IET Renewable Power Generation

Review Article

Battery-supercapacitor hybrid energy storagesystem in standalone DC microgrids: areview

ISSN 1752-1416Received on 31st May 2016Revised 2nd September 2016Accepted on 29th October 2016E-First on 31st January 2017doi: 10.1049/iet-rpg.2016.0500www.ietdl.org

Wenlong Jing1 , Chean Hung Lai1, Shung Hui Wallace Wong1, Mou Ling Dennis Wong1

1Faculty of Engineering, Computing and Science, Swinburne University of Technology Sarawak Campus, Kuching, Malaysia E-mail: wjing@swinburne.edu.my

Abstract: Global energy challenges have driven the adoption of renewable energy sources. Usually, an intelligent energy andbattery management system is deployed to harness the renewable energy sources efficiently, whilst maintaining the reliabilityand robustness of the power system. In recent years, the battery-supercapacitor based hybrid energy storage system (HESS)has been proposed to mitigate the impact of dynamic power exchanges on battery's lifespan. This study reviews and discussesthe technological advancements and developments of battery-supercapacitor based HESS in standalone micro-grid system.The system topology and the energy management and control strategies are compared. The study also discusses the technicalcomplexity and economic sustainability of a standalone micro-grid system. A case study of a standalone photovoltaic-basedmicro-grid with HESS is presented.

1 IntroductionGlobal energy challenges and their impact on the environment haveaccelerated the adoption of renewable energy sources anddevelopment of smart and efficient micro-grid technologies [1, 2].Low voltage micro-grid in particular has attracted increasingattentions from researchers. Micro-grid is a small-scaledautonomous power grid system that consists of multiple energygenerations from renewable and non-renewables resources, energystorage systems (ESS) and power electronic converters. Micro-gridcan be operated either in standalone mode or connected to theutility grid [3–6].

A key advantage of micro-grid is that it allows powergeneration and supply to remote isolated community without theneed for costly and inefficient long-distance high-voltagetransmission and distribution infrastructures [7, 8]. However,maintaining a robust, high quality and reliable standalone micro-grid is challenging due to its relatively small capacity and theintermittent nature of the renewable energy resources [9]. Variousdevelopments have been carried out to improve the power qualityand reliability of the micro-grids, including the introduction ofnovel micro-grid topologies [10–12] and state-of-the-art powermanagement and control strategies [13–16].

Unlike the grid-connected micro-grids that have virtuallyunlimited support from the high inertia power generators,standalone micro-grids leverage heavily on its ESS to balance themismatch between the power it generates and the power beingconsumed [17]. The ESS acts as buffer to store surplus energy andsupply it back to the system when needed. ESS in standalonemicro-grid also play an important role in regulating instantaneouspower variations and maintaining power quality [18]. Table 1summarises the different ESS elements and their keycharacteristics.

In standalone micro-grid, the power flows in and out of the ESSelements varies widely depending on the instantaneous powergeneration and load condition [20]. In general, the powerexchanges in ESS can be categorised into high-frequencycomponents such as sudden surge in power demand or intermittentsolar power generation on a cloudy day, and the low-frequencycomponents such as natural behaviour of renewable energyresources or daily average energy consumption pattern [21]. High-frequency power exchanges generally require ESS elements withfast response time, while low-frequency power exchanges requirehigh energy density ESS elements.

Based on the characteristics of the different ESS elementsshown in Table 1, none of them has the characteristics to respondoptimally to both high and low frequency power exchanges [22].One way to get around this limitation is by combining multipletypes of energy storage elements to form a hybrid ESS (HESS). Abattery-supercapacitor combination has been considered in mostHESS developments because of their availability, similarity inworking principle, relatively low cost and most importantly, theycomplement each other limitations very effectively.

The automotive industry has developed HESS for electricallydriven vehicles. HESS had shown great improvement inmaximising the energy recovered from regenerative braking,increasing the rate of charging and prolonging the service life ofbattery by reducing the strain of deep discharge [23]. Thedevelopment of HESS for residential energy storage applications isbeginning to generate positive outcomes as well [24–26]. HESS istypically connected to the power network via AC or DC coupling.Power converters are used to control the power flow amongdifferent ESS elements [27–29]. Depending on the complexity ofthe control strategies, the use of power converters andmicrocontrollers can be costly [30]. Hence, the trade-off betweeneconomic feasibility and technical advantages exist and it is crucial

Table 1 Characteristics of different ESS elements [19]Energy storage system Energy density Power density Cycle life Response time Costchemical battery high low short medium lowsodium-sulphur (NaS) battery medium low short slow mediumflywheel low high long fast highsupercapacitor low high long fast mediumsuperconducting magnetic energy storage medium high long fast high

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in determining the financial and technical sustainability of micro-grid implementation.

Various battery-supercapacitor HESS topologies have beenproposed [31, 32]. Besides the topology, the energy managementand control strategies used in HESS are crucial in maximisingefficiency, energy throughput and lifespan of the energy storageelements [33–37]. This paper reviews the current trends of battery-supercapacitor HESS used in standalone micro-grid.

Section 2 presents the developments of battery-supercapacitorHESS topology for high-energy storage applications with acomprehensive analysis of different HESS in standalone micro-grid. Section 3 reviews the existing energy management strategiesincluding control goals, power allocation strategies and safetymeasures. In Section 4, a case study of a standalone photovoltaic-based micro-grid with different HESS topologies is presented andcompared. Section 5 gives a comprehensive review of the differentcontrol algorithms used in energy management system (EMS) andan evaluation of their effectiveness as well as economic andtechnical viability. Future trend of HESS development instandalone micro-grid is also presented. Finally, the paper isconcluded in Section 6.

2 Battery-supercapacitor HESS topologiesIn battery-supercapacitor HESS, the two ESS elements can becoupled to either a common DC or AC bus [38–40]. For standalonemicro-grid, common DC bus is the preferred choice due to variousreasons [41, 42]. First, most ESS elements and renewable energygenerators operate in DC voltage. Therefore, maintaining a DC busminimises the needs of power converter [43]. Second, DC bus does

not require synchronisation which greatly reduces the complexityof the overall system [44, 45]. As a result, DC coupling is moreefficient and lower cost than equivalent AC bus systems [46–48].

In general, battery-supercapacitor HESS can be categorisedbased on their connection topology as depicted in Fig. 1 [49, 50].

2.1 Passive HESS

Passive connection of battery and supercapacitor to the DC bus isthe simplest and cheapest HESS topology. It has been shown toeffectively suppress transient current under pulse load conditions,increase the peak power and reduce internal losses [51–54]. Asshown in Fig. 2, the battery and supercapacitor are connected to theDC bus directly. They share the same terminal voltage that dependson the state-of-charge (SoC) and charge/discharge characteristic ofbattery. In some rural micro-grid applications, the battery capacityis sized up to five days as reserve without any external source ofenergy [55]. Consequently, most of the time the battery will becycled with relatively low depth-of-discharge (DoD) and charged/discharged in a relatively low C-rate. As a result, the fluctuation inDC bus voltage will be minimal, ensuring a relatively stable systemvoltage.

However, the system current will be drawn from or feed into thebattery and supercapacitor based on their respective internalresistances [54]. Therefore, the transient power handing capabilityof the supercapacitor is not optimally utilised. In addition, as thevoltage variation of the battery terminal is small, the supercapacitorwill not be operating at its full SoC range which results in poorvolumetric efficiency [52].

2.2 Semi-active HESS

To make better use of the ESS elements in passive HESS, powerelectronic converters are included between the ESS elements andDC bus. This allows the power flow to be actively controlled [56].In semi-active HESS topology, only one of the two ESS elementsis actively controlled. Fig. 3a shows a semi-active HESS topologyin which only the supercapacitor is interfaced to the DC bus via abidirectional DC/DC converter, while the battery is directlyconnected to DC Bus [57]. In this topology, the bidirectionalDC/DC converter isolates the supercapacitor from the DC bus andbattery terminal. In this setting, the supercapacitor can be operatedwithin a wider range of voltages, which significantly improves thevolumetric efficiency. The direct connection of battery also ensuresstable DC bus voltage [58]. However, the passive connection ofbattery unavoidably exposes the battery to fluctuating high currentthat has negative impact on battery's lifespan [59].

The other semi-active HESS configuration is shown in Fig. 3b.The battery is isolated by a bidirectional DC/DC converter, whilethe supercapacitor is passively connected to the DC bus [24, 60,61]. Unlike passive and supercapacitor semi-active HESStopologies, the battery current can be controlled at a relativelygentler manner regardless of the fluctuation in the power demand.The battery terminal voltage is not required to match the DC busvoltage, allowing flexible and efficient sizing and configuration ofbattery bank [62]. However, the volumetric efficiency of thesupercapacitor is low. The linear charge/discharge characteristic ofthe supercapacitor also causes large fluctuation in the DC bus,which may result in poor power quality and system stability. Tomaintain a relatively stable DC bus voltage, the capacity ofsupercapacitor must be extremely large, which leads to high cost.

2.3 Full active HESS

In full active HESS topology, the power flow of battery andsupercapacitor are both actively controlled via bidirectionalDC/DC converters. This enhances the flexibility of the HESS andimproves the overall system performance and cycle life [59]. Twoof the most common full active HESS topologies are shown inFig. 4, namely parallel active HESS and cascaded active HESS.

In parallel active HESS topology, both battery andsupercapacitor are isolated from the DC bus by bidirectionalDC/DC converters as shown in Fig. 4a. Parallel active HESS is oneof the most common topologies for grid scaled storage applications

Fig. 1  Classification of the battery-supercapacitor HESS topologies

Fig. 2  Passive HESS topology

Fig. 3  Semi-active HESS topologies(a) Supercapacitor semi-active HESS topology, (b) Battery semi-active HESStopology

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which allows full control of both ESS elements [63]. With thistopology, the performance, battery life and DC bus stability can beimproved through carefully designed control strategy [64]. Forinstance the battery, as a high energy density ESS, can beprogrammed to meet the low-frequency power exchanges. Thesupercapacitor can be programmed to response to the high-frequency power surges and regulate the DC bus voltage. Thedecoupling of battery and supercapacitor allows both ESS elements

to operate at a wider range of SoC that can greatly improve thevolumetric efficiency of the HESS.

In cascaded topology, two bidirectional DC/DC converters arecascaded to isolate the battery and supercapacitor from the DC bus,as illustrated in Fig. 4b [65]. The bidirectional DC/DC converterthat isolates the battery is normally current controlled to providesmooth power exchange with the battery. This releases the batteryfrom harsh charge/discharge process due to the intermittency ofrenewable power generation and load. The bidirectional DC/DCconverter that isolates the supercapacitor from the DC bus isnormally voltage controlled to regulate the DC bus voltage whileabsorbing the high frequency power exchanges [66]. Since thesupercapacitor has wide operating voltage, a large voltage swingbetween the supercapacitor and DC bus is expected. As a result, thepower losses in the DC/DC converter will be higher as it is difficultto maintain efficiency across wide range of operating voltages [65].

As the number of power converter increases, the overallcoulombic efficiency of the HESS decreases due to losses in thepower converters. The performance of full active HESS system isalso extremely reliant on the reliability of the DC/DC convertersand their control system.

3 Energy management systemGenerally, the objectives of HESS implementation in standalonemicro-grid can be grouped into three main categories: (i)optimising micro-grid performance, (ii) enhancing systemreliability and (iii) lowering set-up and operating cost. Fig. 5summarises the objectives. Active HESS topology enables eachESS elements to be optimised through an EMS.

The role of EMS is to maximise the benefits of HESS.Volumetric and coulombic efficiencies have to be maximised whilemaintaining system stability and power quality at the DC bus. Interms of system reliability, EMS must ensure robust systemoperation in all possible loading conditions, protect the ESSs fromextreme conditions and extend the useful lifetime of the ESSelements. EMS also needs to ensure that cost of implementation,operation and maintenance are kept low. For instance, schedulingof diesel generator and load can be integrated into the EMS tolower the operating cost.

Fig. 6 depicts a typical EMS structure for HESS in standalonemicro-grid applications. In general, the EMS can be divided intotwo levels: (i) the low-level control system regulates the DC busvoltage and controls the current flowing in and out of ESSelements based on the reference signal generated by high-levelcontrol system. (ii) The high-level control system performs powerallocation strategy, SoC monitoring and control, and othersophisticated energy management strategies to achieve the setcontrol goals.

Zhou et al. [67] adopted the parallel active topology andproposed a modular HESS scheme that splits the single batterybank into multiple smaller battery modules. The supercapacitormodule and battery bank modules are interfaced to DC bus usingdual-active-bridge bidirectional DC/DC converters. The authorsemployed a linear filtering approach to remove high frequencypower fluctuations and distribute the smooth power demands toeach battery modules based on their SoC level. The supercapacitormodule will respond the high frequency power exchange throughcascaded inner current control loop and outer voltage control loop.A simple SoC management scheme for supercapacitor module isimplemented where the battery modules will charge thesupercapacitor when the SoC level is lower than a pre-setthreshold. The EMS mainly focuses on balancing the charge/discharge current among different battery modules. However, itdoes not consider the impacts of battery SoC variation in long-termoperation, which may affect the system stability and longevity ofthe battery. Moreover, the proposed modular HESS topologyrequires a large number of DC/DC converters, leading tosignificant increase in power loss and set-up cost.

To address the issue of high charge/discharge rate and possibledelay in converter's response, Kollimalla et al. [63] adopted thelinear filtering approach to decouple the high and low frequencycomponents of the power demand and added a rate limiter to

Fig. 4  Active HESS topologies(a) Parallel active HESS topology, (b) Cascaded active HESS topology

Fig. 5  EMS control goals

Fig. 6    Typical EMS structure for standalone PV DC microgrid withparallel active HESS

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prevent high charge/discharge rate of the battery. An additionalcompensator is implemented to compensate the slow response ofbattery. The proposed EMS mainly focuses on regulating the DCbus voltage and mitigating battery stress by limiting the batterycurrent. The technique assumes that all ESS elements work withinthe acceptable limits throughout the operation. It does not take intoconsideration the SoC control of the battery. This may cause thebattery to experience deep discharge under extreme conditions,which may lead to shorter battery lifespan.

Choi et al. [33] presented an EMS scheme in battery-supercapacitor HESS to achieve two objectives: (i) to minimise theenergy loss caused by the internal resistance of the supercapacitorand (ii) to mitigate the fluctuation of current flowing in/out of thebattery bank. The author mathematically formulated the twoobjectives in order to obtain the optimal solution to control thecurrent flow in each ESS elements. The two objectives wereformulated into convex optimisation problems, which are normapproximation and penalty function approximation, respectively.The two problems are then combined into a single multi-objectivesfunction. In order to obtain the optimal solution, boundaryparameters were determined through multiplicative-increase-additive-decrease principle. The values of the boundary parameterscritically determine the feasibility and optimality of the solution.This control strategy only considers the characteristics of ESSelements. It does not consider the interactions between theelements and other components within the micro-grid. Thus, theresulting optimal EMS scheme tends to be for one particularsystem only.

The above EMS strategies for HESS mainly focus on solvingthe short-term power demand variations and power sharingbetween supercapacitor and battery. However, the impact of SoCdrift in battery is not addressed. Specifically in micro-grid,seasonal variations in renewable energy generation and loaddemand must be carefully addressed to ensure reliable operation inall possible loading conditions.

To accurately monitor the battery SoC and to address the long-term SoC variation, Xue et al. [68] proposed an actively controlled,parallel connected battery-supercapacitor HESS in photovoltaicbased system that employs a multimode fuzzy-logic powerallocator to solve the problem of supply-demand mismatches.Based on the SoC conditions of batteries and supercapacitors, thefuzzy-logic controller selects the appropriate operating mode toallocate power demand to the ESS elements. To avoid overlycharging or discharging the ESS elements, the controller allows thepower exchange between the battery and supercapacitor and theirindividual power contribution to be optimally adjusted. The EMScontrol strategy guarantees all ESSs operate within their safeoperating range and compensates transient mismatches between thepower generation and demand.

Most EMS rely on a centralised controller to manage the powerflow among different ESS elements and DC bus. Therefore, arobust communication link between components is needed. Adisruption in the communication link will lead to catastrophic

system failure. A hierarchical controller for HESS was proposed in[69] to address this risk. In normal operating mode, the centralisedcontroller allocates power to ESS modules based on their ramprate. ESS with the highest ramp rate is normally assigned toregulate bus voltage. In the situation where the centralisedcontroller fails, distributed control at individual ESS elements willbe activated to ensure continuous micro-grid operation.

Due to the complex and non-linear characteristics of battery andsupercapacitor during the charging/discharging operation, simplepower allocation method such as linear filtering may not besufficient to effectively allocate the power demand among theenergy storage elements in HESS. Therefore, advance supervisorycontrol algorithms for EMS have been developed. A number ofdifferent intelligent and complex control algorithms, such asdeterministic rule based strategy, fuzzy logic control, linearprogramming, genetic algorithms, dynamic programming, neuralnetwork, self-adaptive algorithms and etc. have been reported inthe literatures [17, 70, 71]. Fig. 7 illustrates an overview of theclassification of existing EMS algorithms in HESS. The EMSalgorithms are generally categorised into two main classes whichare rule-based approaches and optimisation-based approaches [72–74].

3.1 Rules-based approach

Rule-based approach controls the power exchange of HESS basedon rules that are derived from mathematical models andexperiences [75–77]. Rule-based approach is an effective methodfor real time energy management widely used in HESSapplications. In thermostat control strategy, the battery operateswith constant power at its optimal efficiency point and it will beturned on or off according to the lower and upper SoC limits. Inpower follower control strategy, the battery is set as the primaryenergy storage and the EMS will adjust the battery charge/discharge power that follows the power demand. As a secondaryESS, the supercapacitor covers the difference between the powerdemand and battery response. Unlike thermostat and powerfollower control strategy, the state machine control strategy usesmultiple rules to control the power flow in HESS. The pre-definedrules can be designed based on the allowable upper and lower SoClimits of supercapacitor and battery, maximum charge anddischarge rates, load and generation powers, etc. Based on the real-time operational states of the HESS, power generation and powerdemand, the algorithm selects the appropriate operation mode tooptimise the power distribution between supercapacitor andbattery.

The deterministic rule-based concept is widely used due to itssimplicity and reliability [75, 78–81]. However, the rules aregenerally designed based on the initial state of the ESS elements.This may not accurately reflect the actual conditions of theelements in the long run. Therefore, fuzzy logic control strategyshown in Fig. 8 is introduced.

Fig. 7  Classification of intelligent algorithms for EMS supervisory control in HESS

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The rules are defined based on experiences and empiricalevidences. The transition between different rules is determined bythe fuzzy-rules and membership functions which results insmoother, more flexible and logical operation compared withdeterministic rule-based approaches [68, 82–84]. Fuzzy rule-basedcontrol algorithms can be integrated with other intelligentalgorithms to form hybrid control strategy which further improvethe performance of EMS in HESS [85–88].

3.2 Optimisation-based approach

Optimisation-based EMS employs modern optimisationalgorithms, such as linear programming (if the system is convexand could be mathematically represented via a set of linearfunctions), dynamic programming (both deterministic andstochastic), evolutionary methods such as genetic algorithm,simulated annealing, and particle swarm optimisation [89–93].These algorithms can be classified into global optimisation (off-line) and real-time optimisation (on-line). Unlike the rule-basedapproaches, modern optimisation algorithms are much morecomplex, which require heavy computation capability [72].

4 Case studyPhotovoltaic generator is commonly deployed in remote rural sitesthat are not connected to the utility grid. However, the intermittentnature of solar irradiance and the relatively large fluctuation in load

may lead to system instability [22, 34, 94]. Therefore, battery isnormally included in photovoltaic system. A case study ispresented in this section to demonstrate the effectiveness of HESSin reducing the stress on the battery.

A standalone photovoltaic system with battery-supercapacitorHESS is considered. The system is used to provide electricity to arural community in Sarawak, Malaysia. A supercapacitor semi-active HESS topology is used, as shown in Fig. 9a. A simple linearfiltering power allocation approach is employed in the simulation.The system key parameters are tabulated in Table 2. An actual solarirradiance data recorded on a typical partly cloudy day is used tosimulate the photovoltaic power generation. A daily powerconsumption profile is estimated based on actual survey data froma rural community. The simulated power generation and loadprofiles are shown in Fig. 9b.

To demonstrate the effectiveness of HESS in mitigatingbattery's stress, a battery-only ESS is also simulated forcomparison purpose. The simulation results showing the powerexchange in battery for both battery-only and HESS systems areillustrated in Fig. 10. As can be seen from the enlarged view inFig. 10b, the battery current for system with HESS experiencedless severe fluctuation compared with the battery-only system. Inaddition, the peak current for system with HESS is also reducedcompared with system without HESS. As suggested in batterylifetime characteristic studies, these are two of the many factorsthat accelerate the battery aging and performance deterioration [95,96]. Thus, minimising these factors can potentially improve theservice life of the battery.

To quantify the improvement in battery's health, a battery healthcost function C(T) is formulated based on common life-limitingfactors of chemical battery is shown in the following equation [97].

C T = ∑t = 0

Tn1 ib t 2 + n2

dib tdt + n3 max b t − min b t 2

+ n4

1 ; if ib t × ib t − 1 < 00 ; if ib t × ib t − 1 ≥ 0

+ n5

(1)

Fig. 8    Fuzzy logic control flowchart

Fig. 9  Case study to demonstrate the effectiveness of HESS in mitigating battery's stress(a) Standalone PV DC micro-grid with supercapacitor semi-active HESS topology, (b) PV generation and load profiles used in the simulation

Table 2 System parametersParameter ValuePV array power (peak) 5 kWdaily energy consumption 27.4 kWhbattery nominal voltage 48 Vbattery capacity 1000 Ahbattery internal resistance 0.005 Ωsupercapacitor capacitance 1000 Fsupercapacitor equivalent series resistance 0.001 Ω

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where T is the total operating time, ib(t) is the battery current, b(t)is the battery's SoC, while n1, n2, n3, n4 and n5 are weightages ofeach life-limiting factors. Five life-limiting factors are consideredin this cost function: (i) charge/discharge rate, (ii) dynamicity ofbattery current, (iii) DoD, (iv) charge/discharge transition, (iv)Calendar life. In general, the lower the value of C(T), the slowerthe battery ages. Fig. 11 shows the normalised C(T) for battery-only and HESS systems in 24 h. The system with HESS shows a33% reduction in battery health cost, which suggests substantialslowdown in battery aging and performance deterioration. Thoughthe battery aging process is a complex phenomenon which cannotbe quantified accurately with the simplified cost function as shownin (1), the proposed cost function does suggest a significantimprovement in battery life when HESS is used instead of justusing the battery only.

5 Analysis and discussionThere are varieties of HESS topologies and energy managementand control strategies used in micro-grid. Each one of themimproves different aspects of the micro-grid. They are selectedbased on the system requirements, technical and cost constraintsand end user expectations. The discussion and analysis in thefollowing subsections focuses on standalone micro-grid for ruralcommunities who are without access to the utility grid.

5.1 HESS topologies and EMS

Most researches on HESS are aimed at reducing the stress on thebatteries while maintaining power quality, improving HESSefficiency and lowering set-up cost. For greater controllability,

active HESS topology is commonly used. However, it increasessystem complexity and cost. Passive HESS provides simple,reliable and robust way to mitigate battery stress but at the cost ofcontrollability and performance.

For standalone micro-grid in remote areas where it is the onlysource of electrical power, system reliability and robustness isprioritised [98]. The semi-active HESS topology, which isrelatively simpler than active HESS, is probably the most suited forsuch application. Stress on the battery bank, which contribute themost to set up and maintenance cost, can be reduced by activelycontrolling the power flow between energy storage elements.

Apart from the three HESS topologies discussed above, thereexist many other sophisticated HESS topologies and controlstrategies in the literature. In [15], the battery bank is made up ofmicro-bank modules, each with its own DC/DC converter andEMS. A control strategy that dynamically configures the batterymodules is put in place to optimise the use of the modules and forgreater system efficiency. Similar concept was proposed in [99,100], where banks of varied energy storage elements and batterytypes were used with a global charge allocation algorithm thatcontrols the power flow between the storage banks. With carefulusage of power electronic converters, configurable and modularHESS could be one of the future trends in the development ofmicro-grid power management system. However, it may not besuitable for standalone micro-grid applications in remote area dueto the sophisticated and potentially costly system architecture.

5.2 AC coupled and hybrid AC–DC micro-grid

DC coupling is usually used for small-scaled standalone micro-gridin remote rural sites [101–106]. Passive and supercapacitor semi-active HESS are the most commonly used topologies. Whilst theymay not be the most efficient topologies, they deliver very robustoperation at lower cost [107]. For medium to large-scale micro-grid, AC coupling is commonly used to minimise losses in powertransmission [44]. Fig. 12a illustrates a typical AC coupled micro-grid architecture. For greater flexibility, hybrid AC–DC micro-gridthat caters for AC and DC power generators and ESSs shown inFig. 12b is used [38, 92]. The DC/AC and DC/DC convertersallows high degree of power flow controllability.

5.3 Limitations and future trends

ESS is a vital element that enables stable and reliable micro-gridoperation in the face of fluctuating power generation and loadprofiles. Therefore, enhancing the performance and reliability ofESS will be a research focus for standalone micro-grids. Newbattery technologies, such as graphene, lithium-air, aluminium-airand sodium-ion, are anticipated to replace existing batteries withsignificant improvement in performance and lifespan [108–110].The hybridisation of ESS and development of EMS are expected toevolve as well to make the most out of battery technologies [111].

Fig. 10  Simulated battery current for battery-only and HESS systems(a) Battery current, and, (b) Enlarged view of battery current

Fig. 11  Normalised battery health cost C(T) for battery-only and HESSsystems in 24 h

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The development of HESS is expected to progress in twodirections: (i) robust and reliable HESS in small-scale standalonemicro-grids specifically for remote or isolated sites, (ii)autonomous and intelligent medium to large-scale grid-connectedmicro-grids that are part of smartgrid architecture. In general,micro-grids for remote rural electrification will focus ondeveloping HESS that is robust, simple and easy to maintain due tothe difficulties in reaching the remote sites.

Conversely, high performance HESS with intelligent EMS andcontrol strategy will be the focus in grid-connected micro-grids orsmart-grids. For example, a re-configurable energy storage bankwas proposed in [112] to dynamically change the configuration ofbattery bank to optimise the workload of each cell, leading toimproved ESS performance and service life. Other sophisticatedideas of future energy supply and distribution system such as thenovel concept of ‘energy internet’ will rely heavy on the flexibility,performance and reliability of HESS [113, 114].

6 ConclusionA review of the battery-supercapacitor HESS in standalone micro-grid was presented in this paper. The existing HESS topologies arecategorised into three main groups, which are passive HESS, semi-active HESS and full active HESS. Their correspondingcharacteristics, strengths, weaknesses and possible applicationswere discussed and compared. The availability of activelycontrolled components in semi and full active HESS has enabledthe use of EMS to manage the power exchange within the HESS.Battery stress can be reduced while maintaining high level ofpower quality and reliability. A case study was presented todemonstrate the effectiveness of EMS in HESS in mitigatingbattery stress. The limitations and future trends in the research anddevelopment of HESS is analysed and discussed.

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Fig. 12  Micro-grid structure with AC bus(a) AC Coupled micro-grid, (b) Hybrid AC–DC micro-grid

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