A Robust Method Based Storage Aggregator Model for Grid Dispatch

Transcription

1 Robust Metho Base Storage ggregator Moel for Gr Dspath Zhaoguang an, Stuent Member, I Qngla Guo, Senor Member, I Hongbn Sun, Senor Member, I The Department of letral ngneerng State Key Laboratory of ower Systems, Tsnghua Unversty Bejng, Chna panzg09@163.om bstrat Dstrbute storages have been wely use an stue reently, nlung batteres an eman se resoures, wth the evelopment of strbute energy resoures (DRs). ah strbute storage has small apaty but the number of all strbute storages s very large, so t s not pratal for an nepenent system operator (ISO) to spath these strbute storages retly. storage aggregator s evelope to ontrol massve strbute storages. Ths paper proposes a robust metho base storage aggregator moel for gr spath, so ISO an norporate t nto ts spath moel an avo the large menson ause by strbute storages. Ths moel s forme n the aggregator an the results are sent to ISO as bas vrtual storage parameters. Ths moel s base on the robust metho an an guarantee that any spath plan satsfyng the aggregator moel gven by ISO s exeutable for the aggregator, whh means the aggregator an alloate the spath plan to strbute storages. Ths moel avos many teratons an ommunaton between ISO an the aggregator. heurst parameters generaton metho s evelope an stuy ases are arre out to test the moel. Inex Terms ggregator, Dspath, Dstrbute, ISO, Moel, Robust, Storage W I. INTRODUCTION th the pressure of energy rss an arbon oxe emsson, the renewable energy evelops very fast n reent years, nlung strbute generatons (DGs), suh as solar photovolta power generatons an wn turbnes. s the renewable energy s hghly ntermttent an usually annot math the loa, the loal energy balanng beomes a bg hallenge, as well as the voltage problem. Therefore, strbute storages are nstalle to ope wth these problems [1]. Compare to the large sale storages, strbute storages are muh heaper an more sutable tehnologes an be use. Beses, some flexble eman se resoures suh as heatng ventlaton an ar ontonng (HVC), hot water tan, tmeshftable applanes an nterruptble applanes an be regare as generalze storage. Some researh has moelle these resoures nto the storage moel [2]. In a resental home, there may be batteres, eletr vehles (Vs) an other flexble eman se resoures [3]. In ths researh, strbute storages nlues both batteres an eman se resoures. Therefore many strbute storages loate n the eman se. They an mae ontrbutons to loal energy management. What s more, these strbute storages are also valuable for gr [4]. They an offer many serve suh as balanng, regulaton, anllary serve, et. They wll be atve n the energy an auxlary serve maret n smart gr. Deman response (DR) s wely use to tae avantages of strbute resoures an new tehnologes an moels are uner evelopment. Tae hot water tans for example, they an be use to reue pea or frequeny regulaton by ajustng the power onsumpton. The flexblty omes from the aeptable temperature range of hot water. However, these strbute storages usually loate n strbute resental homes, an the sngle apaty s usually very small but the number s very large. Beses, the parameters of strbute storages ffer great. It s not pratal for an nepenent system operator (ISO) to spath an ontrol these massve strbute storages retly beause of the large menson an nformaton prvay. So the onept of aggregators s evelope to ope wth suh strbute resoures [5], [6]. Mrogr an be regare as an aggregator f t nterats wth ISO. Vrtual power plant (V) s wely aepte to manage strbute resoures [7] as an aggregator. From the vew of an ISO, an aggregator s only one element, an ISO oes not have to now etale nformaton of eah strbute resoure. So the menson of the gr spath s lmte. It s extremely mportant to moel the aggregator properly. Ths moel wll be use by ISO, an t shoul reflet the features of strbute storages. Muh researh on aggregators fousse on the optmzaton an ontrol wthn an aggregator to aheve more profts. Ref [5] etermnes the optmal bng strategy of an V aggregator partpatng n ay-ahea energy an regulaton marets usng stohast optmzaton. Ref [7] onsers Vs as oaltons of wn generators an eletr vehles. These researh not onser the gr spath. The aggregator Ths wor was supporte n part by Natonal Key Bas Researh rogram of Chna (973 rogram) (2013CB228202), the Founaton for Innovatve Researh Groups of the Natonal Natural Sene Founaton of Chna ( ) an NSFC_RCUK-SRC ( ) /15/$ I

2 just etermnes ts own operaton, but o not prove ret ontrollable serves to gr, so ISO annot spath t. Some researh has norporate strbute resoures nto the gr operaton. Ref [8] uses ual eomposton to onser large-sale ntegraton of DR from small loas. It nees many teratons between ISO an aggregators, whh osts muh tme an brngs a hgher requrement for ommunaton. Ref [9] sheules eman response n stohast SCUC to utlze the reserve prove by DR. The reserve moel of DR s not eeply analyze to reflet the features of the strbute DR resoures, whh may lea to ases n whh the spath s not exeutable for strbute resoures. Man ontrbuton of ths paper s the moelng of a storage aggregator, whh an ontrol a lot of strbute storages. storage aggregator moel s propose base on the robust metho an s use for gr spath by ISO. The moel generates bas vrtual storage parameters for an aggregator suh as apaty, hargng/shargng rate range an ntal state. Then the aggregator sen these parameters to ISO, so ISO an spath the aggregator as a vrtual storage an avo the large menson ause by massve strbute storages. There s only one-step teraton between ISO an the aggregator, so t s easy to be aepte by ISO an avos many teratons an ommunaton. From the aggregator s vew, the spath plan from ISO an be onsere as unertanty nput wthn a onstrant set. The propose moel guarantees that eah spath plan gven by ISO s exeutable for the aggregator, whh s benefal for the gr operaton. Ths ea omes from the robust metho. heurst parameters generaton metho s propose to get these aggregator parameters. The propose moel an also be use n other ns of aggregators, suh as V aggregators, DR aggregators, mrogrs, V, et. The remaner of ths paper s organze as follows: Seton II ntroues the storage aggregator moel an parameters generaton metho. Seton III gves stuy ases to test the propose moel an susson. Seton IV proves the onlusons an retons for future stuy. II. STORG GGRGTOR MODL. Storage ggregator storage aggregator s set up to manage massve an verse strbute storages, whh ffer from eah other an loate n strbute resental homes. The aggregator s an agent between ISO an strbute storages as Fgure 1 shows. The storage aggregator has the ablty to ontrol many strbute storages to prove serves to the power gr. Therefore, ISO an spath the storage aggregator as one vrtual storage. Fgure 1 Illustraton of a Storage ggregator Suppose that the storage aggregator has the bas parameters of eah strbute storage suh as the apaty, state of harge (SOC), hargng/shargng/self-shargng rate effeny an an ontrol them retly. The aggregator uses these nformaton to generate new parameters that esrbe just one vrtual storage an sen them to ISO. From the vew of ISO, the aggregator s just a vrtual storage, so the number of storages n the ISO spath moel s muh less. B. Sngle Storage Moel Typal moel for a sngle storage s usually (1). We manly onern the hargng/shargng rate of a battery, whh shoul satsfy the battery s operaton onstrants. s the feasble regon of hargng/shargng rate of the battery., 1 0 1,2... N In (1), nates the number of a tme slot an N s the total number of tme slots. an nate the hargng an shargng rate of the storage respetvely. nates the SOC of the storage, an s the ntal state.,, are the upper lmts an,, are the lower lmts of eah varables. The fourth equaton presents the ynam proess of the storage, nlung hargng, shargng an self-shargng proess, where,, are the effeny. The ffth equaton presents the omplementary onton, whh means that hargng an shargng annot our at the same tme. s epenent on the bas parameters,,,,,,,, an. Suppose there s an eal storage, whose,, are all equale to 1. It means that there s no energy loss urng hargng, shargng an storng. Then (1) an be smplfe nto (2). Compare to (1), (2) s onvex an has less onstrants. eal epens on the parameters,,, an 0. eal (2) 1 1,2... N 0 C. Storage ggregator Moel 0 Fgure 2 shows the relaton between the ISO spath moel an the storage aggregator ontrol moel. The aggregator sens ts parameters to ISO, nlung the lower an upper bouns of SOC,, hargng/shargng rate boun, an ntal state 0. ISO norporates ths storage aggregator moel nto ts spath moel, generates a spath plan for the aggregator an sens t to the aggregator. The responsblty of the aggregator s to ontrol ts strbute storages to (1)

3 meet wth the ISO spath plan. The aggregator nee to alloate the spath plan to eah strbute storage as (3) shows, where s the spath plan vetor from ISO an s the ontrol vetor of strbute storage. In ths paper, we fous on the aggregator parameter generaton, rather than the spath of ISO an the ontrol of the aggregator tself. (3) Fgure 2 ISO Dspath Moel an Storage ggregator Control Moel e s a row vetor. If the optmal value of (4) s zero, the aggregator ontrol moel has a feasble soluton. Otherwse (3) annot be satsfe, an no feasble soluton exsts. The moellng metho propose n ths paper for storage aggregator an be esrbe as follows. When the aggregator sens ts parameters to ISO, t has no ea about the spath plan, whh an be any value that satsfes the aggregator moel onstrants. From the aggregator s vew, the spath plan an be onsere as unertanty nput wthn a onstrant set. In orer to arry out any spath plan gven by ISO, the aggregator nee to tae t nto onseraton when generate these parameters. There are two ey ponts n ths proess: the ablty to arry out any spath plan an parameters generaton. For the frst pont, the aggregator shoul have the ablty to arry out any spath plan that satsfes the moel generate by tself. The ea omes from the robust onept. For a spef spath plan gven by ISO, the aggregator s able to arry out the plan means that the aggregator ontrol moel has a feasble soluton for the spath plan. The moel an be esrbe as (4). represents the onstrants of strbute storage as (1) gven. v an v are sla varables for power balane equaton (3) an 1 1 mn, v, v st. v v, v 0 ev v ev eal gven by ISO, the aggregator s able to arry out the plan means that the aggregator For any spath plan (4) ontrol moel has a feasble soluton for any spath plan. represents the feasble regon of the storage aggregator, usng eal storage moel. s epenent on,,, an, whh are sent by the aggregator to ISO. The moel an be esrbe as (5). It s a typal b-level robust moel. The upper level s to fn the worst ase that maxmzes the objetve. The worst ase s a spath plan that annot be arre out f there s. The lower level s to fn a feasble soluton, as susse before. If the optmal objetve s zero, the aggregator s able to arry out any spath plan. eal eal 0 max mn eal, v, v st. eal ev v v v, v 0 ev The results of (5) are hghly epenent on eal eal. If s large, t s very possble that there s a spath plan not exeutable. Fgure 3 llustrates the ea. presents the largest regon that eah s exeutable. s etermne by eah strbute storages as (6) shows. s exat but t s very omplate an s not sutable to the ISO spath moel. muh smpler regon eal s use to replae to smplfy the moel. In orer to mae sure that any eal s exeutable, eal shoul be satsfe. When eal s small, t an loate wthn. If eal s very large, eal may exee. (5) s a b-level problem, whh s a typal lnear robust optmzaton problem [10]. The lower level problem an be transforme nto polyheron onstrants usng optmalty ontons. Thus the overall problem s onverte to a mathematal program wth equlbrum onstrants (MC). It an be further onverte nto a MIL problem, whh an be solve by many ommeral software suh as CLX, GUROBI, et. For spae lmtaton, etal mathematal ervaton s not presente, an t an be fn n most robust optmzaton boos as the tehnque s wely use. Fgure 3 Illustraton of Storage ggregator Moel (5),, 1,2...N (6)

4 eal epens on the parameters generate by the aggregator. Usually, f the parameters, are smaller or, are larger,, the exe- The seon pont s parameters generaton. eal s also larger. To guarantee uton proess shoul be onsere when generatng the aggregaton parameters. It s reasonable that ISO wants a larger for more flexblty, whh also an brng more rev- eal enue to the aggregator. So the aggregator nees to set these wthn the. eal parameters to maxmze However, t s not easy to evaluate the area of exatly. So the vrtual apaty an vrtual hargng rate range an be use to reflet the approxmately. Therefore, we nee to generate the parameters that an maxmze vrtual apaty an vrtual hargng rate range wthn the zone of. Beause the spath only onerns, whh s a projeton from a larger spae to spae, the results may be not unque. In ths paper, we o not suss muh about ths for spae lmtaton. D. arameters Generaton Metho heurst parameters generaton metho s propose as follows to get,, an. Setp1: get bas parameters of all strbute storages. Suppose there are M strbute storages an N tme slots. Go to step2. Step2: ntal,,, as (7). Go to step3; eal M M 1 1 eal M M M eal Step3: juge f ths set parameters are exeutable by solvng (5). If the objetve of the results s zero, go to step8. Otherwse go to step4. Step4: f v 0, s too large an go to step5. Otherwse go to step6. Step5: f max, mn 0.01, obj / S. Otherwse / S, where S an be set to ontrol the auray. The smaller the S, the more aurate the results, but t osts more tme. obj s the optmal value of (5). Step6: f v 0, s too small an go to step7. Otherwse go to step3. Step7: f mn, mn 0.01, obj / S. Otherwse / S. Go to step3. Step8: These parameters are exeutable. n. III. CS STUDY. Case 1 Ths ase s use to llustrate the neessty of the propose storage aggregator moel. We annot sum all strbute storage parameters to get the aggregator parameters. We all ths summe moel. In some ases, the results of the summe moel are same wth the propose moel, when all the strbute storages are ental for example. But n most ases, the summe parameters annot guarantee any spath plan s (7) exeutable. In orer to explan ths, 2 storages are use to form an aggregator, onserng only 1 tme slot. Suppose that the storages are both eal. Table 1 arameters an Results of Case 1 (all unts are normalze) Storage No Capaty Chargng rate Intal state 1 [0, 6] [-1, 1] 2 2 [0, 4] [-3, 3] 3 Summe [0, 10] [-4, 4] 5 ropose [0, 10] [-4, 2] 5 s eal p eal Table 1 shows the parameters of 2 storages, as well as the results. We an see that the results between the summe moel an the propose moel are fferent. In ths ase, s (8), the exat feasble regon. If the summe moel are use, s (9), whh exees. So t annot guarantee any spath plan s exeutable. For example, f the spath from ISO s 4, whh satsfes the aggregator moel but s not exeutable for the aggregator. The aggregator only an arry out spath between -4 an 2, beause storage 1 s lmte by hargng rate an storage 2 s lmte by apaty. If the pro- s (10), the same wth. It pose moel s use, satsfes the requrement for exeuton s 4 4 eal p 4 2 eal (8) (9) (10) B. Case 2 Base on ase 1, 6 tme slots are onsere an the results are showe n Table 2. It an be nferre that wth more tme slots onsere, the apaty range an hargng rate range s smaller an the fferene between summe metho an propose metho s larger. Table 2 Results of Case 2 (all unts are normalze) Storage No Capaty Chargng rate Intal state Summe [0, 10] [-4, 4] 5 ropose [0, 10] [-1.94, 1.33] 5 C. Case 3 In ase 3, 100 eal strbute storages are organze to form an aggregator. The parameters of all the strbute storage are generate ranomly to present the fferene among these storages, whh s the man feature of strbute storages. Fgure 4 presents the strbuton of these parameters. For eah storage, the lower apaty lmt s zero an the shargng rate lmt s same wth the hargng rate lmt, namely. 2 tme slots are onsere. The results of the propose moel an parameters generaton metho are showe n Table 3, as well as the summe moel.

5 Fgure 4 Intal State Dstrbuton of 100 Storages It an be see that there s a sgnfant fferene between the two moels. In orer to guarantee any spath plan s exeutable, some storage apaty s not use n the gr spath, whh means onservatveness exsts. But these parts of the storage apaty an be use to prove other serves wthn the aggregator. Table 3 Results of Case 3 (all unts are normalze) Capaty Chargng rate Intal state Summe [0, 995] [-602, 602] 530 ropose [180, 905] [-494, 482] 530 D. Dsusson Ieal storage moel s use n our ase stuy. The man fferene between eal storage an real storage s the omplementary onton, whh maes the moel nonlnear. t the upper level problem, aggregator s a vrtual storage so any moel an be use suh as polyheral, sphere, et. In orer to reflet the storage onept, the eal storage moel s use, whh s smple an also maes the ISO spath moel smple. t the lower level problem, eal storage moel s also use n some researh, but t really brngs errors an may ause the results not exeutable n physs. The omplementary onton hanges the property of lower level problem from L to nononvex. The optmalty ontons an stll be use, but the global optmal pont annot be guarantee. There are some methos an be explore, suh as Beners, olumnan-onstrant generaton metho. It s not the fous of ths paper. Beses, Ref [11] prove that the omplementary onton an be exatly relaxe uner some ontons. s the overall problem s a MIL, whh auses muh tme to solve, espeally when the number of strbute storage or tme peros s large. The man ontrbuton of ths paper s the propose aggregator moel for gr spath. More effent algorthms are uner evelopment an muh wor s neee. Beses, parallel omputaton tehnques ether wth herarhal struture or fully strbute arhteture an be apple. Of ourse, a traeoff between auray an effent shoul be further explore. The ISO s spath an over varous tme sale, suh as ay-long, hours-long, mnutes-long. In a ay-long problem, our propose aggregator moel taes muh tme to be solve wthout more effent algorthms. But the tme lmtaton for a ay-long problem s also not so strt. Beses, n a ay-long spath, more teratons an ommunaton between ISO an the aggregator s tratable, so tratonal b mehansm also an be use. In hours-long or mnutes-long spath, the tme peros are muh less, an the solvng tme s also muh less. speally for some eman se resoures suh as ar ontoners, the flexblty s lmte, an long tme spath gans lttle more benefts. The propose moel of storage aggregator has we applatons n gr spath, espeally n short tme spath when many teratons s not allowe. DRs an be moelle as strbute storage. Other DGs an be ae to the moel an the upper level moel an be hange. ggregators suh as retalers, mrogrs an Vs wll be atve n smart gr as more loas beome flexble an atve, an they wll play very mportant roles n the gr operaton. IV. CONCLUSION Ths paper proposes a robust metho base storage aggregator moel for gr spath. The aggregator an manage an ontrol massve an verse strbute storages an s onsere as one vrtual storage from the vew of ISO. The propose moel s forme n the aggregator usng strbute storage parameters an the results are sent to ISO as bas vrtual storage parameters. Then ISO an norporate the aggregator moel nto ts spath moel an avo the large menson ause by massve strbute storages. Ths moel s evelope to guarantee that any spath plan satsfyng the aggregator moel an gven by ISO s exeutable for the aggregator, whh s a typal robust moel. The spath plan from ISO an be seen as unertanty n the aggregators vew beause the aggregator has lttle nformaton about the gr. Ths mehansm avos many teratons between ISO an the aggregator. heurst metho s evelope to generate these storage aggregator parameters. Stuy ases are arre out to test the moel, an the results show that the moel s effetve. Future wor nlues more effent algorthms, less onservatveness, unertanty an usng the moel n other aggregators. Referenes [1] C.. Hll, M. C. Suh, C. Dongme, J. Gonzalez, an W. M. Gray, "Battery energy storage for enablng ntegraton of strbute solar power generaton," I Trans. Smart Gr, vol. 3, no. 2, pp , June [2] J. Qn, Y. Chow, J. Yang, an R. Rajagopal, "Onlne mofe greey algorthm for storage ontrol uner unertanty,", 05/2014. [3]. Zhaoguang, S. Hongbn, an G. Qngla, "Tou-base optmal energy management for smart home," n ro. Innovatve Smart Gr Tehnologes urope (ISGT URO), th I/S, pp.1-5 [4] M. arvana, M. Fotuh-Fruzaba, an M. Shahehpour, "Optmal eman response aggregaton n wholesale eletrty marets," I Trans. Smart Gr, vol. 4, no. 4, pp , De [5] S. I. Vagropoulos, an. G. Bartzs, "Optmal bng strategy for eletr vehle aggregators n eletrty marets," I Trans. ower Syst., vol. 28, no. 4, pp , Nov [6] L. Gatzs, I. Koutsopoulos, an T. Salons, "The role of aggregators n smart gr eman response marets," Ieee J Sel rea Comm, vol. 31, no. 7, pp [7] M. Vasran, R. Kota, R. L. G. Cavalante, S. Ossows, an N. R. Jennngs, "n agent-base approah to vrtual power plants of wn power generators an eletr vehles," I Trans. Smart Gr, vol. 4, no. 3, pp , Sept [8] N. Gatss, an G. B. Gannas, "Deomposton algorthms for maret learng wth large-sale eman response," I Trans. Smart Gr, vol. 4, no. 4, pp , De [9] M. arvana, an M. Fotuh-Fruzaba, "Deman response sheulng by stohast su," I Trans. Smart Gr, vol. 1, no. 1, pp , June [10]. Ben-Tal, an. Nemrovs, "Robust optmzaton - methoology an applatons," Math rogram, vol. 92, no. 3, pp [11] Z. L, G. Qngla, an S. Hongbn, "Suffent ontons for exat relaxaton of omplementarty onstrants for storage-onerne eonom spath," I Trans. ower Syst.,[aepte].