Energy Management of a DC Microgrid With Hybrid Energy Sources · non-conventional sources of energy may range from few watts to megawatts. Thus active sources catering to a group

Energy Management of a DC MicrogridWith Hybrid Energy Sources

D Anitha∗1,R.Uthra2,R.Uthra3

1,2,3 Assistant Professor, SRM Institute of Scienceand Technology , Kattankulatur,

Chennai, Tamil nadu- 603203, India

February 9, 2018

Abstract

The shortage in conventional sources of energy has pavedthe way for power generation using non-conventional energysources. Currently, the use of non-conventional source ofenergy for power generation at various levels is the mostresearched topic. Solar energy is one of the most promis-ing non-conventional sources of energy because of its abun-dance of availability. However, the intermittent nature ofthese sources and hence varying output power makes it un-reliable when connected to the power system. In order tocompensate for the variable power from PV panel and thefluctuating load, the system is equipped with an additionalbattery, supercapacitor and diesel generator. A DC micro-grid is set up to cater the loads in a particular area. Theproposed work aims to manage the energy demand of thissystem efficiently. The effectiveness of the proposed systemwith varying PV power output, load requirement, batterySOC and supercapacitor SOC have been studied and veri-fied by MATLAB/SIMULINK.

Key Words:DC Microgrid, MPPT, energy manage-ment

1

International Journal of Pure and Applied MathematicsVolume 118 No. 19 2018, 2631-2645ISSN: 1311-8080 (printed version); ISSN: 1314-3395 (on-line version)url: http://www.ijpam.euSpecial Issue ijpam.eu

2631

1 INTRODUCTION

Conventional sources of energy have been dominating energy pro-duction until recent years. The sharp increase in power demand,acute shortage of fossil fuels and its harmful effects on the environ-ment has paved the way for inclusion of non-conventional sourcesof energy into the power system. The power generation from thesenon-conventional sources of energy may range from few watts tomegawatts. Thus active sources catering to a group of loads ata demarcated region forms a microgrid. However, there are chal-lenges in integration, control and protection schemes of microgrids.Currently, researchers are oriented towards the improvement of re-liability and stability of the microgrids. Therefore, many effortshave been put in this direction to improve the reliability and oneof those techniques is energy management in a DC microgrid. Amicro grid is actually a small electrical distribution system which isself-sustaining with its own power source and works across a smalllimited area. They are one of the most efficient systems ever de-signed and often tend to have higher control over the componentsof the system due to the highly efficient control system. In en-ergy management, the given sources of energy are efficiently usedpartially or totally depending on the demand of the load. In thefield of solar energy, this technique is accompanied with anothertechnique maximum power point (MPPT) aimed to increase theoutput from the solar panels. Energy management ‘s main aim isto improve the efficiency of the system and use the given sourcesin the most judicious manner possible. Accompanied with MPPTand its different algorithms it makes up a very good system withmany of the desirable qualities but still, it is not enough for thepresent demands, hence still there is increasing research work is go-ing in this field to make it better. There have been almost equalamounts of work on both DC and AC microgrids but the best thingis to work on a hybrid system to offer more versatility and com-bine the advantages of both systems. Both DC and AC systemshave their own advantages like DC systems are more efficient anddurable and are easier to integrate them into the nonconventionalsources. But due to the requirement of a large number of powerelectronic components, make this type of system is complicatedthan AC system. Some of the promising works in this field still has

2

International Journal of Pure and Applied Mathematics Special Issue

2632

been on standalone systems are discussed here. The most commondesign that came up was that of a solar panel accompanied witha battery with different control strategies combined with appropri-ate MPPT algorithms. [8] One of the switching control mechanisminvolved was multivariable nonlinear model predictive voltage regu-lation. Another control mechanism known as coordinated variableand multivariable management strategy was also used, here con-stant voltage and constant current is used to charge the battery forthe increased lifespan of the system. [9] In this paper, the authordevelops a system which uses multiple power sources both AC andDC with multiple loads working on both off the grid and on gridmodes. [10] Here both solar and wind energy is used to satisfy theSOC demand of the lead acid with a supervisory control system.[11] In this three different sources are used namely solar, wind andbioethanol. Here all three sources source a fuel cell which in turnsupplies the load. This system is governed by an advanced geneticalgorithm accompanied by state machine algorithm to control theproduction of hydrogen and make the system stable. All the above-mentioned systems didnt have a proper backup power source andhence are not totally reliable. [12] Here PV source lead acid anddiesel generator are used and two very common control schemes areused namely load flow and cycle charging.Now many other systemsare designed based on the overview of this system but with dif-ferent control schemes accompanied by predictive algorithms anddifferent switching machine state. But in all the above systemsDG is used as a backup so the matter of fuel economy comes uphence in order to control its proper restrained use of the DG in alimited manner is essential. [1] Some of the previous works weremore concerned with the power quality and reduced loss and thusthe innovative droop control mechanism with the help of superca-pacitor was incorporated in this work to supply continuous burstsof good power quality power. This work also used a new conceptof virtual impedance and used the SC to find it. [2] In order toimprove the quality some of the works focused on the distributionside of the system like this one which proposed a two-layer con-trol scheme in order to reduce losses in the distribution system andhave it decentralized and further uses the droop characteristics toget a stable voltage at the output. [3] Another work focused on thepower converters used in this type of works. They proposed that

3


2633

if the converters are interleaved and connected with the grid andare further given preset reference values pertaining to specific casesaccompanied by control theory and power electronics devices a lin-ear model of such an improved model of the converter was madein a specific programming environment.[4]Some works like this onecompared DC and AC microgrids and brought forward each of itsadvantages and disadvantages and proved that DC microgrids arebetter than AC microgrids. They also did an in-depth work onDC microgrid architecture, controlling and other mechanisms. [5]Some other works show that there can be much more application toDC microgrid than the traditional power supply. This work showsthat a DC microgrid with battery and supercapacitor can be usedto charge electric vehicles in namely two ways. The first way isto install a charging station in a residential area or install similarcharging stations in a truck like vehicles for public areas. [6] Thiswork shows that the efficiency of the system can be increased fur-ther by increasing the efficiency of the battery pack used. In orderto do so, they have carefully designed the mechanical structure toreduce thermal losses and reduce the load pressure from it. Theyhave also used supercapacitors here as a protective device to pre-vent the battery from quick degradation and reduce the cost of theproject. [7] Another work suggested that with extensive use of bat-tery packs we can smoothen the output of solar and wind energyoutputs to increase their stability. The proposed system consists ofPV, Lead acid battery, supercapacitor and a diesel generator (DG)connected in parallel supplying a DC load. Each of this sourceis interfaced to the load through a suitable power electronic con-verter. A systematic way to efficiently manage the sources in orderto meet the load has been detailed. Since PV source is weatherdependent a lead-acid battery, supercapacitor, and diesel generatorare used to complement it. The block diagram of the system consid-ered is shown in Fig.1. Depending on the load and the generationfrom the PV source, a systematic algorithm has been developedfor efficient energy management by appropriate switching betweendifferent energy sources. This paper analyzes the working and con-trols the system considered with MATLAB Simulink. The paperis organized as follows: Section II deals with energy managementstrategy, followed by modeling of sources. Section IV describes thepower electronics interface used for each source. Section V discusses

4


2634

the results obtained followed by the conclusion.

2 ENERGY MANAGEMENT STRAT-

EGY

It is well known that the load demand and the solar energy gener-ated are continually varying with time. Incorporating a PV sourceto meet the demand requires some reliable back up for system re-liability and a systematic switching between sources to meet thevarying demand. Thus the energy management strategy aims atsatisfying the load demand and efficient harnessing of solar energy.Hence along with the PV source, other energy sources such as a bat-tery, supercapacitor, and DG are used. Also, the DC voltage at themicrogrid is maintained. Thus the energy management equation isgiven as

P (pv(t))+P (sc(t))+P (dg(t))+P (b(t)) = P (l(t))+CdvDCdt (1)

A PI controllers are incorporated with power electronic interfacein order satisfy the load and maintain the DC link voltage. Theenergy management strategy is the main control scheme, governingthe system and its switching operations is mainly divided into threemain parts which are given below

5


2635

Fig. 1 Block diagram of the system considered

• CASE 1: When PV power output is less than load demand(P(pv) < P(l))

Depending on the state of charge(SOC) of individual source,CASE 1 is further divided into the following subcases

(a) Subcase A: When the PV is not able to satisfy the powerdemand of the load, the battery provides the remaining loadpower. (P(pv) + PB = PL)

(b) Subcase B: When the state of charge of the battery (SOCLB)falls below its minimum value (SOCLB1), the Supercapacitorstarts discharging to maintain the power supply to the loaduntil the state of charge of supercapacitor SOCSC is less thanits minimum value SOCSC1. (P(pv) + PSC = PL)

(c) Subcase C: In the worst case as the supercapacitor SOCreaches SOCSCTH1 the DG is started. It is known that theDG needs some time to get to the stable peak value, the su-percapacitor helps to maintain the stable load demand untilthe DG comes online. Now the load is supplied by PV, Su-percapacitor, and DG. (P(pv) + Psc + PDG = PL)

6


2636

(d) Subcase D: In this case, battery, supercapacitor, and PVsupply the load i.e when the diesel generator fails to operate.(P(pv) + PB + PSC = PL)

• CASE 2: When PV power is equal to load demand (P(pv) =PL). Here PV is able to satisfy the load demand; hence noother energy management support is required.

• CASE 3: When PV power is greater than load demand(P(pv)>PL).

(e) Subcase E: When the Battery SOC is less than the maxi-mum battery SOC (SOCLB2), the excess PV power is used torecharge the battery till its SOC reaches SOCLB2 SOCLB =SOCLB2).

(f) Subcase F: When the battery has been fully charged,the excess PV power charges the supercapacitor till its SOCreaches maximum SOCSCTH2(SOCSC = SOCSCTH2).

(g) Subcase G: Now whenever Supercapacitor gets self-dischargedthe excess power from PV is used to recharge it.

(h) Subcase H: Now after Battery and Supercapacitor bothare recharged then excess PV power is wasted hence afterwardthe PV is damped.

The different cases explained above are depicted in Fig.2

7


2637

Fig. 2 Flow Chart for Energy Management Strategy

2.1 PV PANEL MODELING

An MSX 60 W solar panel is modeled based on equations [13]. Aboost converter is used to interface the PV panel with DC loads.The parameters of MSX 60 W solar panel are shown in Table.1The model is verified by comparing the I-V and P-V curves withthe data sheet. The I-V and P-V curves for different irradiation areshown in Fig.3 and Fig.4.

Table 1. SPECIFICATIONS OF SOLAREX-60Characteristics SpecificationsTypical peak power (Pmpp) 60WVoltage at peak power (Vmpp) 17.1VCurrent at peak power (Impp) 3.5 AShort circuit current (Isc) 3.8AOpen circuit voltage (Voc) 21.1 VTemperature coefficient of open circuit voltage (Kv) -(80 ± 10)mV/CTemperature coefficient of short-circuit current (Ki) -(0.0065±0.01)%/’CApproximate effect of temperature on power -(0.5±0.015)%/’CNominal operating temperature (Ki) 47 ±2’C

8


2638

Fig. 3. I-V curves with different irradiations of 1000,600,800W/m2 for an operating temperature of 25◦ C

Fig. 4. P-V curves with different irradiations of 1000,600,800W/m2 for an operating temperature of 25 ◦ C

2.2 SUPERCAPACITOR AND LEAD ACID BAT-TERY

A supercapacitor is capable of supplying power instantly for a shortduration making it suitable for transient load changes. However,a battery can supply steady and continuous energy at consider-able duration. Thus supercapacitors and batteries complement eachother. In this work, the supercapacitor used serves two purposesnamely: for storage and backup input resource for transient load

9


2639

variations. Secondly, it is used to supply power between the startand steady state operation of the diesel generator (DG). Since DGtakes some time to reach the desired power rating of the load, thesupercapacitor bridges the gap. supplies for the DG and helps theDG to catch up with the whole system. Since supercapacitor hashigh energy density it can release it very rapidly and thus suitableto supply high energy in very short time. A supercapacitor ratingof 55F & 15V is used. The lead acid battery is one of the most com-monly used electrochemical storage devices and is very rugged andinexpensive compared to other counterparts. It is also very durableand reliable. The project uses a 12V, 45Ah Lead acid battery. Thebattery control is managed by controlling and measuring its SOC.

2.3 POWER ELECTRONIC INTERFACE

As shown in fig.1 different power converters are used to interfaceenergy sources and the load. These power converters along withtheir control circuit ensure that the DC voltage is maintained at 24V. A boost converter is used to link PV source and the load. Theoutput of the PV panel is stepped up by the boost converter to havea constant DC link voltage. The boost converter with Perturb andObserve (P&O) based Maximum Power Point Tracking (MPPT)algorithm is used. The design values for the boost converter areInductance L= 4.2mH and Capacitance C =1.2 mF [14].

A buck-boost converter is a DC-DC converter which increasesthe voltage or reduces the voltage level according to the duty cyclefixed in its control circuitry. If the duty cycle is more than 50%then the output voltage will be boosted and if it‘s less than 50%then output voltage gets bucked. The supercapacitor and batteryare interfaced with the load through a buck-boost converter.

A DC source replaces a diesel generator and the rectifier forsimulation purposes.

3 RESULTS

The components of the system have been modeled, integrated andsimulated in MATLAB environment using SIMULINK. The effi-cient management of the energy sources based on energy manage-

10


2640

ment strategy are shown in Fig.5. The different subcases are clearlyindicated and discussed.

Fig.5 shows PV power Vs time, load power Vs time and Batteryand Supercapacitor SOC Vs time. The first curve shows the varyingPV power with respect to varying irradiance. Whenever the PVpower is sufficient to meet the load demand the other sources haveno role to play. Hence the charge in the battery and supercapacitorremains the same. This condition is shown as case 2 in Fig.5.When solar irradiation decreases, the PV source along with batterymeets the load demand (subcase A). When the battery SOC hasreduced below the threshold the supercapacitor comes into actionand the DG is switched ON. This is observed by decreasing value ofsupercapacitor SOC (subcase B &C). Subcase D shows PV, battery,and supercapacitor supplying the load.

When PV power is sufficient to supply the load demand andstill has excess power left it starts charging the battery and thesupercapacitor respectively, which can be seen by observing theirrespective SOC curves (subcase E and F). Now as both of them getstotally recharged and there is still excess power available the PV isoperated in a damped manner (subcase G and H). Fig.6 shows theDC bus voltage for the variations in PV power shown in Fig.5.

11


2641

Fig.5. PV power, Load power, Battery SOC, Super capacitor SOCat different time instants based on energy strategy

Fig.6. DC bus voltage of the system

4 CONCLUSION

The Energy management system has been studied to satisfy the de-mand of the load while maintaining the bus voltage constant. Con-sidering the current power shortages using depletion of fossil fuel

12


2642

for conventional sources, a solution has been proposed to use non-conventional energy sources (major player) and conventional energysources (used only in cases non-conventional sources fail) which in-creases the efficiency and reliability. Thus the system utilizes fourpower sources namely PV, Battery, SC, and DG.The system wassimulated and the intermittency in solar irradiation was simulatedand the behavior of the system was studied. The results with dif-ferent case and subcases have proved to be satisfactory. The systemhas shown the merits of using a microgrid with non-conventionalresources such as solar to increase their productivity. The systemhas high scope in domestic and commercial areas.

References

[1] Hossain E, Kabalci E, Bayindir R, Perez R. Micro grid testbedsaround the world, state of art. Energy Conversion and Man-agement 2014; vol 86, pg132153.

[2] Farhangi H. The path of the smart grid,. IEEE Power andEnergy Magazine 2010; vol8, pg1828.

[3] Planas E, Andreu J, Grate JI, Martnez de Alegra I, Ibarra E.AC and DC technology in micro grids: a review,. Renewableand Sustainable Energy Reviews 2015; vol.43: pg.726749.

[4] Dragicevic T, Lu X, Vasquez JC Guerrero JM. DC micro gridsPart I: a review of control strategies and stabilization tech-niques. IEEE Transactions on Power Electronics, 2016; vol31:pg 48764891.

[5] Dragicevic T, Lu X, Vasquez JC, Guerrero JM. DC micro gridsPart II: a review of power architectures, applications, and stan-dardization issues,. IEEE Journals and magazines, 2016; vol31: pg. 35283549.

[6] Elsayed AT, Mohamed AA, Mohammed OA. DC micro gridsand distribution systems: an overview,. Electric Power SystemResearch, 2015; vol.119: pg. 407417.

[7] Sechilariu M, Locment F. Urban DC micro grid: intelligentcontrol and power ow optimization, chapter connecting and

13


2643

integrating variable renewable electricity in utility grid,. 2016.p. 133.

[8] Dizqah AM, Maheri A, Busawon K, Fritzson P. Standalone DCmicro grids as complementarity dynamical systems: modelingand applications,. Control Engineering Practice. 2015; vol. 35:pg. 102112.

[9] Kumar M, Srivastava SC, Singh SN. Control strategies of a DCmicro grid for grid connected and islanded operations,. IEEETransactions Smart Grid 2015; vol. 6: pg. 15881601.

[10] Valenciaga F, Puleston PF. Supervisor control for a stand-alone hybrid generation system using wind and photovoltaicenergy,. IEEE Transactions Energy Conversions 2005; vol. 20:pg. 398405.

[11] Feroldi D, Degliuomini LN, Basualdo M. Energy manage-ment of a hybrid system based on windsolar power sourcesand bioethanol,. Chemical Engineering Research Design 2013;vol.91: pg.14401455.

[12] Ameen AM, Pasupuleti J, Khatib T.Simplied performancemodels of photovoltaic/diesel generator/battery system con-sidering typical control strategies,. Energy Conversion Man-agement 2015; vol.99: pg. 31325.

[13] Hany M. Hasanien, Shufed Frog Leaping Algorithm for Photo-voltaic Model Identication, IEEE Transactions on sustainableenergy,2015, vol.6, pg.509-515

[14] Pooja Sahu, Deepak Verma, Dr. S Nema, Physical Designand Modelling of Boost Converter for Maximum Power PointTracking in Solar PV systems, 2016 International Conferenceon Electrical Power and Energy Systems (ICEPES), pg. 10-15.

14


2644

2645

2646

Documents

Energy Management of a DC Microgrid With Hybrid Energy Sources · non-conventional sources of energy may range from few watts to megawatts. Thus active sources catering to a group