A computer-implemented method for determining optimal meshing in a low voltage electricity network

Abstract

The present disclosure relates to a computer-implemented method to determine optimal meshing in a low voltage electricity network in network planning stage. The method may comprise: (i) modelling an existing low voltage electricity network; (ii) generating modelled network data, including network topology, and historical and forecast data for each connection point; (iii) processing modelled network data to determine load flow data related to power distribution, including current and voltage magnitude and direction; and to (iv) generate connections data, including a list of alternative connections (5) between network nodes (4) within the same or different subnetworks (1); and (v) processing connections data, network topology, and load flow data to identify any alternative connections (5) from the list of alternative connections (5) that optimize predefined criteria. The method enables electricity network managers to identify the most promising alternative connections (5) for meshing, thereby supporting objective and proactive technical interventions on electricity network.

Description

[0001] DESCRIPTION

[0002] A COMPUTER-IMPLEMENTED METHOD FOR DETERMINING OPTIMAL MESHING IN A LOW VOLTAGE ELECTRICITY NETWORK

[0003] FIELD OF THE DISCLOSURE

[0004] The present disclosure relates to the distribution of electric energy through the electricity network, and more specifically to methods for enhancing electricity network via new interconnections in the network.

[0005] PRIOR ART

[0006] An electricity network is a physical infrastructure for the production, transmission and distribution of electric power. It is a complex system formed by interconnected networks of power stations, transmission lines and substations configured for the supply of electricity from generation sources to end-users.

[0007] The ability to adapt the electric voltage is the basis of the operation of an electricity network. In fact, in order to ensure that electricity is transmitted efficiently and safely, from its generation to its final consumer, an electricity network integrates several electricity voltage networks, which are divided into high, medium and low voltages.

[0008] High voltage electricity networks are transport networks used to transport high voltage electricity over long distances, from generation centres to transformer substations, where electricity is finally converted to medium voltage.

[0009] Medium voltage electricity networks are distribution networks used to distribute medium voltage electricity from transformer substations to distribution substations, used to supply urban areas and large electricity consumers such as large industries, hospitals and airports. For that purpose, distribution substations include transformers to convert medium voltage electricity from distribution networks to lower voltages for distribution to end-users.

[0010] In urban areas, distribution substations are connected to distribution, secondary transformers, which are typically located near connection points, where enduser premises are connected to the electricity network. These transformers reduce the voltage level to low voltage, typically to 400 V. The resulting low voltage electricity network then delivers low voltage electricity to end-users in urban or rural areas, including residential, commercial, and small industrial consumers.

[0011] With the energy transition, the diversification of decentralized energy production sources and electrification are factors that impact the performance of an electricity network and pose significant challenges for distributors, namely in optimizing technical interventions in the network to ensure reliability and efficiency specially in low voltage electricity networks.

[0012] Solutions known in the art involve meshing feeders of low voltage electricity networks as a lever to address these challenges. Such solutions include creating interconnection possibilities between different low voltage subnetworks, thereby enhancing their resilience, by reducing interruptions, losses, voltage issues, and improving the overall capacity potential.

[0013] However, meshing low voltage electricity networks requires the project of new lines and the installation of switching devices to preserve the radial structure of the feeders, following the addition of these new interconnection lines. As the existing solutions are based on human evaluation which, as experienced as it may be, is subjective, they may lead to inefficient or unfounded solutions.

[0014] The present solution intended to innovatively overcome such issues. SUMMARY OF THE DISCLOSURE

[0015] The present disclosure relates to a computer-implemented method to determine optimal meshing in a low voltage electricity network, which include a plurality of distribution transformers, connection points, and feeders; each feeder comprising at least one branch connecting a distribution transformer to at least one connection point, thereby forming a subnetwork. This method may comprise the steps of: i. modelling an existing low voltage electricity network; ii. generating modelled network data, including network topology data, and historical data and forecast data for each connection point; the historical and the forecast data being consumption and generation data; iii. processing modelled network data to determine load flow data relating to distribution of electric power, including magnitude and direction of currents and voltages at various locations within the network; and to iv. generate connections data, including a list of alternative connections between network nodes from the same or different subnetworks, such alternative connections consisting of virtual distribution lines and respective circuit breakers; v. processing connections data, network topology data and load flow data to identify one or more alternative connections from the list of alternative connections, which optimize one or more predefined criteria.

[0016] These predefined criteria may, in addition to the geographical location and urbanistic data of the network nodes and the alternative connections between them, be related to one or a combination of at least the following criterion: a maximum length connection between a distribution transformer and the furthest connection point of a feeder, maintaining a radial operation of the network; the maintenance of voltage levels according to preset standards and regulation; voltage and capacity limits in network assets; the reduction of voltage issues; the minimization of power losses; the reduction in material usage for the installation of new connections between network nodes; and the increase in redundancy.

[0017] By processing connections data, network topology data, and load flow data, including a risk parameter related to a probability of occurrence of overvoltage, undervoltage, losses and outages scenarios, based on those predefined technical, regulatory and economic criteria, this method enables electricity network planners to objectively identify the most promising alternative connections between network nodes for meshing, whether within the same subnetwork or from different subnetworks.

[0018] DESCRIPTION OF FIGURES

[0019] Figure 1 - Representation of two low voltage electricity subnetworks (1) in two different scenarios. In scenario (a), the subnetworks (1) are not connected to each other, unlike in scenario (b), which includes three alternative connections (5) between the subnetworks (1), resulting from the execution of the method disclosed herein. The reference signs represent:

[0020] 1 - subnetwork;

[0021] 2 - distribution transformer;

[0022] 3 - branch;

[0023] 4 - network node;

[0024] 5 - alternative connection.

[0025] DETAILED DESCRIPTION

[0026] The more general configurations of the present disclosure are described in the "SUMMARY" section of the disclosure. Such configurations are detailed below in accordance with other advantageous and / or preferred embodiments of implementation of the present disclosure. A computer-implemented method to determine optimal meshing in a low voltage electricity network, according to the present disclosure, may include: a plurality of distribution transformers (2), a plurality of connection points, and a plurality of feeders. Each feeder may be a electricity line or circuit that carries electricity from a substation, facility equipped with transformers, switches, protection, and monitoring devices used to step down high or medium voltage electricity, to multiple distribution transformers (2) or directly to end-users within the low voltage electricity network, and may comprise at least one branch (3) connecting a distribution transformer (2) to at least one connection point, thereby forming a subnetwork (1). A subnetwork (1) may refer to a localized section of the overall electricity network, typically defined by geographic boundaries or operational characteristics, and may comprise a plurality of network nodes (4). A network node (4) may correspond to a point within a low voltage electricity network where multiple feeders or circuits intersect. This may include components such as cable intersections, switches, junction boxes, or even electric poles. To further clarify the terminology used in this disclosure: a "distribution transformer" (2) may be a transformer device that reduces high or medium voltage from the distribution network to a lower voltage suitable for low voltage electricity networks, making it possible to deliver electricity safely to end-users; and a "connection point" may refer to a specific location where a consumer's premises connects to the low voltage electricity network.

[0027] In a preferred embodiment of the computer-implemented method described herein, it may comprise the steps of: i. modelling an existing low voltage electricity network; ii. generating modelled network data, including network topology data, and historical data and forecast data for each connection point; the historical and the forecast data being consumption and generation data; iii. processing modelled network data to determine load flow data related to distribution of electric power, including magnitude and direction of currents, and voltages at various locations within the network; and to iv. generate connections data, including a list of alternative connections (5) between network nodes (4) from the same or different subnetworks (1), such alternative connections (5) consisting of virtual distribution lines - conceptual or simulated representations of distribution lines used to assess electricity network performance and explore design improvements and respective circuit breakers; v. processing connections data, network topology data and load flow data to identify one or more alternative connections (5) from the list of alternative connections (5), which optimize one or more predefined criteria.

[0028] In some embodiments of the present disclosure, generating modelled network data may include: (i) processing network assets information and respective connectivity status for each subnetwork (1); and (ii) determining the connectivity relationship between network assets of each subnetwork, in order to generate network topology data of each subnetwork (1). In this context, a network asset may refer to any physical component of the low voltage electricity network, including distribution transformers (2), feeders, cables, conductors, poles, boxes, switches, protections, meters, and other equipment, used to deliver electricity, and may include network nodes (4) and branches (3).

[0029] Additionally, this step may include: (i) processing voltage, power and current data for each connection point of a subnetwork (1), such data being collected by sensors deployed on the subnetwork (1), in order to generate historical data; and (ii) executing a probabilistic computation model, preferably a Markov-chain model, to process voltage, power and current data for each connection point, such data being also collected by sensors deployed on the subnetwork (1), in order to generate forecast data.

[0030] In an advantageous aspect, the generation of modelled network data may further comprise collecting geographical location and urbanistic data of each network asset from a Geographic Information System, so that the alternative connections (5) between network nodes (4) are determined based on said geographical location and urbanistic data, ensuring alignment with existent geographical and urbanistic constraints and supporting, thereby, feasible and cost-effective improvements of the low voltage electricity network. The network assets information, respective connectivity status, voltage, power and current data referenced above may be collected from network provider databases, thereby ensuring accurate and real-time data for the design and improvements of the low voltage electricity network. In other embodiments, the determination of load flow data, as disclosed herein, may include at least processing modelled network data, according to a Newton- Raphson, Fast-decoupled or Backward-Forward computational method. Such resulting load flow data may then be used to determine a risk parameter. This risk parameter may be determined by processing historical data and forecast data for each connection point and may be related to a probability of occurrence of overvoltage, undervoltage, losses and outages scenarios. It can also support the anticipation of load flow issues, thereby enhancing the reliability and resilience of low voltage electricity network design and improvement. Within this context, the terms may be understood as follows: "overvoltage": a condition in which the voltage in the electricity network exceeds the normal operating levels, potentially causing damage to equipment and infrastructure; "undervoltage": a condition in which the voltage in the electricity network falls below the normal operating levels, potentially leading to insufficient power supply and operational issues for connected devices; "losses": the loss of energy, typically as heat, or through other inefficiencies, during the transmission and / or distribution of electricity within the electricity network; and "outages": temporary or prolonged loss of electric power supply to end-users, which may be caused by faults, maintenance activities, or other disruptions in the electricity network.

[0031] According to other embodiments of this disclosure, generating connections data may include generating a list of alternative connections (5) between network nodes (4) from the same or different subnetworks (1). These alternative connections (5) may start from and end at any existing node of the network, be identified based on a predefined criterion, and consist of virtual distribution lines and respective circuit breakers. The referred predefined criterion may relate to one or a combination of at least the following criterion: (i) a maximum length connection between a distribution transformer (2) and the furthest connection point of a feeder maintaining a radial operation of the network, which may optionally be of 600 m; (ii) maintenance of voltage levels according to preset standards and regulation; (iii) voltage and capacity limits in network assets; (iv) reduction of voltage issues; (v) minimization of power losses; (vi) reduction of material usage for the installation of new connections between network nodes (4); and (vii) increase in redundancy. They may also relate to economic impact, considering construction costs associated with the new connections. By identifying alternative connections (5) for meshing based on these predefined criteria, the method ensures that proposed low voltage electricity network configurations are technically feasible, economically viable, and compliant with regulatory standards.

[0032] In other aspects, the generation of one or more alternative connections (5) from the list of alternative connections (5) which optimize one or more predefined criteria of the present disclosure, may include processing connections data, network topology data and load flow data according to one or a combination of the following computational algorithms: Heuristic optimization, mixed-integer and non-linear optimization, probabilistic, hill-climbing or Non-dominated Sorting Genetic algorithms. Applying different computational algorithms may help adapt the various dataset types, such as connection, topology, and load flow data, to reduce the risk of overfitting when selecting alternative connections (5) for meshing. This approach may also support the analysis of low voltage electricity network configurations from different optimization perspectives, including efficiency, resilience, and cost. Additionally, it may include iteratively actuating a circuit breaker of a virtual distribution line to enable or disable an alternative connection (5), allowing simulation and validation of various low voltage electricity network configurations, thereby improving their accuracy and reliability.

[0033] Finally, according to another embodiment, the computer-implemented method of the present disclosure may comprise executing the steps i. to v. of the preferred embodiment, according to a predefined periodicity or when a predetermined condition is satisfied; this condition being related to the occurrence of future interventions in the network. By executing the referenced steps periodically or when a specific condition is met, the method ensures that future configurations of the low voltage electricity network are aligned with evolving technical, economic and / or regulatory requirements or needs. As will be clear to one skilled in the art, the present invention should not be limited to the embodiments described herein, and a number of changes are possible which remain within the scope of the present invention.

[0034] Of course, the preferred embodiments shown above are combinable, in the different possible forms, being herein avoided the repetition all such combinations.

Claims

CLAIMS1. A computer-implemented method for determining optimal meshing in a low voltage electricity network; the network including:- a plurality of distribution transformers (2);- a plurality of connection points; and- a plurality of feeders, each feeder comprising at least one branch (3) connecting a distribution transformer (2) to at least one connection point, thereby forming a subnetwork (1); wherein, a subnetwork (1) comprises a plurality of network nodes (4), a network node (4) being a circuit breaker, an electric pole or a junction box; the method comprising the steps of: i. modelling an existing low voltage electricity network; ii. generating modelled network data, including network topology data, and historical data and forecast data for each connection point; the historical and the forecast data being consumption and generation data; iii. processing modelled network data to determine load flow data relating to distribution of electric power, including magnitude and direction of currents and voltages at various locations within the network; and to iv. generate connections data, including a list of alternative connections (5) between network nodes (4) from the same or different subnetworks (1), such alternative connections (5) consisting of virtual distribution lines and respective circuit breakers; v. processing connections data, network topology data and load flow data to identify one or more alternative connections (5) from the list of alternative connections (5) which optimize one or more predefined criteria.

2. The computer-implemented method according to claim 1, wherein the step of generating modelled network data includes: processing network assets information and respective connectivity status for each subnetwork (1); a network asset includes network nodes (4) and branches (3);determining connectivity relationship between network assets of each subnetwork (1), in order to generate network topology data of each subnetwork (1).

3. The computer-implemented method according to claims 1 or 2, wherein the step of generating modelled data further includes: processing voltage, power and current data for each connection point of a subnetwork (1), such data being collected by sensors deployed on the subnetwork (1), in order to generate historical data.

4. The computer-implemented method according to any of the previous claims, wherein the step of generating modelled data further includes: executing a probabilistic computation model to process voltage, power and current data for each connection point, such data being collected by sensors deployed on the subnetwork (1), in order to generate forecast data; preferably, the probabilistic computational model is a Markov-chain model.

5. The computer-implemented method according to any of the previous claims 2 to 4, wherein data relating to: network assets information and respective connectivity status; and voltage, power and current; are collected from network provider databases.

6. The computer-implemented method according to any of the previous claims, wherein the determination of load flow data includes at least processing modelled network data according to a Newton-Raphson, Fast-decoupled or Backward-Forward computational method.

7. The computer-implemented method according to any of the previous claims, further comprising the step of:Processing load flow data in order to determine a risk parameter relating to a probability of occurrence of overvoltage, undervoltage, losses and outages scenarios;said risk parameter being determined by processing historical data and forecast data for each connection point.

8. The computer-implemented method according to any of the previous claims, wherein connections data relates to alternative connections (5) that start from and end at any existing node of the network.

9. The computer-implemented method according to claim 2, further comprises the steps of: collecting, from a Geographic Information System, geographical location and urbanistic data of each network asset; wherein,- modelled network data includes geographical location and urbanistic data for each network asset, so that the alternative connections (5) between network nodes (4) are determined based on said geographical location and urbanistic data.

10. The computer-implemented method according to any of the previous claims, wherein one predefined criterion to identify one or more alternative connections (5) is the urbanist data and geographical location data of the network nodes (4) and of the alternative connections (5).

11. The computer-implemented method according to any of the previous claims, wherein a predefined criterion relates to one or a combination of at least the following criterion: a maximum length connection between a distribution transformer (2) and the furthest connection point of a feeder, maintaining a radial operation of the network; optionally, the maximum length connection is 600 m. maintaining voltage levels according to preset standards and regulation; voltage and capacity limits in network assets; reduce voltage issues; minimize power losses;reduce material usage for the installation of new connections between network nodes (4); increase in redundancy.

12. The computer-implemented method according to claim 10, wherein a predefined criterion further relates: economic impact, considering construction costs associated with the new connections.

13. The computer-implemented method according to any of the previous claims wherein identifying one or more alternative connections (5) from the list of alternative connections (5) which optimize one or more predefined criteria, includes processing connections data, network topology data and load flow data according to one or a combination of the following computational algorithms:- Heuristic optimization, mixed-integer and non-linear optimization, probabilistic, hill-climbing or Non-dominated Sorting Genetic algorithms.

14. The computer-implemented method according to any of the previous claims, further comprising: executing steps i. to v. according to a predefined periodicity or when a predetermined condition is satisfied; said predetermined condition is related to the occurrence of future interventions in the network.

15. The computer-implemented method according to claim 13, wherein generating connections data further includes: iteratively actuating a circuit breaker of a virtual distribution line to enable or disable an alternative connection (5).

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