Journal of New Innovations in Electrical Engineering
Available online at www. jniee.com. Vol. 2, Issue 1, 2017, pp. 28- 38
ISSN: 2534-8809
Design Of The Controller For The Central Primary Frequency
Control In Micro grids Using Load Management And Demand
Response
1
Hadi Zibandeh1, Yashar Emami , Mohammad Mehdi Moghimian
1
1
Department of Electrical Engineering, Ali Abad Katoul Branch, Islamic Azad University, Ali Abad Katoul, Iran
*Corresponding author’s email: hadizibandeh@yahoo.com
Abstract
This paper referred to study frequency control in the smart microgrid with utilizing load management and
demand response and study the efficiency of this procedure with microgrid design and controller design that
control the load because control the frequency. In the introduction , the issue and history of work are
expressed. A brief explanation is given about smart microgrid. The frequency control with the usual method
that based on input mechanical power changes of generation units is expressed. In the next sections ,
Frequency control with Demand Response is expressed and simulated microgrid and case study is explained.
controller and control strategy for frequency control by demand response is demonstrated and Different
scenarios are considered and simulation results are introduced. After the simulation and extract charts,
accuracy and correctness of this claim were to prove that explain in conclusion.
Keywords: Demand
Response; Load Management; Smart Microgrid ; Frequency control
INTRODUCTION
Demand response is one of the issues raised in the revised structure of the systems is. This means
the change in power consumption subscribers to natural pattern of their consumption. Response
to an instrument is that the wicked independent system using it will be able to reliability system
(control frequency also includes it) maintain- redeemed sold energy of the subscribers loading
system gives decrease. In the reference [2] on an isolated microgrid research is being conducted
on demand response and effective control of the frequency of its investigation. Reference [3]
speaks about the difficulties as the lack of automatic control of production and spinning reserves
and costliness of apparatus service Builder in microgrid of smart electricity created and The
complexity discussion frequency control voltage and despite renewable energies and scattered
production level in the distribution of speech and best solution discussion answer demand and
management of load is. In [4] ability systems measuring smart to control domestic demand in
cases of necessity network. However, that delay measurement instruments and
telecommunication high is but the measure of frequency for the local by these devices is
considered . Sometimes a local in Britain, some frequency drop only will be compensated . In
reference [5] the growing use of production and are some concerns that in holding the frequency
in the permissible range that it is studying. Some departments are able to distributed generation
like microturbines that have participation frequency control , but solar and wind units (because
of the lack of control and changes), they cannot participate in this. This paper explains the
usefulness of frequency control with demand response. In [6] expressed in traditional systems,
the control of frequency variation is done in power production, but with the increasing use of
renewable energies and reduction of the share of traditional production units and flexible, the
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Journal of New Innovations in Electrical Engineering
Available online at www. jniee.com. Vol. 2, Issue 1, 2017, pp. 28- 38
ISSN: 2534-8809
demand-side contribution will find more frequency control objectives . One of the reasons that
this is not being done now in the low-and also more comfortable units and control them in
comparison with the number of subscribers and the load at the moment . This paper, the
expression the use of new technologies that Management load and the demand can decrease and
increase the frequency to a good answer. In [7] as well as the effectiveness of the response to
demand in microgrid as well as efficient smart voltage regulation to increase the share of
renewable energies , and demand response that expressed more and better low-cost way to
control frequency is compared to the traditional system.
SMART MICROGRID
A smart grid is an electrical grid which includes a variety of operational and energy measures
including smart meters, smart appliances, renewable energy resources, and energy efficiency
resources. Electronic power conditioning and control of the production and distribution of
electricity are important aspects of the smart grid. Roll-out of smart grid technology also implies
a fundamental re-engineering of the electricity services industry, although typical usage of the
term is focused on the technical infrastructure.
Smart microgrids are modern, small-scale versions of today’s huge centralized electricity system.
Like a centralized grid, microgrids can generate, distribute and regulate the flow of electricity to
consumers. They also can be networked with one another as well as with the central grid to
increase capacity, reliability and efficiency.
Fig 1 . overview of smart grid
Unlike a centralized grid, however, microgrids are not necessarily owned or run by a utility
company. Microgrids can be built, owned and operated by a community, neighborhood,
university, corporation, hospital, individual or any other entity that has legal authority over their
power infrastructure (i.e., power lines, generation source, meters, etc.). This local control, which
allows for private investment in the system, together with their relatively small size makes
microgrids hotbeds for entrepreneurial innovation: They are able to feature the latest smart
technology that increases efficiency and reliability and to create islands of sustainable energy
within the larger grid. Key benefits of smart microgrids include:
Smart microgrids increase reliability.
Smart microgrids make it easier to efficiently meet growing consumer demand.
Smart microgrids make it possible to get the most from clean, renewable energy.
Smart microgrids nurture major technological innovation.
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Journal of New Innovations in Electrical Engineering
Available online at www. jniee.com. Vol. 2, Issue 1, 2017, pp. 28- 38
ISSN: 2534-8809
FREQUENCY CONTROL TO THE TRADITIONAL METHOD
Active power must be produced when required and when taking over at different hours of the
day produces change, so should control production power generators. The power output of a
generator with its mechanical power input control changing. For this work with open or close the
water valve and steam valve, or water and steam turbine flow regulation and control of
mechanical power and causing the power output becomes active the generator. If show the
generator frequency with f0 and its voltage with Vo=|Vo|< 0 , can write the voltage equation as
follows :
v 2 | V 0 | sin( 0 t 0 )
(1)
That in 0 2f 0 is the angular velocity in steady state.
By a small change in the system changes in the dynamical frequency and voltage is created and
Even during the period of time to reach a new steady-state system. In this time , power angle and
voltage changes and achieved with following equation :
(2)
0
0
| V || V | | V |
(3)
Here and | V | are power angle and voltage error that in dynamical state of system , their’s
values are changeable , so can write voltage equation in dynamical state as follows :
v 2 (| V 0 | | V |) sin( 0 0 ) (4)
And with here angular velocity in dynamical state is equal :
d
d
(6)
( 0 0 ) 0
dt
dt
And or :
d
(7)
0
dt
If show the frequency in dynamical state with f , have :
(8)
2f
(9)
2f
With establish in equation we’ll be found :
1 d
(10)
f
2 dt
This equation show the way of frequency changing f according to changing of power angle
and vice versa.
FREQUENCY CONTROL WITH DEMAND RESPONSE
DR in real-time can be a tool more effective in providing a balance between generation and
demand. Sources of demand for the subordinate service of non-rotary defined as they are in
during the 10 minutes or shorter from when the integration will be available.
The proposed DBFC2 scheme is similar in concept to the conventional AGC3 type scheme. The
calculations to determine the adjustment in load necessary to compensate for a supply-demand
1
1
Demand response
Demand based frequency control
3
Automatic generation control
2
30
Journal of New Innovations in Electrical Engineering
Available online at www. jniee.com. Vol. 2, Issue 1, 2017, pp. 28- 38
ISSN: 2534-8809
imbalance are the same as in AGC [5]. The major difference between an AGC type scheme and
DBFC is the discrete nature of the controls for loads. In AGC, participating generators adjust
their power output according to a predetermined level of control for each level of frequency
deviation. Each generator has a continuous response according to its predetermined control gain.
For DBFC, the control gain can only be determined by the aggregation of multiple loads. Two
possible methods for establishing a decentralized, aggregate control gain are: 1) Setting the
sample time for the devices, or 2) Variation of the frequency activation set points for
participating loads. Using the sample time to establish the control gain allows for a simple,
uniform control setting for each load, with no coordination between them. The sample time
determines how many DBFC devices will be activated at any particular time. A longer(shorter)
sample time will reduce(increase) the control gain by reducing the number of devices activated
in any one time period. The use of sampling times for DBFC prevents situations where all the
devices could trip at the same time, resulting in large discontinuities in demand and system
instability. Setting the sampling time for DBFC systems will prevent all from triggering at the
same time. Although, it will possibly be necessary to update the sampling time to adapt to
dynamic changes in the overall power grid, including participation of loads and composition of
generators . The alternative method to using sampling times, would be to assign various levels of
frequency activation to the DBFC devices. Some devices would be set to have a greater
sensitivity to deviations in frequency and others would have less sensitivity. This would allow
for a close approximation of the smooth, linear frequency response curve of generators
participating in AGC. The problem with this method is that the settings must be coordinated so
that the distribution of set points approximates the linear response. The sampling method
alleviates this problem and allows for decentralization of the DBFC, while achieving a frequency
response characteristic that is effectively continuous. The aggregation of many small, discrete
control devices participating in DBFC allows for a smooth frequency response curve (similar to
that of AGC) with the gain (slope of the curve) determined by the sampling time. The following
is a more detailed mathematical analysis of the determination of the sampling time necessary for
frequency control to maintain frequency within specified bounds (See ch. 13 in [5]):
Let
dp
= Change in Power resulting from activation of DBFC devices for frequency control
dt
n = Number of DBFC devices installed
Pli = Amount of Power used by device (i).
Tsi = Sampling time for machine (i).
Pi = probability of availability for device (i).
For frequency control:
n
dp
( Pi * Pli ) / Tsi
dt i 1
(11)
Assuming a uniform, random distribution of activation of devices over the sampling time.
The Sampling time, TS, therefore, will have to be updated as more loads enter into DBFC based
frequency control. This will ensure that the rate of change in Power from the loads is not too
large and frequency adjustments will behave in a manner similar to AGC systems. Of course,
there will have to be a large number of loads participating in the DBFC system in the first place.
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Journal of New Innovations in Electrical Engineering
Available online at www. jniee.com. Vol. 2, Issue 1, 2017, pp. 28- 38
ISSN: 2534-8809
Without a critical mass, the DBFC systems will not be able to shed sufficient load to enable
frequency control.
The gain of the overall DBFC frequency control system will be determined by the sampling time,
Ts. From Chapter 13 of [5], the control needed so that the power imbalance is eliminated in one
control cycle is:
P control ( PGdev PLC ) Pimb
(12)
for a single time period. Where
PGdev - Deviation in power generated from expected,
PLC - Amount of power from load control.
From this, we can derive the corresponding sampling time, Ts, for a DBFC control system, given
the number of loads participating and their characteristics:
Then,
n
P control ( ( Pi * Pli ) / Tsi )
Since, P
i 1
control
Pimb to eliminate frequency deviations, and:
m in
imb
m ax
Pimb Pimb
m in
imb
( G L ) *
m in
m ax
imb
( G L ) *
m ax
P
P
P
(13)
(14)
(15)
(16)
L - Droop characteristic of the System from Load
G - Droop characteristic of the System from Generation
Thus:
n
Ts ( Pi * Pli ) /( G L ) * m in
i 1
(17)
n
Ts ( Pi * Pli ) /( G L ) * m ax
i 1
(18)
DESCRIBING MICROGRID AND CASE STUDY
For the proof of concept of frequency control by demand response in a microgrid , a littleisolated microgrid in this study is considered that this network included a diesel generator and an
asynchronous generator that is representative of the wind turbine and renewable energy.
Generally, the public is also part of a reserve equipment maker is microgrid though, because of
the fact that the usability frequency and voltage control in consolidation methods, this equipment
is not considered storage. Simulation considers three types of active loads that are normal in
households and residential are found, and that can be for the interruption of short that for
customers, be acceptable about the topic (Includes space heating loads, refrigerators and freezers
and storage waterheaters). Designed microgrid is a 480 volts islanded distribution system with a
DG4 (Synchronous Machine) 300 KVA and wind turbine (Asynchronous Generator) with 275
4
Diesel generator
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Journal of New Innovations in Electrical Engineering
Available online at www. jniee.com. Vol. 2, Issue 1, 2017, pp. 28- 38
ISSN: 2534-8809
KVA capacity. Generation of wind turbine accomplishes with the asynchronous generator and
with constant speed (10 m/s).
Fig 2 . Designed Microgrid in MATLAB/SIMULINK
Try to have the loads for this microgrid is to reality be close and as is the following:
1-Constant load 50 KW and 20 KVar
2-Switchable load 20 KW and 8 KVar
3-Responsive load for regulation of system frequency
A collection of constant load and switchable load denominate under the title of the Main Load.
Wind turbine mechanic torque control and regulate with feedback of turbine speed and wind
speed. Wind turbine assumes 10 m/s id est wind turbine has necessary power for generating of
load power.
Be output synchronous machine mechanical zero assumes means agricultural work as a motor.
For R and L values is distribution lines fit and close to actual value is considered. In practice, so
that production can be asynchronous generator is able to sync again, and worked as a
synchronous condenser to maintain system voltage. The responsive load consists of eight threephase resistance sets that are controlled by the switch. Total rated power changes between 0 to
446.25 KW in 1.75 KW steps. In this system, The amount of production of generators to be fixed
and Frequency control just from the load and demand is. This study on the regulation of the load
resistance for stabilizing the frequency of level feed is emphasized. It assumed that each
responsive load included the feed of electric water heater that can be in a state of ON or OFF. In
this study, a central controller is responsible for the regulation of the frequency. In this system,
the assumption is made that the bidirectional communication between the Control Center and
each load is established. The network has been designed in the direction of the correct claim
frequency control from the demand side in the MATLAB/SIMULINK implementation, has been.
DESCRIPTION OF CONTROLLER AND CONTROL STRATEGY
The proposed control strategy regulates the frequency of the islanded microgrid by controlling
the operation of the responsive EWHs5 to match the demand and generation at each instant in
time. On the average, residential EWH electricity consumption accounts for about 11% of total
electricity consumption and it increases to over 30% during peak demand hours [5], [6].
Therefore, there is a considerable potential for EWHs to be effective in demand response
applications for frequency and voltage stabilization. When the frequency deviation, Δf, is
5
Electric water heater
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Journal of New Innovations in Electrical Engineering
Available online at www. jniee.com. Vol. 2, Issue 1, 2017, pp. 28- 38
ISSN: 2534-8809
negative (due to low generation or high demand), then a portion of the responsive loads that are
operating will be turned OFF. On the other hand, when Δf is positive, a part of the responsive
loads that are not operating will turn ON. Therefore, the percentage of the EWHs in the ON/OFF
state is continuously adjusted, as shown in Fig. 3, to regulate the system frequency within the
desired limit. Since EWHs have energy storage capability, turning them ON or OFF for a few
minutes may not have a noticeable effect on the participating customers comfort level, and they
may not even realize the control of their EWH. Moreover, the percentage of participating
responsive load is kept to a minimum at each instant.
Fig 3 . The idea of responsive load control
Fig 4 . The flowchart of the frequency regulation technique
In this process, power, active production units and consumption of loads controlled to balance
the prompt and rapid load and production and the recovery of consistent frequency and
modulation have been. In this method of the Center of the moderate ability of the center with
calculated DR strategy to calculate and compute value DR to regulate the frequency based on the
frequency offset , single settlement system is needed. Emphasis on this project, the solution of
this issue with the introduction of a comprehensive DR strategy and the frequency deviation of
the umbrella on the feedback to set the frequency of the system in real time has been established
by. DR strategy proposed for direct load control is a central referred composed of two modes of
operation that corresponds to the frequency deviation f of the system domain.
Mode 0: normal operation – does not need any control
Mode 1: in this case, f are beyond the scope of the requested control and fitted with very
trying times and with a maximum that is possible to provide for bringing f to the range has
been asked to act
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Journal of New Innovations in Electrical Engineering
Available online at www. jniee.com. Vol. 2, Issue 1, 2017, pp. 28- 38
ISSN: 2534-8809
Fig 5 . The components corresponds to the frequency control block
DIFFERENT SCENARIOS AND SIMULATION RESULTS
Simulation studies are done in different loading for assessment of the efficiency of offered
control strategy.
Scenario 1 - A sudden increase in load and Drop the frequency of the system
Constant load 50 KW and 20 KVar in the circuit is. In seconds 9 , switchable load 20 KW and 8
KVar reduce the system frequency. By reducing frequency , control system act and part of the
responsive load of the circuit gets out to system frequency is regulated.
By entering 20 KW in seconds 9 , control system get out 20 KW of responsive load that total
load is fixed in 200 and relocate frequency. The results, the improvement in the efficiency of the
system by loading the status in that case is controlling active shows. The simulation result is
shown in figure 6.
Scenario 2 - A sudden decrease in load and rise the frequency of the system
Constant load 50 KW and 20 KVar in the circuit is. In seconds 9 , switchable load 20 KW and 8
KVar increase the system frequency. By increasing frequency , control system act and part of the
responsive load of the circuit entered to system frequency is regulated.
By going out 20 KW in seconds 9 , control system enter 20 KW of responsive load that total load
is fixed in 200 and relocate frequency. The results, the improvement in the efficiency of the
system by loading the status in that case is controlling active shows. The simulation result is
shown in figure 7.
Scenario 3 - Drop and rise the frequency of the system as the result of A sudden increase
and decrease in load
Constant load 50 KW and 20 KVar in the circuit is. In seconds 4 , switchable load 20 KW and 8
KVar enter in the circuit and in seconds 9 get out. It means that frequency in the beginning
decrease and then increase that in both time control system act along regulation of frequency.
By entering 20 KW in seconds 4 , control system get out 20 KW of responsive load that total
load is fixed in 200 and relocate frequency. By going out 20 KW in seconds 9 , control system
enter 20 KW of responsive load that total load is fixed in 200 and relocate frequency. The
results, the improvement in the efficiency of the system by loading the status in that case is
controlling active shows. The simulation result is shown in figure 8.
CONCLUSIONS
This article discusses a study on frequency control of intelligent microgrid in use and demand
response management refers to this method and work with the design of a microgrid and a
controller that can control the direction of the load frequency control, investigation. enable the
active participation of customers in demand response as an important expression of the smart
grid project has been. This can keep the balance between production and demand and as a result,
35
Journal of New Innovations in Electrical Engineering
Available online at www. jniee.com. Vol. 2, Issue 1, 2017, pp. 28- 38
ISSN: 2534-8809
the maintenance of the frequency and voltage of the system to be effective in the requested
values. This paper focuses on the proof of claim controls the frequency in a microgrid through
the control of time instead of units of electricity generation are emphasized. Assume that energy
saving type of cargo reaction brakes maker that cut short both of them connected in the wellbeing of customers will not be. This microgrid implemented in MATLAB/SIMULINK. PIDcontroller with switchable load responsible for frequency control in the microgrid. Assume that
in this production system is fixed and therefore the frequency control takes place by the load.
The considering strategy of control and holding the generation and command to load and design
of responsive loads Special complexity has had its. After the simulation and extract charts,
accuracy and correctness of this claim were to prove.
Fig 6 . system frequency reduce and it’s compensation by controller in load sudden increasing
mode
Fig 7. system frequency increase and it’s compensation by controller in load sudden decreasing
mode
Fig 8 . system frequency decreade and increase and it’s compensation by controller in load
sudden increasing and decreasing mode
Conflict of interest
The authors declare no conflict of interest.
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Journal of New Innovations in Electrical Engineering
Available online at www. jniee.com. Vol. 2, Issue 1, 2017, pp. 1- 10
ISSN: 2534-8809
REFERENCES
[1] Mojtaba Khederzadeh, “Frequency Control Of Microgrids By Demand Response” CIRED Workshop - Lisbon
29 30 May 2012 -Paper 0002 .
[2] S.A. Pourmousavi, M.H. Nehrir, “Demand Response for Smart Microgrid: Initial Results” Innovative Smart Grid
Technologies (ISGT), 2011IEEE PES , 978 - 1 - 61284 - 220 - 2/11.
[3] S. Ali Pourmousavi, M. Hashem Nehrir “Real-Time Central Demand Response for Primary Frequency
Regulation in Microgrids” IEEE TRANSACTIONS ON SMART GRID, 1949 - 3053© 2012 IEEE .
[4] Kamalanath Samarakoon, Janaka Ekanayake, and Nick Jenkins “Investigation of Domestic Load Control to
Provide Primary Frequency Response Using Smart Meters” IEEE TRANSACTIONS ON SMART GRID, VOL. 3 ,
c
NO. 1 , MARCH 2012 .
[5] Jason W Black, Marija Ilic, “Demand-Based Frequency Control For Distributed Generation” Power Engineering
Society Summer Meeting, 2002 IEEE (Volume:1 ) .
[6] Angel Molina-García, François Bouffard, and Daniel S. Kirschen “Decentralized Demand-Side Contribution to
Primary Frequency Control” IEEE TRANSACTIONS ON POWER SYSTEMS, VOL. 26 , NO. 1, FEBRUARY 2011.
[7] Seyyed Ali Pourmousavi, Mohammad Hashem Nehrir, “Real-Time Optimal Demand Response For Frequency
Regulation In Smart μgrid Environment” EuroPES 2012 .
[8] L.A. Tuan, K. Bhattacharya, " Interruptible Load Mangement within Secondary Reserve Ancillary Service
Market, " IEEE Power Tech. Proc.Vol.1, Page(s): 6 pp, Sept 2011.
[9] E. J. Paulson, "Demand Response as Ancillary Services in the the PJM RTO" IEEE Power Eng. Soc. General
Meet.pp 2638 - 2641, Jan. 2005 .
[10] Jong-Yul Kim, Seul-Ki Kim and June-Ho Park, “Contribution of an Energy Storage System for Stabilizing a
Microgrid during Islanded Operation” Journal of Electrical Engineering & Technology Vol. 4 , No. 2 , pp.
194 ~ 200, 2009 .
[11] Seon-Ju Ahn and Joon-Ho Choi, “Power Sharing and Frequency Control of an Autonomous Microgrid
Considering the Dynamic Characteristics of Distributed Generations” Journal of International Council on Electrical
Engineering Vol. 2 , No. 1, pp. 39 ~ 44, 2012 .
[12] P. Teimourzadeh Baboli, M. Parsa Moghaddam, F. Fallahi “Utilizing Electric Vehicles on Primary Frequency
Control in Smart power Grids”. 2011International Conference on Petroleum and Sustainable Development
IPCBEE vol. 26 (2011) © (2011) IACSIT Press, Singapore.
[13] Seon-Ju Ahn and Joon-Ho Choi, “Power Sharing and Frequency Control of an Autonomous Microgrid
Considering the Dynamic Characteristics of Distributed Generations”. Journal of International Council on
Electrical Engineering Vol. 2, No.1, pp. 39 ~ 44, 2012. .
[14] Muhammad Ali, Muhammad Zakariya, Muhammad Asif, Amjad Ullah “TCP/IP Based Intelligent Load
Management System in Micro-Grids Network Using MATLAB/Simulink”. Energy and Power Engineering,
Published
Online
July
2012, 4, 283 - 289 doi : 10.4236/epe.2012.44038
2012
(http://www.SciRP.org/journal/epe).
[15] ESAKI Hirotoshi and SUGIHARA Hiroaki, “Simulation of supply-demand control in Micro Grid with
fluctuating natural power supply”. The International Conference on Electrical Engineering 2008 .
[16] S.A. Pourmousavi, M.H. Nehrir, “Providing Ancillary Services through Demand Response with Minimum
Load Manipulation”. North American Power Symposium (NAPS), 2011.
[17] Nuno José Gil, J. A. Peças Lopes, “Exploiting Automated Demand Response, Generation And Storage
Capabilities For Hierachical Frequency Control In Islanded Multi-Microgrides”. 16 th PSCC, Glasgow, Scotland,
July 14 - 18, 2008 .
[18] Coalton Bennett, Steven B. Wicker, Judith Cardell, “Residential Demand Response Wireless Sensor
Network”.Proceedings of the Fourth Annual Carnegie Mellon Conference on the Electricity Industry, 2008 .
[19] V. S. K. Murthy Balijepalli, Vedanta Pradhan, S. A. Khaparde , R. M. Shereef “Review of Demand Response
under Smart Grid Paradigm” 2011 IEEE PES Innovative Smart Grid Technologies – India.
37
Journal of New Innovations in Electrical Engineering
Available online at www. jniee.com. Vol. 2, Issue 1, 2017, pp. 1- 10
ISSN: 2534-8809
[20] Hristiyan Kanchev, Di Lu, Frederic Colas, Vladimir Lazarov, and Bruno Francois, “Energy Management and
Operational Planning of a Microgrid With a PV-Based Active Generator for Smart Grid Applications”, IEEE
TRANSACTIONS ON INDUSTRIAL ELECTRONICS, VOL. 58 , NO. 10 , OCTOBER 2011.
[21] Jong-Yul Kim, Seul-Ki Kim and June-Ho Park, “Contribution of an Energy Storage System for Stabilizing a
Microgrid
during
Islanded
Operation”.
Journal
of
Electrical
Engineering
&
Technology
Vol. 4, No. 2, pp.194 ~ 200, 2009 .
[22] Nikos Hatziargyriou, “Power System Operation and Control Including Demand Response and Microgrids”,
Tutorial “Future of Smart Distribution Grids with Distributed Energy Resources”, Dec 4 - 6 ,2007 , Napa,
California.
[23] R. Gagnon, B. Saulnier, G. Sybille, P. Giroux; "Modeling of a Generic High-Penetration No-Storage WindDiesel System Using Matlab/Power System Blockset" 2002 Global Windpower Conference, April 2002 , Paris,
France.
[24] B. Saulnier, A.O. Barry, B. Dube, R. Reid; "Design and Development of a Regulation and Control System for
the High-Penetration No-Storage Wind/Diesel Scheme" European Community Wind Energy Conference
88, 6 - 10 june 1988 , Herning, Denmark.
[25] http://electrical-engineering-portal.com/the-challenge-of-protecting-microgrids-alstom
[26] P. Mazidi, G. N. Sreenivas; “Reliability Assessment of A Distributed Generation Connected Distribution
System” .International Journal of Power System Operation and Energy Management(IJPSOEM), Nov. 2011.
[27] Sarkar ,B. K ”Theory of Machines Through Practice and Solved Papers” .Allied Publishers,
2000 ISBN 978 - 81- 7764 - 056 - 4 .Retrieved 2013 - 06 - 07.
38