![Battery Dynamics and Energy Management System
Control Algorithm[1].
6
Start
Measure SOC
Pload, PPV
0.3<SOC<0.9SOC<0.3SOC>0.9
PPV>Pload
Add an additional
load or halt
PPV>Pload
Load shedding
PPV<Pload
Charging Discharging
Return
N
N
YY
N
N
Y N
Y
Y
[1] R. Zamora and A. Srivastava, "Energy Management and Control algorithms for Integration of Energy storage Within Microgrid", in IEEE 23rd
International Symposium on Industrial Electronics (ISIE), 2014, pp. 1805 – 1810](https://image.slidesharecdn.com/iceeot-160416065606/85/Iceeot-6-320.jpg)
Iceeot
- 1. Modeling and Simulation of a Solar PV and Battery Based DC Microgrid System. International Conference on Electrical, Electronics and Optimization Techniques (ICEEOT) - 2016 Presenter: Mr. M.H.F Ahamed 1
- 2. DC Vs AC Microgrids. No need to consider about synchronization with utility grid and reactive power. Steadily increasing fraction of power is consumed by DC loads. More resilient in the face of natural disasters. Minimum losses at the interfaces. Any change in the frequency in the utility grid does not effect the operating frequency of ac loads in the DC grid 2
- 3. Usage of DC Microgrids Worldwide 3 Intel Corp. 400V DC UCSD 380VDC Duke energy 380VDC Sycracuce University 380VDC US Validus 550VDC Japan NTT GROUP 380VDC Korea 300/380VDC China Telecom 230/380VDC Sweden Netpower 350/380VDC France Telecom 350/380VDC Taiwan IT Manufacture 380VDC New Zealand Telecom 220VDC Uttar Pradesh rural electrification 24V Solar
- 4. Designed DC Microgrid System. 4 Designed system represents a isolated rural electrification system. Grid Tied Rectifier Solar PV Utility Grid Distribution Transformer Battery Bank DC Loads Micro Grid Central switch Buck Converter Battery Converter 3 km Distribution line 48 V DC Bus
- 5. Critical for Microgrids based on distributed sources. Objectives of Energy Management and Control are: o Control of solar PV: Provides a reference voltage (Vmpp) for the unidirectional DC-DC buck converter. o Control of the DC-DC buck converter at the PV output: Forces the solar array to operate at a voltage to harness the maximum power. o Battery charging and discharging circuit control: Maintains the DC link voltage at a desired value. o Control of grid tied rectifier: Supply power to the loads when solar power is not available. 5 Energy Management and Control.
- 6. Battery Dynamics and Energy Management System Control Algorithm[1]. 6 Start Measure SOC Pload, PPV 0.3<SOC<0.9SOC<0.3SOC>0.9 PPV>Pload Add an additional load or halt PPV>Pload Load shedding PPV<Pload Charging Discharging Return N N YY N N Y N Y Y [1] R. Zamora and A. Srivastava, "Energy Management and Control algorithms for Integration of Energy storage Within Microgrid", in IEEE 23rd International Symposium on Industrial Electronics (ISIE), 2014, pp. 1805 – 1810
- 7. Solar Maximum Power Point Tracking (MPPT). 7 Solar PV array and boost converter in PSCAD Maximum power point tracking model in PSCAD Vpv (V) Ppv (kW) Solar PV Characteristics Curve. Algorithm used for mppt is incremental conductance (IC).
- 8. Simulation Results. 8 Solar irradiance data is an actual variation measured at a particular place in Sri Lanka. Three scenarios are considered for the simulations. During all three scenarios the main objectives are to keep the bus voltage at 48VDC and battery state of charge (SOC) within safe limits. 0 16 32 48 64 7272 0 200 400 600 800 PSCAD simulation time (s) Irradiance(W/m 2 ) Variation of solar irradiance
- 9. Scenarios Considered for the Simulation. 9 Scenario (01) Battery reaches its maximum charging limit and then the system switches to halt mode when there is no additional load available. Scenario (02) Scenario 01 is extended by connecting an additional dynamic load to the system during the charging mode of the battery so that the battery SOC is regulated within its maximum limit. Scenario (03) Battery SOC reaches its minimum limit at a particular point of operation. So in order to keep the DC link voltage at 48 V load shedding is done.
- 10. 10 Scenario (01) 0 16 32 48 64 7272 0 16 32 48 6060 Time(s) (V) 0 16 32 48 64 72 0 16 32 48 60 (V) 0 16 32 48 64 72 50 60 70 80 90 100 SOC(%) 0 16 32 48 64 72 0 0.5 1 1.5 (kW) 0 16 32 48 64 72 0 1 2 33 (kW) 0 16 32 48 64 72 0 15 30 4040 (V) Vmpp Vpv
- 11. 11 Scenario (02) 0 16 32 48 64 7272 0 16 32 48 6060 Time(s) (V) 0 16 32 48 64 72 0 0.5 1 1.5 1.7 (kW) 0 16 32 48 64 72 0 16 32 48 60 (V) 0 16 32 48 64 72 0 1 2 3 (kW) 0 16 32 48 64 72 50 60 70 80 90 100100 SOC(%) 0 16 32 48 64 72 0 10 20 30 40 (V) Vmpp Vpv
- 12. 12 Scenario (03) 0 16 32 48 64 72 0 16 32 48 6060 Time (s) (V) 0 16 32 48 64 72 0 0.5 1 1.5 2 (kW) 0 16 32 48 64 72 0 1 2 3 (kW) 0 16 32 48 64 72 0 10 20 30 4040 (V) Vmpp Vpv 0 16 32 48 64 72 0 16 32 48 60 (V) 0 16 32 48 64 72 10 30 50 70 90 100100 SOC(%)
- 13. Conclusions and Future Work. 13 Simulation results shows that energy management and controls work as expected. The designed system can be used to test various power system scenarios and including transient and protection. System can be further expanded by incorporating wind turbines, super capacitors and diesel engines. Our future work is to design a suitable protection system for the designed microgrid.
- 14. Thank you! 14