SYSTEMS AND METHODS FOR SWITCHING ON OR OFF SINGLE MICRONET SYSTEMS

Abstract

A method for operating a microgrid system (100) comprising: receiving a microgrid on or off schedule input (208) containing a schedule of required electrical power generation for the microgrid system (100) for a given period; filtering the scheduled on or off input and converting the scheduled on or off input into power levels (608) to meet the power demand for required electrical power generation of the on or off schedule input for the microgrid system (100); receiving an actual load level for the microgrid system (100) based on one or more electrical loads (116) electrically coupled to the microgrid system (100); and comparing the schedule of required electrical power generation with the actual electrical power generation required for the microgrid system (100).and switching one or more electrical systems on or off in real time to compensate for a difference between the planned required electrical energy generation and the actual required electrical energy generation.

Description

Technical field

[0001] The present disclosure relates generally to systems and methods for switching electrical systems on or off in a microgrid and in particular to systems and methods for flexibly switching electrical systems on or off in real time. State of the art

[0002] Managing hybrid energy systems in microgrids can be a complex task, but optimizing microgrid performance can be advantageous and lead to realized benefits such as cost reduction, emission reduction, and improved reliability. Hybrid energy systems combine multiple types of power generation and storage, which can include solar panels, wind turbines, batteries, and conventional grid connections. Coordinating these different systems for efficient operation can be problematic due to the variety of technologies and their interactions. Rule-based algorithms can be easily implemented but cannot account for all possible scenarios, especially in highly complex hybrid systems. These approaches may require predefined rules and miss edge cases, resulting in suboptimal performance. Meanwhile, optimization techniques (e.g.,Linear programming, mixed-integer programming, etc., can find optimal solutions to complex problems. However, with the increasing complexity of hybrid energy systems, the computational demands can become unacceptably high. Furthermore, conventional optimization may not account for type-specific aspects of energy systems, such as maintenance, aging, or replacement.

[0003] U.S. Patent No. 10,734,811 (“the '811 Patent”) describes methods and systems for optimizing the control of one or more energy storage systems (ESS). According to the '811 Patent, a system may include data sources, a forecasting engine, a scheduling and switching-on / off engine, an ESS control system, and an optimization block. The scheduling and switching-on / off engine uses optimization techniques to determine a switching-on or switching-off schedule for the ESS. The ESS control system can use the switching-on or switching-off schedule received from the scheduling and switching-on / off engine to determine active and reactive power input or output from a grid or microgrid. The system may use various algorithms, such as a scheduler. However, the '811 Patent does not address various aspects of energy systems that are type-specific, nor does it address the problem of computational complexity as the number of energy systems increases.

[0004] The systems and methods for flexibly switching electrical systems on or off in real time, as disclosed herein, may address one or more prior art problems, for example, problems not covered by Patent 811. However, the scope of this disclosure is defined by the accompanying claims, and not by the ability to solve any specific problem. Brief description

[0005] In one aspect, a procedure for operating a microgrid system involves: receiving a microgrid on / off schedule input, which includes a schedule of the required electrical power generation for the microgrid system for a given period and a schedule of the electrical systems capable of fulfilling the required electrical power generation schedule; filtering the scheduled on / off input and converting it into power levels to meet the power requirements for the required electrical power generation of the microgrid system on / off schedule input; and receiving a current load level for the microgrid system based on one or more electrical loads electrically coupled to the microgrid system.Comparing the schedule of required electrical power generation with the actual required electrical power generation for the microgrid system to determine any difference between the planned and actual required electrical power generation; and switching one or more electrical systems on or off in real time to meet any difference between the planned and actual required electrical power generation. In another aspect, a method for operating a microgrid system involves receiving a planned load signal based on a schedule of electrical load requirements for the microgrid system for a given period.Receiving an expected power generation signal based on the expected power generation of one or more electrical systems electrically coupled to the microgrid system; measuring an actual load at a measurement time within the given time period and receiving an actual load signal to determine the actual load on the microgrid system; comparing the actual load signal with the planned load signal and the expected power generation signal; generating a differential load signal based on the difference between the planned load signal, the expected power generation signal, and the actual load signal; switching one or more electrical systems on or off to meet the differential load based on the differential load signal.

[0006] In yet another aspect, a controller for a microgrid system includes at least one memory that stores instructions; at least one processor, operationally connected to the memory and configured to execute the instructions to: receive a scheduled load signal based on a schedule of electrical load requirements for the microgrid system for a given period; receive an expected power generation signal based on the expected power generation of one or more electrical systems electrically coupled to the microgrid system; measure an actual load at a measurement time within the given period and receive an actual load signal to determine an actual load on the microgrid system; and compare the actual load signal with the scheduled load signal and the expected power generation signal.To develop a differential load signal based on a difference between the planned load signal, the expected power generation signal, and the actual load signal; to switch one or more electrical systems on or off to meet the differential load based on the differential load signal. Brief description of the drawings

[0007] The accompanying drawings, which are incorporated into this patent specification and form part of this patent specification, illustrate various exemplary embodiments and, together with the description, serve to explain the principles of the disclosed embodiments. Fig. Figure 1 is a schematic system diagram showing a micronetwork system according to aspects of the revelation. Fig. 2A is an exemplary system controller for controlling the microgrid system from Fig. 1. Fig. 2B is another embodiment of an exemplary system controller for controlling the microgrid system from Fig. 1. Fig. Figure 3A shows an exemplary procedure for allocating loads in real time to meet load requirements, including any charging requirements, using, for example, the system controller from Fig. 2A. Fig. Figure 3B shows another exemplary method for allocating loads in real time to meet load requirements, including any charging requirements, using, for example, the system controller from Fig. 2B. Fig. Figure 4 shows an exemplary procedure for operating a microgrid system, such as the microgrid system from Fig. 1. Fig. Figure 5 shows another exemplary method for operating a microgrid system, such as the microgrid system from Fig. 1. Fig. Figures 6A-6B are diagrams showing a scheduler profile filter function of one or more of the exemplary scheduling modules shown and described herein, for example, the scheduling modules in the system controllers from Fig. 2A and Fig. 2B. Fig. Figure 7 shows a planned load request over time for a microgrid system such as the microgrid from Fig. 1. Detailed description

[0008] Both the preceding general description and the following detailed description are merely exemplary and explanatory and do not limit the features as claimed. As used herein, the terms "comprises," "comprising," "exhibiting," "including," "comprising," "including," or other variations thereof are intended to cover a non-exclusive inclusion, such that a process, method, article, or device comprising a list of elements may include not only those elements but also other elements not expressly listed or inherent to such process, method, article, or device. Unless otherwise specified, relative terms such as "about," "essentially," or "approximately" are used in this disclosure to indicate a possible deviation of ±10% from the stated value.

[0009] Fig. Figure 1 shows an exemplary microgrid 100. The microgrid 100 includes an electrical bus 102 with multiple systems (which can be arranged in any configuration into system groups) and loads connected to the electrical bus 102. Non-restrictive examples of systems that can be connected to the electrical bus include a utility network 104, one or more renewable energy system groups 124, including, for example, a photovoltaic system 106 and a wind turbine system 122, one or more generator sets 108, and one or more energy storage system (ESS) groups 110. Although in Fig. While Figure 1 represents only one symbol of selected system types, it is understood that the microgrid can embody any set of diverse renewable and non-renewable systems in any combination. For example, the photovoltaic system 106 can be replaced by any combination of systems based on photovoltaics, wind turbines, geothermal energy, hydropower, biomass, tidal energy, biofuel, and the like.Similarly, the generator sets 108 can embody any combination of rotor-stator assemblies driven by a propulsion machine, such as a gas, diesel, or dynamic gas blending (DGB) internal combustion engine, which can be operated at constant or variable speeds, and can include any type of electric generator, for example, without restriction, a diesel generator, a gas reciprocating generator, a gas turbine generator, a hydrogen reciprocating generator, generators with any fuel mixtures, etc. ESS systems can include, without restriction, a battery ESS 112 (lead-acid, Li-ion, etc.), a hydrogen storage ESS 114, and other ESS types. For example, ESS systems in the microgrid 100 can include electrochemical units with various rechargeable battery chemistries, lithium-ion, high-performance lead-acid batteries, fuel cells, ultracapacitors, flow batteries, etc.or mechanical storage devices including flywheels, pumped storage, compressed air storage, gravitational potential energy, etc., or thermal storage devices and the like. The microgrid 100 may further include various loads 116. In some embodiments, these loads 116 may be uncontrollable, but some of them may be intelligent loads that can be controlled by the system controller 130. Each of the various systems and loads may be disconnectable from the electrical bus 102 by a circuit breaker 118 (118a-118h) in order to isolate the various systems and loads from the electrical bus 102. The systems and / or system groups, loads, and circuit breakers may be at least partially controllable by one or more controllers. For example, the microgrid 100 may include a system controller 130 that may be capable of controlling one or more of the asset groups, loads, or other components of the microgrid 100.In some embodiments, the system controller 130 can, for example, control the circuit breakers 118 to open or close them, thereby connecting energy resource groups and / or loads in the micronetwork 100. Additionally, the system controller 130 can control the opening or closing of one or more (not shown) coupling switches between different electrical busbars to electrically connect different busbars (in multi-busbar embodiments of the micronetwork). In multi-busbar embodiments, each busbar can form its own electrical network when isolated from the others. Furthermore, two busbars can form an electrical network separate from the other busbar. The system controller 130 can communicate with a back office 138 via a network 140 (e.g.,a cloud network) or other connection. The system controller 130 can be configured to compare an actual output of the multitude of power sources in the microgrid 100 with a desired output and to selectively control and adjust the power output of each power source to meet the power requirements of the loads 116, as explained in more detail herein.

[0010] The multiple circuit breakers 118 selectively connect busbars, electrical systems, and electrical loads. The circuit breakers can be protective switches that connect two busbars or sections of an electrical busbar, each supplying different power sources or different electrical busbars. When closed, current can flow between them in both directions, from source(s) to sink(s). Each circuit breaker is assigned to the two electrical busbars or sections of a busbar it connects. Different sections of a busbar or different busbars could also be controlled by other controllers connected to the busbar, for example, other controllers similar to the system controller 130.

[0011] The System Controller 130 can communicate at the energy resource group controller level or with individual System Controllers. The System Controller 130 can be located anywhere. For example, it can be on-site (e.g., in the Back Office 138) or remote. The Back Office 138 can include one or more interfaces for an operator to input configuration information to configure the micronet. In some embodiments, the Back Office 138 can also receive operational input and provide interfaces to display one or more configuration or operational outputs (e.g., on a display configured to show micronet operation).

[0012] The System Controller 130 can manage the electrical grid using one or more commands. For example, the System Controller 130 can generate one or more individual system on / off commands to connect generator sets, fuel cells, and other controllable systems to the grid. Renewable energy systems, such as photovoltaic systems, can be connected to the grid, but in some cases, due to their nature, they may need to be disconnected from the grid when capacity is reduced (e.g., due to outages, environmental conditions such as insufficient sunlight, low wind, etc.).

[0013] The system controller 130 can monitor the maximum available power supplied by the non-ESS systems available to the microgrid 100 (e.g., the utility grid 104, the photovoltaic systems 106, and the generators 108). If the non-ESS systems alone cannot handle the loads 116, the system controller 130 can activate the ESS group 110 to supplement load sharing. If the load is less than the minimum required supply from the non-ESS systems, the system controller 130 can divert excess power from the electrical busbar 102 to the ESS group 110 to store the excess power as reserve power in one or more systems within the ESS group 110. Furthermore, the energy storage system is used as a buffer for the economical operation of non-energy storage systems, i.e., charging / discharging, to bring the operation of the non-energy storage systems into an economically viable operating range.Charging / discharging can be activated to keep the energy storage system within the limits of the state of charge (SOC) or state of energy (SOE), i.e., to activate charging when the SOC / SOE is below a minimum, or to activate discharging when the SOC / SOE is above a maximum. In some embodiments, the system controller 130 may not use available electrical capacity to charge the ESS group 110 if, for example, energy costs are currently high (e.g., high costs for electricity from the grid 104) or if there is insufficient power from one or more renewable energy sources. In embodiments, the system controller 130 may select one or more sources based on a volatility factor for intermittent sources, a kW / kVA threshold, or a specific value.evaluate several available power sources and one or more other factors to determine a cost function associated with the use of electrical energy from each plant and / or the microgrid as a whole.

[0014] Network 140 can be, for example, a wired or wireless network, a WLAN, or a cellular network, encompassing a variety of intercommunication devices (e.g., modems, WLAN devices, cellular devices, etc.). Network 140 can include one or more satellites and one or more ground stations (e.g., Backoffice 138), with the ground stations potentially configured to communicate wirelessly to send and receive data to and from the satellites.

[0015] Each of the multiple ESS groups 110 can be of a different type with different properties. The ESS systems usable in the microgrid 100 can include batteries with different capacities, chemistries, and other different properties. One or more of the multiple ESS groups 110 can also include hydrogen storage systems with one or more electrolyzers and / or one or more pumped storage systems.

[0016] Fig. Figure 2A shows the system controller 130 in more detail. The system controller 130 can receive inputs 202 and generate outputs 204. The inputs 202 and the outputs 204 can each be received or generated by one or more software modules or other components of the system controller 130. The system controller 130 can include one or more processors 224, a memory 226, a scheduler processing module 242, a differential evaluation module 216, a module for scheduled system activation or deactivation 218, a module for unplanned system activation or deactivation 220, and a module for unplanned system activation or deactivation 222. The inputs 202 can include a micronet configuration input 206, a micronet turn-on or turn-off plan input 208 (which can include a charge state of the ESS) and feedback of the current load level as input 238, which can include an active load and a reactive load level.Outputs 204 can be an on / off signal 244 and a power signal with power level 246 to the planned systems, as well as an on / off signal 248 and a power signal with power level 250 to the unplanned systems.

[0017] In general, the inputs 202 can be generated, for example, by a system operator (human) in the back office 138 or remotely, or some inputs can be generated and / or determined by the system controller 130 itself. In some embodiments, the system controller, group system controllers, or individual system controllers can be located on-site outdoors or indoors (office) or connected remotely via a network. The inputs 202 can be entered, for example, using a human-machine interface (HMI) and can occur in response to query requests from the system controller 130. In some embodiments, one or more of the outputs can be generated and / or displayed on a display, such as an HMI. It should also be noted that Fig. 2A shows a single controller, but the functions described in relation to the system controller 130 may be distributed across a variety of controllers, microcontrollers, CPUs or other processing devices.

[0018] Input 206 for microgrid configuration can include information that defines the systems, loads, and overall structure of the microgrid. This input typically includes detailed information about generation systems, storage systems, loads, interconnections, grid connections, and / or control logic. For example, Input 206 for microgrid configuration can include information about all power generation systems within the microgrid, including their type (e.g., solar panels, wind turbines, fuel cells), capacity, efficiency, location, and technical specifications. This information can help the System Controller 130 understand the available power sources. The information can also include details about energy storage systems, such as batteries or hydrogen storage systems. This includes capacity, charge / discharge rates, and state-of-charge (SoC) limits.Storage systems can play a crucial role in balancing supply and demand. Input 206 for microgrid configuration can also include information about the electrical loads within the microgrid, including their power requirements, profiles, and priority levels. Some loads may be critical and require continuous power, while others may be less critical and can be switched off during peak load times. Information about interconnections can include how different systems and loads within the microgrid are linked. This includes the wiring, switchgear, and control systems that allow current to flow between components. Information about grid connection can include whether the microgrid is connected to the utility grid and how the microgrid interacts with the grid.This can include information about grid connection points, voltage levels, and protocols for grid interactions.

[0019] The Microgrid On / Off Plan Input 208 can include planned active and reactive power commands for one or more of the systems or system groups connected to the Microgrid 100. The Microgrid On / Off Plan Input 208 can also include a charge state for the various ESS systems connected to the Microgrid 100. It is understood that the planned group active power commands are anticipated commands that can be generated at different time intervals over a predetermined future period and can, for example, serve as guidance for determining real-time active and reactive power commands to be executed at corresponding time intervals. In other words, the planned group active and reactive power commands are intended actions at different time intervals over a moving horizon (e.g., 12 hours, 24 hours, one week, etc.).Active and reactive power commands can be defined by a predetermined future period and can implicitly or explicitly consider future events within that period, such as load variance, costs of the power plant group, availability, or the like. The on / off plan input 208 for the microgrid can be entered by a user, generated by software or module(s) associated with the microgrid system, or a combination of both. If generated by software or module(s) associated with the microgrid system, it can include modules for considering or forecasting time-dependent price changes in the supply network, forecasting time-dependent changes in solar irradiance, forecasting time-dependent load changes, and the like, using algorithms based on current inputs, measurements, and / or historical data.

[0020] The feedback from the current load level input 238 can be the current power, the planned power, and / or the current load of the microgrid 100, as determined based on input from one or more sensors (e.g., current, voltage, power, etc.). The feedback of the current load level can be monitored in real time as new loads are switched on and off in the microgrid 100.

[0021] The system controller 130 can, for example, include a memory 226, which may contain a secondary storage device, and can be coupled to one or more processors 224, such as one or more central processing units, network interfaces, or any other means for accomplishing a task consistent with the present disclosure. The processor(s) 224 can be operationally coupled to the memory 226 and configured to execute one or more instructions stored therein.The memory 226, or the secondary storage device connected to the system controller 130, can store data and software to enable the system controller 130 to perform its functions, including the functions described below with respect to one or more procedures further explained herein, and the functions of the micronet configuration and control system described herein. For example, the memory 226 can store one or more of the limits or thresholds described herein with respect to the various power sources and loads. Unless otherwise specified, this data can be stored as one or more user-selectable settings, allowing a user to adjust the setting via an external computer device (e.g., in the back office 138) that may be communicatively coupled to the system controller 130.The threshold values ​​can be stored as a lookup table that saves the relevant settings for each specific type of power source and / or load. One or more of the devices or systems that are communicatively coupled with the System Controller 130 can be communicatively coupled via a wired or wireless network, such as the Internet, a Local Area Network, WiFi, Bluetooth, or any combination of suitable network configurations and protocols.

[0022] In some embodiments, the memory 226 can store one or more optimal performance maps, and / or properties of the power plant(s) indicated by the optimal performance map(s) can be used by the system controller 130 when optimizations are performed. While the computational effort required to generate or update an optimal performance map can be high, such generation or updating may occur infrequently relative to the optimization(s) performed by the system controller 130. The optimal performance map(s) and / or the properties of the power plant indicated by the optimal performance map(s) can reduce the computational complexity of the optimization(s) performed by the system controller 130.

[0023] In some embodiments, the Scheduler Processing Module 242 can set SOC / SOE targets among the various ESS systems. The Scheduler Processing Module 242 can receive input from the micronet configuration input 206 and / or the micronet power-on or power-off plan input 208. The targets can be updated periodically based on the needs of the micronet system. For example, if an ESS is expected to be heavily used at a later time, an ESS asset can be loaded during periods of relatively low ESS asset usage so that the ESS is ready for use at a later time. The requested power to load the ESS can be expressed as: ES=(%SOC_Target(target)−%SOC_Current(current))*(Capacity / Time until the next planned ESS usage time)

[0024] The power delivered to the energy service unit (ES) can be limited by charge / discharge limits, which can be functions of a state of charge (SOC) or state of operation (SOE) of any energy service unit (ESS). The power requirement of a given ESS can be updated with each real-time on / off sampling until the next scheduled interval, as the duration and SOC change. The remaining load not covered by the portion of available power used to charge an ESS can be met by on / off cycles from unscheduled systems using a rule-based system or optimizer.

[0025] The Scheduler Processing Module 242 can process microgrid schedules based on one or more priorities within a hierarchy of constraints associated with the microgrid. This means that the switching on or off of electrical systems can be segmented and / or prioritized based on priorities for the operation of the microgrid system. Highest priority constraints (Priority 1) might include, for example, providing sufficient net power to meet the load, ensuring that no single system and / or group of systems exceeds its respective maximum limits (active and reactive power), ensuring that no single system or group of systems operates below its respective minimum limits (active and reactive power), ensuring that at least one grid-forming system is present, and complying with resilience / redundancy requirements.Lower priority restrictions (priorities 2-5) may include, for example, maintaining a positive rollover reserve, maintaining a negative rollover reserve, maintaining a SOC / SOE within a minimum and maximum range as closely as possible, charging and / or discharging based on a minimum / maximum SOC of any ESS systems in the microgrid 100, and maintaining a desired load within a desired maximum and minimum load level to maximize the service life of ESS systems in the microgrid and, for example, to avoid wet stacking (unburned fuel in the exhaust).

[0026] In some embodiments, the scheduler processing module 242 can be configured to, for example, receive one or more scheduled power on or off commands (e.g., from the on or off schedule of the micronet on or off schedule input 208), convert the SOC schedules into power schedules, check a power on or off schedule against a minimum / maximum limit, and revise an on or off schedule.

[0027] With brief reference to Fig. 6A and Fig. Figure 6B shows the schedule profile filtering 602, 612, which can be performed in the module for the planned activation or deactivation of systems 218. Schedule profile filtering is a method for determining which planned systems should be used in the micronetwork 100 at a specific operating time. Schedule profile filtering 602, 612 can be used to schedule one or more systems for activation or deactivation in the micronetwork 100. Fig. Figure 6A shows a performance requirement level of the scheduler 604 as a function of a time and a scheduler interval 606. Fig. Figure 6B shows a performance requirement level of scheduler 614 as a function of time and a scheduler interval 616. Levels 608 are shown in Fig. 6A is interpolated from one interval to the next, and levels 618 are in Fig. 6B is held using "Hold". The determination of whether to use interpolation or hold can be integrated into a user input (e.g., using a user input device such as an HMI). Scheduler inputs can be filtered based on operating minimums / maximums for power, charge / discharge limits, ramp rate limits, desired min / max for SOC / SOE, and the filtered data, including any interpolations. These functions can be visualized on a user input device (e.g., an HMI). In some implementations, these functions can be automatically presented to a user (e.g., customer / application engineer) with a filter profile and overriding inputs.

[0028] Fig. Figure 7 shows a diagram 700, which depicts a scheduler 702 load request as a function of time and scheduler intervals 704. The scheduler 702 load requests represent a SOC level desired for a single ESS facility within the micronetwork and can be entered, for example, by a user via a GUI or another system for interface with the micronetwork system controller 130. As shown in Fig. As shown in Figure 7, the hypothetical system operates at point 708 between two planned charging levels (706B, 706C) at different intervals. The planned charging request level in the next planned interval can be higher than the planned charging request level in the previously planned interval. For example, the scheduler processing module 242 can define a SOC / SOE target for a specific ESS system and can generate a power request for that ESS system based on reaching the target level. The target can be met, for example, using the equation: Requested Power = (%SOC Target - %SOC Current) * (Capacity / Time Until Next Scheduled Time). The charging and discharging limits for the specific ESS system can be used to restrict the charging and discharging of the ESS system, and these limits can be stored, for example, in a module of the system controller 130 (e.g., memory 226).In some embodiments, the requested performance level can be updated with each sampling of a real-time activation or deactivation of the various systems. The diagrams in the . Fig. 6A and Fig. Figure 6B illustrates various examples of power requirement inputs based on sampling the real-time power-on or power-off signal. That is, the scheduler inputs can be entered via an interpolated level, as shown in Figure 6B. Fig. 6A can be represented, or entered as a constant (or "hold" level) based on the next or previous requested power signal. In some embodiments, a remaining load among unplanned systems can be distributed using a rule-based system or an optimization-based system.

[0029] The differential evaluation module 216 can include one or more rules or logic for monitoring the actual load of each of the loads 116, as well as the power and energy available in real time from the various systems connected to the microgrid 100 to supply the loads 116. The differential evaluation module 216 can calculate the difference between the current load and the available power to generate a real-time capacity measurement in active and reactive power. Additionally, the differential evaluation module 216 can measure the difference between the current load and the planned load in real time based on the various inputs to the differential evaluation module 216.

[0030] The Scheduled System Activation Module 218 can apply real-time activation or deactivation rules to adjust the operation of the microgrid 100 based on the differences calculated in the differential evaluation module 216. These rules can be rule-based or optimization-based, depending on the situation. For example, the Scheduled System Activation Module 218 can include adaptive activation or deactivation logic that can handle situations where scheduled sources are only partially or not at all available. In such cases, the unscheduled power sources could follow real-time activation or deactivation methods. In the event of significant deviations between the scheduled activation or deactivation and real-time conditions, the system controller 130 can revise the scheduled activation or deactivation for systems, and this revision can also follow either rule-based or optimization-based logic.The on / off logic can be designed to consider various objectives, such as economic efficiency, emission reduction, or increasing the penetration of renewable energies. The selection of objectives can depend on the goals and priorities of the microgrid 100, as determined, for example, based on user input. The module for switching scheduled systems on or off, 218, ensures that the microgrid 100 is flexible and scalable to accommodate changes in the microgrid configuration, the addition of new systems, and evolving objectives. For example, the module for switching scheduled systems on or off, 218, can generate the on / off signal 244 for scheduled systems and / or the level power signal 246. The add / drop module 220 for unscheduled systems can receive an input from the differential evaluation module 216 and generate the power signal 246 for unscheduled systems.Module 222, used to switch unplanned systems on or off, can receive an input from the differential evaluation module 216 and generate the level of the power signal 250 for the unplanned systems. Fig. Figure 2B shows a system controller 130'. Unless explicitly stated otherwise, the system controller 130' can have any of the features or functionalities associated with the system controller 130. The system controller 130' can receive inputs 202' (e.g., a micronet configuration 206', a turn-on or turn-off schedule 208', and a current load level feedback 238'), which may be substantially similar to the inputs 202, and produce outputs 204'. The system controller 130' can include a scheduled turn-on or turn-off processing module 242', a differential evaluation module 216', a processor 224', and memory 226'. Unless otherwise specified, the scheduled turn-on or turn-off processing module 242', the differential evaluation module 216', the processor 224' and the memory 226' can each have any of the features and functionalities associated with the scheduler processing module 242, the differential evaluation module 216, the processor 224 and the memory 226, respectively.are connected to memory 226. The system controller 130' can also include a scheduled system on / off module 218', a delta on / off module 268, and a final on / off module 270.

[0031] Unless explicitly stated otherwise, the Scheduled Systems On / Off Module 218' may include all features and functionalities associated with the Scheduled Systems On / Off Module 218, as well as the additional features described herein. The Scheduled Systems On / Off Module 218' may apply real-time on / off rules to adjust the operation of the microgrid 100 based on differences calculated in the Difference Evaluation Module 216'. These rules may be rule-based or optimization-based, depending on the situation. For example, the Scheduled Systems On / Off Module 218' may include adaptive on / off logic capable of handling situations where scheduled sources are only partially or not at all available. In such cases, the unscheduled power sources could follow real-time on / off methods.In the event of significant deviations between the planned activation or deactivation and real-time conditions, the System Controller 130 can revise the planned activation or deactivation of systems, and this revision can also follow either rule-based or optimization-based logic. The activation or deactivation logic can be designed to consider various objectives, such as economic efficiency, emission reduction, or increasing the penetration of renewable energies. The selection of objectives can depend on the goals and priorities of the Microgrid 100, as determined, for example, based on user input. The 'Planned Systems 218' activation or deactivation module can ensure that the Microgrid 100 is flexible and scalable to accommodate changes in the Microgrid configuration, the addition of new systems, and evolving objectives.The module for switching planned systems 218' on or off can, for example, generate the on / off signal 244' for planned systems and / or the level power signal 246'.

[0032] The delta switch-on or switch-off module 268 is a module that can switch a difference between a planned load and an unplanned load (i.e., a delta load) on or off to one or more unplanned systems. The delta switch-on or switch-off module 268 can receive an input from the difference evaluation module 216' and the switch-on or switch-off module for planned systems 218' and generate the on / off signal 248' for unplanned systems. The final switch-on or switch-off module 270 can receive an input from the delta switch-on or switch-off module 268 and the switch-on or switch-off module for planned systems 218' and generate the level of the power signal 250' for the unplanned systems. Commercial applicability

[0033] The disclosed aspects of the present application can be used to optimally manage hybrid energy systems in microgrids. Currently, microgrid systems cannot effectively manage and individually switch on or off the microgrid's energy generation resources within the context of system-wide operation based on their respective individual limits. This can be particularly difficult to manage for each given ESS system in the microgrid, which has individual charging and discharging limits for each given scenario.

[0034] With reference to Fig. 3A will be a method 300 for operating a micronetwork, such as the micronetwork 100 from Fig. 1, using Control Panel 130 from Fig. 2A is shown. It is understood that the individual steps of the process are shown in Fig. The procedures shown in 3A are merely examples, and implementations of the procedure may involve more or fewer steps than those shown in 3A. Fig. 3A may include.

[0035] In steps 302 and 304, the control unit 130 can receive the current microgrid configuration and status. This information can include detailed data about the systems, loads, and structure of the microgrid (including the state of charge (SOC) or state of energy availability (SOE) of any energy storage systems (ESS) in the grid) and can be based, for example, on the microgrid configuration input 206. This can include information about system types (e.g., solar panels, wind turbines, fuel cells), rated power, technical specifications (such as efficiency and conversion rates), geographic locations and operating states, as well as data about energy storage systems such as batteries or hydrogen storage systems. This input can include the capacity of each storage unit, charge and discharge rates, state-of-charge (SOC) limits, state of energy availability (SOE), and specific operating requirements. It can also identify load types (e.g.,Residential, commercial, industrial), their power requirements, load patterns (including peak and off-peak times), and priority levels (critical vs. non-critical). It can also include how different systems and loads within the microgrid are interconnected, including information on electrical wiring, switching devices, circuit protection, and control systems used to facilitate power flow between different components. If the microgrid 100 is grid-connected (i.e., to a utility grid 104), it can include information on how the microgrid interacts with the utility grid 104, including grid connection points, voltage levels, and protocols for grid interactions, such as frequency regulation, islanding capabilities, and demand response capabilities. The configuration and status can also include details of any predefined control logic or operating modes.This can include rules for peak load shedding, strategies for optimizing self-consumption of renewable energy, and protocols for switching between grid and island operation during power outages. The configuration and status can also include environmental data, such as weather conditions, forecasts, and local climate patterns, to account for factors like solar irradiance and wind conditions. The information can also include economic considerations, such as utility pricing plans, tariffs, and financial incentives or penalties associated with grid interactions.

[0036] In step 306, the system controller 130 can receive and / or estimate the current load level in the system. This information can be derived, for example, from the current load level input 238 (as measured by various sensors or other measuring devices within the microgrid 100), or be an estimate based on one or more schedule inputs, based on historical loads (such as those stored in memory 226), or based on one or more other inputs. The current load level (estimated or actual) can be used to determine a required electrical output power, which can then be used in one or more other steps of procedure 300.

[0037] In step 308, the control unit 130 can receive scheduled power call commands. This information can be received, for example, based on the turn-on or turn-off schedule of the microgrid turn-on or turn-off schedule input 208. In step 310, the control unit 130 can convert the SOC schedules into power schedules. This conversion can involve transforming an expected SOC into the power required to achieve the SOC at a given time, and can be based, for example, on the current SOC for an ESS plant and a desired SOC for the same ESS plant.

[0038] In step 312, the control unit 130 can check a power on / off schedule against minimum and maximum constraints and revise the power on / off schedule based on these constraints. The minimum and maximum constraints can be part of one or more signals from the microgrid on / off schedule input 208, can be stored in memory 226 and retrieved based on the microgrid configuration input 206, or can be supplied to the control unit 130 from another source.

[0039] In step 314, the system controller 130 can determine the total delta load in the microgrid 100 by subtracting the total planned power, as determined, for example, by the microgrid start or stop schedule input 208, from the load in the system, as determined by the current load level input 238. This difference can be determined in the differential evaluation module 216. For space reasons, the total delta load may also be referred to as the "net load" in some of the illustrations.

[0040] In step 316, the control unit 130 can determine, based on a total delta load and a reserve load, whether one or more unplanned systems should be added or removed. This determination can be made, for example, in the differential evaluation module 216. In step 318, the control unit 130 can determine whether the net load exceeds the operating maximum of running, unplanned systems. If the net load exceeds the operating maximum of running, unplanned systems, the control unit 130 can determine whether the total real-time start-up or shutdown power for planned systems equals the load minus the operating maximum of unplanned systems, and whether a delta load for planned systems equals the real-time start-up or shutdown power for planned systems minus the originally planned start-up or shutdown power in step 320.

[0041] If the answer in step 318 is no, the control unit 130 can determine in step 322 whether the net load is below the minimum operating level of unplanned systems. If no, the control unit 130 can perform a real-time switching of the planned power on or off among the planned system groups in step 326 to distribute it to individual systems within the planned system groups. If yes, the control unit 130 can determine in step 324 whether to switch planned systems on or off in real time based on a comparison of the load minus the minimum operating level of unplanned systems.

[0042] In step 328, the system can determine a delta load for scheduled systems. This delta load can be equal to the real-time turn-on or turn-off of scheduled systems minus the originally planned turn-on or turn-off of the systems. Based on this difference, the system controller 130 can determine a distribution of the total delta turn-on or turn-off across scheduled systems, while keeping the respective delta plus the planned turn-on or turn-off for each system within the limits of that system. In step 330, the system can turn systems on or off based on a delta load plus a planned load for each of the scheduled systems.

[0043] In step 332, the system controller 130 can determine a net load (revised) for the unplanned systems. This net load for the unplanned systems can be the load minus any real-time activation or deactivation of planned systems. In step 334, the system controller 130 can determine a distribution of the net load calculated in step 332 across the unplanned systems. These determined distributions can then be applied to the various individual systems within the system.

[0044] With reference to Fig. 3B will be a method 300' for operating a micronetwork such as the micronetwork 100 from Fig. 1 using the system controller 130' from Fig. Figure 2B is shown. In steps 302' and 304', the system controller 130' can receive the current microgrid configuration and status. This information can include detailed data about the systems, loads, and structure of the microgrid 100 and can be based, for example, on the microgrid configuration input 206. This can include information about system types (e.g., solar panels, wind turbines, fuel cells), rated power, technical specifications (such as efficiency and conversion rates), geographic locations and operating states, as well as data about energy storage systems such as batteries or hydrogen storage systems. This input can include the capacity of each storage unit, charge and discharge rates, SOC limits, SOE, and any specific operating requirements. This can further identify load types (e.g.,Residential, commercial, industrial), including their power requirements, load patterns (including peak and off-peak times), and priority levels (critical vs. non-critical). It can also include how different systems and loads within the microgrid are interconnected, including information on electrical wiring, switching devices, circuit protection, and control systems used to facilitate power flow between different components.

[0045] In step 306, the system controller 130 can receive and / or estimate the current load level in the system. This information can be derived, for example, from the current load level input 238 (as measured by various sensors or other measuring devices within the microgrid 100), or be an estimate based on one or more schedule inputs, based on historical loads (such as those stored in memory 226), or based on one or more other inputs. The current load level (estimated or actual) can be used to determine a required electrical output power, which can be used in one or more other steps of procedure 300.

[0046] In steps 303', 305', and 307', the system controller can receive 130 scheduled power on or off commands, convert the SOC schedules into power schedules, and review a power on or off schedule against minimum and maximum constraints to revise the power on or off schedule. The conversion can involve transforming an expected SOC into the power required to achieve the SOC at a given time and may be based, for example, on the current SOC for an ESS facility and a desired SOC for the same ESS facility. Steps 303', 305', and 307' can be substantially similar to steps 308, 310, and 312 of Procedure 300 unless otherwise specified.

[0047] In step 308, planned power commands for scheduled systems and groups can be received from the scheduler processing module, and scheduled systems can be distinguished from unscheduled systems. In step 309, the planned percentage of activation or deactivation for scheduled systems can be specified.

[0048] In step 310', a delta load can be calculated. The delta load can be calculated as the load (as determined, for example, by the feedback of the current load level input 238) minus the total planned power received by the scheduler processing module 242'. In step 312', a distribution of the total delta load for the switching on or off among the individual systems can be determined. The overall delta distribution between the systems can be determined while keeping the individual systems within their respective system constraints. In step 314', the delta load and the planned load for each planned system can be used together with the delta load for the unplanned systems.

[0049] Fig. Figure 4 shows another method 400 for operating a micronetwork system, such as the micronetwork 100 from Fig. 1. Procedure 400 could, for example, be an implementation of the one described in Fig. 3A and Fig. The method shown in 3B could be used and could employ one or more of the methods shown in Fig. 1 and Fig. The features shown in 2A / 2B are executed (e.g., one or more inputs 202, outputs 204, or modules of the system controller 130 of the micronetwork 100). It is understood that the individual steps of procedure 400 are merely exemplary and implementations of procedure 400 may include more or fewer steps than those shown in Fig. 4 shown.

[0050] In step 402, a planned deployment requirement can be obtained, which includes a schedule of the required electrical energy generation for the microgrid system for a given period, as well as a schedule of electrical systems that can fulfill the required electrical energy generation schedule. The planned deployment requirement can be provided to the system controller 130 in the form of data contained, for example, in the microgrid on / off input 208, and can include one or more active power commands for scheduled systems or system groups for a variety of systems or system groups. The microgrid on / off input 208 can be a dynamic input and can be entered by one or more users, generated by software or one or more modules connected to the microgrid system, or a combination of both.Additionally, various modules of the System Controller 130 can utilize historical data and real-time information to optimize the schedule; for example, the System Controller 130 can use a load forecasting module or a similar feature to predict one or more loads in the Microgrid 100. In some embodiments, the forecast may include one or more of the following: predicted cloud cover, predicted weather, and predicted wind speed data.

[0051] In step 404, the planned switching target can be filtered and converted into power levels, refining the input to meet the power requirements for the necessary electrical energy generation for the planned switch-on or switch-off of the microgrid system. The planned switch-on or switch-off target can be filtered and converted, for example, using a control module that can be driven by one or more algorithms and decision logic. The power levels can correspond to the different power levels required to meet the load requirements of the microgrid during a specific period (e.g., a certain number of kW, etc.), taking into account fluctuations in demand during the specified period. This conversion ensures that the microgrid operates efficiently by aligning power generation with demand.

[0052] In step 406, the actual electrical energy required for the microgrid system can be measured based on one or more electrical loads electrically coupled to the microgrid system. Energy measurement can be performed by receiving an energy demand reading from each of the various electrical loads connected to the system and summing each load's reading to quantify the total demand. Accurate measurement of the actual load enables the microgrid 100 to respond precisely to changes in the load and / or the generated power levels, as required. The sum can, for example, be entered into the system controller 130 as the current load level input 238.In some embodiments, the current load level input 238 can be a simulated actual required electrical energy level, based on the type and number of systems coupled to the grid and one or more forecasts, such as those generated by a grid forecasting module and / or a renewable energy generation forecasting module.

[0053] In step 408, the schedule for required electrical power generation can be compared with the actual electrical power generation required for the microgrid system. This comparison can reveal any discrepancies between planned and actual electrical power generation. Additionally, the comparison can serve as a diagnostic tool, allowing the system controller to assess the alignment between planned and actual conditions. Disparities identified between planned and actual power generation requirements may indicate inefficiencies, deviations, or unexpected events within the microgrid system, as well as inaccuracies introduced by forecasts generated using one or more of a grid forecasting module, a renewable energy generation forecasting module, and / or a load forecasting module.The schedule for required electrical energy generation can be updated periodically (e.g., by a user or by software).

[0054] In step 410, one or more electrical systems can be switched on or off in real time to compensate for a difference between the planned and actual electrical power generation. The use of systems in real time provides a dynamic response to meet the electrical load requirements of the microgrid 100. An additional or alternative system that may be required can be activated, for example, via a switch-on or switch-off signal (on / off signal 244 and / or power level signal 246) generated by module 218 of the system controller 130. Switching one or more electrical systems on or off on demand ensures that the microgrid maintains a stable and reliable power supply.These systems can be activated or deactivated as needed, thereby optimizing microgrid performance while adhering to energy generation schedules and accommodating unforeseen demand fluctuations. The activation or deactivation of one or more electrical systems can be optimized and based on one or more modes, including an economic mode, a minimum emission mode, and a renewable energy penetration mode, as determined by logic stored in one or more of the module 218 for scheduling the activation or deactivation of systems (which may, for example, include a load manager) or, for example, in another module of the system controller 130.

[0055] With reference to Fig. 5 is a method 500 for operating a micronetwork system, such as the micronetwork 100 from Fig. 1, shown. Method 500 could, for example, be an implementation of the in Fig. The method shown in 3A / 3B could be used with one or more of the methods described in Fig. 1 and Fig. The features shown in Figure 2 are executed (e.g., one or more inputs 202, outputs 204, or modules of the system controller 130 of the micronetwork 100). It is understood that the individual steps of Procedure 500 are merely exemplary and implementations of Procedure 500 may include more or fewer steps than those shown in Figure 2. Fig. 500 depicted.

[0056] Step 502 allows the reception of a scheduled load signal. This scheduled load signal can be based on a schedule of electrical load requirements for the microgrid system over a specific period. For example, the scheduled load signal can be received based on an input 208 for a microgrid on / off schedule and / or based on an input 238 for a current load level. The scheduled load signal input can include one or more scheduled active power commands for systems or groups of systems. The System Controller 130 can use one or more other modules or System Controller 130 inputs to generate or receive the scheduled load signal (e.g., a load forecasting module), which may include one or more predicted cloud cover, weather, and wind speed data points.

[0057] In step 504, an expected power generation signal can be received based on the expected power generation from one or more electrical systems electrically coupled to the microgrid system. The expected power generation signal can be based on the total expected power generation of the one or more systems in microgrid 100 and can be generated, for example, by a grid forecasting module. The expected power generation signal can be based on the input to microgrid configuration 206, since the microgrid configuration will determine the expected power generation level. In some embodiments, the expected power generation signal can be based on the expected power generation from one or more renewable energy generation systems and the utility network operator costs (e.g., of utility network 104).In some embodiments, the expected power generation of one or more renewable energy generation systems can be based on data relating to one or more of the following: average cloud cover, historical weather data, and historical wind speed data.

[0058] In step 506, an actual load can be measured. The actual load can be measured at a time within the specified time period. Furthermore, an actual load signal can be received to determine the actual load in the microgrid system based on a comparison with the measured load. The measured load can be measured with one or more measuring devices, counters, testers, etc., which can be electrically coupled to the microgrid system.

[0059] In step 508, the actual load signal can be compared with the planned load signal and the expected power generation signal. This comparison can be performed, for example, in the differential evaluation module 216, which can generate a signal that can be used as an input to the planned system start-up or shut-down module 218. In step 510, a differential load signal can be developed based on the difference between the planned load signal, the expected power generation signal, and the actual load signal.

[0060] In step 512, one or more electrical systems can be switched on or off to meet the differential load based on the differential load signal. The electrical systems can be switched on or off, for example, using a switch-on or switch-off signal generated in the planned system switch-on or switch-off module 218 of the system controller 130. In some embodiments, the switching on or off of one or more electrical systems can be based on one or more modes, including an economy mode, a minimum emission mode, and a maximum renewable energy penetration mode. In some embodiments, the switching on or off of one or more energy storage systems to meet differential load requirements can be downgraded in priority based on the state of charge (SOC) and state of operation (SOE) of the energy storage system. For example, if the SOC and / or SOE is below an optimal threshold.In some embodiments, the System Controller 130 can indeed be configured not to use an energy storage system in the microgrid if the SOC / SOE falls below a minimum threshold. Such minimum values ​​can be stored, for example, in a memory 226 of the System Controller 130.

[0061] As explained in more detail above, the systems and methods disclosed herein propose and elucidate a balanced operation for microgrid systems that can utilize priorities evident from cost functions, incorporate different setpoints based on lifetime and efficient operating points based on power and / or energy, and consider various energy generation and storage systems. Such an approach can significantly increase the efficiency, optimal operation, and sustainability of microgrid systems, thus contributing to the further development of the renewable energy sector. It is obvious to experts in the field that various modifications and variations can be made to the disclosed system without deviating from the scope of the disclosure.Other embodiments of the system will be obvious to those skilled in the field upon consideration of the specification and practical application of the system disclosed herein. The description and examples are intended to be considered merely exemplary, with the actual scope of disclosure being specified by the following claims and their equivalents. QUOTES INCLUDED IN THE DESCRIPTION

[0000] This list of documents cited by the applicant was automatically generated and is included solely for the reader's convenience. The list is not part of the German patent or utility model application. The DPMA accepts no liability for any errors or omissions. Cited patent literature

[0000] US 10,734,811

[0003]

Claims

[1] Method for operating a microgrid system (100), comprising: receiving a microgrid on or off schedule input (208) which includes a schedule of required electrical power generation for the microgrid system (100) for a specified period and a schedule of electrical systems capable of meeting the required electrical power generation schedule; Filtering the planned on or off input and converting the planned on or off input into power levels (608) to meet the power requirements for the required electrical power generation of the on or off plan input for the microgrid system (100); Receiving a current load level for the microgrid system (100) based on one or more electrical loads (116) that are electrically coupled to the microgrid system (100); Comparing the planned required electrical energy generation with the actual required electrical energy generation for the microgrid system (100) in order to determine a difference between the planned required electrical energy generation and the actual required electrical energy generation; and The switching on or off of one or more electrical systems in real time to meet a difference between the planned required electrical energy generation and the actual required electrical energy generation. [2] Method according to claim 1, wherein the one or more electrical systems are switched on or off in real time on the basis of constraints that are segmented into groups of different priorities. [3] Method according to claim 1, wherein the schedule of the required electrical energy generation and the schedule of the electrical systems that are capable of fulfilling the required electrical energy generation are updated periodically. [4] Method according to claim 1, wherein the one or more electrical systems comprise one or more generator sets (108), one or more energy storage systems, one or more renewable energy generation systems and a supply network (104). [5] Method according to claim 4, wherein the one or more renewable energy generation systems comprise one or more photovoltaic systems and a wind turbine. [6] Method according to claim 1, wherein one or more renewable energy generation systems are switched on or off based on a predicted cloud cover, predicted weather and predicted wind speed data. [7] Method according to claim 1, wherein the switching on or off of one or more electrical systems is based on one or more modes comprising an economy mode, a minimum emissions mode and a maximum renewable energy penetration mode. [8] Method for operating a microgrid system (100), comprising: Receiving a planned load signal based on a plan of electrical load requirements for the microgrid system (100) for a given period; Receiving an expected power generation signal based on an expected power generation from one or more electrical systems that are electrically coupled to the microgrid system (100); Measuring an actual load at a measurement time that lies within the given period and receiving an actual load signal to determine an actual load in the microgrid system (100); Comparing the actual load signal with the planned load signal and the expected power generation signal; Generating a differential load signal based on a difference between the planned load signal, the expected power generation signal, and the actual load signal; The switching on or off of one or more electrical systems to meet the differential load based on the differential load signal. [9] Method according to claim 8, wherein the planned load is entered by a user of the microgrid system (100). [10] Method according to claim 8, wherein the expected power generation signal is based on one or more expected power generation from one or more renewable energy generation systems and grid operator costs.

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