An Improved Droop Control Strategy for Parallel Inverters in Microgrid

ABSTRACT

This paper proposes an improved droop control strategy for parallel invert er s in micro grid. It employs a double closed loop control method based on measured voltage feedback aiming at the voltage sags problem caused by the introduction of virtual impedance, for invert er control in the micro grid. Firstly, the frequency response character of the closed loop transfer function with virtual impedance and the inductive variation was analyzed in the frequency domain, indicating that the improved droop control method is necessary.

Secondly,

an improved droop control strategy based on inductive virtual impedance with measured voltage feedback was proposed. Lastly, the Mat lab/Sim u link simulation results show that the improved droop control strategy can not only solve the output voltage sags of the invert er, but also improve the accuracy of power allocation of droop control, maintain the system voltage and frequency stability. It is proved that the improved droop control strategy is effective.

KEYWORDS
  1. Micro grid
  2. Invert er
  3. Droop control
  4. Virtual impedance
  5. Voltage sags

SOFTWARE: MAT LAB/SIM U LINK

 BLOCK DIAGRAM:

 

Fig. 1 Block Diagram of Droop Control Based on Inductive Virtual Impedance

 

EXPECTED SIMULATION RESULTS:

Fig. 2 Operation Characteristics of Independent Micro grid in the Case of Casting or Cutting Load

Fig. 3 Operation Characteristics of D G 1 Independent Micro grid in D G 2 Casting or Cutting State

 

CONCLUSION

Aiming at the shortage of the traditional droop control strategy, this paper proposes an improved Q-V droop control strategy based on the inductive virtual impedance. Firstly, the frequency response curves of the closed loop transfer function of invert er control system based on inductive virtual impedance and the inductive virtual impedance variation on closed loop transfer function are analyzed in the frequency domain, indicating that the improved Q-V droop control method is necessary .

simulation

Then, the simulation experiments are built in parallel invert er s operation model of two distributed generations, simulation results of two kinds of operating conditions show that the proposed improved Q-V droop control strategy can eliminate the problem of voltage sags caused by the introduction of the inductive virtual impedance, improve the power allocation accuracy of droop control, and maintain the stability of the system voltage and frequency, so as to ensure the power supply quality of the independence micro grid system. Simulation results show the effectiveness of the improved Q-V droop control strategy.

 

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    micro grid[J].Proceeding of the Chinese Society for Electrical
    Engineering,2012,32(25):126-132.
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    Guerrero.Improved droop control strategy for micro grid-connected
    invert er s [J]. Sustainable Energy, Grids and Networks,2015,1:10-19.
    J i an jun S u, J i e y u n Z hen g, Dem in Cu i, Xi a o b o Li, Z h i j i a n H u, Chen g x u e
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    Micro-Grid Based on Feedback Impedance[J]. Power System and Clean
    Energy, 2015,31(10):34-38.

Autonomous Power Management for Interlinked AC-DC Microgrids

ABSTRACT:

The existing power management schemes for interlinked AC-DC microgrids have several operational drawbacks. Some of the existing control schemes are designed with the main objective of sharing power among the interlinked microgrids based on their loading conditions, while other schemes regulate the voltage of the interlinked microgrids without considering the specific loading conditions. However, the existing schemes cannot achieve both objectives efficiently. To address these issues, an autonomous power management scheme is proposed, which explicitly considers the specific loading condition of the DC microgrid before importing power from the interlinked AC microgrid. This strategy enables voltage regulation in the DC microgrid, and also reduces the number of converters in operation. The proposed scheme is fully autonomous while it retains the plug-nplay features for generators and tie-converters. The performance of the proposed control scheme has been validated under different operating scenarios. The results demonstrate the effectiveness of the proposed scheme in managing the power deficit in the DC microgrid efficiently and autonomously while maintaining the better voltage regulation in the DC microgrid.

KEYWORDS:

  1. Autonomous control
  2. Distributed control
  3. Droop control
  4. Hybrid microgrids
  5. Interlinked microgrids
  6. Power management

SOFTWARE: MATLAB/SIMULINK

 BLOCK DIAGRAM:

Fig. 1. Interlinked AC-DC microgrids and their control strategy.

EXPECTED SIMULATION RESULTS

Fig. 2 Scenario 1: Results showing (a) generators and tie-converter power, (b) DC microgrid voltage and (c) tie-converter control signals for four different load operating conditions.

Fig. 3. Scenario 2: Results showing (a) DC microgrid load demand, (b) generators and tie-converter power, (c) DC microgrid voltage and (d) tie-converter control signals at varying solar PV and load operating conditions.

CONCLUSION:

An autonomous power management scheme has been presented for interlinked AC-DC microgrids having different configurations. The proposed scheme manages the power deficit in the DC microgrid efficiently and autonomously. The number of tie-converters in operation has been reduced with the proposed prioritization to avoid unnecessary operational losses. The scheme has demonstrated better voltage regulation in the DC microgrid. The performance and robustness of the proposed scheme have been validated for two different scenarios of the DC microgrid at variable load conditions.

REFERENCES:

[1] J. Rocabert, A. Luna, F. Blaabjerg, and P. Rodr´ıguez, “Control of power converters in AC microgrids,” IEEE Transactions on Power Electronics, vol. 27, no. 11, pp. 4734–4749, Nov. 2012.

[2] M. Liserre, T. Sauter, and J. Y. Hung, “Future energy systems: integrating renewable energy sources into the smart power grid through industrial electronics,” IEEE Industrial Electronics Magazine, vol.4. no. 1, pp. 18–37, Mar. 2010.

[3] M. Tsili and S. Papathanassiou, “A review of grid code technical requirements for wind farms,” IET Renewable Power Generation, vol. 3, no. 3, pp. 308–332, Sep. 2009.

[4] T. Strasser, F. Andr´en, J. Kathan, C. Cecati, C. Buccella, P. Siano, P. Leit˜ao, G. Zhabelova, V. Vyatkin, P. Vrba, and V. Maˇr´ık, “A review of architectures and concepts for intelligence in future electric energy systems,” IEEE Transactions on Industrial Electronics, vol. 62, no. 4,pp. 2424–2438, Apr. 2015.

[5] A. Kwasinski, “Quantitative evaluation of dc microgrids availability: Effects of system architecture and converter topology design choices,” IEEE Transactions on Power Electronics, vol. 26, no. 3, pp. 835–851, Mar. 2011.

An f-P/Q Droop Control in Cascaded-Type Microgrid

ABSTRACT:

In cascaded-type microgrid, the synchronization and power balance of distributed generators become two new issues that needs to be addressed urgently. To that end, an f-P/Q droop control is proposed in this letter, and its stability is analyzed as well. This proposed droop control is capable to achieve power balance under both resistive-inductive an resistive-capacitive loads autonomously. Compared with the inverse power factor droop control, an obvious advantage consists in extending the scope of application. Finally, the feasibility of the proposed method is verified by simulation results.

 KEYWORDS:

  1. Cascaded-type microgrid
  2. Droop control
  3. Power balance

 SOFTWARE: MATLAB/SIMULINK

 BLOCK DIAGRAM:

Fig. 1. Structure of islanded cascaded-type microgrid.

CONTROL  SYSTEM:

 Fig. 2. The local control diagram of the i-th DG.

EXPECTED SIMULATION RESULTS


Fig.3. Simulation results of case I. (a) Active power. (b) Reactive power

Fig. 4. Simulation results of case II. (a) Active power. (b) Reactive power.

CONCLUSION:

A bridge modular switched-capacitor-based multilevel inverter with optimized UFD-SPWM control method is proposed in the paper. The switched-capacitor-based stage can obtain high conversion efficiency and multiple voltage levels. Meanwhile, it functions as an active energy buffer, enhancing the power decoupling ability and conducing to cut the total size of the twice-line energy buffering capacitance. Furthermore, voltage multi-level in DC-link reduces the switching loss of inversion stage because turn-off voltage stress of switches changes with phase of output voltage rather than always suffers from one relatively high DC voltage. Most importantly, the control method of UFD-SPWM, doubling equivalent witching frequency, is employed in the inversion stage for a high quality output waveform with reduced harmonic. In addition, the optimized voltage level phase maximizes the fundamental component in output voltage pulses to reduce harmonic backflow as possible. Hence, the comprehensive system efficiency has been promoted and up to peak value of 97.6%. Finally, two conversion stages are controlled independently for promoting reliability and decreasing complexity. In future work, detailed loss discussion, including theoretic calculation and validation of loss breakdown, will be presented.

REFERENCES:

[1] M. Jun, “A new selective loop bias mapping phase disposition PWM with dynamic voltage balance capability for modular multilevel converter,” IEEE Trans. Ind. Electron., vol. 61, no. 2, pp. 798-807, Feb. 2014.

[2] N. Mehdi, and G. Moschopoulos, “A novel single-stage multilevel type full-bridge converter,” IEEE Trans. Ind. Electron., vol. 60, no. 1, pp. 31-42, Jan. 2013.

[3] E. Ehsan and N. B. Mariun, “Experimental results of 47-level switchladder multilevel inverter,” IEEE Trans. Ind. Electron., vol. 60, no. 11, pp. 4960-4967, Nov. 2013.

[4] J. Lai, “Power conditioning circuit topologies,” IEEE Trans. Ind. Electron., vol. 3, no. 2, pp. 24-34, Jun. 2009.

[5] L. He, C. Cheng, “Flying-Capacitor-Clamped Five-Level Inverter Based on Switched-Capacitor Topology,” IEEE Trans. Ind. Electron., vol. 63, no.12, pp. 7814-7822, Sep. 2016.

 

 

 

 

New Perspectives on Droop Control in AC Microgrid

ABSTRACT

Virtual impedance, angle droop and frequency droop control play important roles in maintaining system stability, and load sharing among distributed generators (DGs) in microgrid. These approaches have been developed into three totally independent concepts, but a strong correlation exists. In this letter, their similarities and differences are revealed. Some new findings are established as follows: 1) the angle droop control is intrinsically a virtual inductance method; 2) virtual inductance method can also be regarded as a special frequency droop control with a power derivative feedback; 3) the combination of virtual inductance method and frequency droop control is equivalent to the proportional–derivative (PD) type frequency droop, which is introduced to enhance the power oscillation damping. These relationships provide new insights into the design of the control methods for DGs in microgrid.

 

KEYWORDS

  1. Microgrid
  2. Droop control
  3. Virtual Impedance

 

SOFTWARE: MATLAB/SIMULINK

  

BLOCK DIAGRAM:

block diagram

Fig. 1 Equivalent output voltage source considering virtual impedance.

 

EXPECTED SIMULATION RESULTS:

Fig. 2 Power response during load change in conventional frequency droop. (a) Active power, (b) reactive power.

Fig. 3 Power response during load change in frequency droop plus virtual reactance. (a) Active power, (b) reactive power.

Fig. 4 Power response during load change in modified frequency droop. (a) Active power, (b) reactive power.

 

CONCLUSION

This letter compares the similarities and differences among three different concepts, virtual impedance method, angle droop and frequency droop control. Although each of them has been well researched, new perspectives are bought to readers by relating all three together. Thus, the inherent relationships are established, and new insights into the controller design are provided. Finally, the modified droop control unifies these three independently developed droop control methods into a generalized theoretical framework. To the reader, this letter explores the possibilities of further enhancing the existing methods and inspiring the development of new methods.

 

REFERENCES

  • M. Guerrero, L. GarciadeVicuna, and J. Matas, “Output impedance design of parallel-connected UPS inverters with wireless load-sharing control,” IEEE Trans. Ind. Electron., vol.52, no.4, pp.1126-1135, Aug.2005.
  • He and Y. Li, “Analysis, design, and implementation of virtual impedance for power electronics interfaced distributed generation,” IEEE Trans. Ind. Appl., vol.47, no.6, pp. 2525-2538, Nov. 2011.
  • Mahmood, D. Michaelson, and J. Jiang, “Accurate reactive power sharing in an islanded microgrid using adaptive virtual impedances,” IEEE Trans. Power Electron., vol.30, no.3, pp. 1605-1617, Mar.2015.
  • Majumder, G. Ledwich, A. Ghosh, S. Chakrabarti, and F. Zare, “Droop control of converter-interfaced microsources in rural distributed generation, ” IEEE Trans. Power Del., vol. 25, no. 4, pp.2768-2778, Oct. 2010.
  • C, Chandorkar, D. M. Divan, and R. Adapa, “Control of parallel connected inverters in standalone ac supply systems,” IEEE Trans. Ind. Appl., vol.29, no.1 pp.136-143, Jan.1993.

 

Droop Control of Distributed Electric Springs for Stabilizing Future Power Grid

ABSTRACT:

This paper describes the droop control method for parallel operation of distributed electric springs for stabilizing ac power grid. It provides a methodology that has the potential of allowing reactive power controllers to work in different locations of the distribution lines of an ac power supply and for these reactive power controllers to support and stabilize the ac mains voltage levels at their respective locations on the distribution lines. The control scheme allows these reactive power controllers to have automatically adjustable voltage references according to the mains voltage levels at the locations of the distribution network. The control method can be applied to reactive power controllers embedded in smart electric loads distributed across the power grid for stabilizing and supporting the ac power supply along the distribution network. The proposed distributed deployment of electric springs is envisaged to become an emerging technology potentially useful for stabilizing power grids with substantial penetration of distributed and intermittent renewable power sources or weakly regulated ac power grid.

KEYWORDS:

  1. Droop control
  2. Electric springs
  3. Smart gird
  4. Voltage regulation

 SOFTWARE: MATLAB/SIMULINK

CIRCUIT DIAGRAM:

 

Fig. 1. Single phase diagram of the experimental setup of the power grid and loads (with 3 distributed electric springs working as a group).

 EXPECTED SIMULATION RESULTS:

Fig. 2. (a) Measured root-mean-square values of the mains voltage VS1,VS2 and VS3 (b) Measured root-mean-square values of the mains voltage VS1,VS2 and VS3 from 1800 to 1440 sec (ES activated without the proposed droop control) (c) Measured root-mean-square values of the mains voltage VS1,VS2 and VS3 from 1800 to 2160 sec (ES activated with the proposed droop control).

Fig. 3. Measured average value of reactive power generated by the 3 electric springs (Qa1 ,Qa2 and Qa3 ).

Fig. 4. Measured modulation indexes of the electric springs M1,M2 and M3 .

Fig. 5. Measured average value of the critical load power PR1,PR2 and PR3 .

Fig. 6. Measured root-mean-square values of the non-critical load voltage Vo1 ,Vo2 and Vo3 .

Fig. 7. Measured average value of the non-critical load power Po1,Po2 and Po3

.CONCLUSION:

A control scheme has been successfully developed and implemented for a group of electric springs. It enables individual electric springs to generate their mains voltage reference values according to their installation locations in the distribution lines and to work in co-operative manner, instead of fighting against one another, therefore allowing the electric springs to work in group to maximize their reactive power compensation effects for voltage regulation. The control method also leads to more evenly distribution of load power shedding among the non-critical loads. The attractive features of the control scheme have been successfully verified in an experimental smart grid setup.

With the droop control scheme,many electric springs of small VA ratings could be embedded into non-critical loads such as electric water heaters and refrigerators to form a new generation of smart loads that are adaptive to power grid with substantial penetration of renewable energy sources of distributed and intermittent nature. If many small electric springs are deployed in the power grid in a distributed manner, their collective voltage stabilizing efforts can be added together. Because the electric springs allow these smart loads to consume power following the varying profile of intermittent renewable energy sources, they have the potential to solve the stability problems arising from the intermittent nature of renewable energy sources and ensure that the load demand will follow power generation, which is the new control paradigm for future smart grid. Since the electric appliances embedded with the electric springs can share load shedding automatically, this approach should be more consumer-friendly when compared with the on-off control of electric appliances. For example, shutting down refrigerators is intrusive and inconvenient to the consumers (and may involve consumers’ rights issues) and requires some forms of central control. Allowing many smart refrigerators to shed some load without being noticed and central control is more consumer- friendly.

The individual operations of the electric springs have previously been evaluated. The successful implementation of the droop control for 3 electric springs working as a group in a small distributed network in this study is a just a step forward to confirm that multiple electric springs can work together without ICT technology. The collective effects of electric springs and their capacity are new topics that deserve further investigations. Extensive simulation studies are needed to confirm the effectiveness of many such electric springs working together in a large-scale power system model.

REFERENCES:

[1] P. P. Varaiya, F. F. Wu, and J. W. Bialek, “Smart operation of smart grid: Risk-limiting dispatch,” Proc. IEEE, vol. 99, no. 1, pp. 40–57, 2011.

[2] D. Westermann and A. John, “Demand matching wind power generation with wide-area measurement and demand-side management,” IEEE Trans. Energy Conversion, vol. 22, no. 1, pp. 145–149, 2007.

[3] P. Palensky and D. Dietrich, “Demand side management: Demand response, intelligent energy systems, and smart loads,” IEEE Trans. Ind. Informatics, vol. 7, no. 3, pp. 381–388, 2011.

[4] A. Mohsenian-Rad, V. W. S. Wong, J. Jatskevich, R. Schober, and A. Leon-Garcia, “Autonomous demand-side management based on gametheoretic energy consumption scheduling for the future smart grid,” IEEE Trans. Smart Grid, vol. 1, no. 3, pp. 320–331, 2010.

[5] M. Parvania and M. Fotuhi-Firuzabad, “Demand response scheduling by stochastic SCUC,” IEEE Trans. Smart Grid, vol. 1, no. 1, pp. 89–98,2010.

Cascaded Multilevel Inverter Based Electric Spring for Smart Grid Applications

 

ABSTRACT:

This paper proposes “Electric Spring” (ES) based on Single Phase three-level Cascaded H-Bridge Inverter to achieve effective demand side management for stabilizing smart grid fed by substantial intermittent renewable energy sources (RES). Considering the most attractive features of multilevel inverter (MLI), an effective structure of Electric Spring is proposed for suppressing voltage fluctuation in power distribution network arising due to RES and maintaining the critical load voltage. Also, the operation of ES in capacitive as well as inductive mode is discussed. Further, the paper describes droop control method for parallel operation of distributed electric spring for stabilization the power grid. An exclusive dynamic performance of the system using electric spring has been tested and demonstrated through detailed MATLAB simulation.

KEYWORDS:

  1. Critical load
  2. Cascaded H-Bridge Inverter
  3. Droop control
  4. Electric Spring
  5. MLI
  6. RES
  7. Smart load

 SOFTWARE: MATLAB/SIMULINK

SCHEMATIC DIAGRAM:

Fig. 1. Schematic of Electric Spring.

EXPECTED SIMULATION RESULTS:

Fig. 2. Observed RMS value of (a) Source voltage (Vs), (b) Non–critical voltage (Vnc), (c) Electric spring voltage (Va) & current (Ia), (d) Critical voltage (Vc) in capacitive mode.

Fig. 3. Observed Instantaneous value of (a) Source voltage (Vs), (b) Non–critical voltage (Vnc), (c) Electric spring voltage (Va) & current (Ia), (d) Critical voltage (Vc) in capacitive mode.

Fig. 4. Observed RMS value of (a) Source voltage (Vs), (b) Non–critical voltage (Vnc), (c) Electric spring voltage (Va) & current (Ia), (d) Critical voltage (Vc) in inductive mode.

Fig. 5. Observed Instantaneous value of (a) Source voltage (Vs), (b) Non– critical voltage (Vnc), (c) Electric spring voltage (Va) & current (Ia), (d) Critical voltage (Vc) in inductive mode.

Fig. 6. THD analysis of (a) Two-level and (b) Three-level CHMLI based ES.

CONCLUSION:

The paper proposes new approach for regulating the mains voltage using MLI based ES for smart grid applications. The implemented Three-level CHMLI based ES for smart grid application effectively regulates the ac mains voltage and reduces the THD content as compared with Two-level VSI based ES. The effectiveness of ES is validated through digital simulation in terms of THD. Lastly simulation results of droop control for Four Electric springs have been implemented in a large-scale distributed pattern in order to make multiple ES act in coordinating manner so as to have robust stabilizing effect.

REFERENCES:

[1] Edward J.Coster, Johanna M.A.Myrzik, BAS Kruimer, “Integration Issues of Distributed Generation Distribution Grids,” Proceedings of the IEEE, vol.99, no.1, pp.28-39, January, 2011.

[2] Koutsopoulos and L. Tassiulas, “Challenges in demand load control for the smart grid,” IEEE Netw., vol. 25, no. 5, pp. 16–21, 2011.

[3] M.H.J.Bollen, “Understanding Power Quality Problems: Voltage Sags and Interruptions,” IEEE Press, 2000.

[4] N. Hingorani and L. Gyugyi, Understanding FACTS, Concepts and Technology of Flexible AC Transmission Systems. New York: IEEE Press, 2000.

[5] M. Parvania and M. Fotuhi-Firuzabad, “Demand response scheduling by stochastic SCUC,” IEEE Trans. Smart Grid, vol. 1, no. 1, pp. 89–98, Jun. 2010

Model Predictive Control of PV Sources in A Smart DC Distribution System Maximum Power Point Tracking and Droop Control

 

ABSTRACT:

In a dc distribution system, where multiple power sources supply a common bus, current sharing is an important issue. When renewable energy resources are considered, such as photovoltaic (PV), dc/dc converters are needed to decouple the source voltage, which can vary due to operating conditions and maximum power point tracking (MPPT), from the dc bus voltage. Since different sources may have different power delivery capacities that may vary with time, coordination of the interface to the bus is of paramount importance to ensure reliable system operation. Further, since these sources are most likely distributed throughout\ the system, distributed controls are needed to ensure a robust and fault tolerant control system. This paper presents a model predictive control-based MPPT and model predictive control-based droop current regulator to interface PV in smart dc distribution systems. Back-to-back dc/dc converters control both the input current from the PV module and the droop characteristic of the output current injected into the distribution bus. The predictive controller speeds up both of the control loops, since it predicts and corrects error before the switching signal is applied to the respective converter.

KEYWORDS:

  1. DC microgrid
  2. Droop control
  3. Maximum power point tracking (MPPT)
  4. Model predictive control (MPC)
  5. Photovoltaic (PV)
  6. Photovoltaic systems

 SOFTWARE: MATLAB/SIMULINK

CIRCUIT DIAGRAM:

image001

Fig. 1. Multiple-sourced dc distribution system with central storage.

EXPECTED SIMULATION RESULTS:

image002

Fig. 2. Ideal bus voltage and load power as system impedance increases and loads are interrupted to prevent voltage collapse. (a) Bus voltage decreases in response to increased system impedance at t1 to reach the operating point on the new P–V curve at t2 . The new bus voltage is below the UVP limit, so control action cause load to be shed, moving to a new operating point on the same P–V curve at t3 with a higher bus voltage. (b) Load power in the system changes as point-of-load converters are turned OFF to reduce total system load when the bus voltage drops below the UVP.

image003

Fig. 3. Response of dc bus voltage to step changes in the power drained by load.

image004

Fig. 4. Response of dc bus voltage and output power to imbalanced input PV sources

image005

Fig. 5. Response validation of dc bus voltage to step changes in the power drained by load.

image006

Fig. 6. Response validation of dc bus voltage and output power to imbalanced input PV sources.

image007

Fig. 7. Response of dc bus voltage and output power to the input PV sources of Fig. 7.

CONCLUSION:

 High efficiency and easy interconnection of renewable energy sources increase interests in dc distribution systems. This paper examined autonomous local controllers in a single-bus dc microgrid system for MPP tracked PV sources. An improved MPPT technique for dc distribution system is introduced by predicting the error at next sampling time using MPC. The proposed predictive MPPT technique is compared to commonly used P&O method to show the benefits and improvements in the speed and efficiency of the MPPT. The results show that the MPP is tracked much faster by using the MPC technique than P&O method.

In a smart dc distribution system for microgrid community, parallel dc/dc converters are used to interconnect the sources, load, and storage systems. Equal current sharing between the parallel dc/dc converters and low voltage regulation is required. The proposed droop MPC can achieve these two objectives. The proposed droop control improved the efficiency of the dc distribution system because of the nature of MPC, which predicts the error one step in horizon before applying the switching signal. The effectiveness of the proposed MPPT-MPC and droop MPC is verified through detailed simulation of case studies. Implementation of the MPPT-MPC and droop MPC using dSPACE DS1103 validates the simulation results.

REFERENCES:

[1] Z. Peng, W. Yang, X. Weidong, and L. Wenyuan, “Reliability evaluation of grid-connected photovoltaic power systems,” IEEE Trans. Sustain. Energy, vol. 3, no. 3, pp. 379–389, Jun. 2012.

[2] W. Baochao, M. Sechilariu, and F. Locment, “Intelligent DC microgrid with smart grid communications: Control strategy consideration and design,” IEEE Trans. Smart Grid, vol. 3, no. 4, pp. 2148–2156, Dec. 2012.

[3] R. Majumder, “A hybrid microgrid with DC connection at back to back converters,” IEEE Trans. Smart Grid, vol. 5, no. 1, pp. 251–259, Jun. 2013.

[4] R. Lasseter, A. Akhil, C. Marnay, J. Stephens, J. Dagle, R. Guttromson, A. S. Meliopoulous , R. Yinger, and J. Eto, “Integration of distributed energy resources. The CERTS microgrid concept,” U.S. Dept. Energy, Tech. Rep. LBNL-50829, 2002.

[5] T. Esram and P. L.Chapman, “Comparison of photovoltaic array maximum power point tracking techniques,” IEEE Trans. Energy Convers., vol. 22, no. 2, pp. 439–449, Jun. 2007.

 

 

Distributed Generation System Control Strategies in Microgrid Operation

 

ABSTRACT:

Control strategies of distributed generation (DG) are investigated for different combination of DG and storage units in a microgrid. This paper develops a detailed photovoltaic (PV) array model with maximum power point tracking (MPPT) control, and presents real and reactive power (PQ) control and droop control for DG system for microgrid operation. In grid-connected mode, PQ control is developed by controlling the active and reactive power output of DGs in accordance with assigned references. In islanded mode, DGs are controlled by droop control. Droop control implements power reallocation between DGs based on predefined droop characteristics whenever load changes or the microgrid is connected/disconnected to the grid, while the microgrid voltage and frequency is maintained at appropriate levels. This paper presents results from a test microgrid system consisting of a voltage source converter (VSC) interfacing with a DG, a PV array with MPPT, and changeable loads. The control strategies are tested via two scenarios: the first one is to switch between grid-connected mode and islanded mode and the second one is to change loads in islanded mode. Through voltage, frequency, and power characteristics in the simulation under such two scenarios, the proposed control strategies can be demonstrated to work properly and effectively.

KEYWORDS:

  1. Distributed generation
  2. PV
  3. Microgrid
  4. Droop control
  5. PQ control

 SOFTWARE: MATLAB/SIMULINK

BLOCK DIAGRAM:

image001

Fig. 1. Schematic of the microgrid.

CONTROL SYSTEM:

image002

Fig. 2. Schematic of the PQ control.

image003

Fig. 3. Schematic of the droop control.

 EXPECTED SIMULATION RESULTS:

 image004

Fig. 4. PQ control under grid-connected mode.

image005

Fig. 5. Droop control for switching modes.

image006

Fig. 6. Droop control for varying load.

 

CONCLUSION:

In this paper a detailed PV model with MPPT, and PQ and droop controllers is developed for inverter interfaced DGs. The use of PQ control ensures that DGs can generate certain power in accordance with real and reactive power references. Droop controller is developed to ensure the quick dynamic frequency response and proper power sharing between DGs when a forced isolation occurs or load changes. Compared to pure V/f control and master-slave control, the proposed control strategies which have the ability to operate without any online signal communication between DGs make the system operation cost-effective and fast respond to load changes. The simulation results obtained shows that the proposed controller is effective in performing real and reactive power tracking, voltage control and power sharing during both grid-connected mode and islanded mode. To fully represent the complexity of the microgrid, future work will include the development of hierarchical controllers for a microgrid consisting of several DGs and energy storage system. The function of primary controller is to assign optimal power reference to each DG to match load balances and the secondary controllers are designed to control local voltage and frequency.

REFERENCES:

Barsali, S., Ceraolo M., Pelacchi, P., and Poli, D. (2002). Control techniques of dispersed generators to improve the continuity of electricity supply. IEEE Conf., Power Engineering Society, vol.2, pp.789-794.

Cai, N., and Mitra J. (2010). A decentralized control architecture for a microgrid with power electronic interfaces. IEEE conf., North American Power Symposium, pp. 1-8.

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