Annual Energy Production Maximization for Tidal Power Plants with Evolutionary Algorithms

Transcription

1 Internatonal Journal of Flud Machnery and Systems DOI: Vo 10 o. 3 July-September 2017 ISS (Onlne): Orgnal Paper Annual Energy Producton Maxmzaton for dal Power Plants wth Evolutonary Algorthms Evgena Kontoleontos and Smon Wessenberger ADRIZ HYDRO GmbH Lunzerstrasse 78 Lnz 4031 Austra Evgena.Kontoleontos@andrtz.com Smon.Wessenberger@andrtz.com Abstract In order to be able to predct the mum Annual Energy Producton (AEP) for tdal power plants an AEP optmzaton tool based on Evolutonary Algorthms was developed by ADRIZ HYDRO. hs tool can smulate all operatng modes of the unts (b-drectonal turbne pump and slucng mode) and provde the optmal plant operaton that mzes the AEP to the control system. For the Swansea Bay dal Power Plant the AEP optmzaton evaluated all dfferent hydraulc and operatng concepts and defned the optmal concept that led to a sgnfcant AEP ncrease. A comparson between the optmal plant operaton provded by the AEP optmzaton and the full load operatng strategy s presented n the paper hghlghtng the advantage of the method n provdng the mum AEP. Keywords: Annual Energy Producton tdal power plants optmzaton Evolutonary Algorthms Swansea Bay 1. Introducton he optmzaton of the Annual Energy Producton (AEP) for tdal power plants can be a challengng task; not only because an advanced optmzaton software s requred but also because the necessary components of the toolchan employed wthn the optmzaton procedure should enable the optmzaton loop to run robustly and n a tme effcent way. In ths paper the man components of the toolchan used for the AEP optmzaton for tdal power plants are presented. As shown n Fg. 1 ths tool chan conssts essentally of an energy calculaton tool developed by ADRIZ HYDRO and an effcent optmzaton platform (heren the Evolutonary Algorthm System EASY [1]). he energy calculaton software s able to model dfferent operatonal modes of the turbne unts provdng the reservor level durng operaton of the tdal power plant and the energy produced n a specfc tme perod. For the ntaton of the optmzaton loop a set of user-defned parameters (desgn varables) s generated by EASY n order to obtan a set of new canddate solutons. In the AEP optmzaton applcaton the operatonal modes the reservor level path the startng and stoppng head of each mode and the speed (n case of a varable speed bulb unt) for each operatng pont through the year consst the desgn varable set. For each one of these canddate solutons the energy and the operaton of the power plant for a specfc tme perod s calculated. he optmzaton objectve functon refers to the mzaton of the energy produced. he values of the objectve functon ndcate the qualty of each canddate soluton and are subsequently used by EASY to generate the next generaton of canddate solutons. In ths way the optmzaton searches for the optmal operatonal modes and optmal reservor level path for the whole year that mzes the AEP. In addton to that due to operatonal range constrants (generator power output speed and cavtaton lmtatons) and envronmental restrctons the optmal solutons are subject to a number of constrants that can be added n the optmzaton platform. Receved Aprl ; accepted for publcaton August : Revew conducted by Yoshnobu sujmoto. (Paper number O17060S). Correspondng author: Evgena Kontoleontos D Evgena.Kontoleontos@andrtz.com Part of ths paper was presented at the 28th IAHR Symposum on Hydraulc Machnery and Systems held at Grenoble July 4-8th

2 Fg. 1 he AEP Optmzaton Scheme based on the AEP calculaton tool developed by ADRIZ HYDRO and the EASY optmzaton too he optmzaton s based on the defnton of the optmzaton desgn varables and constrants and provdes the mum AEP along wth the optmal tdal plant operaton throughout the yea hs paper s an mproved and enhanced verson of the work and results that have been presented at the 28th IAHR symposum on Hydraulc Machnery and Systems. In what follows the AEP calculaton tool the optmzaton platform and the AEP optmzaton problem are presented and demonstrated n the Swansea Bay dal Power Plant optmzaton applcaton. One advantage of the AEP optmzaton tool presented n the Swansea Bay applcaton s that the optmzaton provdes the optmal combnaton of operatng modes n sequence (between pumpng turbnng and slucng n both drectons) and the optmal operatng ponts for each mode. Addtonally ths paper focuses not only on the descrpton of the AEP optmzaton method and ts successful applcaton but emphaszes also the mportant advantage of ths method comparng the optmal operaton provded by the tool wth full load operaton n the Swansea Bay applcaton. he easly mplemented to the control system full load operaton strategy results n a lower AEP whle the optmal operatng path provded by the AEP optmzaton method contrbutes to the sgnfcant ncrease of the energy produced. hs comparson ndcates also the necessty of performng an AEP optmzaton n order to operate a tdal power plant n the most effcent way. he applcaton of the AEP optmzaton drectly at the tdal power plant n order to provde the optmal operatonal ponts to the control system accordng to tde prognoss s a further advantage of the method presented n ths pape 2. AEP calculaton tool Modellng of the problem In order to set up an optmzaton loop for the AEP mzaton of a tdal power plant a fast robust and relable tool that models the reservor level by smulatng all possble operatonal modes and calculates the energy produced s necessary. hs AEP calculaton tool models 8 dfferent operatonal modes over a tde perod that can be selected by the optmzaton n order to ncrease the AEP. hs operaton s allowed by a trple regulated b-drectonal bulb pump turbne unt that can turbne pump and sluce water n both drectons. ADRIZ HYDRO developed ths new concept of a b drectonal bulb pump turbne wth varable speed turnable runner blades and gude vanes that was appled n the Swansea Bay dal project n order to produce energy at ncomng and outgong tdes [2]. he trple regulated turbnes allow very effcent power generaton and the possblty of pumpng gves an addtonal energy ncrease as t wll be presented n Secton 5. he varous operatonal modes over a tde perod modelled by the AEP calculaton tool are presented n Fg. 2. Durng flood startng from an optmal reservor level water s pumped (Pump Mode Reverse PMR) through the turbne n opposte drecton emptyng the reservor untl the allowed leve hen dle tme (Idle Mode IM I) begns n order to buld up a head for turbnng n reverse drecton (urbne Mode Reverse MR). hs mode ends wth slucng (Slucng Mode SM I) untl sea and reservor levels are equa hen durng ebb water s pumped agan (Pump Mode PM) through the turbne n normal drecton fllng up the reservor untl the allowed leve Subsequently dle tme (Idle Mode IM II) begns n order to buld up once agan the adequate head for turbnng (urbne Mode M) n normal mode. hs mode ends agan wth slucng (Slucng Mode SM II) untl sea and reservor levels are equal agan. Durng SM I and II water can be sluced through the slucng gates and the unts at the same tme n order to ncrease and reduce the reservor level respectvely as much as possble. Another varant of slucng s to start slucng through the gates not at the end of MR and M but n parallel wth power generaton as n Fg. 2. As t can be seen n Fg. 2 n a tdal power plant wde varatons of the reservor level are usua For ths reason through bathymetry studes a relaton between the volume of the reservor V and ts respectve level h s obtaned. In ths way the reservor volume varaton durng the operaton of the tdal power plant s predcted through tme. As t s presented n Fg. 1 and wll be thoroughly explaned n Secton 4 the optmal reservor level h r. l. and speed n for each tme step t (.e. for each operatonal pont) are provded by the optmzaton snce they consttute the optmzaton 265

3 Fg. 2 he varous operatonal modes over a tde perod. Slucng water through the gates (SM I and II) s presented n parallel wth power generaton (MR and M) n order to ncrease and reduce the reservor level respectvely as much as possble and ncrease the energy produced. desgn varables. Each tde cycle s dvded nto small ntervals of tme. For a tme nterval generaton the dscharge through the turbne unts and the net head are gven by ( V -V.. ) 2 r l 1 Q = H net H gr - kq = hs l - hr l - kq ( t - t ) = D t =[ t 1t 2 ] e.g. durng flood. (1) where h s. stands for the sea level and k for the loss coeffcent for turbne ntake and ext losses. he unt generator power output s gven by P = rgh h h H Q (2) M El net where h ( H net Q n) as a relaton of H net Q and n represents the hydraulc effcency that s calculated from the Hydraulc Effcency Hll Chart provded through the hydraulc model testng of the bulb unt. h (n M ) hel ( n PM ) stands for the mechancal and electrcal effcences as a relaton of speed and turbne shaft power P. he total slucng dscharge through the G slucng gates Q SL G and the turbnes Q SL of the power plant s gven by M Q 2 SL= QSL G + QSL = cd G AG 2 gh gr G + cd A gh gr (3) where c d G d turbnes respectvely and c correspond to the slucng gate dscharge coeffcent and the dscharge coeffcent for slucng through the A G A to the gated and turbne area respectvely. he energy produced based on the energy generated durng turbnng (MR and M) and the energy consumed durng pumpng (PMR and PM) n a tme nterval gven by t å 2 2 E = E - E = P Dt - P Dt (4) produced generated consumed t1 MR M t å t1 PMR PM Fgure 2 shows the reservor level durng only one tde cycle. In order to calculate the AEP the optmzaton should be appled for a tme perod that covers one year of operaton. 3. Optmzaton Platform D t s owadays EAs are capable of handlng complex constraned mult objectve problems by accommodatng any analyss/evaluaton software wthout even requrng access to ts source code. Another advantage of EAs s ther ablty to reach the global optmum wthout beng trapped nto local optma. Beng the most known representatve of global optmzaton methods 266

4 EAs are wdely used to solve engneerng optmzaton problems. In fact the only prerequste for carryng out an EA-based optmzaton s the avalablty of an approprate evaluaton software (consdered as a black-box tool by the EA) and well-defned objectve functons and desgn varables. In the AEP optmzaton applcaton the AEP calculaton tool s the evaluaton software. he objectve functons desgn varables and constrants of the AEP optmzaton wll be presented n the Secton 4. In real world applcatons wth computatonally demandng evaluaton software and a great number of optmzaton desgn varables the optmzaton tme ncreases notceably. In order to reduce the wall clock tme of EA-based optmzatons the most common technque s the extensve use of surrogate evaluaton models (or metamodels) the so-called Metamodel-Asssted EAs (MAEAs) [3]. he metamodels are used to nexpensvely approxmately evaluate the objectve functon value(s) after beng traned on prevously-seen evaluated ndvduals. In ths paper artfcal neural networks are used as metamodels. Metamodels can be ncorporated nto EAs n dfferent ways dependng on whether ther tranng takes place durng (on-lne) or separately from the evoluton (off-lne). In ths paper Metamodel-Asssted EAs (MAEAs) wth on-lne traned metamodels are employed [4]. Accordng to the nexact pre-evaluaton (IPE) approach wth the excepton of a few startng generatons all populaton members are approxmately evaluated usng local metamodels traned on the fly. hen a few of them practcally the most promsng among them as ndcated by the metamodel are re-evaluated on the exact mode Although the AEP evaluaton software s not tme expensve the applcaton nvolves a great number of desgn varables and constrants. he hgh number of desgn varables deterorates the effcency of a conventonal EA snce t requres more evaluatons and ncreases the computatonal cost. As EAs are populaton-based search methods one way to overcome ths problem s parallelzaton by concurrently evaluatng canddate solutons on dfferent processors. Also n MAEAs the metamodels tranng tme ncreases and the predcton accuracy decreases as the number of desgn varables ncreases. A way to tackle optmzaton problems wth an excessve number of desgn varables s to decrease the problem dmenson va dmenson reducton technques. hs can be done va prncpal component analyss (PCA) technques. In ths paper PCA s used n EAs by addng new evoluton operators the so-called PCA-drven ones and PCA drven metamodels. he PCA-drven evoluton operators have been proved [5] to mprove the performance of the EA and the PCA-drven metamodels lead to much better performng MAEAs [6]. he Evolutonary Algorthm System - EASY optmzaton platform supported by MAEAs and the PCA technque [1] s used n ths paper for the AEP optmzaton applcaton. 4. AEP Optmzaton Scheme In Fg. 1 the AEP Optmzaton Scheme based on the AEP calculaton tool and the EASY optmzaton platform s presented. For the defnton of the AEP optmzaton problem the objectve functons desgn varables and constrants of the optmzaton are presented as follows. he optmzaton objectve functon F obj refers to the mzaton of the annual energy produced as defned n eq. (4). Apart from ths another optmzaton goal could be the mzaton of the annual ncome based on the dfferent energy prces for the energy generated durng turbnng p gen (t) and the energy consumed durng pumpng (t) that can be changng per tme and affectng the optmal operatonal strategy. p cons F F obj obj = E = ( E produced generated ( t) p gen ( t) - E consumed ( t) p cons ( t)) (5) he goal of the AEP optmzaton s to defne the optmal operatonal modes optmal startng and stoppng head each mode j and optmal reservor level path h r. l. for each tme step t (.e. for each operatonal pont) for the whole year that mze the energy. In case of a speed regulated unt the speed n per operatonal pont s an addtonal desgn varable. he number of operatng unts HOM per operatonal pont can be also part of the group of the desgn varables concludng to an optmzaton platform wth the followng optmzaton desgn space: j of h mn n mn h n n h mn H mn OM j H OM j H OM j (6) where mn h H n mn OM j mn and mn stand for the lower and upper lmts of the reservor level startng and stoppng head of each mode speed and number of operatng unts for each operatonal pont respectvely. he optmzaton s also subject to a number of constrants. Constrants of the operatonal range such as mum generator power output P mum speed n and mum runner blade angle lmtatons along wth mnmum cavtaton mn lmtatonss are some of the constrants that can be appled n the AEP optmzaton. Due to possble envronmental lmtatons the lower and upper allowed reservor level s also taken nto account resultng to the followng constrants: b 267

5 h. mn P n n b b s ³ s P mn ³ h mn. const h h. const (7) he mnmum allowed cavtaton values are defned through hydraulc model testng and provded n a Cavtaton Constrant Hll Chart. 5. AEP Optmzaton Case Study he Swansea tdal project 5.1 Background he Swansea Bay tdal power plant s beng developed by dal Lagoon Swansea Bay PLC (LSB) and wll be located n the Severn Estuary on the west sde of UK. he Severn Estuary holds the second hghest tdal range n the world by featurng an average tdal range of 8.5m durng sprng tdes. Fgure 3 shows the dam the west-south locaton of the powerhouse along wth the martme park for varous recreatonal and educatonal purposes. Swansea Bay tdal power plant s the frst of sx planned tdal power plants n UK and t wll be the frst tdal power plant n the world whch wll have a nomnal power above 320 MW provdng clean renewable and predctable energy for over houses. In the year 2015 after a competton set by LSB ADRIZ HYDRO was nomnated as supple Durng the competton ADRIZ HYDRO developed a new concept for a b drectonal bulb pump turbne unt wth varable speed turnable runner blades and gude vanes that can turbne pump and sluce water n both drectons n an effcent way [2]. Good performance for turbnng and pumpng modes n both drectons was confrmed on the hydraulc test rg. Fgure 3 llustrates also the arrangement of the turbne-generator-unt n a cross sectonal vew. In reference to Shwa tdal power plant n South Korea [7] [8] whch s currently the world s largest operatng tdal plant equpped also by ADRIZ HYDRO two phases of hydraulc model testng were planned durng the competton for Swansea Bay. Frstly the feasblty of the project was nvestgated by evaluatng all possble operatonal concepts through hydraulc model testng asssted by Computatonal Flud Dynamcs (CFD) analyss and AEP optmzaton. In the second phase mprovements were appled on the well-chosen concept n order to ensure the mum AEP. Fg. 3 Illustratve masterplan of Swansea bay tdal barrage (the power plant s located n the lower left corner) and llustratve cross secton of b-drectonal bulb turbne [9] 5.2 Swansea Bay AEP Optmzaton problem he Swansea Bay tdal power plant wll be equpped wth 16 bulb-type turbne-generator unts each havng an nstalled capacty of 20 MW and 8 slucng gates wth a gated surface of 14.5m 13. 5m each. Year 2003 s selected as the representatve reference year for the AEP optmzaton. Fgure 4 shows between others a tme seres that represents the tde varaton n the early days of January he reservor volume n relaton to the reservor level s also avalable based on bathymetry studes n the estuary. hrough hydraulc model testng of the bulb unt Effcency and Cavtaton Constrant Hll Charts are avalable for each operatng mode (PMR PM MR M) resultng to 8 Hll Charts n total for whch the optmzaton searches for the optmal operatonal ponts that respect the cavtaton constrant. he objectve functon of the Swansea Bay AEP optmzaton refers to the mzaton of the annual energy produced for year he goal of the AEP optmzaton s to defne the optmal operatonal strategy (operatonal modes) along wth the optmal startng and stoppng heads for each mode throughout the year as defned n Secton 4. At the same tme the optmal reservor level path and optmal speed needs to be defned thus reachng a total of almost 200 desgn varables per tde cycle. All operatng ponts are subject to the followng constrants: generator power output P 20 MW speed n 73 rpm and cavtaton lmtatons as explaned n Secton 4. Addtonally due to envronmental lmtatons n Swansea Bay the lower and upper reservor level for each tde cycle s restrcted to the lower and upper sea level of the correspondng tde cycle. hs means that pumpng for each tde cycle s allowed untl the aforementoned sea level mtatng nature n ths way (mtgaton pumpng). he optmzaton problem was studed usng a MAEA (PCA) wth μ=10 parents and λ = 50 offsprng. he IPE phase started after 200 exactly evaluated ndvduals were stored n the DB. he λe=6 most promsng ndvduals accordng to the metamodel predcton among the 50 offsprng were then evaluated usng the AEP calculaton too Durng the ntal (non IPE) generatons 268

6 50 concurrent evaluatons were sent to 50 dfferent CPUs. As soon as the IPE phase started the computatonal burden was reduced to 6 concurrent evaluatons thus freeng valuable resources. Fg. 4 he optmal reservor level along wth the tde varaton durng the early days of January 2003 correspondng to an AEP optmal soluton of 540GWh At the cost of AEP evaluatons the optmal operaton along wth the optmal reservor level and speed for each operatonal pont was defned by the optmzaton resultng to an AEP optmal soluton of 540GWh. he optmal reservor level s presented n Fg. 4 for a number of tde cycles durng the early days of January In the same fgure t can be notced that the reservor level s restrcted to the correspondng sea level of each tde cycle (mtgaton pumpng) fulfllng the envronmental constrants. As t can be seen n Fg. 5 the optmal operatonal modes for the Swansea Bay case selected by the optmzaton are the PMR PM MR M SMI SMII IMI and IMII as explaned n detal n Secton 2 Fg. 2. he generator power output that s beng produced through turbnng operaton (MR and M) and the power consumed through pumpng operaton (PMR and PM) sgned as negatve can be seen n Fg. 5. In addton to that the optmal head dfference between sea and reservor level (gross head) along the operaton s presented also n Fg. 5. Fg. 5 he optmal operatonal modes based on turbnng pumpng and slucng through the gates n parallel wth power generaton were used n order to mze the AEP. he optmal generator power output along wth the optmal gross head through 3 tde cycles s presented. Power consumed through pumpng operaton s sgned as negatve. 269

7 5.3 Slucng Mode Contrbuton to the AEP Optmzaton Both slucng mode varants.e. stoppng MR and M operaton when startng gate slucng operaton (seral slucng) or contnung MR and M operaton n parallel wth gate slucng (parallel slucng) were evaluated. Slucng through the gates n parallel wth power generaton ncreased the AEP by almost 2% n comparson to gate slucng operaton only at the end of MR and M. In Fg.6 the optmal reservor level and the generator power for seral and parallel slucng case scenaro are presented. As t can be seen n Fg. 6 although the dfference n the optmal reservor level s small the power generated for seral slucng s less snce by the start of slucng through the gates turbne operaton has to stop. 5.4 Pumpng Mode Contrbuton to the AEP Optmzaton At the early stage of nvestgatons t was proven that wthout pumpng the project would not have been feasble. he contrbuton of mtgaton pumpng n the AEP s sgnfcant by ncreasng the AEP by 10%. Pumpng operaton contrbutes to buld hgher heads needed for the turbnng operaton whch outperforms the energy that s consumed durng pumpng. he full potental of pumpng (full pumpng) n Swansea Bay can be acheved when neglectng the reservor lmtatons due to the envronmental constrants. In ths case pumpng contrbutes to an ncrease of 15% n total n comparson to no-pumpng. In Fg. 7 the optmal reservor level and the generator power for mtgaton and full pumpng case scenaro n comparson to the nopumpng case s presented. 5.5 Optmal power plant operaton control system he AEP optmzaton ndcates at the same tme the operatonal ponts where the unts should be operatng through the year n order to reach the optmum AEP value. Any devaton from the optmal operaton would conclude to devatons from the predcted AEP value. For ths reason the AEP optmzaton can be also used durng operaton of the power plant n order to assure the optmal operaton. An onlne optmzaton based on tde forecast that s avalable some days before can provde n advance the optmal operatonal ponts (optmal speed gude vane angle runner blade angle) to the control system. In Fg. 8 the optmal speed gude vane angle and runner blade angle that are proposed by the optmzaton durng PMR PM MR and M are presented through tme for one of the hghest tdes of year Fg. 6 he optmal reservor level and the generator power output for the seral slucng and parallel slucng (2% ncrease n AEP) case scenaro Fg. 7 he optmal reservor level and the generator power output for the wthout pumpng mtgaton pumpng (10% ncrease n AEP) and full pumpng (15% ncrease n AEP) case scenaro 270

8 Fg. 8 he optmal speed gude vane angle and runner blade angle along wth the gross head proposed by the optmzaton durng PMR PM MR and M durng one of the hghest tdes of year Comparson between optmal operaton and full load operaton In order to ndcate the sgnfcance and contrbuton of such an AEP optmzaton tool to the defnton of optmal operaton for a tdal power plant and of a mum AEP value a comparson between optmal operaton and full load operaton s presented. As mentoned n Secton 5.5 the optmal operatonal ponts (optmal speed gude vane angle runner blade angle) should be 271

9 provded to the control system n order to reach the optmum AEP value durng operaton of the power plant. A control strategy that would operate the unts at full load may be easer to be mplemented n the control system but t can devate from the optmal operaton strategy. In the example that follows ths devaton s presented n terms of energy loss. In Fg. 9 the optmal power plant operaton proposed by the AEP optmzaton tool s compared to the full load operaton durng a medum tde of year Durng full load operaton the unts operate on mum dscharge for each head nstead of operatng on the optmal operatonal ponts provded by the AEP optmzaton. hs full load operaton results n a reservor level dfferent from the optmal one. Startng and stoppng head for each operatng mode s the same as for the optmal operaton n terms of comparson. As t can be seen n Fg. 9 full load operaton flls up and emptes the reservor more quckly (steeper reservor level curve) than the optmal operaton and as an effect the avalable head s reduced. hs has a sgnfcant effect on the energy produced durng ths tme perod that s by 11% reduced for full load operaton compared to the optmal one. However f the full load operaton s optmzed n terms of startng and stoppng head for each operatng mode snce t s the only parameter that can be affected the results are presented n Fg. 10 as optmzed full load operaton. he unts operate stll on mum dscharge for each head but the optmzaton provded the optmal startng and stoppng head for each operatng mode. For ths reason n order to compensate the head reducton of the full load operaton the optmzaton moves the startng tme for MR and M n order to be as close as possble to the optmal operaton. However the energy produced wth the optmzed full load operaton s stll lower than the one proposed by the AEP optmzaton tool as t can be seen n Fg. 10. he energy produced by the AEP optmzaton tool outperforms the optmzed full load operaton by 5% ndcatng the mportance of such an AEP optmzaton tool and the mportance of performng an AEP optmzaton n order to operate a tdal power plant n the most effcent way. Fg. 9 Comparson between optmal power plant operaton proposed by the AEP optmzaton tool (AEP-optmal reservor level and optmal energy produced) and full load operaton (full load operaton-reservor level and energy produced) durng one of the medum tdes of year 2003 Fg. 10 Comparson between optmal power plant operaton proposed by the AEP optmzaton tool (AEP-optmal reservor level and optmal energy produced) full load operaton (full load operaton- reservor level and energy produced) and optmzed full load operaton (Optmzed full load operaton- reservor level and energy produced) durng one of the medum tdes of year

10 6. Concluson hs paper presented an Annual Energy Producton (AEP) optmzaton tool for tdal power plants based on Evolutonary Algorthms that s able to mze the AEP by optmzng the plant operaton throughout the yea he selecton of the optmal operatng modes n sequence between pumpng turbnng and slucng n both drectons n addton to the defnton of the optmal reservor level path for the whole year are the results of the optmzaton. he AEP optmzaton was appled on the Swansea Bay dal Power Plant whch along wth hydraulc desgn development and model testng led to a sgnfcant ncrease of the AEP value of more than 50%. he applcaton of the AEP optmzaton drectly at the tdal power plant n order to provde the optmal operatonal ponts to the control system accordng to tde prognoss s a further advantage. Fnally ths paper focused on the advantage of the AEP optmzaton method n reachng a hgher AEP value n comparson to other operaton strateges (.e. full load operaton). References [1] Evolutonary Algorthm System EASY ( [2] Kragl M. Kontoleontos E. Mchelcc J. Benz B. and Case M Swansea Bay dal Power Plant - B drectonal bulb pump turbne wth varable speed HYDRO 2015 Conference. [3] Jn Y. Olhofer M. and Sendhoff B A Framework for Evolutonary Optmzaton wth Approxmate Ftness Functons IEEE ransactons on Evolutonary Computaton vo 6 no. 5 pp [4] Karakass M. K. and Gannakoglou K. C On the Use of Metamodel-Asssted Mult-Objectve Evolutonary Algorthms Engneerng Optmzaton vo 38 no. 8 p [5] Kyracou S.A. Wessenberger S. and Gannakoglou K. C Desgn of a matrx hydraulc turbne usng a metamodelasssted evolutonary algorthm wth PCA-drven evoluton operators Internatonal Journal of Mathematcal Modellng and umercal Optmzaton (SI:Smulaton-Based Optmzaton echnques for Computatonally Expensve Engneerng Desgn Problems) vo 3 no. 2 pp [6] Kyracou S. A. Asout V. and Gannakoglou K. C Effcent PCA-drven EAs and metamodel-asssted EAs wth applcatons n turbomachnery Engneerng Optmzaton Vo 46 no. 7 pp [7] Collns M. Götsch L. Angerer C. and Grafenberger P Experence on feld testng the world s largest tdal power plant-shwa dal South Korea Ocean Renewable Energy-Energes Marnes Renouvelables-EMR [8] Km J. Heo M. Cha K. Km K. ac S. Cho Y. Hwang J. and Collns M Effect of Intake Vortex Occurrence on the Performance of an Axal Hydraulc urbne n Shwa-Lake dal Power Plant Korea Internatonal Journal of Flud Machnery and Systems Vo 5 o. 4 (October-December) p [9] dal Lagoon Power Ltd (LP) he Proposed dal Lagoon Swansea Bay (Generatng Staton) Order Vo 8 Folder 1 (http :// 273