current or minimum / maximum load state) of the energy storage 6 are currently being followed during the actual operation of other subsystems 1, 4, etc., and whether they are being followed for the remainder of the first time period T1. In other words, planning is performed to ensure that the operating limits of the energy storage 6 are followed. However, now, due to unforeseen facts, the operation of the energy storage 6 differs from the assumptions. Therefore, it is now feasible to no longer follow the operating limits of the energy storage 6, even though planning has been carried out and, for example, certain reserves have been considered during planning.

[0108] If the check result in step S51 indicates compliance with operating restrictions, then control device 9 takes no further action as long as the first time curve E1 of the planned purchase of electricity is involved. Specifically, the control device maintains the planned first time curve E1 unchanged. However, if the check result in step S51 indicates non-compliance with operating restrictions, then control device 9 modifies the planned first operating mode B1, B4, etc., in step S52, but only for the future, thus using the remaining portion of the first time range T1. For example, it can adapt to the rolling speed or match production to hydrogen. Alternatively or additionally, control device 9 modifies the planned first time curve E1 of the electricity purchase in step S53, which is also obviously only for the future, i.e., the remaining portion of the first time range T1. For example, control device 9 can modify the first time curve E1 of the planned purchase of electricity at energy exchange 14 (see...). Figure 11 A certain amount of electrical energy may be directly purchased or returned to at least one sub-range corresponding to the remaining portion of the first time range T1. In steps S52 and S53, the measures taken are intended to comply with the operational limitations of the electrical energy storage device 6.

[0109] therefore, Figure 6 Show Figure 2 One possible design scheme for step S9. Figure 6 The processing method described below is always feasible. However, the preferred approach is to combine the following... Figure 7 Explanation of the design scheme.

[0110] according to Figure 7During the first time range T1, in step S61, control device 9 checks whether other subsystems 1, 4, etc., need to deviate from the planned first operating mode B1, B4, etc. Step S61 essentially corresponds to... Figure 6 Step S51.

[0111] If the inspection indicates that no deviation from the operating mode is required, then in step S62, the operation of other subsystems 1, 4, etc., is performed according to the planned first operating modes B1, B4, etc. The operation of the energy storage device 6 is also performed according to the previously determined (B6). Thus, during the first time range T1, the purchase of energy from the supply network 2 is realized according to the first time curve E1 that defines the purchase of energy.

[0112] Conversely, if the inspection indicates a need for a deviated operating mode, control device 9 operates other subsystems 1, 4, etc., according to the deviated operating mode in step S63. Furthermore, in step S64, control device 9 determines the extent to which the power demand of other subsystems 1, 4, etc., is changed (i.e., the changed operation of other subsystems 1, 4, etc.). The original, unchanged demand serves as the basis for the first time curve E1 for planning and defining power demand.

[0113] In exceptional cases, it is feasible to maintain the same power demand despite changes in the operation of other subsystems 1, 4, etc. In this case, the operation of the energy storage device 6 can obviously remain unchanged as well. However, in any case, corresponding changes are made. Therefore, in step S65, the control device 9 checks whether the first time curve E1 limiting the purchase of power can still be maintained if the operation of the energy storage device 6 is adapted accordingly.

[0114] If this is not the case, then in step S66, control device 9 changes the purchase of electrical energy from supply network 2. This can be done as needed, with or without adapting to the operation of energy storage device 6. The adaptation of electrical energy purchase is aimed at achieving a deviated operating mode from other subsystems 1, 4, etc.

[0115] If the first time curve E1 limiting the purchase of electrical energy can be maintained, then in step S67, control device 9 will determine whether and to what extent the purchase of electrical energy from supply network 2 should be changed. If control device 9 changes the purchase of electrical energy, then in step S68, control device continues to keep the energy storage 6 unchanged, i.e., as determined in step S3 (see...). Figure 2 That has already been defined. Otherwise, in step S69, the control device 9 adapts the operation mode B6 of the energy storage device 6 accordingly, so that the previously defined first time curve E1 for purchasing energy can be maintained.

[0116] Within the scope of the decision in step S67, various facts can be considered. The most important facts are the type and extent of changes in the power demand of other subsystems 1, 4, etc., the current load status of the power storage 6, the progress within the first time period T1, and the estimated price of power to be purchased during the remaining portion of the first time period T1, and, if necessary, the second time period T2. It is also feasible to submit this issue to operator 12 for a decision and receive the corresponding decision from operator 12.

[0117] For the second time range T2, and Figure 6 and Figure 7 A completely similar approach is feasible, i.e., corresponding Figure 2 The design scheme for step S11 is feasible. The only difference is: if it is performed on the second time range T2... Figure 7 The processing method allows only the remaining portion of the second time range T2 to be considered within the scope of step S67.

[0118] Cost functions K1 and K2 can be defined as needed. In many cases, cost functions K1 and K2 include a first cost function K1, the value of which is determined by… Figure 8 and Figure 9 The figure depends on the operating cost of the energy storage device 6 during the second time period T2. For example, operating costs KV due to losses, operating costs KV due to purchase, or the cost of maintenance that may be required can all be included in the cost.

[0119] What is usually meaningful is: according to Figure 8 In the diagram, the first cost function K1 also depends additionally on the cost KE of purchasing electricity from supply network 2. However, it would be meaningful on a case-by-case basis that: Figure 9 In the diagram, the first cost function K1 depends only on the operating costs KA, KV, and KW of the energy storage device 6 itself, and therefore does not consider the cost KE of purchasing electricity from the supply network 2.

[0120] In many cases, according to Figure 8 and Figure 9The cost functions K1 and K2 in the diagram also include a second cost function K2, the value of which depends on the time curve of the load state ZL of the energy storage 6 during the second time period T2. Specifically, the time curve of the load state ZL can be correlated with the upper and / or lower limits of the load state ZL. The upper and / or lower limits can be fixed or time-dependent as needed. Therefore, it is possible to assess what kind of (potentially time-dependent) reserves the energy storage 6 provides at the upper and lower limits (i.e., for additional energy absorption or for energy output). For example, the relevance of the second cost function K2 can be derived when considering the planned second operating modes B1', B4', etc., of other subsystems 1, 4, etc., and / or when considering the expected cost of electrical energy for a specific period of the second time period T2.

[0121] As mentioned above Figure 2 As explained, the method as a whole is typically re-executed iteratively. It is feasible that cost functions K1 and K2 remain constant across different iterations. However, it is preferable that at least one of the cost functions K1 and K2 is individually defined for each different iteration.

[0122] As mentioned above Figure 4 and Figure 5 As explained, control device 9 typically determines several feasible second time curves E2, and then selects one of the second time curves as the second time curve E2 to be used. This selection can be designed in different ways.

[0123] In the simplest case, output is sent to operator 12 via control device 9 (see...) Figure 1 The control device 9 receives a selection from the operator 12. In this case, the control device 9 provides the operator 12 with a series of possibilities, from which the operator 12 selects one.

[0124] Alternatively, control device 9 may automatically select some or all of the previously determined feasible second time curves E2, or receive a selection of multiple feasible second time curves E2 from operator 12, and then independently decide which of the selected second time curves E2 to be used. Possible design schemes for this purpose are combined below. Figure 10 To explain.

[0125] exist Figure 10 The processing method is defined under the following premise: that is, according to Figure 11 In the diagram, control device 9 is connected to energy exchange station 14 via Internet 13. In this case, control device 9... Figure 10In step S71, the diagram shows multiple requests Ai (i=1, 2, 3, etc.) for purchasing electrical energy from the supply network 2 for each of the multiple time periods of the second time range T2 (e.g., each hour of the 24 time periods if the length of the second time range T2 is 24 hours). Request Ai includes the expected quantity Mi of electrical energy and a corresponding condition Ci, such as the expected maximum price. When defining the requests Ai, the control device 9 considers a feasible second time curve E2 for purchasing electrical energy from the supply network 2. Typically, the requests Ai are staggered, meaning the requests differ at least in terms of the corresponding allocated price. Generally, the quantity Mi of each request is also different from each other, but in some cases they may be the same.

[0126] In step S72, the control device 9 outputs the request Ai determined by it at the energy exchange 14. In step S73, the control device 9 receives a response Ri in response to the request Ai. The response Ri contains the following information: whether the energy exchange 14 confirms the purchase of the requested amount Mi of electrical energy for the corresponding request Ai, provided that the corresponding allocation condition Ci is met.

[0127] Then, in step S74, the control device 9 adapts to the request Ai, wherein the energy exchange 14 confirms the purchase of the requested quantity Mi of electrical energy if the corresponding allocation condition Ci is met. Finally, in step S75, the control device 9 makes the following decision based on the request in step S74: which of the feasible second time curves E2 is designated as the second time curve E2 to be used.

[0128] In its simplest case, the energy storage device 6 surrounds only a single, general-purpose storage device. However, according to... Figure 1 As shown in the diagram, the energy storage device 6 can also include multiple sub-storages 6a and 6b. The sub-storages 6a and 6b can be independently configured to: whether and to what extent energy is supplied to the other sub-storages 6a and 6b, or whether and to what extent the other sub-storages 6a and 6b output energy. For this purpose, each of the other sub-storages 6a and 6b typically has its own bidirectional converter unit. The converter units are not shown.

[0129] If the energy storage device 6 is divided into multiple sub-storages 6a and 6b, the sub-storages 6a and 6b are preferably different in terms of their possible power limitations, such as in their capacity and their maximum possible or permissible charge / discharge current (or corresponding power). For example, sub-storage 6a can have a significantly smaller storage capacity than sub-storage 6b, but a significantly larger maximum charge / discharge power. Examples include values ​​of 10 MWh and 100 MW for sub-storage 6a, and values ​​of 100 MWh and 25 MW for sub-storage 6b. Sub-storage 6a can be designed, for example, as a sodium-ion battery, and sub-storage 6b can be designed, for example, as a flow battery or a sodium-sulfur battery.

[0130] Those skilled in the art are familiar with the combined operation of multiple sub-memories 6a and 6b. Therefore, the combined operation will not be explained in detail.

[0131] This invention offers numerous advantages. By pre-defining and subsequently implementing a second curve E2 for purchasing electricity from the supply network 2, the cost of electricity can be reliably planned. In particular, the cost of electricity can be minimized by participating in the energy exchange 14. Furthermore, it is easy to integrate, for example, long-term purchase contracts or individual power generation units 8.

[0132] Although the present invention has been described and illustrated in more detail through preferred embodiments, the present invention is not limited to the disclosed examples, and those skilled in the art can derive other variations therefrom without departing from the scope of protection of the present invention.

[0133] List of reference numerals

[0134] 1. Facilities

[0135] 2. Supply Network

[0136] 3 Converters

[0137] 4. Electrolysis facilities

[0138] 5 Rectifiers

[0139] 6. Energy Storage

[0140] 6a and 6b sub-memories

[0141] 7. Hydrogen storage

[0142] 8. Power generation unit

[0143] 9. Control device

[0144] 10 Control Procedure

[0145] 11 Machine Code

[0146] 12 operators

[0147] 13 Internet

[0148] 14 Energy Exchange

[0149] AI request

[0150] B1, B4, B6, B7, B8 First Operating Mode

[0151] B1', B4', B6', B7', B8' Second operating mode

[0152] Ci conditions

[0153] E1 and E2 time curves

[0154] G descent direction

[0155] G1 and G2 gradients

[0156] k coefficient

[0157] K1 and K2 cost functions

[0158] KA, KE, KV, KW cost

[0159] Mi (amount of electrical energy)

[0160] NB auxiliary conditions

[0161] Ri response

[0162] Steps S1 to S75

[0163] T1, T2 time range

[0164] t0, t1, t2 time points

[0165] Initial states of Z, Z1, Z4, Z6, Z7, Z8

[0166] Final states of Z', ZT, Z4', Z6', Z7', Z8'

[0167] ZL Load Status.

Claims

1. A method for operating a complete system. -in, The overall system includes an energy storage device (6) as a subsystem and other subsystems (1, 4, 7, 8). -The other subsystems (1, 4, 7, 8) include facilities for the metal industry (1). -In this context, the facilities (1) of the metal industry and the energy storage device (6) are directly or indirectly interconnected and connected to the power supply network (2) for the purpose of transmitting electrical energy. - Wherein, before the start of the first time range (T1), the control device (9) controlling the overall system knows the expected initial state (Z1, Z4, Z6, Z7, Z8) of the subsystem (1, 4, 6, 7, 8) at the start of the first time range (T1). -In which, before the start of the first time range (T1), for the first time range (T1), the control device (9) knows the first time curve (E1) of the plan to purchase electrical energy from the supply network (2) and the first operating mode (B1, B4, B7, B8) of the other subsystems (1, 4, 7, 8). - Wherein, based on the initial state (Z6) of the energy storage (6), the first time curve (E1) of the energy purchase plan, and the first operating mode (B1, B4, B7, B8) of the other subsystems (1, 4, 7, 8), the control device (9) determines the expected final state (Z6') of the energy storage (6) at the end of the first time range (T1). -In this context, starting from the expected final state (Z6') of the energy storage device (6) and the second operating mode (B1', B4', B7', B8') of the other subsystems (1, 4, 7, 8) for the second time range (T2) which is known to the control device (9) and planned for the second time range (T2) that directly follows the first time range (T1), the control device (9) determines a second time curve (E2) for which electrical energy can be purchased. - wherein the control device (9) determines the second time curve (E2) for which electrical energy can be purchased, such that each of the second time curves is Pareto optimal in relation to a plurality of corresponding cost functions (K1, K2) depending on the corresponding second time curve (E2) for the purchase of electrical energy. - Wherein, the correlation between the cost function (K1, K2) and the corresponding second time curve (E2) for purchasing electricity is different for different cost functions (K1, K2). - wherein the control device (9) determines one of the second time curves (E2) for which electrical energy can be purchased as the second time curve (E2) for the second time range (T2). - wherein the control device (9) performs the limitation on the second time curve (E2) for purchasing electrical energy before the start of the first time range (T1). Where feasible, the control device (9) operates the other subsystems (1, 4, 7, 8) based on the planned first and second operating modes (B1, B4, B7, B8, B1', B4', B7', B8') during the first and second time ranges (T1, T2), and the control device operates the energy storage device (6) to purchase energy from the supply network (2) during the first and second time ranges (T1, T2) according to the planned first time curve and the defined second time curve (E1, E2) for purchasing energy.

2. The operating method according to claim 1, characterized in that, The cost functions (K1, K2) include a first cost function (K1), the value of which depends on the cost of the energy storage device (6) operating during the second time period (T2) without considering the cost (KE) for purchasing electricity.

3. The operating method according to claim 2, characterized in that, In order to limit the second time curve (E2) for purchasing electrical energy, the control device (9) - Submit multiple requests (Ai) for the purchase of electrical energy of a corresponding amount (Mi) to the energy exchange (14) via the Internet (13) for each of the multiple time periods of the second time range (T2), wherein a corresponding condition (Ci) is assigned to the request (Ai). - Check: Whether the energy exchange (14) confirms the request (Ai) to purchase electricity if the corresponding allocation conditions (Ci) are met, and, if necessary, confirms which of the requests to purchase electricity. -Then, considering the request (Ai), the second time curve (E2) for purchasing electricity is determined, in which the energy exchange (14) confirms the required purchase of electricity if the conditions (Ci) of the corresponding allocation are met.

4. The operating method according to claim 1, characterized in that, The cost functions (K1, K2) include a first cost function (K1), the value of which depends on the cost of the energy storage device (6) operating during the second time period (T2) and the cost (KE) for purchasing energy.

5. The operating method according to any one of the preceding claims, characterized in that, The cost functions (K1, K2) include a second cost function (K2), the value of which depends on the time curve of the load state (ZL) of the energy storage device (6) during the second time range (T2).

6. The operating method according to any one of the preceding claims, characterized in that, The second time curve (E2) that enables the purchase of electrical energy satisfies the unified auxiliary condition (NB).

7. The operating method according to any one of the preceding claims, characterized in that, In order to determine the corresponding second time curve (E2) for purchasing electrical energy, the control device (9) - Set a second time curve (E2) for purchasing electricity for the second time range (T2), and determine the value of the cost function (K1, K2) and the gradient (G1, G2) of the cost function (K1, K2) for the set second time curve (E2). -Based on the total gradients (G1, G2), determine whether the established second time curve (E2) can be Pareto optimized. -If the established second time curve (E2) cannot be Pareto optimized, adapt the established second time curve (E2) to a usable second time curve (E2), and - If the established second time curve (E2) can be Pareto optimal, use the gradient (G1, G2) of the cost function (K1, K2) to determine the descent direction (G), use the descent direction (G) to change the established second time curve (E2), and repeat the determination and change of the value of the cost function (K1, K2) and the gradient (G1, G2) of the cost function (K1, K2) until the established second time curve (E2) is Pareto optimal, and then adapt the established second time curve (E2) to a usable second time curve (E2).

8. The operating method according to any one of the preceding claims, characterized in that, During the second time range (T2), the control device (9) - Check whether the other subsystems (1, 4, 7, 8) need to deviate from the planned second operating mode (BT, B4', B7', B8'). - In the absence of a deviated operating mode, the control device operates the other subsystems (1, 4, 7, 8) according to the planned second operating mode (B1', B4', B7', B8'), and the control device operates the energy storage device (6) to purchase energy from the supply network (2) during the second time range (T2) according to the second time curve (E2) defined for purchasing energy. - In cases requiring a deviated operating mode, the control device operates the other subsystems (1, 4, 7, 8) according to the deviated operating mode, and the control device determines the extent to which the operation alters the energy demand of the other subsystems (1, 4, 7, 8) as defined by the second time curve (E2) based on the purchased energy. - Check whether the second time curve (E2) of the purchase of electrical energy can be maintained by adapting the operation of the electrical energy storage (6). - In cases where the second time curve (E2) limiting the purchase of electrical energy cannot be maintained, the purchase of electrical energy is changed with or without adaptation to the operation of the energy storage device (6) to achieve a deviation in the operating mode of the other subsystems (1, 4, 7, 8), and -Determine whether and to what extent the control device changes the purchase of electricity and operates the energy storage device accordingly, provided that the second time curve (E2) that limits the purchase of electricity can be maintained.

9. The operating method according to claim 8, characterized in that, The control device (9) makes a decision based on the type and extent of changes in the power demand of the other subsystems (1, 4, 7, 8), the current load state (ZL) of the power storage device (6), the progress in the second time period (T2) and / or the estimated price of purchasing power during the remainder of the second time period (T2).

10. The operating method according to any one of the preceding claims, characterized in that, -Continuously re-execute the aforementioned execution method iteratively. - The second time range (T2) of the corresponding iteration is at least partially a component of the first time range (T1) of the corresponding subsequent iteration, and - Determine at least one of the cost functions (K1, K2) individually for different iterations.

11. A control program for a control device (9) of a general system, -in, The overall system includes an energy storage device (6) as a subsystem and other subsystems (1, 4, 7, 8). -The other subsystems (1, 4, 7, 8) include facilities for the metal industry (1). -In this context, the facilities (1) of the metal industry and the energy storage device (6) are directly or indirectly interconnected and connected to the power supply network (2) for the purpose of transmitting electrical energy. -The control program (9) includes machine code (11) that can be processed by the control device (9). - wherein the processing of the machine code (11) by the control device (9) causes the control device (9) to control the overall system in accordance with the operating method according to any one of the preceding claims.

12. A control device for a complete system, -in, The overall system includes an energy storage device (6) as a subsystem and other subsystems (1, 4, 7, 8). -The other subsystems (1, 4, 7, 8) include facilities for the metal industry (1). -In this context, the facilities (1) of the metal industry and the energy storage device (6) are directly or indirectly interconnected and connected to the power supply network (2) for the purpose of transmitting electrical energy. - wherein the control device is programmed using the control program (10) according to claim 11, such that the control device controls the overall system according to the operating method according to any one of claims 1 to 10 when processing the machine code (11) of the control program (10).

13. A general system, -in, The overall system includes an energy storage device (6) as a subsystem and other subsystems (1, 4, 7, 8). -The other subsystems (1, 4, 7, 8) include facilities for the metal industry (1). -In this context, the facilities (1) of the metal industry and the energy storage device (6) are directly or indirectly interconnected and connected to the power supply network (2) for the purpose of transmitting electrical energy. -The overall system includes a control device (9) according to claim 12, which controls the overall system in accordance with the operating method according to any one of claims 1 to 10 when processing the machine code (11) of the control program (10) according to claim 11.

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