Power management in PV-battery-hydro based standalone microgrid

ABSTRACT:

This work deals with the frequency regulation, voltage regulation, power management and load levelling of solar photovoltaic (PV)-battery-hydro based microgrid (MG). In this MG, the battery capacity is reduced as compared to a system, where the battery is directly connected to the DC bus of the voltage source converter (VSC). A bidirectional DC–DC converter connects the battery to the DC bus and it controls the charging and discharging current of the battery. It also regulates the DC bus voltage of VSC, frequency and voltage of MG. The proposed system manages the power flow of different sources like hydro and solar PV array. However, the load levelling is managed through the battery. The battery with VSC absorbs the sudden load changes, resulting in rapid regulation of DC link voltage, frequency and voltage of MG. Therefore, the system voltage and frequency regulation allows the active power balance along with the auxiliary services such as reactive power support, source current harmonics mitigation and voltage harmonics reduction at the point of common interconnection. The experimental results under various steady state and dynamic conditions, exhibit the excellent performance of the proposed system and validate the design and control of proposed MG.

 SOFTWARE: MATLAB/SIMULINK

 CIRCUIT DIAGRAM:
Fig. 1 Microgrid Topology and MPPT Control

(a) Proposed PV-battery-hydro MG

 EXPECTED SIMULATION RESULTS

 

 Fig. 2 Dynamic performance of PV-battery-hydro based MG following by solar irradiance change

(a) vsab, isc, iLc and ivscc, (b) Vdc, Ipv, Vb and Ib, (c) vsab, isa, iLa and ivsca, (d) Vdc, Ipv, Vb and Ib

 

Fig. 3 Dynamic performance of hydro-battery-PV based MG under load perturbation

(a) vsab, isc, Ipv and ivscc, (b) Vdc, Ipv, Vb and Ib, (c) vsab, isc, Ipv and ivscc, (d) Vdc, Ipv, and Vb

CONCLUSION:

In the proposed MG, an integration of hydro with the battery, compensates the intermittent nature of PV array. The proposed system uses the hydro, solar PV and battery energy to feed the voltage (Vdc), solar array current (Ipv), battery voltage (Vb) and battery current (Ib). When the load is increased, the load demand exceeds the hydro generated power, since SEIG operates in constant power mode condition. This system has the capability to adjust the dynamical power sharing among the different RES depending on the availability of renewable energy and load  demand. A bidirectional converter controller has been successful to maintain DC-link voltage and the battery charging and discharging currents. Experimental results have validated the design and  control of the proposed system and the feasibility of it for rural area electrification.

REFERENCES:

[1] Ellabban, O., Abu-Rub, H., Blaabjerg, F.: ‘Renewable energy resources: current status, future prospects and technology’, Renew. Sustain. Energy Rev.,2014, 39, pp. 748–764

[2] Bull, S.R.: ‘Renewable energy today and tomorrow’, Proc. IEEE, 2001, 89  (8), pp. 1216–1226

[3] Malik, S.M., Ai, X., Sun, Y., et al.: ‘Voltage and frequency control strategies of hybrid AC/DC microgrid: a review’, IET Renew. Power Gener., 2017, 11, (2), pp. 303–313

[4] Kusakana, K.: ‘Optimal scheduled power flow for distributed photovoltaic/ wind/diesel generators with battery storage system’, IET Renew. Power  Gener., 2015, 9, (8), pp. 916–924

[5] Askarzadeh, A.: ‘Solution for sizing a PV/diesel HPGS for isolated sites’, IET Renew. Power Gener., 2017, 11, (1), pp. 143–151

 

 

 

Automatic droop control for a low voltage DC Microgrid

ABSTRACT

A DC microgrid (DC-MG) provides an effective mean to integrate various sources, energy storage units and loads at a common dc-side. The droop-based, in the context of a decentralized control, has been widely used for the control of the DC-MG. However, the conventional droop control cannot achieve both accurate current sharing and desired voltage regulation. This study proposes a new adaptive control method for DC-MG applications which satisfies both accurate current sharing and acceptable voltage regulation depending on the loading condition. At light load conditions where the output currents of the DG units are well below the maximum limits, the accuracy of the current sharing process is not an issue. As the load increases, the output currents of the DG units increase and under heavy load conditions accurate current sharing is necessary. The proposed control method increases the equivalent droop gains as the load level increases and achieves accurate current sharing. This study evaluates the performance and stability of the proposed method based on a linearised model and verifies the results by digital time-domain simulation and hardware-based experiments.

 

SOFTWARE: MATLAB/SIMULINK

 

BLOCK DIAGRAM:

Fig. 1 Simplified DC-MG with two DG units

 

EXPECTED SIMULATION RESULTS:

 

Fig. 2 Output currents of the DG units obtained in Simulation Results

a Conventional droop control method with small droop gains

b Conventional droop control method with large droop gains

c Proposed method

 

 

Fig. 3 Output voltages of the DG units obtained in Simulation Results

a Conventional droop control method with small droop gains

b Conventional droop control method with large droop gains

c Proposed method

 

CONCLUSION

This paper presents a new control scheme for DC-MG without using any communication links. In the conventional droop control, small droop gains result in good voltage regulation but inaccurate current sharing, and large droop gains result in accurate current sharing but unacceptable voltage regulation. To overcome this drawback, a new control method is proposed in which the equivalent droop gains automatically change based on the loading condition. The simulation results show and the experimental results verify that by adaptively changing the droop gains according to the load size, both accurate current sharing and desirable voltage regulation are achieved.

REFERENCES

  • Guerrero, J., Loh, P.C., Lee, T.-L., et al.: ‘Advanced control architectures for intelligent microgrids; part ii: Power quality, energy storage, and ac/dc microgrids’, IEEE Trans. Ind Electron., 2013, 60, (4), pp. 1263–1270
  • Vandoorn, T., De Kooning, J., Meersman, B., et al.: ‘Automatic power-sharing modification of p/v droop controllers in low-voltage resistive microgrids’, IEEE Trans. Power Deliv., 2012, 27, (4), pp. 2318–2325
  • Khorsandi, A., Ashourloo, M., Mokhtari, H.: ‘An adaptive droop control method for low voltage dc microgrids’. 2014 Fifth Power Electronics, Drive Systems and Technologies Conf. (PEDSTC), 2014, pp. 84–89
  • Loh, P.C., Li, D., Chai, Y.K., et al.: ‘Hybrid ac-dc microgrids with energy storages and progressive energy flow tuning’, IEEE Trans. Power Electron., 2013, 28, (4), pp. 1533–1543
  • Loh, P., Li, D., Chai, Y.K., et al.: ‘Autonomous operation of hybrid microgrid with ac and dc subgrids’, IEEE Trans. Power Electron., 2013, 28, (5), pp. 2214–2223

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.

 

Coordinated Control and Energy Management of Distributed Generation Inverters in a Microgrid

 

ABSTRACT:

This paper presents a microgrid consisting of different distributed generation (DG) units that are connected to the distribution grid. An energy-management algorithm is implemented to coordinate the operations of the different DG units in the microgrid for grid-connected and islanded operations. The proposed microgrid consists of a photovoltaic (PV) array which functions as the primary generation unit of the microgrid and a proton-exchange membrane fuel cell to supplement the variability in the power generated by the PV array. A lithium-ion storage battery is incorporated into the microgrid to mitigate peak demands during grid-connected operation and to compensate for any shortage in the generated power during islanded operation. The control design for the DG inverters employs a new model predictive control algorithm which enables faster computational time for large power systems by optimizing the steady-state and the transient control problems separately. The design concept is verified through various test scenarios to demonstrate the operational capability of the proposed microgrid, and the obtained results are discussed.

KEYWORDS:

  1. Distributed generation (DG)
  2. Energy management
  3. Microgrid
  4. Model predictive control (MPC)

 SOFTWARE: MATLAB/SIMULINK

 BLOCK DIAGRAM:

Fig. 1. Overall configuration of the proposed microgrid architecture.

EXPECTED SIMULATION RESULTS:

 

 Fig. 2. Per-phase currents drawn by loads 1, 2, and 3.

Fig. 3. Waveform of the SB current during charging.

Fig. 4. SOC of the SB during charging.

Fig. 5. Waveforms of three-phase load current (top), three-phase DG current (middle), and three-phase grid current (bottom).

Fig. 6. Waveforms of grid voltage and grid current for phase a.

Fig. 7. Real (top) and reactive (bottom) power consumed by loads.

Fig. 8. Real (top) and reactive (bottom) power delivered by the main DG unit.

Fig. 9. Real (top) and reactive (bottom) power delivered by the grid.

Fig. 10. Real (top) and reactive (bottom) power delivered by the grid.

Fig. 11. Real power delivered by SB.

Fig. 12. Real (top) and reactive (bottom) power delivered by the grid.

Fig. 13. Real power delivered by SB.

Fig. 14. Real (top) and reactive (bottom) power consumed by loads.

CONCLUSION:

In this paper, a control system that coordinates the operation of multiple DG inverters in a microgrid for grid-connected and islanded operations has been presented. The proposed controller for the DG inverters is based on a newly developed MPC algorithm which decomposes the control problem into steady-state and transient subproblems in order to reduce the overall computation time. The controller also integrates Kalman filters into the control design to extract the harmonic spectra of the load currents and to generate the necessary references for the controller. The DG inverters can compensate for load harmonic currents in a similar way as conventional compensators, such as active and passive filters, and, hence, no additional equipment is required for power-quality improvement. To realize the smart grid concept, various energy-management functions, such as peak shaving and load shedding, have also been demonstrated in the simulation studies. The results have validated that the microgrid is able to handle different operating conditions effectively during grid-connected and islanded operations, thus increasing the overall reliability and stability of the microgrid.

REFERENCES:

[1] S. Braithwait, “Behaviormanagement,” IEEE Power and EnergyMag., vol. 8, no. 3, pp. 36–45, May/Jun. 2010.

[2] N. Jenkins, J. Ekanayake, and G. Strbac, Distributed Generation. London, U.K.: IET, 2009.

[3] M. Y. Zhai, “Transmission characteristics of low-voltage distribution networks in China under the smart grids environment,” IEEE Trans. Power Del., vol. 26, no. 1, pp. 173–180, Jan. 2011.

[4] G. C. Heffner, C. A. Goldman, and M. M. Moezzi, “Innovative approaches to verifying demand response of water heater load control,” IEEE Trans. Power Del., vol. 21, no. 1, pp. 1538–1551, Jan. 2006.

[5] R. Lasseter, J. Eto, B. Schenkman, J. Stevens, H. Vollkommer, D. Klapp, E. Linton, H. Hurtado, and J. Roy, “Certs microgrid laboratory test bed, and smart loads,” IEEE Trans. Power Del., vol. 26, no. 1, pp. 325–332, Jan. 2011.

Dynamic Modeling of Microgrid for Grid Connected and Intentional Islanding Operation

 

 ABSTRACT:

 Microgrid is defined as the cluster of multiple distributed generators (DGs) such as renewable energy sources that supply electrical energy. The connection of microgrid is in parallel with the main grid. When microgrid is isolated from remainder of the utility system, it is said to be in intentional islanding mode. In this mode, DG inverter system operates in voltage control mode to provide constant voltage to the local load. During grid connected mode, the Microgrid operates  in constant current control mode to supply preset power to the main grid. The main contribution of this paper is summarized as

  • Design of a network based control scheme for inverter based sources, which provides proper current control during grid connected mode and voltage control during islanding
  • Development of an algorithm for intentional islanding detection and synchronization controller required during grid
  • Dynamic modeling and simulation are conducted to show system behavior under proposed method using

From the simulation results using Simulink dynamic models, it can be shown that these controllers provide the microgrid with a deterministic and reliable connection to the grid.

 KEYWORDS:

  1. Distributed generation (DG)
  2. grid connected operation
  3. intentional islanding operation and islanding detection
  4. Microgrid

SOFTWARE: MATALAB/SIMULINK

BLOCK DIAGRAM:

Fig.1. Dynamic model of microgrid with controller.

EXPECTED SIMULATION RESULTS:

Fig. 2. Line Current without current controller

Fig.3. Line Voltage without Voltage controller

Fig. 4. Line Voltage with voltage controller

Fig. 5. Phase voltage waveform (a) without re-closure controller (b) with re-closure controller

Fig. 6. Synchronization for grid reconnection (a) without re-closure algorithm (b) with re-closure algorithm

CONCLUSION:

Current and voltage Control techniques have been developed for grid connected and intentional islanding modes of operation using PI controllers. An intentional islanding detection algorithm responsible for switching between current control and voltage control is developed using logical operations and proved to be effective. The reconnection algorithm coupled with the synchronization controller enabled the DG to synchronize itself with the grid during grid reconnection. The performance of the microgrid with the proposed controllers and algorithms  has been analyzed by conducting simulation on dynamic model using SIMULINK. The simulation results presented here confirms the effectiveness of the control scheme.

REFERENCES:

[1] L. Shi, M.Y. Lin Chew. “A review on sustainable design of renewable energy systems,” science direct journal present in Renewable and Sustainable Energy Reviews, Vol. 16, Issue 1, 2012, pp. 192–207.

[2] Q. Lei, Fang Zheng Peng, Shuitao Yang. “Multi loop control method for high performance microgrid inverter through load voltage and current decoupling with only output voltage feedback,” IEEE Trans. power. Electron, vol. 26, no. 3, 2011, pp. 953–960.

[3] J. Selvaraj and N. A. Rahim, “Multilevel inverter for grid-connected PV system employing digital PI controller,” IEEE Trans. Ind. Electron., vol. 56, no. 1, 2009, pp. 149–158.

[4] I. J. Balaguer, Fang Zheng Peng, Shuitao Yang, Uthane Supatti Qin Lei. “Control for grid connected and intentional islanding modes of operations of distributed power generation,” IEEE Trans. Ind. Electron., vol. 56, no. 3, 2009, pp. 726–736.

[5] R. J. Azevedo, G.I. Candela, R. Teodorescu, P.Rodriguez , I.E-Otadui “Microgrid connection management based on an intelligent connection agent,” 36th annual conference on IEEE industrial electronics society, 2010, pp. 3028–3033.

Deadbeat Weighted Average Current Control with Corrective Feed-forward Compensation for Microgrid Converters with Non-Standard LCL Filter

ABSTRACT

Microgrid converters are required to have the capability of both grid-tied mode and islanding mode operation. For this dual-mode operation, large shunt capacitors are often used in the interfacing converter output LCL filter, as it can help to stabilize supply voltage and to reduce switching ripple pollutions to sensitive loads during autonomous islanding operation. At the same time, this modification causes a few challenges, including the low frequency harmonic distortions, the steady-state tracking errors and the slow dynamic response, to the line current regulation during grid-tied operation. To overcome these drawbacks, a modified weighted average current controller is developed. First, to realize a fast line current response, a deadbeat control of weighted average current is developed based on a reduced-order virtual filter plant. Second, a grid voltage feed-forward term is added to the weighted average current reference to mitigate the steady-state line current tracking errors. Note that this compensation term is directly added to the current reference, thus, it is very well decoupled from the closed-loop current regulator. In addition, it can be seen that the low-order line current harmonics caused by grid voltage distortion is inherently compensated by this proposed corrective feed-forward control.

KEYWORDS:

  1. Virtual filter
  2. Deadbeat control
  3. Weighted average current control
  4. Active damping
  5. LCL filter
  6. Microgrid

SOFTWARE: MATLAB/SIMULINK

CIRCUIT DIAGRAMS:

Fig. 1. Diagram of a grid-tied converter controlled by conventional weighted average current feedback.

Fig. 2. Diagram of the proposed control deadbeat scheme with weighted average current feedback and line current tracking error compensation.

EXPECTED SIMULATION RESULTS:

Fig.3. Performance of the system using the proposed deadbeat control method (compensation term is activated in 0.5sec). (from top to bottom: (1) grid voltage Vgrid; (2) line current I2 ; (3) output current I1 ; (4) current tracking errors ( Iref-I2).)

Fig. 4. Performance of the system using the proposed deadbeat control method and the method in [14]. (from top to bottom: (1) grid voltageVgrid ; (2) line current I2; (3) output current I1 ; (4) current tracking errors ( ).)

Fig. 5. Performance of the system using the proposed method, operating in a distorted grid with grid impedance variation

Fig. 6. Performance of the system using the proposed deadbeat control method with feed-forward control. Grid frequency changes from 50Hz to 50.15Hz at 0.2sec. (from top to bottom: (1) Grid voltage Vgrid; (2) line current I2 ; (3) output current I1; (4) weighted average current I12 .)

Fig. 7. Performance of the system using the proposed deadbeat control method but without feed-forward control. Grid frequency changes from 50Hz to 50.15Hz at 0.2sec. (from top to bottom: (1) Grid voltage Vgrid ; (2) line current I2; (3) output current I1; (4) weighted average current I12 .)

Fig. 8. Performance of the system using the PI control for weighted average current regulation, with feed-forward control. Grid frequency changes from 50Hz to 50.15Hz at 0.2sec. (from top to bottom: (1) Grid voltage Vgrid ; (2) line current I2; (3) output current I1; (4) weighted average current I12.)

CONCLUSION

An enhanced current controller is proposed in this paper. The research work of this paper is summarized here as:

1) In order to realize rapid control of converter current, the deadbeat control is applied to regulate the weighted average current based on a virtual filter plant.

2) The feed-forward compensator is developed to mitigate the steady-state fundamental current tracking errors caused by conventional weighted average current control.

3) The frequency-selective capacitor leg current estimation is proposed and the corresponding compensation term can be used to increase the robustness of the converter against grid harmonic distortions. The design and implementation of this compensator are highly decoupled from the closed-loop deadbeat current regulator. Thus, both the current regulator and the compensator can be independently designed.

REFERENCES

  • Blaabjerg, Z. Chen, and S. B. Kjaer, ―Power electronics as efficient interface in dispersed power generation systems,‖ IEEE Trans. Power Electron., vol. 19, no. 5, pp. 1184-1194, May. 2004.
  • Rocabert, A. Luna, F. Blaabjerg, and P. Rodriguez, ―Control of power converters in AC microgrids,‖ IEEE Trans. Power Electron., vol. 27, no. 11, pp. 4734–4749, Nov. 2012.
  • W. Li, D. M. Vilathgamuwa and P. C. Loh, ―Design, analysis and real-time testing of a controller for multibus microgrid system,‖ IEEE Trans. Power Electron., vol. 19, pp. 1195-1204, Sep. 2004.
  • M. Guerrero, L. G. Vicuna, J. Matas, M. Castilla, and J. Miret, ―A wireless controller to enhance dynamic performance of parallel inverters in distributed generation systems,‖ IEEE Trans. Power Electron., vol. 19, no. 4, pp. 1205-1213, Sep, 2004.

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.

Chen, X., Wang, Y.H., and Wang, Y.C. (2013). A novel seamless transferring control method for microgrid based on master-slave configuration. IEEE Conf., ECCE Asia, pp. 351-357.

Cho, C. H., Jeon, J.H., Kim, J.Y., Kwon, S., Park, K., and Kim, S. (2011). Active synchronizing control a microgrid. IEEE Trans., Power Electron., vol. 26, no. 12, pp. 3707-3719

Choi, J.W. and Sul, S.K. (1998). Fast current controller in three-phase AC/DC boost converter using d-q axis crosscoupling. IEEE Trans., Power Electron., vol.13, no.1, pp. 179-185.

A New Control Strategy for a Multi-Bus MV Microgrid Under Unbalanced Conditions

 

ABSTRACT:

This paper proposes a new control strategy for the islanded operation of a multi-bus medium voltage (MV) microgrid. The microgrid consists of several dispatchable electronically-coupled  distributed generation (DG) units. Each DG unit supplies a local load which can be unbalanced due to the inclusion of singlephase  loads. The proposed control strategy of each DG comprises a proportional resonance (PR) controller with an adjustable resonance frequency, a droop control strategy, and a negative-sequence impedance controller (NSIC). The PR and droop controllers are, respectively, used to regulate the load voltage and share the average power components among the DG units. The NSIC is used to effectively compensate the negative-sequence currents of the unbalanced loads and to improve the performance of the overall microgrid system.Moreover, the NSIC minimizes the negative-sequence currents in the MV lines and thus, improving the power quality of the microgrid. The performance of the proposed control strategy is verified by using digital time-domain simulation studies in the PSCAD/EMTDC software environment.

KEYWORDS:

  1. Distributed generation
  2. Medium voltage (MV)
  3. Microgrid
  4. Negative-sequence current
  5. Power sharing
  6. Unbalance load
  7. Voltage control

SOFTWARE: MATLAB/SIMULINK

CIRCUIT DIAGRAM:

 image001

 Fig. 1. MV multi-bus microgrid consisting of two DG units.

EXPECTED SIMULATION RESULTS:

image002

Fig. 2 Unbalanced load changes in feeder F1 (a) instantaneous real, and (b)

reactive power components.

image003

Fig. 3. Amplitude of (a) positive- and (b) negative-sequence currents of the feeders.

image004

Fig. 4. Instantaneous voltages at DG terminals during unbalanced load changes in feeder F1, (a) DG1and (b) DG2 .

image005

Fig.5. Frequency of islanded microgrid during unbalanced load changes.

image006

Fig. 6. (a) Negative-sequence output impedance of each DG, and (b) amplitude of negative-sequence current of DG units.

image007

Fig. 7. Dynamic response of DG units to unbalanced load changes in feeder F1: (a) real power, and (b) reactive power components of DG units.

image008

Fig. 8. Unbalanced load changes in feeders F3 and F2 (a, b) instantaneous real and reactive power of feeders.

image009

Fig. 9. Amplitude of (a) positive and (b) negative-sequence currents of the feeders.

image010

Fig. 10. (a) Negative-sequence output impedance, and (b) amplitude of negative- sequence current for each DG.

CONCLUSION:

This paper presents a new control strategy for amulti-bus MV microgrid consisting of the dispatchable electronically-coupled DG units and unbalanced loads. The negative-sequence current of a local load is completely compensated by its dedicated DG. However, the negative-sequence current of the nonlocal loads is shared among the adjacent DGs. The proposed control strategy is composed of a PR controller with non-fixed resonance frequency, a droop control, and a negative-sequence impedance controller (NSIC). The PR and droop controllers are, respectively, used to regulate the load voltage and to share the average power among the DG units. The NSIC is used to improve the performance of the microgrid system when the unbalanced loads are present. Moreover, the NSIC minimizes the negative- sequence currents in the MV lines, and thus, improving the power quality of the microgrid. The performance of the proposed control strategy is investigated by using digital time-domain simulation studies in the PSCAD/EMTDC software environment. The simulation results conclude that the proposed strategy:

  • robustly regulates voltage and frequency of the microgrid;
  • is able to share the average power among the DGs;
  • effectively compensates the negative-sequence currents of local loads; and
  • shares the negative-sequence current of the nonlocal loads such that the power quality of the overall microgrid is not degraded.

 REFERENCES:

[1] N. Hatziargyriou, H. Asano, R. Iravani, and C. Marnay, “Microgrids,” IEEE Power Energy Mag., vol. 5, pp. 78–94, Jul.–Aug. 2007.

[2] A. G. Madureira and J. A. P. Lopes, “Coordinated voltage support in distribution networks with distributed generation and microgrids,” IET Renew. Power Gener., vol. 3, pp. 439–454, Sep. 2009.

[3] IEEE Recommended Practice for Monitoring Electric Power Quality, IEEE Std. 1159, 2009.

[4] IEEE Recommended Practice for Electric Power Distribution for Industrial Plants, ANSI/IEEE Std. 141, 1993.

[5] R. Lasseter, “Microgrids,” in Proc. IEEE Power Eng. Soc. Winter Meeting, 2002, pp. 305–308.