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Proceedings ArticleDOI

Development of Dynamic Equivalents for MicroGrids using System Identification Theory

TL;DR: In this paper, the authors proposed an approach based on system identification theory for developing dynamic equivalents for microgrids, which are able to retain the relevant dynamics with respect to the existing medium voltage (MV) network.
Abstract: Large deployment of microgrids will have a considerable impact on the future operation of the electrical networks and will greatly influence the power system dynamics mainly at the Medium Voltage (MV) level whenever the upstream system has been lost. In dynamic studies the whole power system cannot be represented in a detailed manner because the huge system dimension would require a very large computational effort. Therefore dynamic equivalents for microgrids need to be derived. The proposed approach is based on system identification theory for developing dynamic equivalents for microgrids, which are able to retain the relevant dynamics with respect to the existing MV network.

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      
        
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
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
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(+
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"-+,./01
 , $,%   !# "-   
* '  (   +'+
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(  + ' "&
"' '+"+*$2#% 
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:"++2"(22
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@2=!"++2"(2"+
+':2;:'
+  * 2 2 2' $>4
/? '%
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,$,%"++&*"+
+ "- +  >, 2/ 
56789$8%'(+(&+*'
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B''+,
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("+' 
+&'('+,(&+*'
&   ' + & '
B' * + ' ( "+  
'&(B'
+' '+*(*
,"++#"-(
' ' '  + 
(B'*,B'
* ( B'* +B'  
+ "  0914 $% +( E $%
 + E $%  "-
'E $*%   * D"* 
 " ( +(   
(  (   ,   
+!#"-+'+*
+ (+*('
+&('(
"+*"('
**"+,
*( * "-  + '&
* , B'* * + & 
 '+ B'* *  *( ' +
*(B'*
,'(+(
:@2=! 

A
' ( +B'  (  +( +
&)&(B'*,
  "+ (  ( 
"++&&'+&
 &*   + ( &  
+'&'' +'
+++(
+ ' *  -"  +( +
&' + ( *( ' "+   
''" & -  4<- &)
( &)  0F1 + ) &- &)  
'"-"(''(
&' ( B'*  , 081   + "
(&'"+0F1
+++*&+(-"&'+
,()+''&''
-"+( ""+ +'-"
 +'&+(&)
+   ( -"  +(  
 +  ''   +(
0G1
+B'*+'&"'
,('"+*'&
+ # * '  - # "-   
"      " *'
+'+ ' +' +'(
++'+&,(B'*


,

D
,!#&'("++
'  (   + "+ !#
 :
:  , +'  '    
*
+ ,  (    &( 
,$,%+#H!#
'&  "++  * -( '  +
+++('B'+
  *
&+ '  $%  ! 
$!% +   ++  * 
&+  + ' $%   *4 
(+**"'*
&!+'++
'&(
 ,
2
!
!
>

,

: + ) + ,  )&( +
#*'&++'"+
,'&+(
   "( +  , +'  ,   -
 + &( ' * - '  + '
" (  &(   - 
B'
:",+'( 
,"&-"++#"-
"+ + (+' +  + #
**B'(
 ( B'*(   "+
* " (  ,   * 
  &+ +(   
+ - -'+"
( +'   &' ( B'*  ,
&  +(   +  (  
*  "  +    + ' 
'' ,       
&((+"
 
*    ' '   '& 
"   2# ( +* &  071
D"* +"-():'$:%
+++'&$%'"+
+"  $H*:
 HH *%*"
' " *'
"+ "   $HH * 
("+H*&%
 !"
*&"
4 2I *   # ' *
$#%  061 + 2I * /  +  +
" *&   ' + * " /
  > *' "++  & 
+('(+
,0A13 +(+(&+*'
 ,  *   ( &( + 
' +"+
+#'+&+*'(+'+
**B'(  + ,'
D"*&
 "++#"-+
' B'( 

+ # * " '' 
 &( + B'(  +   
:A

C
:A:B'(
 # '   * '
 ' ' *  * "
:B'(  '' * '  &+
+'+    + +  
"#('&$)
+%&(*&
051
# $#
3 +*+,"
(*+B'(
"&&*'+
 + #  +   ' " ' "
* &( / &&  ' *
"(+,B'(*
+'+    * '  * +*
 (   ( ' +( 
+ + ( B'( +' &  +
*'
%
+#*"'
:+'"(
&"4('2
 + &    ( 
&(+,&+ *'*
"''+(('+'&
&+B'(*01 :
CD"* ++(+(
("
:C!(B'(&
3 +  ,    + ' "
( +(+'++#*
" &&&  '( D"*
"'&+#*-" 
( B'( +  # * "
*++
( B'(  & 
+(B'(+*'+'++
  " * "    + (
(''+,"&'+"+
+ (+' + & * " 
'(
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::
!
J
J
  "+ (  ( 
"++&&'+&
 + &*   + ( <   '&
 '' +   '  + 
++(&0G1
+ '((
)   + & ( 
&(''&''
 /'      +
 ' ( B' &(  
<+("++' 
&'  +  ''  #&' 
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*(    () * + "+ +  +
'& (
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:9+&''+++
(''"&)'+'
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:9<'+'(+(

++&'"+'&
 + ' +" " +   + (
(&+*' "+ ++ "  +
   + + ' + 
&+*+&-
' ( + + +'+ 
+ ++''*
2''(&
  +  +  + &
 * , "++ *  +  
+(''+(
''''(-B''
+*&(B'$% 
( )
=
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+
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A
KE
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θ
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 0F1 +   +B' 
'+ &"  & +B' +
   +B' * '
'+'+*++ "++
   +    +  
& &( +&'+  '+   
&(**+ 
'++*
'*&'

9
+&+
'  + +  &(  **
*'( + $% '  + 
&++B'0F1
2"$2%++&
'  (    "+ 
 2*+(
*&*0A1*'(2
"  $2% & + &  
2  +'+ + ' +  *
*(0C1'
&'
:(   *' "++ +  
'++';+*+
+-++*&'
''+(+*
(&-+'*
+*'
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+  +  , ( B'*
* ) (  +( ( 
+(  +  + '  (
&  + *& +( -"  (
*'(+,(B'*B'
&   ( '   
'+*(,"++#
"-" (,
"    + + -" &'
+ , ( " ' + "+ + 
' &+"
 
:('+"+,"-*
4 +"-"+ '&-
 "+ +  + ( B'*  &
&*  + ) ("+  
 + (    B'  +  
&  &( B'*+'
+)(+,
+"-+,"-
+ +( " + & + , ( "
'+ &" "  ( 
 + *   + ,4 % +  
* "+  #  * (  (
 "+ &% + &  "+  2I *
 ( " (    
+'++
!#  +'+ * "+ 2I   + 
&+'+&
+ '   '& ( B'*  ,
++*#
  
, (  ++  , " ( '
 :F

&



'
"


:F,(B'*
+ , ( B'* "  "+ + 
"- +'+ + (&'(4 + &'( &' 
+"&)&(&+&'(&'*
(B'(*&(*(+/
'+(:F

+ -( '   (  '  +
 ''   +  + +( "+
 ) + , " ( ' + '(
'+(++
* + * "     ' +' +
((&(''
   *  "++   '
.
/
0
/
* +'+ + &- 
:8
1
A
A
+
2
+
2
:8''+,(B'*
+ ''  "+ *' +* &
'+'+
+* 
[
]
221
AA
=
θ
$9%
+ *&
3

 : 8  + * " 
&(+,+#+
+ ' " +( 091 " '  
"+''
44!
+**&($9% 2
 ) + "+ + ' B'  
B'$A%+'+
*'   '& ( ' 
+   &" 2  + (
'   B' 2  + 
*+('+
 '  2 * +  
'*':G
-  ' + '  + + 
*    + *  "++  " &
'  *     &  +


F
Σ
:G2+
#
J
!
2
!:
 '  " * '
./
0/
*'>+(
*' +   '( + , (
B'* + '  " ' +
,    "   
  +  + , (
B'*+'+++:G
(  *   (  : 
,+!#"-+'+
+ *   "      
&     " +'
+#*'(+'+
8+  +"+'*'
$(%*>'&
5$
  0F1 "  ! 
      
B'*  *( +  "-
'&+#!# &(+
)&'
5$

#
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!
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B'*+,+(
:7 "++,+,(
"'(+'$F55-#%
+#"-+"+#!#
 #H!# &'  ; +
, + , " C5-3   C5-3
:  +   * $("+% + '(
("+,'+:7
+    &  +  (
 :" + ,   +
'" (   " 
+ # "- "   ' 
B''&'7
$!%   +  + '   ' * 95
$+  '     LA 
LA5% "++'+(
   ' + *&   * F
"+*5
>8
+,
&&
'%
(
:7(>4$%(E$&%'
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2,
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:
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!$M#% ,'$-3 E-#%
#"- F55N/55 4AF5EA4A55
, F5N/5 LALFN/A
:LFN/AE#L/F
  +    +
+( & &* +  + ,
(B'*&+,&+*'"
+,  '" "*'
: +''+*&'
+&'"++&"++
, + (+,
(B'**" 
&+*'''",
&&&A
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!$M#% ,'$-3 E-#%
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, F5N/5 L5N/AE#L/F
AL:LFN/A
 + "   + "
B'*"'4%#"-
LFE A%   " '   LA5E C%
 + '*'(
L95    &" +  & 
'(:6>
:  +"   &" + * "
/&(+, "(B'*+
:"+,
   B'( *   & +"
: 5 +' + # / * "  
++,*''
 + +  "+ (  B'( 
 + "+ + (+' + 
B'('+
(&&*:6 *(

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Journal ArticleDOI
TL;DR: A robustness-improved method for dynamic equivalent modeling of ADN is proposed and long short-term memory neural network is adopted to generalize the identified parameters and enhance the robustness of equivalent model.
Abstract: Accurate equivalent model can be efficient to analyze the dynamic properties of active distribution network (ADN) as well as assess their impacts on stabilities of interconnected power system However, due to the stochastic nature of renewable resources and time-varying configurations of load conditions, traditional ADN equivalent model may not be robust enough to different operation conditions To overcome the limitations, this article proposed a robustness-improved method for dynamic equivalent modeling of ADN To sketch out the most representative operation conditions of ADN, two-step clustering method with fisher discriminant analysis are used for grouping of operation conditions featured characteristic data sets With the key parameter based identification technique applied, the multiple solution issue in parameter identification process could be effectively avoided To further enhance the robustness of equivalent model, long short-term memory neural network is adopted to generalize the identified parameters The performance of proposed modeling method is comprehensively evaluated by an actual ADN based verification cases

7 citations


Cites methods from "Development of Dynamic Equivalents ..."

  • ...In [6] and [7], gray-box equivalent models, incorporated with different kinds of parameter identification algorithms, were developed....

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01 Jan 2015
TL;DR: This thesis investigates the applicability of modal analysis as a tool for dynamic model equivalencing of grid connected hybrid microgrids while introducing a new index to identify the dominant modes of the system.
Abstract: Increasing levels of penetration of distributed energy resources (DERs) have transformed distribution networks from passive to active networks and introduced the concept of microgrids. Dynamic characteristics of microgrids operating either in grid connected or islanded modes can be different from the traditional distribution networks due to the combination of different DERs. In order to make microgrid operation attractive, the issues associated with microgrids need to be properly analysed. This thesis examines the modelling of microgrids and investigates different aspects of their operation. In the first phase of the work presented in this thesis, dynamic characteristics of microgrids comprising different distributed generators are investigated. The importance of understanding the dynamic behaviour of microgrids is highlighted through a comparative analysis carried out on a hybrid microgrid. A simulation model of a hybrid microgrid comprising a PV system, a doubly-fed induction generator (DFIG) based wind power plant, a mini hydro power plant, and loads is developed for the analysis. This study revealed that the dynamic characteristics of the microgrid are significantly influenced by the characteristics of individual DERs and their control systems. It has been noted that during grid connected mode, features of the external grid also have an impact on microgrid behaviour. The second phase of this thesis is focused on aggregated modelling of grid connected microgrids comprising both inverter interfaced and non-inverter interfaced DERs. For stability analysis, the common practice is to separate the power system into a study area of interest and external areas. In general, the study area is represented in a detailed manner while external areas are represented by dynamic equivalents. This thesis investigates the applicability of modal analysis as a tool for dynamic model equivalencing of grid connected hybrid microgrids while introducing a new index to identify the dominant modes of the system. The grid connected microgrid is represented as a single dynamic device while retaining the important iii dynamics. Linearised models of different DERs with control systems and loads are developed for this study. Several case studies are carried out to validate the reduced order dynamic model of the microgrid by testing under different operating conditions. Furthermore, the model equivalencing is applied on microgrids in a multi-microgrid environment to validate the methodology. Similar to the large generators in conventional power systems, grid connected microgrids have the potential to participate in energy markets to achieve technical, financial and environmental benefits. In order to enable such operation, a systematic approach in developing a capability tool for a grid connected microgrid is presented in the next phase of this thesis. A grid connected microgrid can be viewed as a single generator or a load depending on power import or export at the grid supply point. However, unlike in a single generator with simple machine limitations, active and reactive power transfer limits of a grid connected microgrid depend on many factors, including different and multiple machine capability limits, local load demands, and distribution line capacities. A mathematical model is developed to establish the active and reactive power transfer capability at the point of common coupling, considering all aspects of grid connected microgrids. Capability diagrams for different microgrid scenarios are derived using the mathematical model, and the applicability of microgrid capability diagram as a tool in the energy market operation is also presented. The low voltage ride through (LVRT) capability of grid connected microgrids and the potential to provide voltage support as an ancillary service for the main grid are investigated in the final phase of the thesis. Two approaches are followed to investigate the LVRT capability of a microgrid as a single entity. In the first approach, dynamic voltage support at the microgrid point of common coupling is improved by using a distribution static synchronous compensator (DSTATCOM) connected to the low voltage side of the distribution transformer of the microgrid. The collective effect of the LVRT capabilities of the distributed generators in the microgrid is used to provide voltage and reactive power support to the external grid in the second iv approach. Furthermore, operation of the DSTATCOM in multi-microgrid environment and islanded mode are also investigated under different operating conditions. Impact of the DSTATCOM location in the microgrid is also analysed by installing it at the low voltage side of the microgrid distribution transformer, at distributed generator terminals and at the bus bar with lowest reactive power margin. Variations of the microgrid system parameters during the fault and after fault clearance are analysed to identify the most appropriate location for DSTATCOM operation. It was identified that having the DSTATCOM at the low voltage side of the microgrid distribution transformer is far more beneficial in situations of microgrid transition from grid connected to islanded mode of operation, which would improve the microgrid voltage profile. DSTATCOM operation would reduce the reactive power demand from the external grid which arises due to faults in microgrids containing mains connected induction motor loads. Based on the studies presented in this thesis, it can be identified that integration of multiple microgrids into the utility grid will allow the microgrids to provide ancillary services to the main grid during grid connected mode, and provide emergency services to adjacent microgrids during a utility grid outage. The work presented in this thesis provides the groundwork which will enable microgrids to perform such ancillary services.

7 citations


Cites background or methods from "Development of Dynamic Equivalents ..."

  • ...A grey-box technique is combined with an evolutionary particle swarm optimisation algorithm for parameter estimation of a microgrid in [80]....

    [...]

  • ...In white-box modelling, model parameters are identified from a known structure, and mathematical model of each physical component of the system is determined [80]....

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Proceedings Article
01 Aug 2011
TL;DR: This paper presents the development of a dynamic equivalent model for a Distribution Network Cell (DNC) based on the UK 11kV distribution system that utilises the k-means clustering procedure to approximate the input and output dynamic responses of the network.
Abstract: This paper presents the development of a dynamic equivalent model for a Distribution Network Cell (DNC) based on the UK 11kV distribution system. In a new and innovative approach, the methodology utilises the k-means clustering procedure to approximate the input and output dynamic responses of the network. By grouping together similar dynamic responses, the developed methodology is able to significantly redu ce the computation time required to approximate the dynamic response of the network. The accuracy of the procedure is quantified by analysing the deviation of the true r esponse from the approximated cluster centre. The computational efficiency of the approach is compared against para meter estimation without clustering, and the resulting approximation errors and computational improvements highlighted.

7 citations


Cites methods from "Development of Dynamic Equivalents ..."

  • ...In [1], a grey-box approa ch was applied to a large power system network and in [2] a grey-box approach was combined with an Evolutionary Particle Swarm Optimization (EPSO) algorithm for parameter estimation of an MG....

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  • ...Previous research on dynamic equivalent models has been applied to both large power system networks[1] and MicroGrids (MGs) [2]....

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DOI
01 Jan 2019
TL;DR: In this article, a method for the dynamic modeling of reference systems that can be parameterized in a stochastic way is presented, where systemic key data can be identified which is used to parameterize the equivalent systems.
Abstract: Current energy policy goals lead to a redesign of the electrical energy system, which results in an increasing substitution of conventional power plants by distributed energy resources. The distributed systems are usually fed by renewable energies and they are usually installed in the distribution grids. To sustain the overall system stability and to prevent blackouts in the European transmission grid, analyses of transient stability, among other stability aspects, are necessary. The amount of information as well as the modelling and computational efforts for distribution grids must be kept as small as possible, using equivalent models. In this work a method for the dynamic modelling of reference systems that can be parameterized in a stochastic way. Using these reference systems, systemic key data can be identified which is used to parameterize the equivalent systems. For this purpose, laboratory tests are performed to identify realistic stochastic parameter spaces. The stochastic component modelling that is developed within this thesis is successfully tested on pure machine systems, machine systems with controllers, power electronic systems and hybrid systems. The approach allows a much more realistic modelling of reference systems than before, where only single grid sections with fixed component parameters are used. With the help of a more detailed overall equivalent model than in previous works, new features can be included in the equivalent systems. For example, different specifications of the reactive current droop control within one grid, or geographical as well as manufacturer-specific clusters can be modelled. Using a variancebased sensitivity analysis, systemic key data is identified that can be used to parameterize the equivalent model: the primary indicator is the peak power of the infeed and loads. The secondary indicator is the cumulated frequency of the plant sizes, which can be used to increase the quality of the solution and to decrease the safety margins. The dynamic parameterization as a novel approach is validated against synthetic grids and a real grid. The results show that the models themselves and the whole method is valid. Using simple functional dependencies, generic equivalent models can be parameterized using a small amount of systemic information on the grid. The only exceptions are the coupling impedances. They need to be modelled as impedances with an exponentially increasing dependency on the voltage. If enough information on the grid is available, approaches for initial parameterization, which are further developed in this thesis, can be used to increase the quality of the solution. Inhaltsverzeichnis i

6 citations

Journal ArticleDOI
TL;DR: In this paper , a comprehensive review of active probing-based system identification methods in the context of power system applications is presented, highlighting the advantages of using modern power electronics-based sources in the identification process and discusses the emerging research directions for future.

6 citations

References
More filters
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TL;DR: In this paper, a new instantaneous reactive power compensator comprising switching devices is proposed, which requires practically no energy storage components, and is based on the instantaneous value concept for arbitrary voltage and current waveforms.
Abstract: The conventional reactive power in single-phase or three- phase circuits has been defined on the basis of the average value concept for sinusoidal voltage and current waveforms in steady states. The instantaneous reactive power in three-phase circuits is defined on the basis of the instantaneous value concept for arbitrary voltage and current waveforms, including transient states. A new instantaneous reactive power compensator comprising switching devices is proposed which requires practically no energy storage components.

3,331 citations

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TL;DR: What are the common features in the different approaches, the choices that have to be made and what considerations are relevant for a successful system-identification application of these techniques are described, from a user's perspective.

2,031 citations

Proceedings ArticleDOI
07 Aug 2002
TL;DR: In this article, the authors present a control technique for distributed generation (DG) plants that use feedback of only locally measurable variables, which allows correct system operation and switching between parallel and isolated modes without needing online communication of control signals between the generators.
Abstract: It is expected that dispersed generation (DG) will play an increasing role in electric power systems in the near future. Among the benefits that DG can give to the power system operators and to the electricity customers, one of the most attractive is the possibility of improving the continuity of power supply. DG plants can be designed to supply portions of the distribution grid in the event of an upstream supply outage. Techniques for controlling DG plants that use feedback of only locally measurable variables are presented. This solution allows correct system operation and switching between parallel and isolated modes without needing online communication of control signals between the generators. The control technique is described with particular reference to inverter-interfaced systems (micro-turbines, fuel cells). Simulations of sample cases including different size and type of generators are presented.

310 citations

Journal ArticleDOI
TL;DR: In this article, a sequence of actions and conditions to be checked during service restoration in the low voltage area are identified and tested through numerical simulation, and the need of storage devices is addressed in order to ensure system stability, achieve robustness of operation, and not jeopardize power quality.
Abstract: Under normal operating conditions, a MicroGrid is interconnected with the medium voltage network; however, in order to deal with black start and islanded operation following a general blackout, an emergency operation mode must be envisaged. A sequence of actions and conditions to be checked during the restoration stage are identified and tested through numerical simulation. Voltage and frequency control approaches, inverter control modes, and the need of storage devices are addressed in this paper in order to ensure system stability, achieve robustness of operation, and not jeopardize power quality during service restoration in the low voltage area

269 citations

Proceedings ArticleDOI
12 May 2002
TL;DR: A new meta-heuristic (EPSO) built putting together the best features of evolution strategies (ES) and particle swarm optimization (PSO), including an application in opto-electronics and another in power systems is presented.
Abstract: This paper presents a new meta-heuristic (EPSO) built putting together the best features of evolution strategies (ES) and particle swarm optimization (PSO). Examples of the superiority of EPSO over classical PSO are reported. The paper also describes the application of EPSO to real world problems, including an application in opto-electronics and another in power systems.

246 citations

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