**5.3 Distribution applications**

Distribution applications (DIS): In distribution systems, WAMS applications are known as automation applications. According to IEEE definition (Gruenemeyer, 1991), Distribution Automation (DA) systems have been defined as systems that enable a distribution company to monitor, coordinate, and operate distribution components and equipments from remote locations in real time. The DAs aim to reduce costs, to improve service availability, and to provide better consumer services. In general, DA may be classified into three main groups: substation automation, feeder automation, and consumer-side automation (Shahraeini & Alishahi, 2011).

#### **5.3.1 Substation automation**

Substation Automation (SA) is the integration of smart sensors with a communication infrastructure to control and monitor substation equipments in real-time (Shahraeini & Alishahi, 2011). The major functions of SA are: service restoration via bus sectionalizing, bus voltage control, substation parallel transformer circulating current control, line drop compensation, and automatic reclosing (Cassel, 1993).

some examples of conventional EMS applications (Shahidehpour & Wang, 2003). The aforementioned applications may be considered as conventional WAMS applications since

After introducing phasor measurement units to the power systems, phasor data may contribute conventional WAMS applications or may introduce some new modern WAMS applications. For instance, if a state estimation uses only phasor data as its input, the state equations of the system will be linear. While conventional SEs (that use conventional data) are non-linear and they must use numerical method to solve their equations, iteratively.

Xiaorong et al. (2006) have summarized modern WAMS applications in the power systems. Some of these applications use only phasor data (e.g. Integrated Phasor Data Platform) and

Some modern WAMS applications are as follows (Xiaorong et al., 2006): Integrated Phasor Data Platform, Wide-Area Dynamic Monitoring and Analysis, Synchronized Disturbance Record and Replay, Online Low-Frequency Oscillation Analysis, Power Angle Stability Prediction and Alarming, and PMU based State Estimation. Combination of these modern

In the above mentioned applications, the state estimation is the most important WAMS application and is considered as kernel of EMS (Shahraeini et al., 2011). This has been resulted from the fact that this application extracts creditable data from raw data provided by data resources. Other WAMS applications use obtained creditable data as their input

State estimations, based on their utilized data, are classified into the three different types:

Conventional state estimations use conventional operational data i.e. voltage and current

Distribution applications (DIS): In distribution systems, WAMS applications are known as automation applications. According to IEEE definition (Gruenemeyer, 1991), Distribution Automation (DA) systems have been defined as systems that enable a distribution company to monitor, coordinate, and operate distribution components and equipments from remote locations in real time. The DAs aim to reduce costs, to improve service availability, and to provide better consumer services. In general, DA may be classified into three main groups: substation automation, feeder automation, and consumer-side automation (Shahraeini &

Substation Automation (SA) is the integration of smart sensors with a communication infrastructure to control and monitor substation equipments in real-time (Shahraeini & Alishahi, 2011). The major functions of SA are: service restoration via bus sectionalizing, bus voltage control, substation parallel transformer circulating current control, line drop

applications with the conventional ones forms a modern EMS in the control center.

conventional, PMU based and hybrid state estimations (Shahraeini et al., 2011).

magnitude, active and reactive power flow, and active and reactive power injection.

some ones may use both phasor and conventional data e.g. hybrid SEs.

data is fundamental part of all of them.

(Shahidehpour & Wang, 2003).

**5.3 Distribution applications** 

**5.3.1 Substation automation** 

compensation, and automatic reclosing (Cassel, 1993).

Alishahi, 2011).

Data resources of SA are located in distribution substations including bus phase voltages, transformer and feeder active and reactive power, feeder currents, statuses of circuit breakers, capacitors and reclosers cut-off switches, load tap changer and voltage regulator positions and statuses, transformer temperatures and relay settings (Cassel, 1993).

Typically, measurement data and status data are measured by pre-mentioned data resources. Then, Remote Terminal Units (RTUs) collect data and send it to SCADA systems. Finally, communication infrastructure has the responsibility of data transmitting from SCADA to the control center(s) (Shahraeini & Alishahi, 2011).

### **5.3.2 Feeder automation**

Nowadays, due to rapid growth in metros, distribution networks have been one of the most extensive infrastructures in metros. In such networks, Feeder Automation (FA) is one of the key elements for efficient management of the power distribution networks. The main purposes of FA are twofold. Firstly, FA aims to automate feeder switching. Secondly, FA controls voltages and active/reactive powers of feeders (Cassel, 1993).

The main data resources and controllable devices of this function are line reclosers, load break switches, sectionalizers, capacitor banks and line regulators. Typically, these data resources are much more than resources of SA and are located at distribution poles (Shahraeini & Alishahi, 2011).

#### **5.3.3 Consumer side automation**

Consumer side automation tries to automate the final points of electricity delivery i.e. metering devices of customers. Beyond this, customer equipments may be automated by this application and may be controlled through the control center. Advanced Metering Infrastructure (AMI) and Automatic Meter Reading (AMR) are two main systems utilized to automate consumer sides.

The AMI may be assumed as the central nervous system of the smartgrid architecture in distribution systems. AMI collects consumption data from smart meters and transmits it to the control center. This function of AMI is similar to the purposes of AMR systems. In addition to reading functions, AMI also relays demand signals and pricing information to smart meters in near real-time; and thereby, feedback loop is closed by AMI system (Shahraeini & Alishahi, 2011).

Data resources of AMI /AMR systems are metering devices. But the difference between AMI and AMR is that metering devices of AMI can also be remotely controlled by system operator. Since huge numbers of metering devices are distributed in entire system, the cost of communication system, which is utilized by an AMI/AMR system, is vital. In the view of this fact, low cost communication infrastructure means more automated customers.
