Energy storage in renewable-based residential energy hubs

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1 IET Generation, Transmission & Distribution Researc Article Energy storage in renewable-based residential energy ubs ISSN Received on 3rd August 2015 Revised on 12t May 2016 Accepted on 17t June 2016 doi: /iet-gtd wwwietdlorg Moammad Hossein Barmayoon 1, Mamud Fotui-Firuzabad 2, Abbas Rajabi-Ganavie 1, Moein Moeini-Agtaie 3 1 Department of Energy Engineering, Sarif University of Tecnology, Teran, Iran 2 Department of Electrical Engineering, Sarif University of Tecnology, Teran, Iran 3 Sarif Energy Researc Institute, Sarif University of Tecnology, Teran, Iran rajabi@sarifedu Abstract: Energy storage systems are expected as a near-term solution for renewable energy application in te residential energy ubs Witin tis context, tis study investigates te feasibility of using storage systems in improving te tecnical and financial performance of te residential renewable-based energy ub A new approac as been proposed in tis study in wic economic dispatc problem as been formulated for an energy ub including bot electrical and eat storage system Te proposed approac determines te optimal supply of energy demand and storage system operation to minimise te total energy cost of te ub Te economic benefit of storage system due to energy cost saving and emission reduction as been determined and te investment payback of te storage system ave also evaluated in te proposed approac Te proposed approac as been applied to 12 different residential energy ubs and te impact of energy tariff and storage size as been analysed Te obtained simulation results demonstrate te importance of correctly modelling te ub elements in evaluating te storage system benefit in residential energy ub Nomenclature Variables P energy ub input vector (kw) v dispatc factor g combination factor Q i, Q o storage power input and output (kw) E te level of stored energy (kw) ESB energy storage benefit SIC storage investment cost SIP storage investment payback Sets C e g c t set of convertors electricity gas eating cooling time (our) Parameters L te energy ub output vector (kw) EP energy price ($/kw) CE carbon dioxide emission (g/kw) N t operation period P pv output power of potovoltaic unit (kw) P sw output of solar water eater (kw) η C air conditioner efficiency η AC absorption ciller efficiency η T transformer efficiency η GTe electrical efficiency of te CHP unit η GT termal efficiency of te CHP unit η F boiler efficiency + ES, ES electrical carging, discarging efficiency + HS, HS termal carging, discarging efficiency E stb loss of standby stored energy P T upper bounds of te transformer output (kw) P CHP upper bounds of te CHP output (kw) P F upper bounds of boiler output (kw) P C upper bounds of air conditioner output (kw) P AC upper bounds of absorption ciller output (kw) Q, Q upper and lower bounds of storage power (kw) E, E upper and lower bounds of stored energy (kw) 1 Introduction Increasing application of renewable energy resources, energy storage systems, distributed generation units and combined eat and power generation (CHP) tecnologies [1 4] ave brougt into existence te interaction between different energy infrastructures Wile te energy infrastructures ave been yet independently planned and operated, new concepts, metods and tools are required to study te interaction between te energy infrastructures Te concept of Energy Hub as been introduced in [5, 6]toproperly model te synergies among different forms of energy Energy ub is defined as an interface between different energy infrastructures in wic energy carriers can be stored, converted or transferred witin it Energy ub intakes various types of energy carrier at te input ports, connected to te energy infrastructures, to supply te energy demand at te output ports Witin te ub, te energy is converted and conditioned using energy conversion tecnologies Recent researces ave focused on tecnical and financial study of multi-carrier energy systems using te energy ub approac to evaluate efficacy of suc a combined or integrated approac [4 11] Evaluation and optimisation of te energy flow in te building as been well evaluated in te available researc works [12, 13] Bianci et al[12] ave investigated decentralised CHP systems comprised of an innovative CHP unit, an auxiliary boiler and electric as well as termal storage in te residential context IET Gener Transm Distrib, pp 1 8 1

2 Some recent researc works ave applied te energy ub concept to analyse te building energy flow [9, 14, 15] A two-level ierarcical sceme as been proposed in [9] in wic te ouseold energy consumption as been optimised at te micro-ub level wile te set of ouses is controlled at te macro-ub level by te system operator Optimal size of a combined cooling, eat and power (CCHP) system for a ouse as been determined in [14] using te energy ub concept Taking into account te concept of energy ub, te autors in [15] as tried to demonstrate te benefits of employing renewable-based DGs in te urban areas for procuring or supplying bot electricity and eating demands of te consumers Analysis of energy flow in te residential loads as been implemented in [16] by te concept of energy ub Tis paper is aimed to perform a compreensive study on te effect of energy storage application on te optimal operation of residential energy ub A new approac as been proposed in tis paper in wic te economic dispatc (ED) problem for te residential ub is formulated and solved to investigate te abilities of different storage systems in improving energy efficiency, reducing te energy cost and alleviating te emission cost Te ED of te ub is modelled as a non-linear programming optimisation problem A residential area in Iran is considered and different case studies are introduced to sow tat ow te presence of storage units can affect te tecnical and financial aspects of tis system Bot of electrical and eat storages are considered in te ub to lend te operator a and in more efficiently use of te available energy resources Major innovations in te paper are: (i) Considers termal and electrical storage simultaneously in energy ub (ii) Includes te emission cost in economic evaluation of storage system (iii) Evaluate te impact of ub elements on storage application benefit Te rest of tis paper is arranged as follows: Section 2 describes te basic concepts to model te ome energy system as energy ub Proposed residential ub model is described in Section 3 Application of te proposed approac as been explained in Section 4 Metod comparison is discussed in Section 5 Sensitivity analysis results and concluding remarks ave been presented in Sections 6 and 7, respectively 2 Residential energy ub 21 Energy ub concept An integrated system, in wic te energy carriers can be converted, conditioned and stored, is referred to as te energy ub Fig 1 illustrates different levels of a general energy ub In an energy ub, different forms of energy are received at te input ports connected to te energy infrastructures and te energy services in form of electricity, eating, and cooling are delivered at te output ports [5] Witin an energy ub, different forms of energy are converted and conditioned using converter tecnologies suc as transformers, air conditioner (A/C), CHP tecnology, eat excangers and absorption ciller In an energy ub, te mapping of input energy carriers, P, to te loads at te output ports, L, is matematically modelled troug a matrix named te coupling matrix (C) as sown L a C aa C va P a = (1) L v C av C vv P v Eac element of te coupling matrix is called coupling factor wic relates one input to a particular output Coupling factor incorporates Fig 1 General model of an energy ub efficiency and dispatc factor associated wit te converters used to convert te input energy into te output 22 House energy model as an energy ub In eac ouse, tere are many appliances wic utilise different forms of energy to provide daily needs of te consumers Te way to optimally manage te energy flows in a ouse is so called ousing energy model Many works are available in wic different metods ave been proposed to systematically model te energy flow in a ouse including energy-services supply systems [17], basic units [18, 19], and so-called ybrid energy ubs [20] To develop te energy ub framework for a ouse, te energy carriers tat are fed to te ouse via urban energy infrastructures sould be determined, energy conversion tecnologies sould be identified and, finally, te ouse load sould be categorised based on te required energy Fig 2 is an illustrative example depicts te energy flow model in a residential area based on te concept of energy ub As sown in Fig 2, te energy demands of te ouse are categorised into four different groups including non-replicable electricity, cooling needs, eating and ot water demand Te grid electricity, natural gas, potovoltaic generation and solar water eater are te forming te input carriers Electrical output of te CHP unit is utilised to supply te electric need Electricity can also be stored in te battery storage system Te cooling demand is provided from te A/C or absorption ciller Te output of boiler, CHP unit or solar water eater can be employed to supply te eat demand or to be stored in eat storage for future uses Fig 2 is a compreensive model tat can be used to study and explain different operating modes of te residential energy ub, as discussed in Section 3 3 ED problem Te objective of ED problem for residential energy ub is to minimise te cost of energy during te operation period of N t witout affecting te customer s comfort [21] Te total energy cost (TEC) of suc a system can be formulated as follows TEC = N t t=1 ( ) EPeP t e t + EPgP t g t + OCF v t GTe Pg t (2) Te TEC is sum of te imported electricity and gas cost as well as te operation cost of te CHP unit In tis equation, EP t e and EP t g, respectively, stand for electricity and gas price It is assumed tat te electricity cannot be sold to te electric grid Te objective function in (2) is calculated wit and witout use of storage system, as explained ereafter 2 IET Gener Transm Distrib, pp 1 8

3 Fig 2 Energy ub model of a ome 31 No storage system Te energy ub supply electricity (L t e), eating (L t ) and cooling (L t c) loads at te output port Witout use of energy storage systems, te energy demand is supplied troug te grid electricity (Pe t ), natural gas (Pg t ), potovoltaic system (Pt pv ) and solar water eating (Pt sw ) Te converter tecnologies, namely, transformer, CHP, A/C and absorption ciller are used Te dispatc factor v t represents te fraction of te natural gas tat is devoted to CHP unit wile te remaining goes to te boiler Furtermore, te combination factor g t sows te fraction of te cooling load comes from ciller and te rest is supplied by A/C Te balance of input output power te system sould be kept [ L t ] e L t + g t ( C 1 g t ) AC T v t GTe Lt c = 0 v t ( GT + 1 v t ) F Pt e Pg t + Pt pv Psw t Limits on dispatc factor and combination factor value are te last inequality constraints of te problem (3) 0 v t 1 (4) 0 g t 1 (5) Loading limit of te converter elements sould also be considered as in (6) (10) P t e P T (6) v t GTe Pg t P CHP (7) ( 1 v t ) F Pg t P F (8) g t L t c P C (9) ( 1 g t ) L t c P AC (10) Te objective function (2) along wit te constraints in (3) (10) forms a non-linear optimisation problem Once solved, te optimal values of Y can be found [ Y= v t, P() t ] (11) Once te optimal values of Y is obtained, te TEC witout storage, TEC NS is calculated In addition, Based on (11) and Iran Energy Flow Diagram in [22], te cost of carbon emission (CCE) of te energy ub is obtained as follows CCE = PCE N t=1 [ CE PG Pe t + CE CHP vt GTe Pg t + CE ( F 1 ) ] vt F Pg t (12) Based on te optimal values of Y, CCE witout storage, CCE NS is also calculated 32 Storage benefit evaluation Wen electrical and termal energy storage systems are used, te storage systems contribute to bot energy supply and demand of te ub, depending on being carged/discarged Te balance of input output power of te system canges as follows (see (13) at te bottom of next page) Te variation in state of carge of te electrical and termal storage systems is presented in te following equation [ E t ] ( e E t = 1 ) Estb e E t 1 e ( 1 E stb ) E t 1 + Qt ie + ES Q t i + HS Qt oe / ES Q t o / HS (14) Limits on te carge and discarge rates and stored energy of te bot electricity (e) and eat () storage units are also considered as follows Q ia Q t ia Q ia a [ e, (15) Q oa Q t oa Q oa a [ e, (16) E a E t a E a a [ e, (17) IET Gener Transm Distrib, pp 1 8 3

4 Table 1 Various case studies Table 2 Energy ub parameters [23, 24] Case Trans CHP Boiler A/C Ciller PV SWH S1 S2 S3 S4 S5 S6 S7 S8 S9 S10 S11 S12 Aimed to reac sustainable storage utilisation, te energy stored in a storage unit at te end of study period sould be equal to te initial value as in E 1 a = E24 a a [ e, (18) An important issue regarding te dispatc problem is tat te problem sould be solved for te steady state condition Tis means tat te period for wic te TEC is optimised sould be repeatable and tis requires tat te storage level at te end of te operation period sall be equal to te level at te beginning of te period Tat is wy (18) as been considered in te paper Te objective function (2) along wit te constraints in (4) (10) and (13) (18) forms a non-linear optimisation problem Once solved, te optimal values of Y s can be found Y s [ = v t, P(), t Q t i (), Q t ] o () (19) Once te optimal values of Y s is obtained, te TEC and CEE wit storage system, TEC S and CCE S are calculated Cange in TEC and CEE due to te application of storage system are calculated as DCEE = CCE NS CCE S (20) DTEC = TEC NS TEC S (21) Te energy storage benefit (ESB) is ten obtained as follows ESB = DCEE + DTEC (22) As an economic performance index for storage system application, storage investment payback (SIP) is defined as follows SIP = SIC ESB (23) In wic storage investment cost (SIC) includes te capital cost associated wit te deployed energy storage systems SIP represents te number of operation periods required to payback te initial investment of te storage system Any judgment on te feasibility of storage system application sould be based on a cost-benefit analysis SIP can be used as an index to evaluate te economic attractiveness of storage application Smaller SIP means tat storage system application is more profitable Device Variable Value Unit transformer P T 5 kw η T 098 CHP P CHP 1 kw η GTe 035 η GT 04 OCF 0006 $/kw CE CHP 230 g/kw boiler P F 6 kw η F 09 CE F 250 g/kw air conditioner P C 2 kw η C 06 absorption ciller P AC 2 kw COP 15 electricity storage Ee 18 kw Q ie 03 kw Q oe 06 kw Ee stb 05 %/ + ES, ES 095 eat storage E 10 kw Q i 3 kw Q o 5 kw E stb 08 %/ + HS, HS 09 4 Metod application 41 Study data To investigate te role of different elements in optimal operating strategy of a residential energy ub, 12 case studies ave been defined as itemised in Table 1 Eac of te case studies represents a possible structure for energy conversion devices available in a ome For eac case, bot eat and electricity storage systems are considered Unit cost of electrical and termal energy storage systems are considered 10 and 3 $/kw, respectively SIC for te storage systems in te study cases is, so, equal to 15 $ Parameters of te energy ub elements related to a sample ome in Teran are listed in Table 2 Tese components parameters are collected from teir catalogue Efficiency of absorption ciller and A/C is calculated as follows AC = COP 1 + COP (24) Study ome energy demand profiles during te summer and te winter ave been presented in Figs 3a and b, respectively, based on te ome energy demand in Teran [23] Price of carbon emission is considered as 20 $ per ton of carbon dioxide [25] Electricity and natural gas tariff for purcasing from te network during te summer and te winter ave been sown in Fig 4a, according to [26, 27] As can be seen in Fig 4a, te tariff of natural gas is fixed during te day, wile te electricity tariff follows a time-of-use trend for low (23 cent/kw), medium (33 cent/kw) and peak (4 cent/kw) load periods Daily output profile for PV system wit 4 m 2 panel and SWH system wit 4 m 2 flat plate collector during te summer and te winter ave been sown in Fig 4b, based on calculations made for Teran [28] It as been assumed tat extra SWH output will be passed to te eat dump radiator g t L t e L t + ( C 1 g t ) T v t GTe P t Lt c = 0 v t ( GT + 1 v t ) e F Pg t + Pt pv Psw t Qt ie Q t i + Qt oe Q t o (13) AC 4 IET Gener Transm Distrib, pp 1 8

5 Fig 3 a In summer b In winter Study ome energy demands 42 Results and discussion Te case studies ave been analysed using te proposed metod for te study period of one year Te optimisation problem as been solved using BARON solver in GAMS platform [29] on a Dell Laptop, 17 GHz Intel CPU wit 2 GB of RAM Te calculated TES wit and witout energy storage as well as ESB and SIP for all te 12 cases ave been presented in Table 3 It can be seen in Table 3 tat te smallest TEC is obtained for case S12 in bot wit and witout storage However, different values for ESB and SIP ave been obtained for te different case In particular, SIP varies between 088 year for case S11 to 277 year for case S1, sowing tat storage application benefit depends igly on te elements used in te ub However, for all cases, SIP is quite small, meaning tat storage application is economically justified It can be seen in Table 3 tat te largest ESB is obtained for case S11 in wic te electricity demand can be supplied troug te CHP or te grid CHP generation is also used in case S11 to carge te battery for selling back at peak load price Fig 5a represents te electricity demand supply for S11 in a summer day: te electricity is stored in period of 5:00 am to 13:00 and is discarged between 19:00 to 22:00 During te winter, te electrical energy is stored in period of 4:00 to 11:00 and is discarged in te interval 17:00 to 21:00 Due to te electrical storage application, te electricity supply from te grid in summer and winter decrease from 06 to 02 kw and 075 to 03 kw, respectively Fig 5b sows te ome termal load supply during te winter It canbeseeninfig5b tat, during te winter, a little extra eat is produced during 13:00 to 15:00 wic is stored for being consumed during 16:00 to 19:00 During te summer, owever, extra CHP eat production in te period of 1:00 to 6:00 is stored for consumption during 7:00 to 10:00 Likewise, extra output energy of solar water eater is stored and is used in te period of 18:00 to 23:00 5 Metod comparison Te proposed approac to minimise ome energy cost as been compared wit two oter metods to minimise te ome energy cost: Metod I: determine te optimal use of electrical energy storage system, as in [30], to minimise TEC Metod II: based on te metod presented in [31], uses termal energy storage system to minimise TEC Te 12 case studies ave been analysed using Metod I and Metod II based on te study input data For eac case, TEC and CCE ave been determined wit and witout storage systems using te proposed approac, Metod I and Metod II and te storage impact as been calculated Results ave been presented in Table 4 It can be seen in Table 4 tat te TEC and CCE reduction obtained wit Metod I is larger tan tose obtained by Metod II in te cases S7 S11 wic include CHP unit As Metod I is just based on te electricity storage, it can be concluded tat te electricity storage is more beneficial wen CHP is applied Regarding te results obtained for Metod II, it can be seen tat for bot of cases S2 and S11, energy storage is more beneficial tan in oter cases As Metod II considers te termal storage, it can be concluded tat application of solar water eater or CHP wit ciller (CCHP) will increase te benefit of termal energy storage However, for all cases, it can be seen in Table 4 tat te benefit obtained using te proposed approac is larger of tose obtained using Metod I or Metod II Tis appens, in particular in S7 to S11 were bot storage systems are contributing to supply ub energy demand It can also be seen in Table 4 tat, for some cases, suc as S1, S3, S4 and S6, te results obtained by te proposed metod is equal to tose obtained by eiter Metod I or Metod II Tis sows tat in tose cases, just one of te electrical or termal storage systems is working and te oter one is not beneficial Hence, one may claim tat te proposed approac is not useful in suc cases However, te applicability of eiter of te storage systems cannot be determined a priori Even te ub element cannot merely be used to determine wic storage system is beneficial For example, S2 as all elements of S1 wit an extra solar water eater However, wile te termal storage is of no use for S1, it as contributed to ub energy system in S2 Fig 4 Study input data a Electricity and natural gas price b Output of renewable-based devices IET Gener Transm Distrib, pp 1 8 5

6 Table 3 Optimal results for case studies Table 4 Total benefit calculation comparison Case TEC ($) ESB ($/y) SIP (y) Wit storage witout storage Case Proposed approac Metod I (elec storage) Metod II (termal storage) S S S S S S S S S S S S Hence, as do te proposed approac, bot storage systems sould be considered simultaneously to evaluate te storage system benefit Tis sows tat te proposed approac as te advantage of obtaining te largest profit as it simultaneously considers termal and electrical storage Anoter issue in Table 4 is tat CCE reduction in S7 to S12 is comparable wit TEC reduction and a good sare of SIB acieved for cases S7 to S12 is due to te emission reduction In te oter words, if CCE reduction is not considered in ESB calculation, te results presented in Table 3 would cange drastically and te economic performance of storage system application could be negligible for some cases Hence, te emission reduction benefit as an important role in economic justification of storage system application and sould be clearly considered 6 Sensitivity analysis 61 Energy price Fig 6a sows te variation in te ESB of te case studies against cange in te electricity tariff in wic a multiplication factor as been applied to te tariff presented in Fig 6a A multiplication factor greater tan unity sows an increase in te electricity tariff from tose presented in Fig 6a Te obtained results sowed tat as long as te electricity tariff increases, more benefit can be experienced by te application of energy storage Better improvement can be observed in Fig 6a for te cases S7 S12 in wic CHP electricity generation is used to carge te electricity storage unit for selling back in te peak ours Te grap sown in Fig 6b represents te impact of gas price on te storage benefit It can be seen in Fig 6b tat, for cases S2 and S11, ESB as been decreased once te gas price as increase from tose presented in Fig 6b and it as been well increased according to te increase in te gas price However, if te gas price increases 15 times of te base case, 50% energy cost can be seen in te cases 2 and 11 Te cases 5, 7, 8 and 9 also ΔTEC ΔCCE ΔTEC ΔCCE ΔTEC ΔCCE S S S S S S S S S S S S experience a ligt increasing trend For cases of 10 and 12 wic ave CCHP system, it can be seen tat te eat storage as te igest improvement Te impact of CHP size on te storage benefit for cases S7 S12 as been analysed and te results ave been presented in Fig 6c It can be seen in Fig 6c tat, for cases S7 S12, te benefit as been decreased wit increase in te CHP size Tis is due to te reason tat te increased CHP generation cannot be anymore stored in te electricity storage unit and te economic attractiveness of te storage system will be decreased In te cases wic potovoltaic and CHP ave been deployed simultaneously (S9 and S11), for te conditions wit smaller CHP size, te system tends to store all te excess potovoltaic output, resulting to increase in te storage benefit For te oter cases, owever, storage benefit as been decreased once CHP size reduced Te electricity sell to te electric grid as been considered and te electricity sale price is considered as a fraction of te EP Te impact of variation in te electricity purcase price on ESB as been evaluated Results ave been presented in Fig 6d It can be traced in Fig 6d tat as long as te electricity purcase price rises, te benefit of electricity storage decreases In particular, if te electricity sale price is equal to te grid electricity price, te storage unit is of no elp to improve te cost of energy ub as te surplus electricity is sold to te grid directly 62 Uncertainty impact Sensitivity analysis as also been performed to investigate te impact of uncertainties associated wit te electricity demand and PV output Te impact of 10% variation in te ub electricity demand on SEB as been presented in Fig 7a It can be seen in Fig 7a tat, in cases S1, S2, S4 and S5 were neiter PV nor CHP is used, SEB does not depend on te Fig 5 a Electrical demand b Heating demand Demand supply for S11 in a summer day 6 IET Gener Transm Distrib, pp 1 8

7 Fig 6 Sensitivity analysis on energy prices and CHP size a Storage benefit against te electricity tariff cange b Termal storage benefit against te gas tariff canges c Storage benefit against te canges in CHP size d Electrical storage benefit against te canges in power price Fig 7 Impact of uncertainty on storage benefit a Electricity demand uncertainty b PV generation uncertainty Fig 8 Impact of storage size on te economic performance of te storage system a Electrical storage capacity variation b Termal storage capacity variation electricity demand In S3 and S6 wic just use just, SEB as decreased wit increase in te demand However, in oter cases wic use CHP, SEB as increased wit increase in te ub electricity demand Tis sows tat te impact of uncertainty in te ub demand on ESB depends mainly on te ub elements In particular, CHP application results to increase te sensitivity of ESB to variation in te ub electricity demand Te impact of 10% variation in PV generation on ESB associated wit te cases tat use PV as been studied and te results depicted in Fig 7b As can be traced in Fig 7b, te variation in SEB associated wit te cases are not te same: in cases S3 and S6 wic do not use CHP, SEB igly depends on PV generation However, for cases S9 and S12 were bot CHP and PV are used, SEB does not cange significantly wit variation in PV output Tis sows tat CHP application in energy ub elps to reduce te sensitivity of ESB to te uncertainty in renewable generation However, load and generation uncertainty is an important issue in energy ub Te autors are working on an advanced tecnique to fully include te uncertainty in energy ub dispatc problem IET Gener Transm Distrib, pp 1 8 7

8 63 Storage size Te impact of storage size on te economic performance of te storage system as been evaluated Fig 8a sows te variation in SIP against cange in te electrical storage size As presented in Fig 8a, SIP increases as te size of storage system increases Tis sows tat, wit increased storage size, te economic attractiveness of storage system application reduces Variation in SIP associated wit termal storage wit cange in te size is presented in Fig 8b It can be seen in Fig 8b tat SIP variation is different for te study cases: for S10 and S12, SIP increases quickly wit storage size However, for S2, SIP variation in negligible as te capacity increases to 6 kw Tis sows tat for S2, te termal storage capacity can be increased to 6 kw witout losing te economic attractiveness Hence, te elements of energy ub directly affect te suitable storage capacity Suitable models and metods sould be used to determine te optimal size of storage system according to te ub elements 7 Conclusions Tis paper as presented an approac to investigate te impact of electrical and termal storage systems in improving tecnical and financial performance of a residential energy ub Modelling te energy flow of a ome as an energy ub, te formulation of ED problem in te ome as been extracted Te benefit and investment payback of storage system application in various study cases ave been analysed Results sowed tat te ub elements affects directly te benefit and payback of storage systems It was also observed tat a great sare of storage benefit is due to te reduction in carbon emission and te storage benefits generally increase wit increase in te energy tariff However, selling te electricity to te grid can reduce te storage benefit CHP size generally ave positive impact on te storage benefit wile in some cases it migt as negative impact on te storage benefit Te impact of variation in te electricity demand and PV generation on te storage benefit can be positive, negative or negligible, depending on te elements of te ub In particular, CHP application in te ub results to protect te storage benefit against te variation in PV generation 8 References 1 Moeini-Agtaie, M, Deganian, P, Fotui-Firuzabad, M, et al: Multiagent genetic algoritm: an online probabilistic view on economic dispatc of energy ubs constrained by wind availability, IEEE Trans Sustain Energy, 2014, 5, (2), pp Pazeri, FR, Otman, MF, Malik, NH: A review on global renewable energy scenario, Renew Sustain Energy Rev, 2014, 31, pp Pazeri, FR: Tri-generation based ybrid power sceduling for renewable resources ric area wit energy storage, Energy Convers Manage, 2015, 103, pp Moeini-Agtaie, M, Abbaspour, A, Fotui-Firuzabad, M, et al: Optimized probabilistic PHEVs demand management in te context of energy ubs, IEEE Trans Power Deliv, 2015, 30, (2), pp Geidl, M, Koeppel, G, Favre-Perrod, P, et al: Energy ubs for te future, IEEE Power Energy Mag, 2007, 5, (1), pp Krause, T, Andersson, G, Frolic, K, et al: Multiple-energy carriers: 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