The document describes the available infrastructure for an IoT microgrid laboratory, including smart sensors, appliances, a wind turbine, solar PV, battery storage, and various IoT and communications gateways. It also provides overviews of the logical architecture, data visualization system, demand response strategies implemented, experimental test methodology, and definitions of key microgrid components and control features.

1. The Energy Internet –
Integration of IoT into Smart Grids
CASE-STUDY
Microgrid Research Programme
www.iot-energy.et.aau.dk

2. Available Infrastructure
From the outside
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3. • Smart sensors for indoor/outdoor environment (weather station, motion, parking, etc)
• Smart plugs and relays
• AC and IoT-ready appliances
• AC and DC supply installation for household loads
• Multi-zonal smart under-floor heating system
www.iot-energy.et.aau.dk
IoT Microgrid Laboratory
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• 2.5kW Wind turbine, 3kW solar
PV and 8KW battery
• Zigbee, WI-FI, LoRa, WM-BUS
and bluetooth gateways
• Support for FIWARE and
VICINITY IoT architecture
• Home energy management
system
• Integrated e-Health for next
generation of smart homes

4. Available Infrastructure
Layout
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5. Available Infrastructure
Resources
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6. Available Infrastructure
Supply Possibilities
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7. Available Infrastructure
Upgrading the Converters
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8. Available Infrastructure
IoT System
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9. Available Infrastructure
Develco Gateway
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The Squid.link Gateway has options for :
- Zigbee,
- Z-Wave,
- Wireless M-Bus,
- Bluetooth WLAN HAN networks.
- Communication with smartphones can be
established via WLAN, or Cellular 2G/3G.

10. Available Infrastructure
Develco Devices
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The world's smallest
ZigBee-based
Relay + Meter
Zigbee interface for
Kamstrup OMNIPOWER
Smart Meters
Prosumer Meter to measure:
- Production (solar PV)
- Household consumption
- Utility grid
PCC Monitoring
Smart Cable
- Same features of
Smart Plug
- Different Structure
www.iot-energy.et.aau.dk

11. Logical Architecture
Functional Blocks
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12. Data Visualisation
Original System
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• Set of isolated applications
• Limited usability
• Not support for 3rd party
Services
• Sometimes not event interface
is provided
www.iot-energy.et.aau.dk

13. Data Visualisation
Our IoT-Based System
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14. Demand Response Strategies
Implementation
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Approach
• Real-time status from the
Context Broker
• Subscription Based Notifications
• Direct actuation over entities
Implementation
• Node.js
• Event oriented asynchronous
programming
• RESTful based Web Service
API
www.iot-energy.et.aau.dk

15. Demand Response Strategies
Data Model
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Blue boxes are IoT Devices
• Real entities (Sensor &
Actuators)
• Data coming from IoT Agents
Red boxes are Grouping Entities
• Physical Modelling of the
household, building…
Yellow boxes are Energy Assets
• Virtual Appliances
• Control Setting for DR
• Flexible association of sensors
and actuators
www.iot-energy.et.aau.dk

16. Demand Response Strategies
Algorithms Overview
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17. Demand Response Strategies
Load Priority
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18. Implementation of the EMS
Architecture
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• EMS is implemented as a Web
Service
• The same EMS is able to manage
different buildings
• A database is attached with key
information of each building
• Intercommunication by means of
HTTP protocol
• RESTful Requests
• Human readable
• Broad compatibility
www.iot-energy.et.aau.dk

19. Experimental Test Methodology
Detailed EMS Architecture
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Smart
Meter
Smart
Meter
Smart
Meter
Data
Concentrator
OMNISOFT®
Alarm Server
NI WebServer
LabVIEW
Utilidriver®
admin RESTFul
Server
Alarms
Capture
On-Demand
Readings
Loggers
Readings
Java EE
RESTFul
Service
AMI MDMS EMS
Data
Processing
JDBC Driver
Java EE
WeatherForecast
Load Estimation
RT Energy Prices
JDBC
Driver
GAMS
API
Data
Processing
Power References
Curtailments*
RESTFul
Service
Power
Energy
THDI, THDU
Voltages
Currents
www.iot-energy.et.aau.dk

20. Traditional Grid
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Generation
Step-up
Transformer
Transmission
Lines
Transmission
Substation
Distribution
Substation
Step-down
Transformer
Consumers
10kV, 20kV
400kV, 220kV,
150kV
60kV, 45kV,
30kV
20kV, 15kV,
10kV
400V, 230V
High Voltage (HV)
Medium Voltage (MV)
Low Voltage (LV)
www.iot-energy.et.aau.dk

21. Traditional Grid vs Smart Grid
The Paradigm of the Smart Grid
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Consumer
Prosumer
Producer
Producer
Smart Grid
Distributed: Producer ↔ Consumer
Consumers = Active agents = Prosumers
Advanced capabilities
Bi-direction power flow; Feed-in tariffs
Demand response, Energy Management

22. Definitions and Components
Microgrid Components
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Microgrids
Operation modes
Energy Management
Systems
Advanced Metering
infrastructure
Energy Storage Systems
Distributed Generation
Power Electronics Interfaces
Communications
Protections
CIGRÉ WG6.22 Microgrids are electricity distribution systems containing loads and distributed
energy resources, (such as distributed generators, storage devices, or controllable loads) that can be
operated in a controlled, coordinated way either while connected to the main power network or
while islanded.

23. Microgrids Control
Enhance Features
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Who am
I?
Communication
Protocols
Diagnostics
Prognosis
Condition
monitoring
Fault
tolerance
Islanding
detection
Decentralized
power control
Mode flexibility
Reactive
power
sharing
Ramp rate
control
Soft start
Who am
I?
Plug and Play
Self-Awarness
Autonomy
Cooperativeness
Adaptability

24. Grid Flexibility
What creates the flexibility?
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Demand
Response
Resources
Distributed
Generators
(DGs)
Intermittent DGs
(PV, Wind)
Controllable
DGs (Diesel,
CHP)
Loads
Shiftable Loads
(WS, DW)
Curtailable
Loads (Heating,
Fridge)
Energy Storage
Systems (ESS)
Static Storage
(Batteries, Fuel
Cell)
Dynamic
Storage (EV,
Trading)

25. Generalised Formulation Price-Based EMS or DR
Determine the combination of resources that minimise the cost
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Minimise 𝐶 𝑇 =
𝑖=1
𝑚
𝐶𝑖(𝑃𝐺 𝑖
)
Subject to
𝑖=1
𝑚
𝑃𝐺 𝑖
= 0
The cost consists of:
• Operating cost
• Efficiency
• Others (Battery Life, start-up cost…)
The process is subject to certain constraints
The Basic one is the total power constraint
You cannot consume
or produce more than
what you have
Including Losses!

26. More Information
E. Rodriguez-Diaz, E. J. Palacios-Garcia, A. Anvari-Moghaddam, J. C.
Vasquez and J. M. Guerrero, Real-time Energy Management System for
a hybrid AC/DC residential microgrid, 2017 IEEE 2nd International
Conference on DC Microgrids (ICDCM), Nuremburg, 2017, pp. 256-261.
doi: 10.1109/ICDCM.2017.8001053
E. J. Palacios-Garcia, E. Rodriguez-Diaz, A. Anvari-Moghaddam, M.
Savaghebi, J. C. Vasquez, J. M. Guerrero, A. Moreno-Munoz, Using smart
meters data for energy management operations and power quality
monitoring in a microgrid, 2017 IEEE 26th International Symposium on
Industrial Electronics (ISIE), Edinburgh, 2017, pp. 1725-1731.
doi: 10.1109/ISIE.2017.8001508
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