Autonomous Power Control and Management Between Standalone DC Microgrids

ABSTRACT:

Renewable integrated DC Microgrids (DCMGs) are gaining popularity by feeding remote locations in qualitative and quantitative manner. Reliability of autonomous DC microgrids (ADCMG) depend on battery capacity and size due to stochastic behavior of renewables. Over charging and discharging scenarios compel the microgrid into insecure zone. Increasing the storage capacity is not an economical solution because of additional maintenance and capital cost. Thus interconnecting neighbor microgrids increases virtual storing and discharging capacity when excess power and deficit scenario arises respectively in any of the DCMG. Control strategy plays vital role in regulating the power within and between microgrids. Power control and management technique is developed based on bus signaling method to govern sources, storages and loads to achieve effective coordination and energy management between microgrids. Proposed scheme is simple and reliable since bus voltages are utilized in shifting the modes without having dedicated communication lines. Proposed scheme is validated through real time simulation of two autonomous DC grids in real time digital simulator (RTDS) and its results are validated by hardware experimentation.

KEYWORDS:

  1. Autonomous DC Microgrid
  2. Bus signaling method
  3. Power control and management scheme
  4. Renewable sources
  5. Real time simulation

SOFTWARE: MATLAB/SIMULINK

 BLOCK DIAGRAM:

 

Fig. 1. System architecture for interconnection of two ADCMGs.

 EXPECTED SIMULATION RESULTS

 

 

Fig. 2. Operating zones of ADCMG1: (a) Bus voltage, (b) Irradiation, (c) PV

output power, (d) Battery terminal voltage, (e) Battery output power, and (f) Load power.

Fig. 3. Operating zones of ADCMG2: (a) Bus voltage, (b) Irradiation, (c) PV

output power, (d) Battery terminal voltage, (e) Battery output power, and (f)  Load power.

Fig. 4. Operation of BDC using PCMS: (a) ADCMG1 voltage, (b) ADCMG2

voltage, (c) Power exported from ADCMG1, (d) Power exported from

ADCMG2, (e) Powers within ADCMG1, and (f) Powers within ADCMG2.

CONCLUSION:

A PCMS is developed based on bus signaling technique for inter DC grid power flow in case of ADCMGs to increase the system reliability and efficient utilization of resources. Two practical DC grid voltages (380V, 48V) are considered for evaluating the performance of developed scheme in simulation. PCMS is explored under normal and extreme scenarios including the over and under loading conditions of ADCMGs, further more with over charging and discharging of battery. It can be observed from above analysis that proposed PCMS is stable, efficient and effective in realizing communication independent control even under dynamic power variations during the power exchange. This statement is also justified with experimental results obtained through prototype model developed in the laboratory with reduced voltage of ADCMG1. Proposed system provides isolation and also enhances system reliability. Application potential of system suits low and medium voltage customers like domestic consumers, data centers, telecommunication systems, etc. in isolated locations where utility connection is not present or feasible.

REFERENCES:

[1] T. Dragicevi, X. Lu, J. C. Vasquez, and J. M.Guerrero, “DC Microgrids – Part II: A Review of Power Architectures, Applications and Standardization Issues,” IEEE Trans. Power Electron., vol. 31, no. 5, pp. 3528–3549, May. 2016.

[2] Q. Yang, L. Jiang, H. Zhao, and H. Zeng, “Autonomous Voltage Regulation and Current Sharing in Islanded Multi-inverter DC Microgrid,” IEEE Trans. Smart Grid, vol. PP, no. 99, pp. 1–1, 2017.

[3] J. Torreglosa, P. Garcia, L. Fernandez, and F. Jurado, “Predictive Control for the Energy Management of a Fuel Cell-Battery-Supercapacitor Tramway,” IEEE Trans. Ind. Informat., vol. 10, no. 1, pp. 276-285, Feb. 2013.

[4] L. Herrera, W. Zhang, and J. Wang, “Stability Analysis and Controller Design of DC Microgrids with Constant Power Loads,” IEEE Trans. Smart Grid, vol. 8, no. 2, pp. 881–888, March. 2017.

[5] D. E. Olivares, A. Mehrizi-sani, A. H. Etemadi, C. A. Cañizares, R. Iravani, M. Kazerani, A. H. Hajimiragha, O. Gomis-bellmunt, M. Saeedifard, R. Palma-behnke, G. A. Jiménez-estévez, and N. D. Hatziargyriou, “Trends in Microgrid Control,” IEEE Trans. Smart Grid, vol. 5, no. 4, pp. 1905–1919, July. 2014.

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