BUILDING ENERGY SIMULATION & OPTIMAL ENERGY … · Energyplus. With the help of MLE+ co-simulation tool, Energy-plus can be integrated with MATLAB for controlling certain inputs from

BUILDING ENERGY SIMULATION &OPTIMAL ENERGY MANAGEMENTCONTROL STRATEGY FOR GRIDCONNECTED PHOTOVOLTAICDIESEL - BATTERY HYBRIDPOWER SUPPLY SYSTEMS

D.Suchitra1,R.Rajarajeswari 2,G.Sidharth3

1,2 Assistant Professor,Department ofElectrical and Electronics Engineering,

SRM Institute of Science and Technology ,Kattankulatur, Chennai,

Tamil nadu- 603203, India3 PG Scholar,Department of

Electrical and Electronics Engineering,SRM Institute of Science and Technology ,

Kattankulatur, Chennai,Tamil nadu- 603203, India

February 9, 2018

Abstract

Building energy management system(BEMS) is an in-telligent method for managing the energy utilization withincreased efficiency and cost reduction.Improved focus onenergy cost savings would progress the visibility of build-ing energy simulation.Energyplus is an innovative simula-tion tool used to model BEMS. Energyplus and MATLAB

1

International Journal of Pure and Applied MathematicsVolume 118 No. 19 2018, 2647-2668ISSN: 1311-8080 (printed version); ISSN: 1314-3395 (on-line version)url: http://www.ijpam.euSpecial Issue ijpam.eu

2647

are utilized to do recreation and analysis of building energyperformance. A virtual model for a single floor, a multi-zonecommercial building equipped with a variable air volume(VAV) cooling system is built by Energyplus. The Zone op-erative temperature results are obtained from Energyplusand are compared with the real-time temperature data us-ing MATLAB to check the accuracy and to ensure that thebuilding occupants are in comfort zone. Proper Schedul-ing of Loads is done to get accurate temperature resultsin each zone. The power consumption of lighting system,equipment and VAV system are also obtained from Energy-plus. MLE+ co-simulation tool is used to integrate Energy-plus with MATLAB. This paper proposes an optimal energymanagement control strategy for grid-connected PV-Diesel-Battery hybrid power supply systems. The energy systemconsists of solar panel (PV), battery and Diesel Generator(DG) for continuous power flow management.The controlstrategy is developed in MATLAB to control and supervisethe operations of PV/Grid/Battery and Diesel power gen-eration systems. The objective of this model is to minimizeenergy and fuel cost while maximization of PV energy con-sumption. The Control Strategy is developed in such a waythat it co-ordinates when power ought to be generated byPV & Battery and when power should be generated by grid& Diesel generators. The Control Simulation demonstratesthat the created control strategy reduces the operationalhours of the grid and the Diesel generator thereby reducingthe running cost of the hybrid energy system. Depreciationcost analysis is also focused in this work.

Key Words:Energyplus, MLE+, Optimal Control, Bat-tery, Diesel Generator, Cost minimization

1 INTRODUCTION

Commercial and Residential Buildings account for about 20-40%of the total energy consumption in developed countries, and thisamount has been increasing at the rate of 0.5-5% per annum. Afterraising concerns over the depletion of fossil fuel reserves and theenvironmental impact of using them, the importance of designingand operating low energy buildings is highlighted. Since the lifes-

2

International Journal of Pure and Applied Mathematics Special Issue

2648

pan of the buildings is long, it is necessary to increase the energyefficiency of buildings, i.e. to reduce utility and energy costs whileassuring the comfort for building occupants. Building energy mod-eling tools can provide a feasible solution for reducing the energydemand. The energyplus software is a well-developed, validated andconstantly updated tool utilized for carrying out BEM. It has high-order detailed building geometry and system modeling capability.Reducing the operating energy cost is the primary objective of usingEnergyplus. With the help of MLE+ co-simulation tool, Energy-plus can be integrated with MATLAB for controlling certain inputsfrom Energyplus. There are two types of simulation-based controlsystem studies. The first type, known as static simulation-basedcontrol, in which the simulation was performed during the controlsystem design period to generate a set of scenarios for the controlsystem to select in operation. The second type, known as real-timemodel-based control used real-time building system models, expertsystems, or a combination of both to assist control systems in realtime.

In a grid-connected system, the batteries are often used as backup when the DG runs out of fuel and also to cover up the loadwhen the DG is shut down for maintenance. The DG and batteryare used as a backup source when there is a blackout. By usingthe PV, Battery, Diesel hybrid systems in a grid-connected mode,significant savings can be achieved in the overall operating costs ofDG and grid. A optimal strategy has to be deviced to efficientlymanage energy between PV/grid and backup sources.

2 RELATED WORK

BEMS are PC based system which are intended to control andobserve the use of building energy. The objective of BEMS are op-timization of energy efficiency and stipulated energy criterias. Afeasible study of on battery integrated DG system for rural electricsupply by using Hybrid Optimization Model for Electric Renewable(HOMER) was discussed by M.Ashari[1]. An optimization algo-rithm based upon the simulated annealing technique for a batteryintegrated DG hybrid system have been presented by C D Barleyet.al.[2]. S.Katipamula et.al.,[3] developed an algorithm for peak

3


2649

loads reduction and improved performance in terms of comfort andenergy savings. The use of daily load profile by using non-linearoptimization algorithm was proposed by C D Corbin et.al [4] todefine non-linear optimization problem to schedule power from thebattery and DG. The control of airflow distribution in a multi-zone office using exhaustive search algorithm was carried out byT.Salabury et.al., [5]. Supervision control and reducing energy coston DC microgrid, design and simulation was explained in [7]. HansDoukas et.al., presented an intellectual choice support model em-ploying rule set depending on classic BEMS system [8]. Peng Zhaoet.al., proposed an semi centralized decision making methodologyusing multi-agent system for BEMS [9]. Taein Hwang et.al., [10]designed a BEMS for joint management of energy generation, uti-lization, storing etc to manage equilibria between energy demandand energy supply in customer building.

3 ENERGYPLUS FOR BUILDING EN-

ERGY MANAGEMENT

Energyplus is used to model the energy management of a building,the temperature data of Chennai is used in this modeling. Theoptimal control strategy developed is aimed at reducing the oper-ating costs of the building. The control strategy is developed insuch a way that when the PV, DG, Grid and battery should supplypower to the building during the normal as well as blackout period.The main purpose is to reduce the running costs of DG and grid,thereby optimally utilizing the PV and battery energy sources. Thesimulation of seven different combination of energy sources are per-formed using EnergyPlus and MATLAB are given in Table 1. Theresults are compared for all the simulation types. Simulation type3 is considered as the conventional scenario, where the grid is usedto supply power during the normal period and DG is used to supplypower during the blackout period. Simulation type 7 is consideredas the future scenario where all the energy sources are used forsupplying power to the building according to the control strategydeveloped. The results of all the simulation types are discussed.

Table 1 Simulation Types

4


2650

SIMULATION ENERGY SOURCE USED1 Grid only2 DG only3 Grid - DG4 Grid - DG - PV5 Grid - DG - Battery6 PV - Battery7 Grid - DG - PV - Battery

EnergyPlus modeling of the building involves three importantsteps. The first step in the building energy simulation is structurecreation, where all the necessary details of the building like thedimensions, materials used are collected. The second step is zoning,which divides the building into a number of zones. The final stepwill be the scheduling of Loads present in the building.

3.1 Structure Creation

Modeling is performed in fifth floor of a building in Chennai. Inorder to model the building using Energyplus, the structural de-tails like dimensions of the building and the materials used in thebuilding are needed. The Table 2 the structural details required asinput for Energyplus are listed.

Table 2 Structural details needed for the building

Dimensionsof the Building1. Length (m)2. Width (m)3. Height (m)

Types of Materials used in (Like concrete, plaster, carpet )

1. Walls2. Roofs3. Floors4. Doors5. Windows

Properties of Materials

1. Thickness (m)2. Conductivity (W/m-k)3. Density (kg/m3)4. Specific heat (J/kg-k)

3.2 Zoning the Building

Zoning the building is defined as dividing the single floor or a build-ing into several small areas. Zoning depends on two main factors.The first factor is the temperature distribution of the building, i.e.whether the building is sun exposed or not. The second factor is the

5


2651

air conditioning system of the building, i.e. whether the buildinghas centralised or CAV or VAV types of air conditioning systems. Inthis model, the building is equipped with VAV type. The proposedbuilding model is divided into five zones as per the VAV types usedin the building as shown in Figure 1.

Figure 1. Dividing of Zones

3.3 Scheduling of Loads

The loads considered in this building are Lights, Computers andVAV. Scheduling of these loads is very much crucial as it determinesthe power consumption of the building. The accurate operatinghours of these loads has to be given in the EnergyPlus to determinethe exact power consumption of the building.

For Zones 1 4,The Load of lights and Computers is given as follows, Load of

Lights = 30 Watts * Number of people (Maximum limit is 1100W)Load of Computers = 200 Watts * Number of people For Zone

5,The Load of lights and Computers is given as follows,Load of Lights = constant (Maximum limit is 2400W) Load of

Computers =

1. For 10 People = 300W

2. For 20 people = 600W



5. More than 40 = 1500W to 2000W

6


2652

The above mentioned load data are given as input to the Ener-gyplus software. As it was explained earlier, Energyplus software isintegrated to MATLAB by using the toolbox MLE+. This toolboxis used to run Energyplus in MATLAB. The main reason for inte-grating Energyplus to MATLAB is to add additional energy sourcessuch as battery, DG and PV to the building. The MLE+ acts as alink between Energyplus and MATLAB to import and export datafrom Energyplus.

4 HYBRID SYSTEM COMPONENTS

Hybrid system components used in this building model includesPV, Grid, Diesel Generator and Battery. A conditional strategy isdeveloped to decide the sequence at which the energy sources wouldsupply power.

4.1 Solar Panel

The installed PV capacity in the proposed building is 10 kW. Forsimulation of the building, the real time solar panel power is con-sidered. Since the real time data of PV is used, the PV will supplypower only during the day time, to utilize its maximum efficiencyand also to minimize the peak cost of grid and fuel cost of DG. Ifthe demand is low, power from the PV is used to charge the battery.The efficiency of the PV is found to be 7%.

4.2 Grid

The maximum peak of grid power in the building is found to be 25kW. The cost of the grid power is considered as 0.10 $/kWh. Thegrid supplies power only when the PV is not able to meet the totaldemand of the building and also used to charge the battery whenthe battery power is below the SOC.

4.3 Battery

The Capacity of the battery used in this building model is 7.8 kWh.When PV and grid is able to meet the demand, the battery getscharged by the remaining power from PV. The battery power is

7


2653

discharged when the power from PV and Grid is not able to meetthe total demand of the building. Battery is the third most prioritynext to PV and Grid in this hybrid components used in the buildingmodel.

SOC(j+1) = SO(j)(Eff(Bat)/Enom) ∗ PBat(j) (1)

Where, SOC is the state of charge of the battery; Eff(Bat) isthe battery charging or discharging efficiency; Enom is the batterysystem nominal energy; PBat is the power flowing from the batterysystem.

4.4 Diesel Generator

The Diesel generator(DG) is designed in such a way that they al-ways operate close to their power rating to achieve high efficiency.The capacity of the DG used in this proposed model is 500 kVAand supplies power during blackout. DG is the least prioritizedamong the hybrid energy system considered, because of its highestfuel cost. The fuel cost calculation for diesel generator:

Dollar per kWh =34.019 ∗ exp(LoadFactor ∗ 1.00961) ∗ FuelCost Dollar

(LoadFactor ∗ DG Capacity)(2)

The priority of energy source usage is listed in the Table 3.

Table 3 Priority of Energy SourcesPRIORITY TYPE

1 PV2 GRID3 BATTERY4 DG

5 SYSTEM CONTROL STRATEGY

In current scenario, grid and DG are used to meet the demand in theproposed building model. Optimized control strategy is developedto overcome the issues faced in the conventional scenario. The issuesof the conventional scenario and the proposed strategy is discussedbelow.

8


2654

5.1 Conventional Scenario

In the conventional (Present) scenario, grid is used for supplyingthe demand during the normal period whereas DG supplies thedemand during the blackout period.The flowchart of the power flowin conventional scenario is given in Figure 2.

Figure 2. Battery charging (CC/CV)with MPPT

Where EB represents the power from grid and DG representsdiesel generator. Simulation for a day is carried out (July 17th 2015)and the maximum peak obtained from the grid is found to be 25kW. The cost of power from grid is found to be 160$. The estimatedcost of DG for the same day is 170 $. In this scenario, 6 hours, i.e.from 01.00-02.00, 08.00-09.00 and 12.00-15.00 are considered as theperiod of blackout.

5.2 Future Scenario

In the Future Scenario, a strategy is proposed to reduce the peakdemand and also to reduce the operating cost of grid and DG. Bat-tery and PV sources are used in addition to the grid and DG. It isvery much essential to determine when PV and Battery should sup-ply the power, and when battery has to be charged and discharged.It is also equally important to determine which source has to chargethe battery. The first priority among the four energy resources used

9


2655

in this model is PV and followed by grid, battery and DG. The firstpriority for charging the battery is given to PV, followed by gridand DG, provided the condition that PV, grid and DG are able tomeet the total demand of the building. The control system alsoconstantly checks for the SOC of the battery. The flowchart of thepower flow in future scenario is given in Figure 3.

Figure 3. Powerflow of Future Scenario

where, Xmin is the minimum limit of battery capacity, Pb() isthe total battery power, Xmax, the maximum limit of battery ca-pacity, X(t + 1), the current state SOC, P(t), the total power, X(t),the previous State SOC, Pv(t) the total PV power, Pd(t), the totalpower demand and Peb(), the total power from grid. The Strategyinitially checks whether the remaining power from PV & grid is ableto meet the total demand of the building. Then, it checks SOC levelof the battery. Depending on the remaining power available in thePV, grid combination and the battery SOC level, six different con-ditions are formed for the operations of all the four energy sourcesand for charging & discharging the batteries. It is to be noted thatgrid will be in OFF condition during the blackout period.

Condition 1:

10


2656

When less demand is given on the system this condition is appli-cable. If the total demand of the building is less than the combinedpower of PV & Grid, and if the battery SOC level is greater than95% then , PV & Grid will supply power to the building and battery& DG will be in OFF Condition.

Condition 2:This Condition focuses on the less demand time period and

battery charging when its SOC level is lower than 95%. If thecombined power of PV & grid is able to meet the demand and ifthe battery level is below the rated SOC level, then PV & grid willsupply power to the building. The remaining power from the gridis used for charging the battery, until the battery SOC reaches 95%of its rated level. Therefore, in this condition PV & grid will be inON condition, battery will be in charge mode and DG will be inOFF mode.

Condition 3:This condition focuses on battery usage when demand is high.

If power from PV & grid is not able to meet the total demand ofthe building, and the battery SOC is greater than 10%, then itdischarges the battery and the DG will be in OFF condition.

Condition 4:If the combined power of PV-grid is not able to meet the demand

of the building and the battery SOC level is below 10%, then theremaining power will be supplied by the DG and the power fromDG is used for charging the battery.

Condition 5:Concentration on DG and battery usage is considered in this

case when the demand is high. If the combined power of PV &Grid is not able to meet the total demand of the building and ifthe battery SOC is greater than 10%, then the battery will supplypower to the building. If the battery could not meet the demand,then DG will start supplying power to the building. During thiscondition, all the sources will be in ON condition and the batterywill be in discharge mode.

Condition 6:This aims on DG usage when demand is high and when the

battery has the SOC level below 10%. If the combined power fromPV & Grid is not able to meet the total demand of the building,and if the battery SOC level is below 10%, then the battery will

11


2657

be in OFF condition and the DG will supply the remaining powerto the building. During this condition, PV-Grid-DG will be in ONcondition, and Battery will be in OFF condition. The reason for notcharging the battery by DG is because it would result in increasedDG fuel cost. The operating modes briefed above is given in Table4.

Table 4 Operating modes of the Energy sourcesCondition PV EB DG Battery

1 ON ON/OFF OFF OFF2 ON ON/OFF OFF ON/Charging3 ON ON OFF ON/Discharging4 ON ON ON ON/Charging5 ON ON ON ON/Discharging6 ON ON ON OFF

6 RESULTS

The problem is formulated and simulated using Energy plus soft-ware in comination with MLE+ and Matlab and the results soobtained are explained below.

6.1 EnergyPlus Output

The simulation using Energyplus is performed, the outputs liketemperature in each zone of the building, the number of people ineach zone, power consumption by lights in each zone and computersin each zone are obtained and given through Figures 4 -7.

Figure 4 Temperature in each zone

12


2658

Figure 5 Number of people in each zone

Figure 6 Power Consumption of lights in each zone

Figure 7 Power Consumption of Computers in each zone

13


2659

6.2 Conventional Scenario

In this scenario, only DG and Grid is used for supplying power tothe building. The maximum demand is found to be 25 kW. Figure8 depicts simulation result for the power supply of conventionalscenario per day (17/7/2015). The cost curve and cost details areshown in Figure 9 and Table 5 respectively.

Figure 8 Power Supply of Conventional Scenario for one daysimulation [17-07-2015]

Figure 9 Cost curve of Conventional Scenario

Table 5 Cost of the power supply unit in conventional mode

14


2660

S.no List of source Cost in US dollars1 Total cost of Grid supply 170.7762 Total DG Fuel Cost 181.4943 Total Energy Cost 352.270

6.3 Future Scenario

All the four energy sources are used for supplying power to thebuilding. The maximum power that the grid can supply is limitedto 17 kW so that the peak electricity cost can be minimized. Theassumed power output from PV panel is shown in Figure 10. Theresults of the power supply and cost for future scenario are plottedFigure 11 and 12 and tabulated in Table 6. From the cost tabulatedfor future scenario,it is found that, as compared to conventionalscenario there is a considerable cost saving of Rs 3275.

Figure 10 PV curve for One day simulation [17-07-2015]

Figure 11 Power Supply of Future Scenario for one day simulation[17-07-2015]

15


2661

Figure 12 Cost curve of Future Scenario

Table 6 Cost of the power supply unit in future modeS.no List of source Cost in US dollars

1 Total cost of Grid supply 117.422 Total DG Fuel Cost 176.1353 Total Energy Cost 293.558

Figure 13 Charging and Discharging Curve of Battery

Several combinations of Energy sources are also simulated tocheck the optimal energy saving. The results of the various simu-lations are plotted in Figures 14-18.

16


2662

Figure 14 Power Supply - Grid only

Figure 15 Power Supply - DG only

Figure 16 Power Supply Grid-DG-PV

17


2663

Figure 17 Power Supply Grid-DG-Battery

Figure 18 Power Supply PV-Battery

7 Depreciation Cost Analysis

The depreciation cost calculation considering the initial cost set upof Table 7 is carried out in this study.The operating and mainte-nance cost of the solar panel is considered as 224.60 $ / year andthe life time of the solar panel and battery is considered as 15 and10 years repectively. The comparison of the cost details for a monthunder present and future scenario is shown in Table 8.

Table 7 Initial set up costTYPE CAPACITY COST ($)Battery 7.8 kWh 10,683

Solar Panel 10 kW 53,319

18


2664

Table 8 Comparison of Conventional & Future ScenarioConventional Scenario Future ScenarioFor 1 month: For 1 month:Grid cost = 5125 $ Grid cost = 3688.199 $DG cost = 5447 $ DG cost = 5288.782 $Total Energy Cost = 10572 $ Total Energy Cost = 8976.98 $

In a month, a huge amount can be saved by using the hybrid energysystem with proper control strategy developed.

Figure 19 Depreciation Cost Curve

From the Figure 19, it clearly shows that, it takes 3.8 years tocompensate the initial set up cost of PV and Battery.

8 Conclusion

This paper investigates the building energy management system.For achieving the efficient result the load was analysed and a con-trol strategy was developed to minimize the operating cost of thePV-Grid-Battery-DG hybrid power supply system. Energy plusintegrated with Matlab was used for solving the problem undervarious criteria and condition.The simulation result shows that byusing the battery integrated PV-Grid-DG hybrid system, consider-able monthly savings is possible. By using this simulation model,it is concluded that the initial set up cost can be compensated in a

19


2665

period of 3.8 years. Thus BEMS makes the power management ofthe building to be effective and economic.

References

[1] M. Ashar, Optimisation of photovoltaic/diesel/battery hybridpower systems for remote area electrification, Masters thesis,Department of Electrical and Computer Engineering, 1997.

[2] C.D.Barley, L.T.Flowers, P.J.Benavidez, R.L.Abergas, and R.B. Barruela, Feasibility of hybrid retrofits to off-grid dieselpower plants in the Philippines, Prepared for Windpower99,Burlington, Vermont, June 20-23, 1999.

[3] S.Katipamula, M.R.Brambley, Review article: Methods forfault detection, diagnostics, and prognostics for building sys-temsa review, Part I, HVAC & Research 11 (1) (2005) 325.

[4] C.D.Corbin, G.P.Henze, P.May-Ostendorp, A model predictivecontrol Optimization environment for real-time commercialbuilding application, Journal of Building Performance Simu-lation , volume6 (2013).

[5] J.Ma, J.Qin, T.Salsbury, P.Xu, Demand reduction in buildingenergy systems based on economic model predictive control”,Chemical Engineering Science 67 (1) (2012) 92100.

[6] U.S.D.o.E. Office of Energy Efficiency and Renewable Energy,EnergyPlus Energy Simulation Software: About EnergyPlus.

[7] U.S. DOE, Buildings Energy Data Book,http://buildingsdatabook.eren.doe.gov/, 2011.

[8] Haris Doukas, Konstantinos D. Patlitzianas, Konstantinos Ia-tropoulos, John Psarras, Intelligent building energy manage-ment system using rule sets, Building and environment 42(2007) 3562-3569.

[9] Peng Zhao, Siddharth Suryanarayanan, Marcelo Godoy Simes,An Energy Management System for Building Structures Usinga Multi-Agent Decision-Making Control Methodology, IEEE

20


2666

transactions on industry applications, vol. 49, no. 1, Jan-uary/February 2013.

[10] Taein Hwang, Ilwoo Lee, Design of a Building Energy Man-agement System for transcactive Energy, IEEE InternationalSymposium on Consumer Electronics (ISCE),2015.

21


2667

2668

Documents

BUILDING ENERGY SIMULATION & OPTIMAL ENERGY … · Energyplus. With the help of MLE+ co-simulation tool, Energy-plus can be integrated with MATLAB for controlling certain inputs from