Content for TS 22.104 Word version: 17.4.0
A.4 Electric-power distribution
A.4.1 Overview
A.4.2 Primary frequency control
A.4.3 Distributed voltage control
A.4.4 Distributed automated switching for isolation and service restoration
A.4.5 Smart grid millisecond-level precise load control
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A.4 Electric-power distribution Word‑p. 45
A.4.1 Overview
The energy sector is currently subject to a fundamental change, which is caused by the evolution towards renewable energy, i.e. an increasing number of power plants based on solar and wind power. These changes lead to bi-directional electricity flows and increased dynamics of the power system. New sensors and actuators are being deployed in the power system to efficiently monitor and control the volatile conditions of the grid, requiring real-time information exchange [11] [12].
The emerging electric-power distribution grid is also referred to as Smart Grid. The smartness enhances insight into both the grid as a power network and the grid as a system of systems. Enhanced insight improves controllability and predictability, both of which drive improved operation and economic performance and both of which are prerequisites for the sustainable and scalable integration of renewables into the grid and the potential transition to new grid architectures. Smart Grid benefits spread across a broad spectrum but generally include improvements in: power reliability and quality; grid resiliency; power usage optimisation; operational insights; renewable integration; insight into energy usage; and safety and security.
Overviews of (future) electric-power distribution can be found elsewhere in the literature [13] [14].
A.4.2 Primary frequency control
Primary frequency control is among the most challenging and demanding control applications in the utility sector. A primary frequency control system is responsible for controlling the energy supply injected and withheld to ensure that the frequency is not deviating more than 0.02 % from the nominal value (e.g., 50 Hz in Europe). Frequency control is based on having sensors for measuring the features in all parts of the network at all points where energy generation or storage units are connected to the grid. At these points, electronic power converters, also known as inverters, are equipped with communication units to send measurement values to other points in the grid such as a frequency control unit, or receive control commands to inject more, or less, energy into the local network.
With the widespread deployment of local generation units, i.e. solar power units, or wind turbines, hundreds of thousands of such units, and their inverters, may have to be connected in a larger power distribution network.
Primary frequency control is carried out in one of three ways:
-
Centralised control, all data analysis and corrective actions are determined by a central frequency control unit.
-
Decentralised control, the automatic routine frequency control is performed by the individual local inverter based on local frequency values. Statistics and other information is communicated to the central frequency control unit.
-
Distributed control, the automatic routine frequency control is performed by the individual local inverter based on local and neighbouring frequency values. Statistics and other information are communicated to the central frequency control unit.
Use case #
Characteristic parameter
Communication service availability: target value [%]
Communication service reliability: mean time between failures
End-to-end latency: maximum
Influence quantity
Message size [byte]
Transfer interval: target value
Survival time
# of UEs
Service area
1
99.999
TBD
~ 50 ms
~ 100
~ 50 ms
TBD
≤ 100,000
several km² up to 100,000 km²
Use case one
Periodic communication service supporting message exchange for primary frequency control.
A.4.3 Distributed voltage control Word‑p. 46
In the evolution towards 100 % renewable electric power production, the objective of voltage control is to balance the voltage in future low voltage distribution grids connecting local loads and prosumers, as well as energy storage facilities. The aim is to stabilise the voltage as locally as possible, so that decisions and control commands can be issued as quickly as possible. Distributed voltage control is a challenging and demanding control application. Consumer devices rely on having stable voltage levels to operate successfully. When future energy networks rely on thousands of local energy generation units relying mostly on solar and wind power, then it is crucial to stabilise the voltage levels in all segments of the distribution grid. Inverters, or electronic power converters, measure the voltage and power and change the amount of power injected into the grid, and they connect and disconnect end points from the distribution network.
Distributed control means that the automated voltage control shall be performed by the local voltage control units based on local and neighbouring voltage and impedance values. Statistics and other information shall be communicated to the central distribution management system, though.
Use case #
Characteristic parameter
Communication service availability: target value [%]
Communication service reliability: mean time between failures
End-to-end latency: maximum
Influence quantity
Message size [byte]
Transfer interval: target value
Survival time
# of UEs
Service area
1
99.999
TBD
~ 100 ms
~ 100
~ 200 ms
TBD
≤ 100,000
several km² up to 100,000 km²
Use case one
Periodic communication service supporting message exchange for distributed voltage control.
A.4.4 Distributed automated switching for isolation and service restoration
A power distribution grid fault is a stressful situation. There are self-healing solutions for automated switching, fault isolation and, service restoration. Furthermore, these solutions are ideally suited to handle outages that affect critical power consumers, such as industrial plants or data centres. Supply interruptions must be fixed within less than a second for critical power consumers. Automated solutions are able to restore power supply within a few hundred milliseconds.
The FLISR (Fault Location, Isolation & Service Restoration) solution consists of switch controller devices which are especially designed for feeder automation applications that support the self-healing of power distribution grids with overhead lines. They serve as control units for reclosers and disconnectors in overhead line distribution grids.
The system is designed for using fully distributed, independent automated devices. The logic resides in each individual feeder automation controller located at the poles in the feeder level. Each feeder section has a controller device. Using peer-to-peer communication among the controller devices, the system operates autonomously without the need of a regional controller or control centre. However, all self-healing steps carried out will be reported immediately to the control centre to keep the grid status up-to-date. The controllers conduct self-healing of the distribution line in typically 500 ms by isolating the faults.
Peer-to-peer communication via IEC 61850 GOOSE (Generic Object Oriented Substation Event) messages provides data as fast as possible (Layer 2 multicast message). They are sent periodically (in steady state, with changing interval time in fault case) by each controller to several or all other controllers of the same feeder and are not acknowledged.
The data rate per controller is low in steady state, but GOOSE bursts with high data rate do occur, especially during fault situations. GOOSE messages are sent by several or all controller units of the feeder nearly at the same point in time during the fault location, isolation and service restoration procedure with a low end-to-end latency.
Use case #
Characteristic parameter
Communication service availability: target value [%]
Communication service reliability: mean time between failures
End-to-end latency: maximum
Service bitrate: user experienced data rate
Influence quantity
Message size [byte]
Transfer interval: target value
Survival time
UE speed
# of UEs
Service area (note 1)
1 (note 2)
99.999 9
–
< 5 ms
1 kbit/s (steady state) 1.5 Mbit/s (fault case)
< 1,500
< 60 s (steady state) ≥ 1 ms (fault case)
transfer interval (one frame loss)
stationary
20
30 km x 20 km
Use case one
GOOSE (a)periodic deterministic communication service supporting bursty message exchange for fault location, isolation, and service restoration.
A.4.5 Smart grid millisecond-level precise load control Word‑p. 48
Precise Load Control is the basic application for smart grid. When serious HVDC (high-voltage direct current) transmission fault happens, Millisecond-Level Precise Load Control is used to quickly remove interruptible less-important load, such as electric vehicle charging piles and non-continuous production power supplies in factories.
Use case #
Characteristic parameter
Communication service availability: target value in %
Communication service reliability: mean time between failures
End-to-end latency: maximum
Service bitrate: user experienced data rate
Influence quantity
Message size [byte]
Transfer interval: target value
Survival time
UE speed
# of UEs
Service area
1
99.999 9
–
< 50 ms
0.59 kbit/s 28 kbit/s
< 100
n/a (note)
–
stationary
10 km² to 100 km²
TBD
Use case one
A non-periodic deterministic communication service between control primary station and load control terminals for removing interruptible less-important load quickly.
A.4.1 Overview
The energy sector is currently subject to a fundamental change, which is caused by the evolution towards renewable energy, i.e. an increasing number of power plants based on solar and wind power. These changes lead to bi-directional electricity flows and increased dynamics of the power system. New sensors and actuators are being deployed in the power system to efficiently monitor and control the volatile conditions of the grid, requiring real-time information exchange [11] [12].
The emerging electric-power distribution grid is also referred to as Smart Grid. The smartness enhances insight into both the grid as a power network and the grid as a system of systems. Enhanced insight improves controllability and predictability, both of which drive improved operation and economic performance and both of which are prerequisites for the sustainable and scalable integration of renewables into the grid and the potential transition to new grid architectures. Smart Grid benefits spread across a broad spectrum but generally include improvements in: power reliability and quality; grid resiliency; power usage optimisation; operational insights; renewable integration; insight into energy usage; and safety and security.
Overviews of (future) electric-power distribution can be found elsewhere in the literature [13] [14].
A.4.2 Primary frequency control
Primary frequency control is among the most challenging and demanding control applications in the utility sector. A primary frequency control system is responsible for controlling the energy supply injected and withheld to ensure that the frequency is not deviating more than 0.02 % from the nominal value (e.g., 50 Hz in Europe). Frequency control is based on having sensors for measuring the features in all parts of the network at all points where energy generation or storage units are connected to the grid. At these points, electronic power converters, also known as inverters, are equipped with communication units to send measurement values to other points in the grid such as a frequency control unit, or receive control commands to inject more, or less, energy into the local network.
With the widespread deployment of local generation units, i.e. solar power units, or wind turbines, hundreds of thousands of such units, and their inverters, may have to be connected in a larger power distribution network.
Primary frequency control is carried out in one of three ways:
- Centralised control, all data analysis and corrective actions are determined by a central frequency control unit.
- Decentralised control, the automatic routine frequency control is performed by the individual local inverter based on local frequency values. Statistics and other information is communicated to the central frequency control unit.
- Distributed control, the automatic routine frequency control is performed by the individual local inverter based on local and neighbouring frequency values. Statistics and other information are communicated to the central frequency control unit.
Use case #
Characteristic parameter
Communication service availability: target value [%]
Communication service availability: target value [%]
Communication service reliability: mean time between failures
End-to-end latency: maximum
Influence quantity
Message size [byte]
Message size [byte]
Transfer interval: target value
Survival time
# of UEs
Service area
1
99.999
TBD
~ 50 ms
~ 100
~ 50 ms
TBD
≤ 100,000
several km² up to 100,000 km²
Use case one
Periodic communication service supporting message exchange for primary frequency control.
A.4.3 Distributed voltage control Word‑p. 46
In the evolution towards 100 % renewable electric power production, the objective of voltage control is to balance the voltage in future low voltage distribution grids connecting local loads and prosumers, as well as energy storage facilities. The aim is to stabilise the voltage as locally as possible, so that decisions and control commands can be issued as quickly as possible. Distributed voltage control is a challenging and demanding control application. Consumer devices rely on having stable voltage levels to operate successfully. When future energy networks rely on thousands of local energy generation units relying mostly on solar and wind power, then it is crucial to stabilise the voltage levels in all segments of the distribution grid. Inverters, or electronic power converters, measure the voltage and power and change the amount of power injected into the grid, and they connect and disconnect end points from the distribution network.
Distributed control means that the automated voltage control shall be performed by the local voltage control units based on local and neighbouring voltage and impedance values. Statistics and other information shall be communicated to the central distribution management system, though.
Use case #
Characteristic parameter
Communication service availability: target value [%]
Communication service reliability: mean time between failures
End-to-end latency: maximum
Influence quantity
Message size [byte]
Transfer interval: target value
Survival time
# of UEs
Service area
1
99.999
TBD
~ 100 ms
~ 100
~ 200 ms
TBD
≤ 100,000
several km² up to 100,000 km²
Use case one
Periodic communication service supporting message exchange for distributed voltage control.
A.4.4 Distributed automated switching for isolation and service restoration
A power distribution grid fault is a stressful situation. There are self-healing solutions for automated switching, fault isolation and, service restoration. Furthermore, these solutions are ideally suited to handle outages that affect critical power consumers, such as industrial plants or data centres. Supply interruptions must be fixed within less than a second for critical power consumers. Automated solutions are able to restore power supply within a few hundred milliseconds.
The FLISR (Fault Location, Isolation & Service Restoration) solution consists of switch controller devices which are especially designed for feeder automation applications that support the self-healing of power distribution grids with overhead lines. They serve as control units for reclosers and disconnectors in overhead line distribution grids.
The system is designed for using fully distributed, independent automated devices. The logic resides in each individual feeder automation controller located at the poles in the feeder level. Each feeder section has a controller device. Using peer-to-peer communication among the controller devices, the system operates autonomously without the need of a regional controller or control centre. However, all self-healing steps carried out will be reported immediately to the control centre to keep the grid status up-to-date. The controllers conduct self-healing of the distribution line in typically 500 ms by isolating the faults.
Peer-to-peer communication via IEC 61850 GOOSE (Generic Object Oriented Substation Event) messages provides data as fast as possible (Layer 2 multicast message). They are sent periodically (in steady state, with changing interval time in fault case) by each controller to several or all other controllers of the same feeder and are not acknowledged.
The data rate per controller is low in steady state, but GOOSE bursts with high data rate do occur, especially during fault situations. GOOSE messages are sent by several or all controller units of the feeder nearly at the same point in time during the fault location, isolation and service restoration procedure with a low end-to-end latency.
Use case #
Characteristic parameter
Communication service availability: target value [%]
Communication service reliability: mean time between failures
End-to-end latency: maximum
Service bitrate: user experienced data rate
Influence quantity
Message size [byte]
Transfer interval: target value
Survival time
UE speed
# of UEs
Service area (note 1)
1 (note 2)
99.999 9
–
< 5 ms
1 kbit/s (steady state) 1.5 Mbit/s (fault case)
< 1,500
< 60 s (steady state) ≥ 1 ms (fault case)
transfer interval (one frame loss)
stationary
20
30 km x 20 km
Use case one
GOOSE (a)periodic deterministic communication service supporting bursty message exchange for fault location, isolation, and service restoration.
A.4.5 Smart grid millisecond-level precise load control Word‑p. 48
Precise Load Control is the basic application for smart grid. When serious HVDC (high-voltage direct current) transmission fault happens, Millisecond-Level Precise Load Control is used to quickly remove interruptible less-important load, such as electric vehicle charging piles and non-continuous production power supplies in factories.
Use case #
Characteristic parameter
Communication service availability: target value in %
Communication service reliability: mean time between failures
End-to-end latency: maximum
Service bitrate: user experienced data rate
Influence quantity
Message size [byte]
Transfer interval: target value
Survival time
UE speed
# of UEs
Service area
1
99.999 9
–
< 50 ms
0.59 kbit/s 28 kbit/s
< 100
n/a (note)
–
stationary
10 km² to 100 km²
TBD
Use case one
A non-periodic deterministic communication service between control primary station and load control terminals for removing interruptible less-important load quickly.
Use case #
Characteristic parameter
Communication service availability: target value [%]
Communication service availability: target value [%]
Communication service reliability: mean time between failures
End-to-end latency: maximum
Influence quantity
Message size [byte]
Message size [byte]
Transfer interval: target value
Survival time
# of UEs
Service area
1
99.999
TBD
~ 100 ms
~ 100
~ 200 ms
TBD
≤ 100,000
several km² up to 100,000 km²
Periodic communication service supporting message exchange for distributed voltage control.
Use case #
Characteristic parameter
Communication service availability: target value [%]
Communication service availability: target value [%]
Communication service reliability: mean time between failures
End-to-end latency: maximum
Service bitrate: user experienced data rate
Influence quantity
Message size [byte]
Message size [byte]
Transfer interval: target value
Survival time
UE speed
# of UEs
Service area (note 1)
1 (note 2)
99.999 9
–
< 5 ms
1 kbit/s (steady state) 1.5 Mbit/s (fault case)
< 1,500
< 60 s (steady state) ≥ 1 ms (fault case)
transfer interval (one frame loss)
stationary
20
30 km x 20 km
GOOSE (a)periodic deterministic communication service supporting bursty message exchange for fault location, isolation, and service restoration.
Precise Load Control is the basic application for smart grid. When serious HVDC (high-voltage direct current) transmission fault happens, Millisecond-Level Precise Load Control is used to quickly remove interruptible less-important load, such as electric vehicle charging piles and non-continuous production power supplies in factories.
Use case #
Characteristic parameter
Communication service availability: target value in %
Communication service availability: target value in %
Communication service reliability: mean time between failures
End-to-end latency: maximum
Service bitrate: user experienced data rate
Influence quantity
Message size [byte]
Message size [byte]
Transfer interval: target value
Survival time
UE speed
# of UEs
Service area
1
99.999 9
–
< 50 ms
0.59 kbit/s 28 kbit/s
< 100
n/a (note)
–
stationary
10 km² to 100 km²
TBD
Use case one
A non-periodic deterministic communication service between control primary station and load control terminals for removing interruptible less-important load quickly.
