IEEE Power & Energy Magazine - May/June 2017 - 44

Data Hub
Control Hub
Weather Hub

TSO
Balance
Responsible Party

DSO
SCADA DMS

Market
Operator
Platform

Energy Retailer

IED

CIS

Substation Automation
RTU

Scheduling
and Bidding
Systems

IED

MDMS NIS

Enterprise Service Bus

Commercial Aggregator

DER Automation

NIS

Secondary
Substation
Automation
DER Automation

Weather
Data

IED

RTU
Smart
Meters

IED

PMU
Secondary
Substation
Automation
PMU

IED

Smart
Meters

figure 1. An overview of the IDE4L automation solution.

and controlling of all MV and LV networks and direct control of DERs. Traditional distribution automation solutions
[e.g., centralized supervisory control and data acquisition
(SCADA)/DMS] are not rapid and scalable enough to monitor and control large-scale DERs in real time on both MV
and LV networks.
Therefore, a novel hierarchical decentralized automation
architecture is proposed for ANM and implemented by three
actors: IEDs, substation automation units (SAUs), and DMSs.
The primary and secondary substations are the central elements of the architecture. The SAU manages monitoring and
control within the substation, stores the collected data, and
makes independent decisions. Externally, the SAU sends
alarms and reports to the control center (and possibly to
other substations). The majority of real-time data is seen by
the SAU only, although data can be retrieved by the control
center if needed. The SAU data are received and sent from/
to the IEDs, which are heterogeneous devices not limited to
the typical substation IEDs. The SAU has external links (the
DSO's communication infrastructure) to DER automation,
which is part of the commercial aggregator's automation
system. This link is used to send, in an emergency, direct
control commands to DERs, which are considered a type of
IED in the architecture.
Control center information systems consist of several IT
systems used for operational and planning purposes, and the
integration of these systems is necessary to get the most out
of the available data. For example, smart-metering data is
primarily used for billing, but it may also be used for planning purposes to create enhanced customer load profiling
and clustering, which is becoming more challenging due
to prosumers, consumers capable of producing their own
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ieee power & energy magazine

energy. Similarly, the smart-metering data may be used for
operational purposes like outage alarms and voltage deviations. Alarms go directly to SCADA/DMS, and everything
else is stored in the meter data management system, which
is further integrated with the customer information system
for billing and the network information system for customer
profiling and clustering.
The second major automation system is owned and operated by the commercial aggregator that, in addition to its current market operations, is assumed to be selling flexibility
services to the DSO to prevent or resolve congestion. This
automation system is also hierarchical and decentralized, and
the first central layer includes IT systems to collect and store
DER data, schedule DERs to maximize profit, and communicate with the market operator platform for bidding and flexibility validation purposes. The second layer is DER automation (possibly including building or home energy-management
systems monitoring DERs), which coordinates local DERs and
realizes the activation of DER scheduling. The lowest level of
the hierarchy consists of the IEDs themselves, which are programmable logic controllers or advanced thermostats of DER
units. The development of the automation system for the commercial aggregator is not in the focus of IDE4L project, and,
therefore, further implementations details are not included.
Commercial Aggregator

Flexibility can be described as the modification of consumption patterns and generation injection in reaction to a price
signal or activation request to provide a service within the
energy system. The sole source of flexibility is assumed to be
prosumers, in the form of industrial, commercial, and domestic providers.
may/june 2017

Table of Contents for the Digital Edition of IEEE Power & Energy Magazine - May/June 2017