Dynamic formation and reconfiguration of standalone power systems for critical infrastructure

Abstract

A dynamic Stand-Alone Power System (SAPS) formation optimization system is developed to facilitate resilience in large utility sites with complex networks connected to multiple substations. The system ensures uninterrupted power to critical loads during substation outages while preventing reverse power flow (RPF). The system intelligently reconfigures the network at the feeder level and optimizes distributed energy resources (DERs). Operating in two phases, it first continuously evaluates how to form SAPS islands by allocating DERs to critical loads under current constraints, proactively preparing for outages and mitigating RPF risks. Once SAPS islands are formed, the system monitors and reassesses their configuration to improve service to critical loads. This adaptive and proactive approach enhances reliability and resilience in power distribution, ensuring essential operations are maintained even during disruptions.

Description

P23-1380WQ01 (GOV)DYNAMIC FORMATION AND RECONFIGURATION OF STANDALONE POWER SYSTEMS FOR CRITICAL INFRASTRUCTURECROSS REFERENCE TO RELATED APPLICATIONS

[0001] This application claims priority to U.S. Patent Application Serial No. 63 / 739,982 filed December 30, 2024 entitled, “Network Model Integrated Reconfiguration And Optimal Dispatch Of Distributed Energy Resource Assets For Resilient Supply Of Energy To Critical Loads”.GOVERNMENT CONTRACT

[0002] This invention was made with government support under W9132T-21-C-0006 awarded by the U.S. Department of Defense. The government has certain rights in the invention.FIELD OF THE INVENTION

[0003] The disclosed concept relates generally to power distribution networks, and in particular, to systems and methods for managing critical loads during long-term outages in large-scale power distribution networks.BACKGROUND OF THE INVENTION

[0004] Critical loads are widely distributed at certain large utility customer sites, including military bases and large campuses such as universities, data centers, correctional facilities, and utility networks. These types of large utility customer sites are typically centrally powered through a medium voltage electrical distribution network. The traditional option for providing backup power during an electrical outage for critical loads at these large sites is through a building level emergency backup generator supporting dedicated and pre-identified loads. As the duration of an outage becomes longer and the criticality of a load changes with time, this traditional approach loses efficacy. Additionally, traditional diesel generators are being replaced with inverter-based renewables, which in many cases may provide grid forming capabilities like synchronous machines.

[0005] For context, certain military bases are spread over large areas and primarily rely on central utility power, often using aging overhead distribution systems that are vulnerable toP23-1380WQ01 (GOV)faults. Renewable energy sources are also treated centrally, and backup generators are limited in capacity, powering only connected facilities and not being set up to export to any neighboring building(s), for example. Critical loads are scattered during long-term outages, and their priorities may change, which centralized power setups have a limited ability to address.

[0006] There is thus room for improvement in systems and methods for managing critical loads during long-term outages in large-scale power distribution networks.SUMMARY OF THE INVENTION

[0007] These needs, and others, are met by embodiments of a dynamic stand-alone power system (SAPS) formation optimization system for use in a power distribution network. The SAPS formation optimization system: (1) continuously assesses how a number of SAPS islands should be formed to optimally allocate available distributed energy resource (DER) assets to critical loads under current system constraints in order to proactively prepare for a utility power outage, and (2) after any SAPS islands have been formed, continually assesses whether the formed SAPS islands need to be reconfigured in order to better serve the critical loads of the power distribution network.

[0008] In accordance with one aspect of the disclosed concept, a SAPS formation optimization system dynamically manages power supplied to a plurality of loads in a power distribution network. The utility side of the power distribution network comprises a plurality of substations with a number of feeders connected to each substation and configured to supply power from each substation to downstream entities. The customer side of the power distribution network comprises for each given feeder a corresponding network reconfiguration switch, with each network reconfiguration switch being configured to open and close a connection between one of the substations and a load side of the given feeder. The customer side of the power distribution network comprises a number of DERs configured to be connected to and disconnected from the number of loads via a number of DER breakers, and each DER comprises a local DER controller. The SAPS formation optimization system comprises: an orchestrator, a user I / O interface, a forecaster module, an optimizer module, a number of SAPS controllers, and a number of gateway devices. The orchestrator comprises: a central controller; a message bus configured to publish messages that can be received by any entity subscribing to the message bus; a fault detection, reconfiguration, and resource management, FDRRM, module; a pluralityP23-1380WQ01 (GOV)of network attribute databases, each network attribute database being configured to store data dedicated to a unique metric related to the state of the power distribution network; a state-to-event stream interface connector configured to receive data from each network attribute database; a topological model module; and a SAPS formation data module. The user I / O interface is configured to receive input from a user and to transmit output to the user. The forecaster module and optimizer module are in communication with the central controller. The number of SAPS controllers are in communication with a number of the network reconfiguration switches and a number of the local DER controllers. The number of gateway devices are configured to facilitate communication between the orchestrator and the number of SAPS controllers. The central controller, the forecaster module, the optimizer module, and the state-to-event stream interface connector are configured to subscribe to the message bus and to transmit messages to the message bus. The FDRRM module is configured to transmit updated data to each network attribute database as the FDRRM module receives information from the power distribution network. For each given network attribute database, the state-to-event stream interface connector is configured to observe changes to the state of the data in the given network attribute database and translate each change into a discrete event, such that the state-to-event stream interface connector is configured to output a stream of events to the message bus. The central controller is configured to communicate with the user I / O interface and receive designations from the user indicating which of the loads are critical loads and which of the loads are non-critical loads. The FDRRM module is configured to receive information from the number of SAPS controllers reflecting how entities in the power distribution network are connected to one another and to transmit instructions output by the optimizer module to the number of SAPS controllers. Each critical load has a predetermined ideal level of power to receive and the optimizer module is configured to continuously assess whether each critical load is being powered at its predetermined ideal level. The optimizer module is configured to prescribe how each of the network reconfiguration switches, DERs, and loads need to be configured in order to ensure that all critical loads are powered as closely as possible to their predetermined ideal levels. When there is a substation outage such that one or more of the substations is disconnected from the customer side: the optimizer module is configured to prescribe how all of the loads connected to the one or more substations can be connected instead either to any of the substations that remain connected to the customer side or to a number of theP23-1380WQ01 (GOV)DERs; when the optimizer module determines that a number of standalone power systems islanded from the plurality of substations should be formed in order to power one or more of the critical loads with a number of the DERs, the optimizer is configured to prescribe how the network reconfiguration switches, DERs, and loads need to be configured in order to form the number of standalone power systems; after the number of standalone power systems has been formed in a first configuration, the optimizer module is configured to continuously assess whether the number of standalone power systems needs to be reconfigured to a different configuration; and when the optimizer module determines that the number of standalone power systems does need to be reconfigured to the different configuration, the optimizer module is configured to output instructions for reconfiguring the network reconfiguration switches, DERs, and loads into the different configuration.BRIEF DESCRIPTION OF THE DRAWINGS

[0009] A full understanding of the invention can be gained from the following description of the preferred embodiments when read in conjunction with the accompanying drawings in which:

[0010] FIG. 1 is a conceptual diagram showing how a SAPS (standalone power system) formation optimization system in accordance with an example embodiment of the disclosed concept is used to optimally form standalone power systems in an electrical power distribution network;

[0011] FIG. 2 is a block diagram of the SAPS formation optimization system referenced in FIG. 1 , in accordance with an example embodiment of the disclosed concept; and

[0012] FIG. 3 is a flowchart of a method for forming a SAPS in a power distribution network, in accordance with an example embodiment of the disclosed concept.DETAILED DESCRIPTION OF THE INVENTION

[0013] Directional phrases used herein, such as, for example, left, right, front, back, top, bottom and derivatives thereof, relate to the orientation of the elements shown in the drawings and are not limiting upon the claims unless expressly recited therein.

[0014] As used herein, the singular form of “a”, “an”, and “the” include plural references unless the context clearly dictates otherwise.P23-1380WQ01 (GOV)

[0015] As employed herein, when ordinal terms such as “first” and “second” are used to modify a noun, such use is simply intended to distinguish one item from another, and is not intended to require a sequential order unless specifically stated.

[0016] As employed herein, the term “controller” shall mean a programmable analog and / or digital device that can store, retrieve and process data; a processor; a control circuit; a computer; a workstation; a personal computer; a microprocessor; a microcontroller; a microcomputer; a central processing unit; a mainframe computer; a mini- computer; a server; a networked processor; or any suitable processing device or apparatus.

[0017] As employed herein, the term “number” shall mean one or an integer greater than one (i.e., a plurality).

[0018] FIG. 1 is a conceptual diagram showing how a SAPS (standalone power system) formation optimization system 100 in accordance with an exemplary embodiment of the disclosed concept operates in order to optimally form standalone power systems (SAPSs) in an electrical power distribution network 1 and dynamically reconfigure each SAPS in response to network conditions to provide sustained power to critical loads during a utility outage. As used herein, the abbreviation “SAPS” refers to a single standalone power system and the abbreviation “SAPSs” refers to multiple standalone power systems. The structure of the SAPS formation optimization system 100 is shown in FIG. 2 and detailed further later herein in connection with FIG. 2. The power distribution network 1 shown in FIG. 1 comprises multiple substations and feeders that supply power to a single large utility customer. Non-limiting illustrative examples of large utility customers who receive power from multiple substations in a power distribution network such as that shown in FIG. 1 include military bases and large campuses. In FIG. 1, dashed lines are drawn to divide the diagram into columns (Column A, Column B, Column C, Column D) and rows.

[0019] In FIG. 1, Column A shows the entities of the power distribution network 1 with each hierarchical level of the power distribution network 1 in its own row, such that the entities furthest upstream (substations) are provided in the top row and the entities furthest downstream (distributed energy resources (DERs)) are provided in the bottom row. It is noted that Column A spans two drawing sheets. The utility side of the power distribution network 1 comprises a plurality of substations 2, feeders 3, and feeder circuit breakers (feeder breakers) 4. Each substation 2 is connected to a number of downstream feeders 3. Each feeder 3 is connected to itsP23-1380WQ01 (GOV)corresponding substation 2 by a feeder breaker 4. The customer side of the power distribution network 1 comprises a plurality of network reconfiguration switches 5, a plurality of loads 6 and a plurality of DERs 7. Each network reconfiguration switch 5 is connected on the load side of each feeder 3. In order for any load 6 to receive power from the utility grid, the load 6 must be connected to the utility grid by a network reconfiguration switch 5 that is electrically connected to a feeder 3. Each DER 7 is connected on the load side of the network reconfiguration switches 5.

[0020] The plurality of loads 6 includes critical loads 6A and non-critical loads 6B. Each of the critical loads 6A and non-critical loads 6B can be referred to generally with the reference number 6. It will be appreciated that each DER 7 comprises its own dedicated local controller 7A and must have its own dedicated overcurrent protection (e.g. circuit breaker). In FIG. 1, the reference number 7A is used to denote that a dedicated local controller is inherent to each DER 7, and the reference number 8 is used to denote that there is a circuit breaker dedicated to each DER 7 (said circuit breakers being referred to hereinafter as “DER breakers 8”). It will be appreciated that the DER controller 7A for a given DER 7 is in communication with the breaker 8 dedicated to that given DER 7.

[0021] The network reconfiguration switches 5 are configured to operate as tie circuit breakers, often referred to as “tie breakers” in the relevant technological field. That is, any network reconfiguration switch 5 having a first set of connected downstream loads 6 can be configured to connect to a number of the other network reconfiguration switches 5 having a second set of connected downstream loads 6, such that forming the connection between the network reconfiguration switches 5 results in the first and second sets of loads 6 being electrically connected to the same power sources. Subsequently breaking that connection causes the first set of loads 6 and the second set of loads 6 to once more be supplied with power from separate power sources. It is noted that tie breakers are traditionally used to route power or perform reconfiguration with predefined settings. As detailed further later herein, one of the innovative aspects of the SAPS formation optimization system 100 is that it includes an optimizer module 108 that dynamically coordinates re-routing of power to provide power to critical loads during the next time horizon. That is, when the SAPS formation optimization system 100 is implemented in a power distribution network 1, the network reconfiguration switches 5 are not confined to routing power only with predefined settings. This ability toP23-1380WQ01 (GOV)dynamically reconfigure the network reconfiguration switches 5 ensures that mission critical loads are powered to the greatest extent possible during a shortage of utility power.

[0022] Prior to discussing FIG. 1 further, it is noted that the term “standalone power system” or “SAPS”, as used herein, refers to a group of loads 6 and non-utility power sources (i.e. DERs 7) that are electrically connected to each other and to a control entity (a SAPS controller 110 that is discussed further later herein), and that are islanded from the upstream substations 2. A SAPS can alternatively be referred to as an “island”. It is noted that a SAPS / island is typically formed when there is a utility fault or other circumstance preventing the critical loads 6A from reliably receiving power from the utility. When a load 6 is being powered by the utility grid (i.e. not islanded), the load 6 can be referred to be as being powered or operated in the “grid-connected” mode.

[0023] Column B in FIG. 1 depicts feeder reconfiguration for islanding tasks performed for each hierarchical level in the power distribution network 1 by the SAPS formation optimization system 100 when a utility fault occurs. At the level of the feeders 3, feeder fault management is performed. That is, if a fault is detected upstream of a given feeder 3, the feeder breaker 4 gets opened in order to isolate the fault from the downstream entities, and action is taken by the utility to address the upstream fault. At the level of the network reconfiguration switches 5, each network reconfiguration switch 5 is closed or opened in order to form a number of SAPSs. The number of SAPSs are formed to prioritize maintaining a supply of power to all critical loads 6A. Each SAPS includes a number of critical loads 6A and a number of DERs 7. At the level of the loads 6, non-critical loads 6B are shed. That is, when there is not enough capacity from the DERs 7 to power all islanded critical loads 6A, then no islanded non-critical load 6B will be supplied with power from any of the DERs 7. If there is sufficient capacity to power all islanded critical loads 6A and there is sufficient additional capacity, then the SAPS formation optimization system 100 can decide to selectively connect any non-critical loads 6B to DERs 7, provided that doing so will not adversely affect powering of the critical loads 6A. At the level of the DERs 7, the DERs 7 provide data to an optimizer module 108 of the SAPS formation optimization system 100. The optimizer module 108 is detailed further later herein.

[0024] Column C in FIG. 1 depicts the dynamic optimal SAPS formation and management tasks performed for each level in the power distribution network 1 by the SAPS formation optimization system 100 after performing the Column B tasks. At the level of theP23-1380WQ01 (GOV)feeders 3, feeder fault management continues. At the level of the network reconfiguration switches 5, dynamic optimal SAPS formation is performed by the SAPS formation optimization system 100. That is, each network reconfiguration switch 5 is dynamically opened or closed as necessary in order to ensure optimal SAPS formation in the overall power distribution network 1. Optimal SAPS formation means that all critical loads 6A that need power are being powered, and to the extent that conditions in the power distribution network 1 change after initial SAPS formation and there is no longer sufficient capacity among the available DERs 7 in the initially formed SAPS to power all critical loads 6A, lower priority critical loads 6A will be disconnected from any DERs 7 before higher priority critical loads 6A are. In addition, if a critical load 6A that was powered by a previously formed SAPS no longer requires power, that critical load 6A can be disconnected from the relevant DER(s) 7 in order to reconfigure the SAPS and power another load 6, provided that doing so does not comprise any other higher priority / critical loads 6.

[0025] Continuing to refer to Column C in FIG. 1, at the level of the loads 6, load scheduling to manage load priority is performed by the SAPS formation optimization system 100. To the extent that all critical loads 6A cannot have their power requirements met by the available DERs 7, the SAPS formation optimization system 100 determines a schedule that optimizes the available DERs 7 while adhering to the goals of powering all critical loads 6A and adhering to any other system constraints and priorities as closely as possible. At the level of the DERs 7, the SAPS formation optimization system 100 performs optimal DER management to meet resilience metrics. Example metrics for resilience include: how many critical loads 6A are supported during a grid outage and how long the critical loads 6A are supported during the outage. The highest level of resilience is reached by maximizing the number of critical loads 6A supported during a grid outage and by supporting the critical loads 6A for the full length of the grid outage. That is, the predetermined ideal level of power for a critical load 6A to receive when islanded is the same level of power that the critical load 6A receives when grid-connected. The SAPS formation optimization system 100 is configured to ensure that each DER 7 is deployed as optimally as possible in light of the need to power all critical loads 6A for as long as necessary during a grid outage and to power the critical loads 6A at their predetermined ideal levels during the outage. As detailed further later herein, the optimizer module 108 executes two functions: (1) optimizing power sources within a SAPS to support the critical loads 6 A for aP23-1380WQ01 (GOV)desired duration, and (2) reconfiguring the power distribution network 1 to optimally form different SAPSs that allow the critical loads 6A to be supported when the currently formed SAPSs no longer adequately support the critical loads 6A.

[0026] Column D in FIG. 1 depicts the feeder reconfiguration for restoration tasks performed for each level in the power distribution network 1 by the SAPS formation optimization system 100 after the utility fault has been cleared at one or more of the substations 2. It will be appreciated that because the power distribution network 1 is served by multiple substations 2, it is possible for a fault to be present at some substations 2 while other substations 2 are restored to normal service. At the level of the feeders 3, feeder fault management continues to the extent necessary. At the level of the network reconfiguration switches 5, seamless reconnecting of the critical loads 6A in each SAPS to the appropriate substations 2, to the extent possible, is performed by the SAPS formation optimization system 100. If reconnecting every critical load 6A from any existing SAPS to a substation 2 is not possible, the SAPS formation optimization system 100 also seamlessly reconfigures each remaining SAPS as necessary to optimize the allocation of the remaining islanded critical loads 6A to the available DERs 7. At the level of the loads 6, the SAPS formation optimization system 100 reconnects all islanded non-critical loads 6B to the appropriate substations 2, to the extent possible. Finally, at the DER level 7, the SAPS formation optimization system 100 optimizes DER management in preparation for a future utility grid outage. For example and without limitation, for any of the DERs 7 that are battery energy storage systems, the SAPS formation optimization system 100 would need to ensure that any depleted battery energy storage systems are recharged.

[0027] Reference is now made to FIG. 2, which shows the SAPS formation optimization system 100, in accordance with an exemplary embodiment of the disclosed concept. The SAPS formation optimization system 100 comprises an orchestrator 102 that includes a central controller 104 connected to a user input / output (I / O) interface 105, a forecaster module 106, an optimizer module 108, a number of SAPS controllers 110, and a number of gateway devices 112 that facilitate communication between the orchestrator 102 and the SAPS controllers 110. The SAPS formation optimization system 100 can be implemented as either an on-premise solution with software installed at a customer server or as cloud-based software. As indicated in FIG. 2, the optimizer module 108 comprises three sub-modules: an Opt-A module 108A, an Opt-B module 108B, and an Opt-C module 108C. Each of these modules 108A-C is detailed furtherP23-1380WQ01 (GOV)later herein. As an initial matter, it is noted that a bidirectional arrow positioned between two entities in FIG. 2 is used to indicate that there is two-way communication between the two entities. A unidirectional arrow positioned between two entities in FIG. 2 is used to indicate that the entity adjacent to the tail of the arrow provides data to the entity adjacent to the head of the arrow.

[0028] The orchestrator 102 has some functionality similar to known feeder automation (FA) products, but the orchestrator 102 differs from known FA products, as known FA products focus on isolating faults to as close to the fault as possible in order to minimize the portion of the power distribution network that loses service and prevent power outages to other areas of the power distribution system. In contrast, the orchestrator 102 is additionally directed toward the dynamic and optimal configuration and reconfiguration of SAPSs within the power distribution network 1 after a fault occurs.

[0029] In addition to the central controller 104, the orchestrator 102 comprises: a publisher-subscriber message bus 114; a fault detection, reconfiguration, and resource management (FDRRM) module 116; and a state-to-event stream interface connector 118. The publisher-subscriber message bus 114 (referred to hereinafter as the “message bus 114” for brevity) enables the SAPS formation optimization system 100 to be easily scalable, as the publisher-subscriber model means that any entity subscribing to the message bus 14 will receive all data relevant to the system 100 at the same time as all other subscribers. That is, to the extent that a new entity needs to be added to the system 100, providing the system data to the new entity is simple, as the message bus 114 does not need to be reconfigured in any manner, and the new entity only needs to be configured to subscribe to the message bus 114 in order to receive any data made available by the message bus 114.

[0030] The SAPS formation optimization system 100 further comprises a plurality of network attribute databases 119. The FDRRM module 116 provides various metrics related to the state of the power distribution network 1 to the network attribute databases 119. For example and without limitation, a first of the network attribute databases 119 can be used to store power quality data from a first SAPS, a second of the network attribute databases 119 can be used to store power quality data from a second SAPS, and for any of the DERs 7 that is an energy storage system (such as a battery energy storage system), a third of the network attribute databases 119 can be used to track how much charge remains in the energy storage system.P23-1380WQ01 (GOV)

[0031] In addition, parameters of the power distribution network 1 and updates to the topology of the power distribution network 1 can be logged by the FDRRM module 116 and added to another one of the network attribute databases 119. Alternatively, the parameters of the power distribution network 1 and updates to the topology of the power distribution network 1 can be input to the central controller 104 either manually or through automated additional data exchange, and subsequently added to the appropriate network attribute database 119. A further network attribute database 119 can store user input indicating fault type so that evaluation of potential failure modes can be performed. Another of the network attribute databases 119 can store weather data. The weather data can be obtained from a variety of sources, such as the utility’s ADMS (Advanced Distribution Management System) platform, satellite services, or a weather station located with any of the DERs 7 that are solar photovoltaic (PV) arrays in order to estimate solar PV output.

[0032] For each given network attribute database 119, the state- to- event stream interface connector 118 observes changes to the state of the data in the given network attribute database 119 and translates each change into a discrete event such that the connector 118 outputs a continuous, chronological sequence (i.e. stream) of event data structures 121 to the message bus 114. In the message bus 114 in FIG. 2, the block of event data structures 121 represents the publication by the message bus 114 of the event stream that is output by the state-to-event stream interface connector 118. Because the optimizer module 108 subscribes to the message bus 114, the optimizer module 108 always has access to the most recently updated information on the power distribution network 1 and other information published from the network attribute databases 119. In particular, through the gateways 112, the FDRRM module 116 obtains the status of all breakers (the feeder breakers 4, network reconfiguration switches 5, and DER breakers 8) and DERs 7 in the power distribution network 1. The status of the breakers 4, 5, 8 provides the network connectivity information whereas the data from the DERs 7 provides the current output from the DERs 7. The optimizer module 108 receives this SCADA data when it is published by the message bus 114 (the term “SCADA” is detailed further later herein).

[0033] For any entities that subscribe to (i.e. are in communication with) the message bus 114, each message transmitted by the message bus 114 or received by the message bus 114 from any of those entities is categorized as a specific topic. Certain entities, such as the forecaster module 106, may only want to subscribe to receive information on specific topics. For example,P23-1380WQ01 (GOV)the forecaster module 106 subscribes to power demand information provided by a corresponding network attribute database 119 and uses the demand information for demand forecasting. It will be appreciated that the power generating capacity of certain types of DERs 7 (e.g. solar PV systems) is weather-dependent, and the forecaster module 106 also subscribes to weather information provided by a corresponding network attribute database 119 and published to the message bus 114 in order to forecast power generation by each of the DERs 7. In addition, the publisher-subscriber model of the message bus 114 enables a variety of other on-platform applications 122 to subscribe and use the published data to perform other services. Non-limiting examples of the services that can be provided by the other on-platform applications 122 include Volt-VAR monitoring and demand response (DR) programs.

[0034] The FDRRM module 116 combines FLISR (fault location isolation service resolution), DERMS (DER management system), and SCADA (supervisory control and data acquisition) functionality. The FLISR aspect of the FDRRM module 116 uses automated intelligent switching operations to isolate faults and quickly restore power to unaffected areas of a power distribution system, i.e. by actuating the network reconfiguration switches 5 as necessary. The DERMS aspect of the FDRRM module 116 facilitates the optimal dispatch of DERs, distribution power flow control, and locational dispatch functions. To ensure that the dispatch of the DERs 7 is as seamless as possible, the DERMS aspect of the FDRRM module 116 provides voltage and power factor control, including voltage management during forward and reverse power flow conditions due to integration of the DERs 7. The SCADA aspect of the FDRRM module 116 uses a human machine interface (HMI) to enable a user to directly interact with industrial and infrastructure devices of the power distribution network 1 in order to control machine processes either locally or remotely and to monitor, gather, and process real-time data. The FDRRM module 116 enables data collection for forecasting the loads and sources and enables the optimizer module 108 to know the state of the network, such as: which breakers 4, 5, 8 are closed and which are open, which DERs 7 are operating, which DERs 7 are not operating, and the state of charge of a BESS (battery energy storage system). During the orchestration of the control functions, the FDRRM module 116 also enables the orchestrator 102 to close and open breakers 4, 5, 8 as well as send set points to the DERs 7 or the SAPS controllers 110.

[0035] The central controller 104, forecaster module 106, and optimizer module 108 all communicate directly with one another. This enables the forecaster module 106 and optimizerP23-1380WQ01 (GOV)module 108 to receive user input from the central controller 104 and also enables a user to receive forecast and optimization information via the central controller 104. User input can include, for example and without limitation, updates to the criticality designation of each load 6 (i.e. critical or non-critical, priority rankings of each load 6 within the critical category and within the non-critical category). The orchestrator 102 further comprises a topological model module 123 and a SAPS formation data module 124. The topological model module 123 is a dynamically updated topological model that reflects the most up-to-date connections between all of the entities in the power distribution network 1. The SAPS formation data module 124 specifies how each of the network reconfiguration switches 5, DERs 7, and loads 6 need to be configured in order to form the optimal SAPSs as prescribed by the optimizer module 108 under the current system constraints. It is noted that the real-time operations of the assets (i.e. DERs 7 and loads 6) in the SAPSs are controlled and actuated by the SAPS controllers 110, with the SAPS controllers 110 acting upon the instructions output by the optimizer module 108.

[0036] The optimizer module 108 will now be discussed in more detail. As previously noted, the optimizer module 108 comprises three sub-modules: an Opt-A module 108A for proactive contingency preparation, an Opt-B module 108B for optimal SAPS formation and dynamic SAPS reconfiguration, and an Opt-C module 108C for intra-SAPS operation. While each of the Opt-A, Opt-B, and Opt-C modules produce distinct outputs, they receive similar inputs. The Opt-A, Opt-B, and Opt-C modules 108A, 108B, 108-C all receive the inputs of network information in order to determine grid constraints, user input in order to determine user constraints, and DER information in order to determine DER constraints. Network information includes: topology of the power distribution network 1 and data on the loads 6, including forecasted power consumption information for the loads 6. User input includes: criticality designations for the loads 6, capacities of the DERs 7, mission critical requirements, and outage horizon. DER information includes: state of charge for each of the DERs 7 that are energy storage devices, forecasted photovoltaic data, and distributed generation data for the Opt-B module 108B and Opt-C module 108C.

[0037] The Opt-A module 108A is designed to estimate the impact of various utility grid outage contingencies on the power distribution network 1, and proactively increase energy reserves of the DERs 7 in anticipation of the contingencies occurring. The Opt-A module 108A uses load consumption forecast data and power generation forecast data generated by theP23-1380WQ01 (GOV)forecaster module 106 in order to perform these functions. The load consumption forecast data pertains to predictions regarding the consumption needs of each load 6 over predetermined future periods of time. The power generation forecast data pertains to predictions regarding the ability of each power source in the power distribution network 1 to provide specified amounts of power over predetermined future periods of time. As previously noted, the DERs 7 can include energy storage (ES) devices. Opt-A generates optimal charging / discharging schedules for all ES devices, i.e., to ensure that the state of charge (SOC) of all ES devices are maximized prior to the contingency. Opt-A ensures that all operations of the power distribution network 1 and SOC of ES devices are within pre- determined acceptable ranges, and that network constraints are satisfied.

[0038] The Opt-B module 108B is designed to form and dynamically reconfigure optimal standalone power systems for supporting critical loads 6A through the duration of the utility outage contingencies. In addition, when utility grid power is available, Opt-B continuously monitors voltage profiles throughout the power distribution network 1. The voltage profile refers to voltage magnitude detected at various points across a distribution line, e.g. one of the feeders 3. Monitoring voltage levels at various points across a distribution line provides information about whether a particular distribution line is in good health and whether it is being strained beyond its rated capacity. It will be appreciated that, even when utility grid power is available, supplementing utility power with DER power can be desirable to alleviate strain on the grid, among other objectives. Furthermore, it is possible for some of the substations 2 to be out of service while other substations 2 remain in service, such that some portion of the customer side of the power distribution network 1 may need to be configured into a number of SAPSs so that some of the critical loads 6A can be powered by a number of DERs 7 within a SAPS while other critical loads 6A remain powered by the utility grid. To the extent that any voltage profile in the power distribution network 1 is sub-optimal while some or all of the loads 6 are receiving power from the utility grid, the Opt-B module 108B determines whether any of the loads 6 should be reconfigured to receive utility power from a different substation 2, in order achieve a net improvement to the voltage profiles in the power distribution network 1.

[0039] The Opt-B module 108B continuously assesses the feasibility of different configurations of the power distribution network 1 network topology to supply loads 6 based on specified criticality constraints. This assessment includes using forecasts of solar photovoltaicP23-1380WQ01 (GOV)PV data for those DERs 7 that are PV systems, evaluating capacity data for other available DERs 7, and reviewing projected load consumption data. Also included in the assessment are reviewing statuses of the network breakers (including the opening of any feeder tie breakers, i.e. network reconfiguration switches 5, or DER breakers 8 due to a fault), reviewing power setpoints of available DERs 7, and reviewing whether designations of which loads 6 are critical loads 6A have changed. Because the Opt-B module 108B continuously performs this assessment, the determination of how each SAPS should be formed can change after the initial formation of the SAPSs, especially when the criticality designations of the loads 6 have changed such that reconfiguration of the SAPSs is necessary to support those loads that are presently designated as the critical loads 6A. Whenever the Opt-B module 108B determines that the topology of any of the SAPSs needs to be reconfigured in order to power the critical loads 6A, the Opt-B module 108B outputs instructions for the SAPS controllers 110 to implement the reconfiguration recommended by the Opt-B module 108B. For utility outage contingencies that involve only a partial outage, i.e. such that only some substations 2 are out of service while other substations 2 are still in service, the Opt-B module 108B dynamically reconfigures the feeders 3 in order to connect certain loads 6 to a different substation 2 than the substation 2 to which they are currently connected. In sum, the outputs of the Opt-B module 108B are: prescribed configurations for the network configuration switches 5 in order to form the optimal SAPSs, distributed generation (DG) set-points for each prescribed SAPS, prescribed charging / discharging rates for all of the energy storage in each prescribed SAPS, and load shedding set points for each SAPS.

[0040] The Opt-C module 108C is directed toward ensuring that resources are allocated optimally within each given SAPS and focuses on the operations of DERs 7 to support the critical loads 6A within each given SAPS. The Opt-B module 108A and Opt-C module 108C have similar functionalities, but while Opt-B recommends how to optimally form SAPSs with tiebreaker operations and schedules of DERs 7 that are germane to the entire islanded portion of the power distribution network 1 network, Opt-C allocates schedules of each DER 7 within the electrical boundaries of each individual SAPS. The Opt-C module 108C adapts to changes such as changes in the availability of DERs 7, opening of any of the network breakers (including the feeder tie breakers, i.e. network reconfiguration switches 5, or DER breakers 8) due to a fault, and changes in forecasted data to meet the mission critical demand for a user-specified timeP23-1380WQ01 (GOV)horizon. When the solutions yielded by Opt-C are not mathematically feasible or if a SAPS no longer has enough DERs 7 to supply its critical loads 6A, particularly when the designations of which loads 6 are critical loads 6A have changed, Opt-B will dynamically provide a newer SAPS topology, following which Opt-C will optimize the schedules of DERs 7 within the newly formed SAPS. In sum, the outputs of the Opt-C module 108C are: DG set-points for each DER 7 within each SAPS, prescribed charging / discharging rates for all of the energy storage DERs 7 within each SAPS, and load shedding set points within each SAPS.

[0041] The SAPS formation optimization system 100 is configured to operate the SAPS controllers 110 in four different modes of operation, with each possible SAPS mode of operation corresponding to a unique state of the power distribution network 1. The four states of the power distribution network 1 are: (1) normal operation, (2) new outage, (3) prevailing outage, and (4) recovery. The power distribution network 1 is in the normal state when all loads 6 are able to receive power from the utility grid (i.e. from the substations 2). In the normal state, the SAPS formation optimization system 100 is configured to bypass the SAPS controllers 110 so that all loads 6 are controlled in the grid- connected mode. The power distribution network 1 is in the new outage state when an outage is initially detected and the feeder breakers 4 and network reconfiguration switches 5 are operated to form SAPSs. All of the loads 6 that have been islanded from the utility grid after detection of a new outage can be thought of as forming an islanded microgrid, and for this islanded microgrid the DERs 7 with the highest capacity and reserve are selected to function as the grid-forming generator. The SAPS controllers 110 then configure the other DERs 7 and loads 6 to form the SAPS prescribed by the optimizer module 108 based on priority.

[0042] The power distribution network 1 is in the prevailing outage state when an outage persists after the formation of the initial SAPSs. In this state, each SAPS controller 110 continually assesses whether a different SAPS configuration is needed to improve resiliency. The assessment is based on the solution received from the optimizer module 108, and specifically the Opt-B module 108B. If the assessment results in the determination that a different SAPS configuration does need to be implemented in order to improve resiliency, then each SAPS controller 110 actuates the network reconfiguration switches 5 to reconfigure the SAPSs in accordance with the recommendation of the Opt-B module 108B, and the grid-forming DERs 7 operate accordingly. The power distribution network 1 reaches the recovery state onceP23-1380WQ01 (GOV)the grid recovers from the outage, and the SAPS formation optimization system 100 instructs the SAPS controllers 110 to actuate the network reconfiguration switches 5 to restore the loads 6 and DER 7 to the pre-outage network configuration. In addition, any of the DERs 7 that are diesel generators are disconnected from the power distribution network 1 once the recovery state is reached.

[0043] Reference is now made to FIG. 3, which is a flowchart of a method 200 for forming a SAPS in a power distribution network, in accordance with an exemplary embodiment of the disclosed concept. The method 200 is executed, for example, by the SAPS formation optimization system 100 depicted in FIG. 2 and is described in conjunction with the SAPS formation optimization system 100. However, it will be appreciated that the method 200 may be employed in other systems as well without departing from the scope of the disclosed concept. As an initial matter, due to the highly interconnected nature of the various entities within the SAPS formation optimization system 100, each block in the flowchart includes a header that indicates which entity in the SAPS formation optimization system 100 performs the step described in the block. In addition, it should be noted that collection of data from the power distribution network 1 is continuously performed by the various entities of the SAPS formation optimization system 100.

[0044] The first set of steps in the method 200 are steps 201A, 201B, and 201C. At 201 A, the FDRRM module 116 collects field data. The field data includes electrical operational data from the power distribution network 1 , and can also include other relevant environmental data such as weather data. At 201B, a user provides input through the user I / O 105. Nonlimiting examples of user input that can be provided at 20 IB include load criticality designation (i.e. critical or non-critical), load priority designation (i.e. within the critical designation or non-critical designation, how a given load should be prioritized compared to other loads within the same designation), historical data, power generation capacities of individual DERs 7, storage capacity of energy storage DERs 7, and mission critical requirements. At 201C, the central controller 104 receives the field data and user input data provided at 201A and 201B.

[0045] From step 201 C, the method proceeds concurrently to steps 202A and 202B. At 202A, the FDRRM 116 formats the field data with nomenclature to reflect the topology of the power distribution network 1 network. At 202B, the forecaster module 106 generates forecast data. This forecast data includes projected power consumption use for each load 6 over futureP23-1380WQ01 (GOV)periods of time based on historical use, and projected power supply capacity for each DER 7 over future periods of time based on present power supply capacity and projected future consumption by the loads 6, among other metrics. The field data output at step 202A and forecast data output at step 202B are both input to the optimizer module 108 at step 203. At step 203, the optimizer module 108 determines which combinations of DERs 7 and loads 6 should be grouped together in distinct islands (i.e. each island being a SAPS) in order to optimize the use of available DER power supply capacity and power as many of the critical loads 6A at normal levels of power consumption for as long as possible, should a disruption in the utility grid occur at the present moment.

[0046] Continuing to refer to step 203, it is noted that, because the power distribution network 1 includes multiple substations 2 and feeders 3, the optimizer module 108 considers the possibility of partial grid failures (i.e. some substations 2 being out of service while other substations 2 remain in service), in addition to total grid failure (i.e. all substations being out of service). As such, the determination made at step 203 regarding optimization of resources includes a determination of whether certain loads 6 presently receiving grid power should be reconfigured to be connected to a different feeder 3 and / or a different substation 2. In addition, the condition of reverse power flow anywhere in the power distribution network 1 at step 203 will also lead to a determination that certain loads 6 should be reconfigured to receive power from a different power source. Reverse power flow will occur when a DER 7 supplies power to the utility grid. The method proceeds to step 204 and step 207 from step 203. At step 204, the optimizer determination produced at 203 is provided to the user through the user I / O 105. Step 207 is discussed later herein.

[0047] After step 201 A, in addition to proceeding to step 201 C in order to provide the field data collected by the FDRRM 116 to the controller 104, the method also proceeds to step 205 in order to determine whether there is a grid event, i.e. an outage, fault, or other disruption to power being supplied at normal capacity to any loads 6 by the utility grid. When there is no grid event, the method returns to step 201 A to continue collecting field data. When there is a grid event, the method proceeds to step 206 from step 205. At step 206, the central controller 104 receives the field data collected by the FDRRM 116 at step 201 A. The method then proceeds to step 207.

[0048] At 207, the FDRRM 116 transmits commands to the relevant SAPS controllersP23-1380WQ01 (GOV)110 in order to form a number of SAPSs (islands) in the power distribution network 1 based on the information output by the central controller 104 after step 206 and according to the determination output by the optimization module 108 at step 203. In order to form the prescribed SAPSs as commanded by the FDRRM 116, the SAPS controllers 110 actuate the network reconfiguration switches 5 as necessary in order to island the relevant loads 6 and DERs 7 from the utility grid, and actuate each DER’s local controller 7A to be connected to the prescribed load(s) 6.

[0049] The method proceeds to 208 from 207, where the FDRRM 116 collects data on each formed SAPS, including power consumption by each load 6 and power supplied by each asset (i.e. DER 7), among other data. The data output by the FDRRM 116 at step 208 and the data output by the forecaster module 106 at step 202B is provided to the optimizer module 108 at step 209. At step 209, the optimizer prescribes, for each formed SAPs, how long and at what power supply rate each DER 7 can supply power to the connected loads 6. At step 210, each SAPS controller 110 provides set points to each given DER 7 (i.e. output targets for voltage and current by the given DER 7) and instructs each local DER controller 7A to actuate its DER 7 accordingly. Step 210 is represented as multiple blocks in FIG. 3 simply to denote that each individual SAPS controller 110 is commanded separately from every other SAPS controller 110.

[0050] While specific embodiments of the invention have been described in detail, it will be appreciated by those skilled in the art that various modifications and alternatives to those details could be developed in light of the overall teachings of the disclosure. Accordingly, the particular arrangements disclosed are meant to be illustrative only and not limiting as to the scope of disclosed concept.

Claims

P23-1380WQ01 (GOV)What is claimed is:

1. A SAPS formation optimization system for dynamically managing power supplied to a plurality of loads in a power distribution network, wherein a utility side of the power distribution network comprises a plurality of substations with a number of feeders connected to each substation and configured to supply power from each substation to downstream entities, wherein a customer side of the power distribution network comprises for each given feeder a corresponding network reconfiguration switch, each network reconfiguration switch being configured to open and close a connection between one of the substations and a load side of the given feeder, wherein the customer side of the power distribution network comprises a number of DERs configured to be connected to and disconnected from the number of loads via a number of DER breakers, wherein each DER comprises a local DER controller, the SAPS formation optimization system comprising:an orchestrator, the orchestrator comprising:a central controller;a message bus configured to publish messages that can be received by any entity subscribing to the message bus;a fault detection, reconfiguration, and resource management, FDRRM, module; a plurality of network attribute databases, each network attribute database being configured to store data dedicated to a unique metric related to the state of the power distribution network;a state-to-event stream interface connector configured to receive data from each network attribute database;a topological model module; anda SAPS formation data module;a user I / O interface configured to receive input from a user and to transmit output to the user;a forecaster module in communication with the central controller;an optimizer module in communication with the central controller;a number of SAPS controllers in communication with a number of the network reconfiguration switches and a number of the local DER controllers; andP23-1380WQ01 (GOV)a number of gateway devices configured to facilitate communication between the orchestrator and the number of SAPS controllers,wherein the central controller, the forecaster module, the optimizer module, and the state-to-event stream interface connector are configured to subscribe to the message bus and to transmit messages to the message bus,wherein the FDRRM module is configured to transmit updated data to each network attribute database as the FDRRM module receives information from the power distribution network,wherein for each given network attribute database, the state-to-event stream interface connector is configured to observe changes to the state of the data in the given network attribute database and translate each change into a discrete event, such that the state-to-event stream interface connector is configured to output a stream of events to the message bus,wherein the central controller is configured to communicate with the user I / O interface and receive designations from the user indicating which of the loads are critical loads and which of the loads are non-critical loads,wherein the FDRRM module is configured to receive information from the number of SAPS controllers reflecting how entities in the power distribution network are connected to one another and to transmit instructions output by the optimizer module to the number of SAPS controllers,wherein each critical load has a predetermined ideal level of power to receive and the optimizer module is configured to continuously assess whether each critical load is being powered at its predetermined ideal level,wherein the optimizer module is configured to prescribe how each of the network reconfiguration switches, DERs, and loads need to be configured in order to ensure that all critical loads are powered as closely as possible to their predetermined ideal levels, and wherein, when there is a substation outage such that one or more of the substations is disconnected from the customer side:the optimizer module is configured to prescribe how all of the loads connected to the one or more substations can be connected instead either to any of the substations that remain connected to the customer side or to a number of the DERs,when the optimizer module determines that a number of standalone powerP23-1380WQ01 (GOV)systems islanded from the plurality of substations should be formed in order to power one or more of the critical loads with a number of the DERs, the optimizer is configured to prescribe how the network reconfiguration switches, DERs, and loads need to be configured in order to form the number of standalone power systems,after the number of standalone power systems has been formed in a first configuration, the optimizer module is configured to continuously assess whether the number of standalone power systems needs to be reconfigured to a different configuration, andwhen the optimizer module determines that the number of standalone power systems does need to be reconfigured to the different configuration, the optimizer module is configured to output instructions for reconfiguring the network reconfiguration switches, DERs, and loads into the different configuration.

2. The SAPS formation optimization system of claim 1 ,wherein the optimizer module includes an Opt-A module configured to utilize load consumption forecast data and power generation forecast data generated by the forecaster module in order to perform proactive contingency preparation for a number of contingencies, wherein the load consumption forecast data reflects predictions regarding the consumption needs of each load over pre-determined future periods of time,wherein the power generation forecast data reflects predictions regarding the ability of each power source in the power distribution network to provide specified amounts of power over pre-determined future periods of time, andwherein, for any given contingency in the number of contingencies, the Opt-A module is configured to estimate an impact of the given contingency on the customer side and output instructions to proactively increase energy reserves on the customer side based on the estimate.

3. The SAPS formation optimization system of claim 2,wherein the proactively increasing energy reserves comprises actuating optimal charging and / or discharging of all energy storage devices in the customer power distribution system in order to ensure that the state of charge of the energy storage devices are maximized prior to the given contingency occurring.P23-1380WQ01 (GOV)4. The SAPS formation optimization system of claim 1 ,wherein the optimizer module includes an Opt-B module configured to continuously monitor voltage profiles in the power distribution network and dynamically output instructions for reconfiguring the connections between the loads and the feeders when the Opt-B module determines that reconfiguring the connections will result in a net improvement to the voltage profiles in the power distribution network.

5. The SAPS formation optimization system of claim 4,wherein the Opt-B module is configured to generate instructions to optimize formation of the number of standalone power systems so that each critical load will receive power at its predetermined ideal level for an expected duration of the substation outage.

6. The SAPS formation optimization system of claim 4,wherein the Opt-B module is configured to use solar PV forecast data, load consumption forecast data generated by the forecaster module, and power generation data for all of the DERs generated by the forecaster module to continually assess feasibility of different configurations of a network topology of the power distribution network to supply the loads based on pre-specified criticality constraints.

7. The SAPS formation optimization system of claim 5,wherein the optimizer module includes an Opt-C module configured to generate optimal dispatch schedules of the number of DERs within each standalone power system to supply power to the critical loads at their predetermined ideal levels.

8. The SAPS formation optimization system of claim 7,wherein, for any given standalone power system in the number of standalone power systems, the Opt-C module provides instructions for shedding of the loads in the given standalone power system to be executed in the event that the number of DERs in the given standalone power system cannot power all critical loads in the given standalone power system for an expected duration of the substation outage.P23-1380WQ01 (GOV)9. The SAPS formation optimization system of claim 7,wherein after the number of standalone power systems has been formed in the first configuration, when the dispatch schedules of the number of DERs generated by the Opt-C module for a given standalone power system of number of standalone power systems cease to be sufficient to supply power to the critical loads at their predetermined ideal levels, the Opt-B module is configured to dynamically generate new instructions to reconfigure the network reconfiguration switches, DERs, and loads into the different configuration.

10. The SAPS formation optimization system of claim 1 ,wherein at least one of the network attribute databases is configured to store power demand information,wherein the forecaster module is configured to subscribe to the stream of events containing power demand information published by the message bus and use the power demand information to produce demand forecasts.

11. The SAPS formation optimization system of claim 1 ,wherein at least one of the network attribute databases is configured to store weather information,wherein the forecaster module is configured to subscribe to the stream of events containing weather information published by the message bus and use the weather information to produce a forecast of power generation for each of the DERs.

12. The SAPS formation optimization system of claim 1,wherein the optimizer module is configured to determine that the number of standalone power systems needs to be reconfigured to the different configuration when the optimizer module receives feedback from the power distribution network that any of the feeder breakers, network reconfiguration switches, or DER breakers has opened due to a fault.

13. The SAPS formation optimization system of claim 1,P23-1380WQ01 (GOV)wherein the optimizer module is configured to determine that the number of standalone power systems needs to be reconfigured to the different configuration when the central controller receives a designation indicating that a second subset of the loads are critical loads after having received a previous designation indicating that a first subset of the loads are critical loads.

Images