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IJRET: International Journal of Research in Engineering and Technology eISSN: 2319-1163 | pISSN: 2321-7308
_______________________________________________________________________________________
Volume: 03 Issue: 06 | Jun-2014, Available @ http://www.ijret.org 127
MULTI-AGENT SYSTEMS BASED INTELLIGENT CONTROL OF
MICROGRID
Princy Khamesra1
, Jitendra Kasera2
, Rahul Mehta3
1
P.G. student, Pacific University, Udaipur
2
Assistant Prof. & H.O.D. (Electrical Engg.), Pacific University, Udaipur
3
Phd student, National University of Singapore, Singapore
Abstract
The electric power system supports the operation of developments & economic growth of the country. The transition of power
system towards deregulation & profit driven operation will led to a decrease of reverse & reliability of entire power network. It is
necessary to design reliable & autonomous reconfigurable electric power system to secure against natural as well as man-made
disasters. The adequate and secure power system concept can be achieved by intelligent or smart micro grid. The smart grid
system incorporated with several interconnected sub systems those having cellular structure and capable to operate autonomously
during system faults. Every sub system called cell have enough power generating capacity to meet critical load demand with
ability of internal communication among generation, transmission, distribution and controlling devices. The smart grid will
supply uninterrupted power supply to higher priority loads to maintain integrity of critical infrastructure. This paper presents
concepts, components, architect and procedure to implement smart grid system.
Keywords: Autonomous, APS, DER, DSM, IDAPS, Smart grid.
--------------------------------------------------------------------***----------------------------------------------------------------------
1. INTRODUCTION
Electricity supply play important role to provide services
such as natural gas supply, water supply, transportation,
communication, financial, commercial & health care
services. On site distributed energy resources (DER) are
installed by commercial and many residential customers to
increase reliability of electrical power supply. But still no
mechanism to adopt & coordinate these customer owned
DER to supply power to critical load at distribution level.
Therefore a place to organize, manage and convert customer
owned DER into smart micro grid system to integrate
critical load power supply at distribution level. Electrical
power generation capacity of distribution system can be
organize & utilized by smart micro grid concepts.
2. IDAPS MICROGRID
IDAPS is group of several autonomous power systems.
Autonomous power systems are identifying with existing
power network for autonomous operation, independent of
grid on the event of grid failure. IDAPS secured critical
distribution load located near APS during outage/faults via
distributed power generations. Intelligent agent provides
communication to generator, load & controlling devices
with other elements in the cell. The intelligent agent
coordinates with generators, loads & control utilities to
prevent loss of such critical load in smart & efficient
manner.
Fig. 1: Typical structure of intelligent distributed
autonomous power system.
2.1 Control & Communication Architecture
A framework is developed for intelligent distributed
autonomous power system (IDAPS). IDAPS is a special
purpose micro grid designed for customer owned DER for
residential as well as commercial consumer. Frame work of
IDAPS consist physical & cyber layers. It composed of
loosely connected DER and load with communication in one
by one manner. IDAPS have two working mode (i) normal
operating mode (ii) emergency operating condition. IDAPS
structure is complementary of main electric grid in normal
operating condition. The end user customers get a choice to
buy electricity from nearest available DER if it provides
IJRET: International Journal of Research in Engineering and Technology eISSN: 2319-1163 | pISSN: 2321-7308
_______________________________________________________________________________________
Volume: 03 Issue: 06 | Jun-2014, Available @ http://www.ijret.org 128
either competitive price or green power sources. When a
fault detected in grid power supply the DER isolate it self
from grid & start operate autonomously. IDAPS one agent
starts communication with another agent and reconfigure &
coordinate IDAPS component in such way to secure critical
load on outage/faults.
Some assumptions are made for IDAPS those are:
 Each IDAPS micro grid has sufficient DER
capability to secure load situated in each cell on
event of outages.
 Technical, regulatory and economic barriers are
bypassed for interconnection of distributed
generators.
 All DER & control devices are communicate,
interface & addressed only by IP address.
 One communication medium must be available to
communicate generators, load & controlling
devices.
2.2 IDAPS Supply-Driven-Demand Management
The IDAPS micro grid has a bulletin board to transact
business by electricity buyers and sellers. The decision is
based on real time electricity price offered by supplier in
grid. The residential as well as commercial customer having
choice to buy electricity from most economic distributed
generators on normal & outage conditions. Scheduled
availability of electricity supply will be posted on bulletin
board with price & quantity of electricity to be sold for next
24 hours.
2.3 IDAPS Agent Base Framework
IDAPS is multi-agent concept which is based on web
service layer. Multi-agent system is an idea to break a
complex problem into smaller simple problems handled by
several entities. A software based entity that sense and
respond to change in signal to accomplish individual goal is
known as agent. Four types of agents are present in multi-
agent system.
 Control agent: A control agent has software that
can perform synchronization of generators,
maintain required operating frequency & voltage
level, sustain reactive & real power, loading,
unloading and other controlling actions.
 DER agent: A DER agent is responsible for
controlling & operation of any DER that is
dispatched. DER agent contains ID, location, type,
price, quantity and availability of associated DER.
 User agent: User agent provides a gateway to enter
a user into the rest of the system. It collects real
time information & display all related information
on electronic console on the end user premises.
User agent provides price, quantity, availability for
buying from bulletin board with electricity price
information from utilities.
 Database agent: A database agent keep database
electricity price & demand information. Users &
other agents can access this database via database
agent.
Fig. 2: Messages exchanged among agents and physical
entities.
3. FLOWCHART FOR USER AGENT
OPERATION
Fig. 3: Flowchart for User agent operation.
IJRET: International Journal of Research in Engineering and Technology eISSN: 2319-1163 | pISSN: 2321-7308
_______________________________________________________________________________________
Volume: 03 Issue: 06 | Jun-2014, Available @ http://www.ijret.org 129
Fig. 4: Flowchart for DER agent operation.
4. SIMULATIONS & RESULTS
A MATLAB model of IDAPS is developed. The proposed
model has three 65KVA distributed generators, two critical
loads 50 KW each, normal load 50KW & circuit breakers.
Fig. 5: IDAPS smart Grid Hardware Simulation.
NO
NO
NO
YES
YES
YES
START
CHECK FOR
ISLANDING
MODE
CHECK IF
DER IS
ONLINE
CHECK IF THE
USER AGENTS
ARE
DEMANDING
POWER
DER CIRCUIT
BREAKER
TURNS TO ON
END
DER CIRCUIT
BREAKER REMAIN
OFF
DER
CIRCUIT
BREAKER
REMAIN
OFF
IJRET: International Journal of Research in Engineering and Technology eISSN: 2319-1163 | pISSN: 2321-7308
_______________________________________________________________________________________
Volume: 03 Issue: 06 | Jun-2014, Available @ http://www.ijret.org 130
5. RESULTS
Three cases are observed with proposed model.
5.1 Transition from Grid-Connected to Islanded
Mode and Securing Critical Loads
Fig. 6(a): Voltage and current waveform for critical load 1.
Fig. 6(b): Voltage and current waveform for critical load 2.
Fig. 6(c): Voltage and current waveform for non-critical
load.
Fig. 6(d): Power taken from DER1, DER2, DER3 and the
main grid.
Fig. 6(e): Power taken by critical load 1, critical load 2,
non-critical load
5.2 Transition from Grid-Connected to Islanded
Mode and Securing Critical Loads as well as Non-
Critical loads
IJRET: International Journal of Research in Engineering and Technology eISSN: 2319-1163 | pISSN: 2321-7308
_______________________________________________________________________________________
Volume: 03 Issue: 06 | Jun-2014, Available @ http://www.ijret.org 131
Fig. 7(a): Voltage and current waveform for critical load 1
Fig. 7(b): Voltage and current waveform for critical load 2
Fig. 7(c): Voltage and current waveform for non-critical
load
Fig. 7(d): Power taken from DER1, DER2, DER3 and the
main grid
Fig. 7(e): Power taken by critical load 1, critical load 2,
non-critical load
5.3 Transition from Grid-Connected to Islanded
Mode considering Load Variations.
Fig 8(a): Voltage and current waveform for critical load 1
IJRET: International Journal of Research in Engineering and Technology eISSN: 2319-1163 | pISSN: 2321-7308
_______________________________________________________________________________________
Volume: 03 Issue: 06 | Jun-2014, Available @ http://www.ijret.org 132
Fig 8(b): Voltage and current waveform for critical load 2
Fig 8(c): Voltage and current waveform for non- critical
load
Fig 8(d): Power taken from DER1, DER2, DER3 and the
main grid
Fig 8(e): Power taken by critical load 1, critical load 2, non-
critical load
3. CONCLUSIONS
The Intelligent Distributed Autonomous Power System
(IDAPS) concept is presented, also describing the IDAPS
parts & simulation model. The main focuses on coordinating
DER units concern with the same utility. The IDAPS
designed for managing customer owned DER in the
distribution network. The novel supply-driven-demand
management model keep demand side management (DSM)
within the IDAPS micro grid under normal operating
conditions and allows critical loads to be served during
emergency conditions. IDAPS micro grid communicates
with one another and also ensures portability and
interoperability among various DG systems via utilization of
web services enables components.
REFERENCES
[1] Pipattanasomporn, M., Feroze, H., Rahman, S.,
“Multi-Agent Systems in a Distributed Smart Grid:
Design and Implementation“, IEEE Power Systems
Conference and Exposition, Seattle, WA, USA,
March 15-18, 2009.
[2] S. Rahman, M. Pipattanasomporn and Y. Teklu,
“Intelligent Distributed Autonomous Power Systems
(IDAPS)”, in Proc. of the IEEE PES Annual General
Meeting, Tampa,Florida, pp. 8, 2007.
[3] A. Dimeas and N.D Hatziargyriou, “Operation of a
multiagent system for microgrid control”, IEEE
transaction on Power Systems, Vol. 20, No. 3, pp.
1447-1455, 2005
[4] S.D.J. McArthur, E.M. Davidson, J.A. Hossack, and
R. McDonald, “Automating power system fault
diagnosis through multi-agent system technology”, in
Proc. of the 37th Hawaii International Conference on
System Sciences, 8pp, 2004.
[5] A. Dimeas and N.D Hatziargyriou, “Operation of a
multiagent system for microgrid control”, in Power
Engineering Society General Meeting, Vol. 1, pp. 55-
58, 2004.
IJRET: International Journal of Research in Engineering and Technology eISSN: 2319-1163 | pISSN: 2321-7308
_______________________________________________________________________________________
Volume: 03 Issue: 06 | Jun-2014, Available @ http://www.ijret.org 133
[6] J. Hossack, S.D.J. Mcanhur, J.R. Mcdonald, J.
Stokoe and T. Cumming, “A multi-agent approach to
power system disturbance diagnosis”, in Proc. of
International conference on power system
management and control, Vol. 488, pp. 317-322,
2002.
[7] T. Nagata and H. Sasaki, “A multi-agent approach to
power system restoration”, IEEE Transactions on
Power Systems, Vol. 17, pp. 457-462, 2002.
[8] H.F. Wang, “Multi-agent co-ordination for the
secondary voltage control in power system
contingencies”, in Proc. of IEE Generation,
Transmission and Distribution, Vol. 148, pp. 61-66,
2001.

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Multi agent systems based intelligent control of microgrid

  • 1. IJRET: International Journal of Research in Engineering and Technology eISSN: 2319-1163 | pISSN: 2321-7308 _______________________________________________________________________________________ Volume: 03 Issue: 06 | Jun-2014, Available @ http://www.ijret.org 127 MULTI-AGENT SYSTEMS BASED INTELLIGENT CONTROL OF MICROGRID Princy Khamesra1 , Jitendra Kasera2 , Rahul Mehta3 1 P.G. student, Pacific University, Udaipur 2 Assistant Prof. & H.O.D. (Electrical Engg.), Pacific University, Udaipur 3 Phd student, National University of Singapore, Singapore Abstract The electric power system supports the operation of developments & economic growth of the country. The transition of power system towards deregulation & profit driven operation will led to a decrease of reverse & reliability of entire power network. It is necessary to design reliable & autonomous reconfigurable electric power system to secure against natural as well as man-made disasters. The adequate and secure power system concept can be achieved by intelligent or smart micro grid. The smart grid system incorporated with several interconnected sub systems those having cellular structure and capable to operate autonomously during system faults. Every sub system called cell have enough power generating capacity to meet critical load demand with ability of internal communication among generation, transmission, distribution and controlling devices. The smart grid will supply uninterrupted power supply to higher priority loads to maintain integrity of critical infrastructure. This paper presents concepts, components, architect and procedure to implement smart grid system. Keywords: Autonomous, APS, DER, DSM, IDAPS, Smart grid. --------------------------------------------------------------------***---------------------------------------------------------------------- 1. INTRODUCTION Electricity supply play important role to provide services such as natural gas supply, water supply, transportation, communication, financial, commercial & health care services. On site distributed energy resources (DER) are installed by commercial and many residential customers to increase reliability of electrical power supply. But still no mechanism to adopt & coordinate these customer owned DER to supply power to critical load at distribution level. Therefore a place to organize, manage and convert customer owned DER into smart micro grid system to integrate critical load power supply at distribution level. Electrical power generation capacity of distribution system can be organize & utilized by smart micro grid concepts. 2. IDAPS MICROGRID IDAPS is group of several autonomous power systems. Autonomous power systems are identifying with existing power network for autonomous operation, independent of grid on the event of grid failure. IDAPS secured critical distribution load located near APS during outage/faults via distributed power generations. Intelligent agent provides communication to generator, load & controlling devices with other elements in the cell. The intelligent agent coordinates with generators, loads & control utilities to prevent loss of such critical load in smart & efficient manner. Fig. 1: Typical structure of intelligent distributed autonomous power system. 2.1 Control & Communication Architecture A framework is developed for intelligent distributed autonomous power system (IDAPS). IDAPS is a special purpose micro grid designed for customer owned DER for residential as well as commercial consumer. Frame work of IDAPS consist physical & cyber layers. It composed of loosely connected DER and load with communication in one by one manner. IDAPS have two working mode (i) normal operating mode (ii) emergency operating condition. IDAPS structure is complementary of main electric grid in normal operating condition. The end user customers get a choice to buy electricity from nearest available DER if it provides
  • 2. IJRET: International Journal of Research in Engineering and Technology eISSN: 2319-1163 | pISSN: 2321-7308 _______________________________________________________________________________________ Volume: 03 Issue: 06 | Jun-2014, Available @ http://www.ijret.org 128 either competitive price or green power sources. When a fault detected in grid power supply the DER isolate it self from grid & start operate autonomously. IDAPS one agent starts communication with another agent and reconfigure & coordinate IDAPS component in such way to secure critical load on outage/faults. Some assumptions are made for IDAPS those are:  Each IDAPS micro grid has sufficient DER capability to secure load situated in each cell on event of outages.  Technical, regulatory and economic barriers are bypassed for interconnection of distributed generators.  All DER & control devices are communicate, interface & addressed only by IP address.  One communication medium must be available to communicate generators, load & controlling devices. 2.2 IDAPS Supply-Driven-Demand Management The IDAPS micro grid has a bulletin board to transact business by electricity buyers and sellers. The decision is based on real time electricity price offered by supplier in grid. The residential as well as commercial customer having choice to buy electricity from most economic distributed generators on normal & outage conditions. Scheduled availability of electricity supply will be posted on bulletin board with price & quantity of electricity to be sold for next 24 hours. 2.3 IDAPS Agent Base Framework IDAPS is multi-agent concept which is based on web service layer. Multi-agent system is an idea to break a complex problem into smaller simple problems handled by several entities. A software based entity that sense and respond to change in signal to accomplish individual goal is known as agent. Four types of agents are present in multi- agent system.  Control agent: A control agent has software that can perform synchronization of generators, maintain required operating frequency & voltage level, sustain reactive & real power, loading, unloading and other controlling actions.  DER agent: A DER agent is responsible for controlling & operation of any DER that is dispatched. DER agent contains ID, location, type, price, quantity and availability of associated DER.  User agent: User agent provides a gateway to enter a user into the rest of the system. It collects real time information & display all related information on electronic console on the end user premises. User agent provides price, quantity, availability for buying from bulletin board with electricity price information from utilities.  Database agent: A database agent keep database electricity price & demand information. Users & other agents can access this database via database agent. Fig. 2: Messages exchanged among agents and physical entities. 3. FLOWCHART FOR USER AGENT OPERATION Fig. 3: Flowchart for User agent operation.
  • 3. IJRET: International Journal of Research in Engineering and Technology eISSN: 2319-1163 | pISSN: 2321-7308 _______________________________________________________________________________________ Volume: 03 Issue: 06 | Jun-2014, Available @ http://www.ijret.org 129 Fig. 4: Flowchart for DER agent operation. 4. SIMULATIONS & RESULTS A MATLAB model of IDAPS is developed. The proposed model has three 65KVA distributed generators, two critical loads 50 KW each, normal load 50KW & circuit breakers. Fig. 5: IDAPS smart Grid Hardware Simulation. NO NO NO YES YES YES START CHECK FOR ISLANDING MODE CHECK IF DER IS ONLINE CHECK IF THE USER AGENTS ARE DEMANDING POWER DER CIRCUIT BREAKER TURNS TO ON END DER CIRCUIT BREAKER REMAIN OFF DER CIRCUIT BREAKER REMAIN OFF
  • 4. IJRET: International Journal of Research in Engineering and Technology eISSN: 2319-1163 | pISSN: 2321-7308 _______________________________________________________________________________________ Volume: 03 Issue: 06 | Jun-2014, Available @ http://www.ijret.org 130 5. RESULTS Three cases are observed with proposed model. 5.1 Transition from Grid-Connected to Islanded Mode and Securing Critical Loads Fig. 6(a): Voltage and current waveform for critical load 1. Fig. 6(b): Voltage and current waveform for critical load 2. Fig. 6(c): Voltage and current waveform for non-critical load. Fig. 6(d): Power taken from DER1, DER2, DER3 and the main grid. Fig. 6(e): Power taken by critical load 1, critical load 2, non-critical load 5.2 Transition from Grid-Connected to Islanded Mode and Securing Critical Loads as well as Non- Critical loads
  • 5. IJRET: International Journal of Research in Engineering and Technology eISSN: 2319-1163 | pISSN: 2321-7308 _______________________________________________________________________________________ Volume: 03 Issue: 06 | Jun-2014, Available @ http://www.ijret.org 131 Fig. 7(a): Voltage and current waveform for critical load 1 Fig. 7(b): Voltage and current waveform for critical load 2 Fig. 7(c): Voltage and current waveform for non-critical load Fig. 7(d): Power taken from DER1, DER2, DER3 and the main grid Fig. 7(e): Power taken by critical load 1, critical load 2, non-critical load 5.3 Transition from Grid-Connected to Islanded Mode considering Load Variations. Fig 8(a): Voltage and current waveform for critical load 1
  • 6. IJRET: International Journal of Research in Engineering and Technology eISSN: 2319-1163 | pISSN: 2321-7308 _______________________________________________________________________________________ Volume: 03 Issue: 06 | Jun-2014, Available @ http://www.ijret.org 132 Fig 8(b): Voltage and current waveform for critical load 2 Fig 8(c): Voltage and current waveform for non- critical load Fig 8(d): Power taken from DER1, DER2, DER3 and the main grid Fig 8(e): Power taken by critical load 1, critical load 2, non- critical load 3. CONCLUSIONS The Intelligent Distributed Autonomous Power System (IDAPS) concept is presented, also describing the IDAPS parts & simulation model. The main focuses on coordinating DER units concern with the same utility. The IDAPS designed for managing customer owned DER in the distribution network. The novel supply-driven-demand management model keep demand side management (DSM) within the IDAPS micro grid under normal operating conditions and allows critical loads to be served during emergency conditions. IDAPS micro grid communicates with one another and also ensures portability and interoperability among various DG systems via utilization of web services enables components. REFERENCES [1] Pipattanasomporn, M., Feroze, H., Rahman, S., “Multi-Agent Systems in a Distributed Smart Grid: Design and Implementation“, IEEE Power Systems Conference and Exposition, Seattle, WA, USA, March 15-18, 2009. [2] S. Rahman, M. Pipattanasomporn and Y. Teklu, “Intelligent Distributed Autonomous Power Systems (IDAPS)”, in Proc. of the IEEE PES Annual General Meeting, Tampa,Florida, pp. 8, 2007. [3] A. Dimeas and N.D Hatziargyriou, “Operation of a multiagent system for microgrid control”, IEEE transaction on Power Systems, Vol. 20, No. 3, pp. 1447-1455, 2005 [4] S.D.J. McArthur, E.M. Davidson, J.A. Hossack, and R. McDonald, “Automating power system fault diagnosis through multi-agent system technology”, in Proc. of the 37th Hawaii International Conference on System Sciences, 8pp, 2004. [5] A. Dimeas and N.D Hatziargyriou, “Operation of a multiagent system for microgrid control”, in Power Engineering Society General Meeting, Vol. 1, pp. 55- 58, 2004.
  • 7. IJRET: International Journal of Research in Engineering and Technology eISSN: 2319-1163 | pISSN: 2321-7308 _______________________________________________________________________________________ Volume: 03 Issue: 06 | Jun-2014, Available @ http://www.ijret.org 133 [6] J. Hossack, S.D.J. Mcanhur, J.R. Mcdonald, J. Stokoe and T. Cumming, “A multi-agent approach to power system disturbance diagnosis”, in Proc. of International conference on power system management and control, Vol. 488, pp. 317-322, 2002. [7] T. Nagata and H. Sasaki, “A multi-agent approach to power system restoration”, IEEE Transactions on Power Systems, Vol. 17, pp. 457-462, 2002. [8] H.F. Wang, “Multi-agent co-ordination for the secondary voltage control in power system contingencies”, in Proc. of IEE Generation, Transmission and Distribution, Vol. 148, pp. 61-66, 2001.