- Email: [email protected]
Parallel operation of converter interfaced multiple microgrids
Electrical Power and Energy Systems 55 (2014) 486–496
Contents lists available at ScienceDirect
Electrical Power and Energy Systems journal homepage: www.elsevier.com/locate/ijepes
Parallel operation of converter interfaced multiple microgrids Ritwik Majumder ⇑, Gargi Bag ABB Corporate Research Center, Forskargrand 7, Vasteras, Sweden
a r t i c l e
i n f o
Article history: Received 21 May 2012 Received in revised form 10 September 2013 Accepted 24 September 2013
Keywords: Microgrids Back to back converters Stability Communication
a b s t r a c t This paper proposes methods to control utility connected multiple microgrids. Microgrids with renewable energy sources and autonomous operations do not have high reliability while the smart grid vision demands a highly reliable and efficient grid. Thus the connections of the microgrids to the main grid have to be smart itself. A back to back (B2B) converter connection can provide a reliable interface and also can provide isolation between utility and microgrids. However, with multiple microgrids connected through B2B converter connections can lead to system instability. In this paper, a method to coordinate the B2B connections without losing the possibility of autonomous operation of the microgrids is proposed. The system stability is improved first with a decentralized control of the B2B converters. Then with smart grid scenarios in mind, an application of communication is proposed and simulated. The proposed control strategy demonstrates stable system operation with multiple microgrids connected to utility through B2B converters. The mathematical model of the system with analysis and closed loop simulation of power network and communication network are presented to validate the claim. Ó 2013 Elsevier Ltd. All rights reserved.
1. Introduction Microgrid can generally be viewed as a cluster of distributed generators connected to the main utility grid [1], usually through Voltage Source Converter (VSC) based interfaces. The power management in a microgrid is mainly based on voltage-droop characteristic, voltage regulation, and load reactive power compensation [2]. The real and reactive power sharing can be achieved by controlling two independent quantities – the power angle, and the fundamental voltage magnitude [2–4]. The system stability during load sharing has been explored by many researchers [3,5,6]. Transient stability of power system with high penetration level of power electronics interfaced (converter connected) distributed generation is explored in [3]. While [6] explores the microgrid testing, [7] define converter control strategy for microgrid operation. In [8], a study for a Smart Energy Management System (SEMS) to optimize the operation of the microgrid is presented. The SEMS consists of power forecasting module, Energy Storage System (ESS) management module and optimization module. A knowledge-based expert system is proposed for the scheduling of an energy storage system installed in a power system [9]. Different converter and storage controls for microgrid operation are discussed in [10–14]. While a virtual synchronous generator aspect is addressed in [10], the converter control for DC/DC operation is investigated in [14]. An economic sizing of storage for microgrid is proposed in [11] and storage control for frequency ⇑ Corresponding author. Tel.: +46 738 150002. E-mail address: [email protected] (R. Majumder). 0142-0615/$ - see front matter Ó 2013 Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.ijepes.2013.09.008
support, primary reserve and peak shaving is discussed in [12,13]. The proposed method is successfully tested to two actual isolated microgrid different sizes and with different generation pattern. As the microsources are not reliable source of power and so a microgrid operates both in autonomous or grid connected mode to balance the demand supply. In general, a microgrid is interfaced to the main power system by a fast semiconductor switch called the Static Switch (SS). However, in a smart grid scenario, it is not advisable to connect a highly reliable and efficient utility to microgrids in an uncontrolled way. For a better power management, it is important to achieve control over the power flow. A voltage and frequency isolation between the grid and the microgrid will always ensure a safe operation and a B2B converter can provide both the power flow control and isolation. Smart utility grid has been proposed to upgrade the present grid structure through integration of information technology, communication network, automatic control and distributed intelligent devices [15]. It is understood that the vision for a more secure, more robust electrical grid can only be achieved by better communication. In [16], it is examined how this information can be utilized more effectively for real-time operation as well as for subsequent decision making. A new methodology for coordinated voltage support in distribution networks with large integration of distributed generation and microgrids is proposed in [17]. Given the characteristics of the Low Voltage (LV) networks, it is shown that traditional control strategies using only reactive power control may not be sufficient in order to perform efficient voltage control. A stage by stage
R. Majumder, G. Bag / Electrical Power and Energy Systems 55 (2014) 486–496
487
development for network power flow with DG (Distributed Generators) output control is described in [18]. A hybrid power system component with communication ports allowing communication with a supervisory controller and a communication network between each component is considered in [19], to prepare a foundation for further development in the intelligent adaptable supervisory controller. The tests were conducted that confirm the capability of this concept to use in hybrid power system. It is very important to control the power flow between the grid and microgrid and maintain voltage isolation between the two systems. The need of power quality improvement while achieving economic optima in a distributed generation is addressed in [20]. A new concept related to the revitalized microgrid concept and the vision of the smart grid is presented in [21]. In this paper, the connection and coordinated control of multiple microgrids to utility grid is proposed. 1.1. Purpose Aim of this paper is to propose a method for connecting the existing microgrids to utility with B2B converter connections. System stability with multiple B2B connections is investigated with mathematical model and time domain simulations. A coordinated control method for the B2B connections is proposed to improve the system stability. First a decentralized control method is proposed. Then an application of communication is simulated. The closed loop simulations of power network and communication show improvement in system stability and maintain the high reliability of the grid connected with multiple microgrids. 1.2. Organizations Section 2 describes the system structure and operation scenarios. The proposed control techniques are given in Section 3. Simulation results are presented in Section 4.
Fig. 2. Back-to-back connections.
corresponding signal input BLK1 and BLK2. DG-1 and DG-2 are connected through VSC to the microgrid. Although the proposed control is demonstrated with first two and then four microgrids, it can be applied to any number of microgrids connected to the utility as shown in Fig. 1. The control schemes are described in the next sections.
2. System structure and operation 3. Control and reference generation A simple power system model with B2B converters, connected to multiple microgrids is shown in Fig. 1. Each of the microgrids has their own micro-sources and loads. The utility loads and line impedances (z) are also incorporated as the connection of the B2Bs are not very close to each other. A simple microgrid with two sources and one load connected through the B2B connection is shown in Fig. 2. The B2B converters (VSC-1 and VSC-2) are supplied by a common DC bus capacitor with voltage of VC. The converters can be blocked with their
In this section the control scheme and reference generation for the VSCs are described. The control can work in two different modes. In mode one, with low power demand and contractual scenario with utility, the utility can supply a fixed amount of power to the microgrid while the microgrid DGs shares the rest of the power demand through droop control. In mode two, with a high load demand, the microgrids DGs supply their maximum power and the utility provides the deficit power through B2B to the microgrid.
Fig. 1. The microgrids and utility system.
488
R. Majumder, G. Bag / Electrical Power and Energy Systems 55 (2014) 486–496
It is assumed that, in case of a very high power demand in the microgrid, loads are switched out. In either case control of VSC-1 (Fig. 2) is same and described first with the proposed control methods. The control of VSC-2 and the DGs are described subsequently. 3.1. VSC-1 reference generation and proposed capacitor voltage control Both the VSCs of B2B are supplied from a common capacitor of voltage VC as shown in Fig. 2. First the fixed capacitor voltage control VSC-1 is described and then the proposed controls are shown. 3.1.1. Control-1: Fixed capacitor voltage reference In this case reference angle for VSC-1 is generated as shown in Fig. 3a. First the measured capacitor voltage VC is passed through a low pass filter to obtain VCav. This is then compared with the reference capacitor voltage VCref. The error is fed to a Proportional Integral (PI) controller to generate the reference angle dref. VSC-1 reference voltage magnitude is kept constant, while angle is the output of the PI controller. The instantaneous voltages of the three phases are then derived from the references. This controller works well with a microgrid connected to the utility, however with multiple microgrids connected as shown in Fig. 1, it can lead to system instability (shown in simulation section) due to low system damping. This low system damping arises from the connection of the parallel B2B converters. The B2B provides the much needed isolation between the utility and microgrid for superior control but has some disadvantages. The inherent system damping due to utility line resistance is lost at the microgrid side due to B2B connection. The output voltage angle control of the second VSC (VSC-2) through droop also create system stability problem similar to parallel operation of converters. Moreover, the fixed value control of capacitor voltage from utility side converter leads to large power circulation in the utility side line during a small disturbance (as the DC capacitor voltage is used for output voltage angle calculation of the converter).
3.1.1.1. Mathematical model and eigen value analysis. A mathematical model of the B2B converter is developed as shown in Appendix A. A system with four B2B connections (Fig. 1) is considered for the analysis. The effect of DC voltage controller gains (VSC-1) and droop gains (VSC-2) are shown in Fig. 4 at nominal operating point with different number of B2B connections. Fig. 4 shows the eigen value trajectory of the dominant modes with change in power controller gain with two, three or four parallel B2B connections. It can be seen that increased number of connections lead the system to instability for the same value of the feedback gains. A selection of lower value of controller gain would result in an inferior DC voltage dynamics (VSC-1) and slower droop characteristic (VSC-2). In this paper control methods are proposed to improve the system stability with acceptable feedback gains. 3.1.2. Control-2: Drooping capacitor voltage reference As the DC capacitor supplies VSC-1 and VSC-2, regulating the capacitor voltage will result in improving dynamic response of the B2B converters. The reference capacitor voltage is then drooped from the rated value based on the power flow from utility to microgrid. The control scheme is shown in Fig. 3b. However, this controller fails to ensure a stable system condition with two close B2B connections and /or reverse power flow (from microgrid to utility) in some of the B2B connections. 3.1.3. Control-3: Improving damping with voltage angle measurement The system damping can be further improved by adding a secondary loop based on the measured voltage angle difference as shown in Fig. 3c. The measured angle is passed through a low pass filter and the output is used to rectify the angle reference as shown in Fig. 3c. However the angle information can be derived from the real and reactive power flow which is discussed in the next section. 3.1.4. Control-4: Improving damping with communication It can be seen in controller 3 that, modulating the angle would result in a much better system damping. However we need the
Fig. 3. Angle controller.
R. Majumder, G. Bag / Electrical Power and Energy Systems 55 (2014) 486–496
489
Fig. 4. Eigen value trajectory with parallel back to back connections.
angle information referred to a common frame. Hence it would be effective if we can use controller-2 (Fig. 3b) but modulate the Vcrated based on the common angle information. The angle information can be derived from the real and reactive power flow in the lines. To derive the angle information from the real and reactive power flow, let us consider the system shown in Fig. 1. It is assumed that four microgrids with their own DGs and loads are connected through B2B and loads. The utility loads are representing the main outgoing feeders. If the line impedance Zi has resistance Ri and reactance Xi. The power flow equations over the line for small angle differences can be written as
d11 d22 ¼ R11 Q M1R þ X 11 PM1R R22 Q M2L þ X 22 PM2L
ð1Þ
where R11 = R1/(V11V), R22 = R2/(V22V), X11 = X1/(V11V) and X22 = X2/(V22V). Similarly, the Point of Common Coupling (PCC) voltage angle of B2B3 and B2B4 can also be represented with respect to d22 as,
d33 d22 ¼ R22 Q M2R þ X 22 PM2R R33 Q M3L þ X 33 PM3L d44 d22 ¼ R33 Q M3R þ X 33 PM3R R44 Q M4L þ X 44 PM4L The output voltage angle with respect to a common reference is derived from the power flow and then used to control the capacitor voltage as
V Cref ¼ V cr KP:PG K FL ðddiff Þ The reference voltages of the B2Bs are then derived as,
V Cref 1 ¼ V cr1 KP1:P G1 K FL1 :ðd11 d22 Þ
ð2Þ
V Cref 2 ¼ V cr2 KP2:PG2 K FL2 :ðd22 Þ
ð3Þ
V Cref 3 ¼ V cr3 KP3:PG3 K FL3 :ðd33 d22 Þ
ð4Þ
V Cref 4 ¼ V cr4 KP4:PG4 K FL4 :ðd44 d22 Þ
ð5Þ
The controller is shown in Fig. 3d. The primary loop is shown with PG while the secondary control based on (2) is shown as VCpq . It is to be noted that in (1) the power flow data from one point of the network need to be communicated to other part. In smart grid scenarios, communication of these power flow data can be implemented. Here a switched Ethernet network is considered. It is to be noted that in (2)–(5), the first primary control loops based on local power measurements PGi , and will ensure system stability in most of the cases. The microgrids operations do not need any frequent change of capacitor voltages and hence a low bandwidth communication would be sufficient. As evident from Eqs. (2)–(5)(where the reference voltages of the B2B converter capacitor are generated) the first term is a constant and the second term is derived from the local power measurement. The communication is needed for the last part. Hence the impacts of communication delay or errors are only in part of the reference generation. However a limiter is placed to limit the communicated measurement in case of communication error. In general, the B2B control performance is not sensitive to communication delay in most of the scenarios. However, in multiple parallel operations with continuous change in power requirement and power flow direction, a large delay can fail to meet the control requirement. In that case, the particular B2B can be switched to fixed power supply mode, to improve the system stability.
490
R. Majumder, G. Bag / Electrical Power and Energy Systems 55 (2014) 486–496
During fault, both the converters of the B2Bs are blocked by their protection functions and the capacitor voltages are held. During fault, the secondary control loop (with angle) is also bypassed. The communication network is shown in Fig. 5. The communication network is simulated in MATLAB–SIMULINK based communication network simulator TrueTime as switched Ethernet network [22]. The detail parameters are given in Table 1.
In case of high power demand, the DGs supply their maximum available power while utility needs to supply any deficit in the power requirement through B2B converters. Let the maximum rating of the B2B converters are given by PTmax, QTmax. Then the voltage magnitude and angle reference of VSC-2 is generated as
3.2. VSC-2 reference generations
where VTmax and dTmax are the voltage magnitude and angle, respectively, when VSC-2 supplies the maximum load.
VSC-2 of Fig. 2 is connected with PCC through an output inductance LG and controls the real and reactive power flow between the utility and the microgrid. As mentioned before the B2B can supply a fixed amount power to the microgrid or the power deficit. Let us assume that in fixed power supply mode the references for the real and reactive power be PTref and QTref respectively and the VSC-2 output voltage be denoted by VT\dT and the PCC voltage by VP\dP. Then the reference VSC-2 voltage magnitude and its can be calculated as
VT ¼
V 2P þ Q Tref X G V P cosðdT dP Þ
dT ¼ tan1
PTref X G V 2P þ Q Tref X G
ð6Þ ! þ dP
ð7Þ
dT ¼ dTmax mT ðPT PTmax Þ V T ¼ V Tmax nT ðQ T Q Tmax Þ
ð8Þ
3.3. Reference generation for DG sources In this section, the reference generation for the DGs is presented. It is to be noted that in this paper the DGs are assumed as constant DC sources and the converters are controlled as VSC. The DG could be a fuel cell or Photovoltaic, and DC chopper maintains the output DC voltage of the DG as [23]. The DG interfacing converter can run in two different modes as stated in [24]. One mode is PQ converter control where the converter is used to supply a given active and reactive power set-point. The other mode is VSC control where the converter is controlled to ‘‘feed’’ the load with pre-defined values for voltage and frequency. In this paper, the interfacing converters are controlled as VSCs. The voltage and frequency are then controlled with the load frequency control based on the real and reactive power output. The control strategy for both the DGs is the same and hence only DG-1 reference generation is discussed here. It is assumed that when the utility supplies a part of load demand in microgrid by a fixed amount power through the B2B converters, rest of the power demand in the microgrid is supplied and regulated by the DGs. The output voltages of the converters are controlled to share this load proportional to the rating of the DGs. The power requirement can be distributed among the DGs, similar to a conventional droop by dropping the voltage magnitude and angle as
d1 ¼ d1rated m1 ðP1 P1rated Þ V 1 ¼ V 1rated n1 ðQ 1 Q 1rated Þ
ð9Þ
where V1rated and d1rated are the rated voltage magnitude and angle respectively of DG-1, when it is supplying the load to its rated power levels of P1rated and Q1rated. The coefficients m1 and n1 respectively indicate the voltage angle drop vis-à-vis the real power output and the magnitude drop vis-à-vis the reactive power output. These values are chosen to meet the voltage regulation requirement in the microgrid. In high loading condition, the DGs supply their maximum available power and the utility supplies the deficit power. Let us denote the available active power as P1avail. Then based on this and the current rating of the DG the reactive power availability Q1avail of the DG can be determined. Based on these quantities, the voltage references is calculated as
Fig. 5. Communication network structure.
V1 ¼
V 2P1 þ Q 1av ail X 1 V P1 cosðdP1 dP Þ 1
d1 ¼ tan
Table 1 Communication network. Wired
Ethernet
Network type Data rate Minimum frame size Total switch memory Switch overflow behavior
Switched Ethernet 1,000,000 bits/s 512 80,000 Retransmit
P1av ail X 1 V 2P1 þ Q 1av ail X 1
ð10Þ ! þ dP1
ð11Þ
The references for the other DGs are generated in a similar way. It is to be noted that there could be non-linear and unbalanced loads. The reference for the DGs then needs to be compensating [25]. In [26], design aspects of various passive components and switching dynamics of a voltage source inverter (VSI) for compensating unbalanced and nonlinear load are presented. A novel
491
R. Majumder, G. Bag / Electrical Power and Energy Systems 55 (2014) 486–496
method is proposed for VSI to track desired reference currents smoothly. In case of a DSTATCOM (Distributed Static Compensator), any change in the load affects the dc-link voltage directly [27]. A novel fast-acting dc-link voltage controller based on the energy of a dc-link capacitor is proposed. For a microgrid connection through B2B connection, we need to modulate the DC capacitor reference voltage to improve the system damping. This has been the main focus of the proposed controllers and the performances of the controllers are described in next subsections. It must be noted that parallel operation of converter interfaced sources has many challenges [25,28–30]. Different control techniques and synchronization method is proposed by many authors [25,28–30]. However the proposed method in this paper of B2B converter interfaced multiple microgrids is not directly related to the number of microgrid microsources and can be extended to more number of microgrid connection or DGs. The main reason of taking a small test microgrid (Fig. 2) is the limitation of the computer and software capability. With the each B2B converter also has two VSC converters, for multiple microgrid case microsource number in each microgrid is limited. A real microgrid will have many more microsources and the proposed method can be applied to such system as the main controllability issues are at the microgrid PCC with voltage, frequency and power exchange. The generalized concept and control result of multiple converter sources microgrid with B2B converter interfaced is shown in [31]. In this paper the control approach for parallel back to back connections is proposed.
Table 2 System and controller parameters. System Quantities
Values
Systems frequency Source voltage (Vs) Feeder impedance
50 Hz 11 kV rms (L–L) Rs = 3.025 X, Ls = 57.75 mH
Load Impedance (Balanced) or Induction motor
RL = 100.0 X, LL = 300.0 mH Rated 40 hp, 11 kV rms (L–L)
DGs and VSCs DC voltage (Vdc1, Vdc2) Transformer rating VSC losses (Rf) Filter capacitance (Cf) Inductances (L1, L2) Inductances (LG) Hysteresis constant (h)
3.5 kV 3 kV/11 kV, 0.5 MVA, 2.5% reactance (Lf) 1.5 X 50 lF 20 mH and 16.0 mH 28.86 mH 105
Angle controller Proportional gain (Kp) Integral gain (KI)
0.2 5.0
Droop coefficients Power-angle m1 m2 Voltage-Q n1 n2
0.3 rad/MW 0.24 rad/MW 0.15 kV/MVAr 0.12 KV/MVAr
4. Simulation studies Simulation studies are carried out in PSCAD/EMTDC (version 4.2) with converter model for all the cases except case 4. In case 4, the power network and communication network are simulated in closed loop in MATLAB SIMULINK. The power network is modeled in SimPower, with VSC bridges while the communication network is modeled in TrueTime. The close loop simulation structure is shown in Fig. 6. Different configurations of load and its sharing are considered. The DGs are considered as inertia-less dc source supplied through a VSC. The system data are given in Table 2. 4.1. Case 1: Control 1-fixed capacitor voltage First it is assumed that only one B2B is connected to the utility shown in Fig. 1. It is desired that B2B-1 supplies 50% of the load power requirement in microgrid-1 and rest of the power requirement is supplied by the DGs. With the system running in steady state, the load power demand is changed from 1 MW to 0.525 MW at 0.1 s. The system response is shown in Fig. 7a. It can be seen that B2B continues to supply 50% of the load power demand. Rest of the power requirement is shared by the
Fig. 7. Power output of back-to-back converters.
DG proportional to their ratings. At 0.35 s system is revert back to initial condition and DGs, B2B power go back to initial condition. This validates individual B2B operation. To investigate the parallel operation of the B2Bs, B2B-1 and B2B-2 are then connected to each other at 0.1 s (an utility breaker between the two microgrids is used). The power flows through the B2Bs are shown in Fig. 7b. It can be seen that system oscillation increases and the system becomes unstable. The DC capacitor voltage is shown in Fig. 8a. The PCC voltage, DG output power and DG output current is also shown in Fig. 8. The DG output power starts oscillating and also PCC voltage. Then the system becomes unstable. 4.2. Case 2: Control 2-drooping capacitor voltage
Fig. 6. Close loop simulating of power and communication network.
To improve the system damping, the DC capacitor reference voltage is drooped with the power flow through B2B as shown in Fig. 3b. While both microgrids connected in parallel and utility is supplying, system is operated as case 1. Fig. 9 shows the system response. The stable DC capacitor voltage is shown in Fig. 9a. The
492
R. Majumder, G. Bag / Electrical Power and Energy Systems 55 (2014) 486–496
Fig. 8. System instability.
Fig. 9. Capacitor voltage and DG output.
PCC voltage is also stable and the DG output powers share the load as desired (case 1). DG output current shown in Fig. 9 also ensures a stable system operation. To further verify the controller ability and system stability, the power flow through the B2B 2 is reversed and microgrid-2 start supplying power to the utility at 0.1 s. The system response is shown in Fig. 10. The DC capacitor voltage and angle controller output are also shown in Fig. 10. The voltage and angle oscillations lead the system to instability. Thus only drooping the DC capacitor voltage is not sufficient to ensure stable system operation.
4.3. Case 3: Control 3-voltage angle measurement To further improve the system stability, the PCC voltage angle difference is measured and passed through a low pass filter as shown in Fig. 3c. The system is simulated with this controller in same operating condition as in previous case. Fig. 11 shows the power flow through the B2Bs and it can be seen that a stable system operation is achieved. The B2B supplies (absorb) power to (from) microgrids as desired. The DC capacitor voltage and angle controller output are shown in Fig. 11b and c. A stable system
Fig. 10. Power flow through back-to-back converters and angle controller output: Unstable Case.
condition is apparent. Thus including the voltage angle information improves the system stability.
R. Majumder, G. Bag / Electrical Power and Energy Systems 55 (2014) 486–496
493
4.4. Case 4: Control 4-with communication
Fig. 11. Power flow through back-to-back converters and angle controller output: Stable Case.
Fig. 12. Power flow through the B2Bs and PCC voltage.
In the next section the angle information for a multiple microgrid scenario is derived from the real and reactive power flow in the network. Communication is used to carry the power flow measurement from one part of the network to the B2Bs.
In this case, system shown in Fig. 1, with four microgrid connected through B2B connections are considered. The aim is to improve the system stability by modulating the DC capacitor voltage based on the power flow through the B2B and PCC voltage angle. To calculate the angle with same reference, real and reactive power flow in the network is used as (2)–(5). The communication network shown in Fig. 5 is used in this case. This is a TrueTime communication network, which has four send and four receive ports. The measured data are fed to send port and received at the receive port as shown in Fig. 5. The data communications are controlled through the trigger signal. When a node tries to transmit a message, a triggering signal is sent to the network block on the corresponding input channel. At the end of the simulated transmission (in communication network) of the message is finished, the network block sends a new triggering signal on the output channel corresponding to the receiving port. The transmitted message is put in a buffer at the receiving port. A message contains information about the sending and the receiving computer port, measurement signals or control signals, the length of the message, and optional real-time attributes such as a priority or a deadline. In this case, the power flow data at PCC of the B2B converters are communicated to other B2B connections to calculate the converter output voltage angle difference as in (1)–(5). The network parameters are given in Table 1. It is assumed that utility is connected to microgrids 1, 2 and 3 through the B2Bs and supply power. Microgrid 4 is connected to the grid at 0.5 s. The system response (power flows through the B2Bs) is shown in Fig. 12a. PCC voltage and current through the B2B-4 are shown in Fig. 12b and c. It can be seen a stable PCC voltage is maintained and the current becomes balanced within 2–3 cycles. The power flow of the utility network is communicated through the communication network as shown in Fig. 5. The network has four send ports and four receive ports. The scheduling of the network is shown in Fig. 13a. The power flow in the network, as shown in Fig. 5, is measured and communicated. Fig. 13b and c show the measured power and the power data received through the network. It can be seen that they are close and moreover, the proposed control has the primary term based on local power measurement ((2)–(5)). The control will work even with a much slower sampling of this secondary term. The data rate could be chosen based on communication infrastructure available.
Fig. 13. Network schedule and communicated power signals.
494
R. Majumder, G. Bag / Electrical Power and Energy Systems 55 (2014) 486–496
Fig. 14. Change inflow in B2B4 with different communication bandwidth.
In this paper, the coordination of B2B connections of multiple microgrids is demonstrated with switched Ethernet communication. To investigate the effect of communication delay, the bandwidth is varied for this particular operating condition. It is found the control performance deteriorates significantly below 200 kbps. However, this would vary with measurement data precision, number of port, switched memory and scheduling topology. The control performances with different bandwidth are given in Fig. 14, where the change in power flow for B2B4 is shown for various communication bandwidths. It must be noted that the communication of the power flow measurement for control is done with low bandwidth communication network with acceptable system response as mentioned. The fault data (converter blocking)/outage are communicated with high priority for shorter time delay and deactivation of the secondary control.
with five parallel microgrids (for limitation in computing ability number of DGs in each microgrid is limited to two). With the connection of microgrid 4, the power sharing is shown in Fig. 15b. The stable system operation with expansion within a microgrid or a new microgrid verifies the dynamic system growth support of the proposed control method. 5. Conclusions This paper demonstrates the possibility of connecting multiple microgrids to utility through B2B converters connections. The system stability with multiple B2B connections is addressed. The proposed decentralized controller modulates the DC capacitor voltage based on power flow through B2B. A secondary control loop based on real and reactive power flow in the network through communication is also proposed. The power network and communication network is simulated in closed loop. The proposed control schemes show stable system operations in different operating conditions.
4.5. Case 5: Control 4 and system expansion validation Acknowledgement In this case the expansion of microgrid is tested to ensure the proposed control can handle dynamic system growth. First three parallel microgrid (Fig. 1 without microgrid 4) each having 4 DGs is simulated. The power sharing and stable system operation (Fig. 15a) validate the expansion of individual microgrid with the proposed control method. Then the microgrid in Fig. 1 is modified
The authors would like to thank ABB Corporate Research, Sweden. Appendix A The equivalent circuit of a B2B converter is shown in Fig. A.1. From equivalent circuit shown in Fig. A.1, the following equations are obtained for each of the phases of the three phase system For VSC-1.
ðv cf 1 þ u1 :V dc Þ di11 RT1 ¼ i11 þ dt LT1 LT1
ðA:1Þ
dv cf 1 ði11 i21 Þ ¼ Cf 1 dt
ðA:2Þ
v cf 1 v t1 ¼ Lf 1
di21 dt
ðA:3Þ
For VSC-2
Fig. 15. System expansion with the proposed control method.
ðv cf 2 þ u2 :V dc Þ di12 RT2 ¼ i1 þ dt LT2 LT2
ðA:4Þ
495
R. Majumder, G. Bag / Electrical Power and Energy Systems 55 (2014) 486–496
Fig. A.1. Equivalent circuit.
dv cf 2 ði12 i22 Þ ¼ Cf 2 dt
ðA:5Þ
The current references can be expressed in terms of voltage references as
v cf 2 v t2
di22 ¼ Lf 2 dt
ðA:6Þ
Pdc
d V2 ¼ V dc C dc ðV dc Þ þ dc dt Rdc
ðA:7Þ
Pac ¼ ðv 1d i12d þ v 1q i12q Þ ¼ ðv cf 1d i21d þ v cf 1q i21q Þ
ðA:8Þ
Equating the power we get,
¼ ðv cf 1d i21d þ v cf 1q i21q Þ
ðA:9Þ
Taking Vdc2 as a state, we get,
1 1 ðV 2 Þ þ ðv cfd i21d þ v cfq i21q Þ Rdc C dc dc C dc
xi1 ¼ ½i11d
i11q
i21d
i21q
v cf 1d v cf 1q T
xi2 ¼ ½i12d
i12q
i22d
i22q
v cf 2d v cf 2q T
ðA:10Þ
ðA:11Þ
It is assumed here that the tracking is perfect and hence, in the limit, switching function u can be represented by uc. From (A.11), ucdq can be expressed as
udq1 ¼ k2 i11dq þ ðk2 k1 Þi21dq k3 v cfdq1 þ k1 i21refdq þ k2 icf 1refdq þ k3 v cf 1refdq
ðA:12Þ
The above equation can be written in matrix form as
¼ Gi1 xi1 þ Hi1 yrefdq1
ðA:13Þ
where
i21refq
icf 1refd
icf 1refq
¼4
1
0
xLf
x1L
0
f
3 5
2
v cf 1refd 4 0 þ v cf 1refq x1L
1
x Lf f
0
3 v 5 t1d
v t1q
x_ i1 ¼ ACONV1 xi1 þ BT1 v cf 1refdq þ BBUS1 v t1dq
ðA:15Þ
where ACONV = Ai + B1Gi and BCONV = BiHi. A.2. Converter output voltage controller
Ki d1 ¼ dref ¼ ðV dcref V dc Þ K p þ s
v cf 1refd v cf 1refq
du ¼ ðV dcref V dc Þ dt The converter voltage angle is
½d1 ¼ ½K i ½u þ ½K p ½V dcref
x_ i1 ¼ Ai1 xi1 þ B11 ucdq1 þ B21 v tdq1
yrefdq1 ¼ ½i21refd
2
v cf 1refd v cf 1refq
We can write linearized state equation and output converter voltage angle equation as,
The state equation in the d–q frame is given by (for VSC-1)
ud1 uq1
xC f
Assuming a state u, where
The Eqs. (A.1)–(A.6) are translated into a d–q reference frame of converter output voltages, rotating at system frequency x. Defining a state vector as for VSC-1 and VSC-2
xC f 0
0
For VSC-1, the voltage magnitude is kept constant while voltage angle is controlled as (assuming tracking is perfect)
d V2 V dc C dc ðV dc Þ þ dc ¼ ðv 1d i12d þ v 1q i12q Þ dt Rdc
¼
¼
The converter model can be written as,
In ac side the power can be expressed as (neglecting the resistance)
ðV 2dc Þ
i21refd i21refq
The power consumed by the DC side can be expressed as
icf 1refq
A.1. DC voltage
icf 1refd
½Du ¼ ½0½Du þ ½1½DV dc þ ½1½DV dcref
ðA:16Þ
½Dd1 ¼ ½K i ½Du þ ½K p ½DV dcref
ðA:17Þ
For VSC-2, the converter output voltage magnitude is controlled as
v cf 2refd ¼ V cf 2ref
¼ V rated2 n2 ðQ 2 Q rated2 Þ
ðA:18Þ
where the reference voltage is aligned in d axis. The output angle is controlled as,
d2 ¼ d2ref ¼ d2rated m2 ðP2 Prated2 Þ
ðA:19Þ
From (A.18) and (A.19), the linearized voltage controller equation can be written as
Dd2 ¼ m2DP2 Dv cfrefd ¼ nDQ
2
The power output is measured through a low pass filter and can be derived as,
T
xC
ðv cf 2d i22d þ v cf 2q i22q Þ
P2 ¼
x_ i1 ¼ ðAi1 þ B1 G1 Þxi þ B11 Hi1 yrefdq1 þ B21 v tdq1
xC xC q ¼ ðv cf 2d i22q v cf 2q i22d Þ Q2 ¼ s þ xC 2 s þ xC
ðA:14Þ
s þ xC
p2 ¼
xC
Substituting (A.13) into (A.11) we get
s þ xC
496
R. Majumder, G. Bag / Electrical Power and Energy Systems 55 (2014) 486–496
Linearizing we get,
"
DP_ 2 DQ_ 2
#
¼
xC
0
0
xC
Dv cf 2dq DP 2 þ BP Di22dq DQ 2
ðA:20Þ
A.3. Model of B2B converter The model of the B2B converter is then derived by linearzing (A.10), (A.15) and then combining with (A.16) and (A.20) as
Dx_ ib2b1 ¼ Aib2b1 Dxib2b1 þ Bb2b1 Dv cf 1refdq þ BBUSb2b1 Dv t1dq where
Dxib2b1 ¼ ½DV 2dc Du Dxi1 Dxi2 DP2 DQ 2
T
Considering there is Z B2B connection to the utility network, the total state space
Dx_ Z ¼ AZ DxZ þ BZ Dv tZdq where
AZ ¼ diagð Aib2b1
Aib2b2
Aib2bZ Þ
References [1] Lasseter RH. MicroGrids. IEEE Power and Energy Society General Meeting; 2002, p. 305–8. [2] Katiraei F, Iravani MR. Power management strategies for a microgrid with multiple distributed generation units. IEEE Trans Power Deliv 2006;21(4):1821–31. [3] Reza M, Sudarmadi D, Viawan FA, Kling WL, Van Der Sluis L. Dynamic stability of power systems with power electronic interfaced DG. In: IEEE power systems conference and exposition; 2006, p. 1423–8. [4] Dai M, Marwali MN, Jung JW, Keyhani A. Power flow control of a single distributed generation unit with nonlinear local load. In: IEEE power systems conference and exposition; 2004, p. 398–403. [5] Guerrero JM, de Vicuna LG, Matas J, Castilla M, Miret J. A wireless controller to enhance dynamic performance of parallel inverters in distributed generation systems. IEEE Trans Power Electron 2004;19(1):1205–13. [6] Lasseter RH, Paigi P. Microgrid: a conceptual solution. In: IEEE power electronics specialists conference; 2004, p. 4285–90. [7] Yunwei L, Vilathgamuwa DM, Poh CL. Design, analysis, and real-time testing of a controller for multibus microgrid system. IEEE Trans Power Electron 2004;19(5):1195–204. [8] Chen C, Duan S, Cai T, Liu B, Hu G. Smart energy management system for optimal microgrid economic operation. IET Renew Power Generat 2011;5(3):258–67. [9] Ross M, Hidalgo R, Abbey C, Joós G. Energy storage system scheduling for an isolated microgrid. IET Renew Power Generat 2011;5(2):117–23.
[10] Bevrani H, Ise T, Miura Y. Virtual synchronous generators: a survey and new perspectives. Int J Electric Power Energy Syst 2014;54:244–54. [11] Aghamohammadi MR, Abdolahinia H. A new approach for optimal sizing of battery energy storage system for primary frequency control of islanded microgrid. Int J Electric Power Energy Syst 2014;54:325–33. [12] Serban I, Marinescu C. Battery energy storage system for frequency support in microgrids and with enhanced control features for uninterruptible supply of local loads. Int J Electric Power Energy Syst 2014;54:432–41. [13] Sigrist L, Lobato E, Rouco L. Energy storage systems providing primary reserve and peak shaving in small isolated power systems: an economic assessment. Int J Electric Power Energy Syst 2013;53:675–83. [14] Kumar L, Jain S. A multiple source DC/DC converter topology. Int J Electric Power Energy Syst 2013;51:278–91. [15] Wang Y, Li W, Lu J. Reliability of wide area measurement system. IEEE Trans Power Deliv 2010;25(3):1483–91. [16] Bose A. Smart transmission grid applications and their supporting infrastructure. IEEE Trans Smart Grid 2010;1(1):11–9. [17] Madureira AG, Pecas Lopes JA. Coordinated voltage support in distribution networks with distributed generation and microgrids. IET Renew Power Generat 2009;3(4):439–54. [18] Jupe SCE, Taylor PC. Distributed generation output control for network power flow management. IET Renew Power Generat 2009;3(4):371–86. [19] Abdulwahid U, Manwell JF, Mcgowan JG. Development of a dynamic control communication system for hybrid power systems. IET Renew Power Generat 2007;1(1):70–80. [20] Soultanis NL, Papathanasiou SA, Hatziargyriou ND. A stability algorithm for the dynamic analysis of inverter dominated unbalanced LV microgrids. IEEE Trans Power Syst 2007;22(1):294–304. [21] Hadjsaid N, Caire R, Raison. Decentralized operating modes for electrical distribution systems with distributed energy resources. IEEE Power & Energy Society General Meeting; 2009. p. 1–4. [22] TrueTime 2.0 beta 5 – Reference manual, Department of Automatic Control, Lund University, Sweden; June 2010. [23] Shahnia F, Majumder R, Ghosh A, Ledwich G, Zare F. Operation and control of a hybrid microgrid containing unbalanced and nonlinear loads. Electric Power Syst Res 2010;80(8):954–65. [24] Pecas Lopes JA, Moreira CL, Madureira AG. Defining control strategies for microgrids islanded operation. IEEE Trans Power Syst 2006;21(2):916–24. [25] Majumder R, Ghosh A, Ledwich G, Zare F. Load sharing and power quality enhanced operation of a distributed microgrid. IET Renew Power Generat 2009;3(2):109–19. [26] Mishra MK, Karthikeyan K. An investigation on design and switching dynamics of a voltage source inverter to compensate unbalanced and nonlinear loads. IEEE Trans Ind Electron 2009;56(8):2802–10. [27] Mishra MK, Karthikeyan K. A fast-acting DC-link voltage controller for threephase DSTATCOM to compensate AC and DC loads. IEEE Trans Power Deliv 2009;24(4):2291–9. [28] Xiaonan L, Guerrero J, Teodorescu R, Kerekes T, Kai Sun S, et al. Control of parallel-connected bidirectional AC–DC converters in stationary frame for microgrid application. IEEE Energy Convers Cong Expos (ECCE) 2011:4153–60. [29] Sao CK, Lehn PW. Control and power management of converter fed microgrids. IEEE Trans Power Syst 2008;23(3):1088–98. [30] Majumder R, Ghosh A, Ledwich G, Zare F. Control of parallel converters for load sharing with seamless transfer between grid connected and islanded modes, IEEE power and energy society general meeting – conversion and delivery of electrical energy in the 21st century; 2008. p. 1–7. [31] Majumder R, Ghosh A, Ledwich G, Zare F. ‘Power management and power flow control with back-to-back converters in a utility connected microgrid. IEEE Trans Power Syst 2010;25:821–34.
Contents lists available at ScienceDirect
Electrical Power and Energy Systems journal homepage: www.elsevier.com/locate/ijepes
Parallel operation of converter interfaced multiple microgrids Ritwik Majumder ⇑, Gargi Bag ABB Corporate Research Center, Forskargrand 7, Vasteras, Sweden
a r t i c l e
i n f o
Article history: Received 21 May 2012 Received in revised form 10 September 2013 Accepted 24 September 2013
Keywords: Microgrids Back to back converters Stability Communication
a b s t r a c t This paper proposes methods to control utility connected multiple microgrids. Microgrids with renewable energy sources and autonomous operations do not have high reliability while the smart grid vision demands a highly reliable and efficient grid. Thus the connections of the microgrids to the main grid have to be smart itself. A back to back (B2B) converter connection can provide a reliable interface and also can provide isolation between utility and microgrids. However, with multiple microgrids connected through B2B converter connections can lead to system instability. In this paper, a method to coordinate the B2B connections without losing the possibility of autonomous operation of the microgrids is proposed. The system stability is improved first with a decentralized control of the B2B converters. Then with smart grid scenarios in mind, an application of communication is proposed and simulated. The proposed control strategy demonstrates stable system operation with multiple microgrids connected to utility through B2B converters. The mathematical model of the system with analysis and closed loop simulation of power network and communication network are presented to validate the claim. Ó 2013 Elsevier Ltd. All rights reserved.
1. Introduction Microgrid can generally be viewed as a cluster of distributed generators connected to the main utility grid [1], usually through Voltage Source Converter (VSC) based interfaces. The power management in a microgrid is mainly based on voltage-droop characteristic, voltage regulation, and load reactive power compensation [2]. The real and reactive power sharing can be achieved by controlling two independent quantities – the power angle, and the fundamental voltage magnitude [2–4]. The system stability during load sharing has been explored by many researchers [3,5,6]. Transient stability of power system with high penetration level of power electronics interfaced (converter connected) distributed generation is explored in [3]. While [6] explores the microgrid testing, [7] define converter control strategy for microgrid operation. In [8], a study for a Smart Energy Management System (SEMS) to optimize the operation of the microgrid is presented. The SEMS consists of power forecasting module, Energy Storage System (ESS) management module and optimization module. A knowledge-based expert system is proposed for the scheduling of an energy storage system installed in a power system [9]. Different converter and storage controls for microgrid operation are discussed in [10–14]. While a virtual synchronous generator aspect is addressed in [10], the converter control for DC/DC operation is investigated in [14]. An economic sizing of storage for microgrid is proposed in [11] and storage control for frequency ⇑ Corresponding author. Tel.: +46 738 150002. E-mail address: [email protected] (R. Majumder). 0142-0615/$ - see front matter Ó 2013 Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.ijepes.2013.09.008
support, primary reserve and peak shaving is discussed in [12,13]. The proposed method is successfully tested to two actual isolated microgrid different sizes and with different generation pattern. As the microsources are not reliable source of power and so a microgrid operates both in autonomous or grid connected mode to balance the demand supply. In general, a microgrid is interfaced to the main power system by a fast semiconductor switch called the Static Switch (SS). However, in a smart grid scenario, it is not advisable to connect a highly reliable and efficient utility to microgrids in an uncontrolled way. For a better power management, it is important to achieve control over the power flow. A voltage and frequency isolation between the grid and the microgrid will always ensure a safe operation and a B2B converter can provide both the power flow control and isolation. Smart utility grid has been proposed to upgrade the present grid structure through integration of information technology, communication network, automatic control and distributed intelligent devices [15]. It is understood that the vision for a more secure, more robust electrical grid can only be achieved by better communication. In [16], it is examined how this information can be utilized more effectively for real-time operation as well as for subsequent decision making. A new methodology for coordinated voltage support in distribution networks with large integration of distributed generation and microgrids is proposed in [17]. Given the characteristics of the Low Voltage (LV) networks, it is shown that traditional control strategies using only reactive power control may not be sufficient in order to perform efficient voltage control. A stage by stage
R. Majumder, G. Bag / Electrical Power and Energy Systems 55 (2014) 486–496
487
development for network power flow with DG (Distributed Generators) output control is described in [18]. A hybrid power system component with communication ports allowing communication with a supervisory controller and a communication network between each component is considered in [19], to prepare a foundation for further development in the intelligent adaptable supervisory controller. The tests were conducted that confirm the capability of this concept to use in hybrid power system. It is very important to control the power flow between the grid and microgrid and maintain voltage isolation between the two systems. The need of power quality improvement while achieving economic optima in a distributed generation is addressed in [20]. A new concept related to the revitalized microgrid concept and the vision of the smart grid is presented in [21]. In this paper, the connection and coordinated control of multiple microgrids to utility grid is proposed. 1.1. Purpose Aim of this paper is to propose a method for connecting the existing microgrids to utility with B2B converter connections. System stability with multiple B2B connections is investigated with mathematical model and time domain simulations. A coordinated control method for the B2B connections is proposed to improve the system stability. First a decentralized control method is proposed. Then an application of communication is simulated. The closed loop simulations of power network and communication show improvement in system stability and maintain the high reliability of the grid connected with multiple microgrids. 1.2. Organizations Section 2 describes the system structure and operation scenarios. The proposed control techniques are given in Section 3. Simulation results are presented in Section 4.
Fig. 2. Back-to-back connections.
corresponding signal input BLK1 and BLK2. DG-1 and DG-2 are connected through VSC to the microgrid. Although the proposed control is demonstrated with first two and then four microgrids, it can be applied to any number of microgrids connected to the utility as shown in Fig. 1. The control schemes are described in the next sections.
2. System structure and operation 3. Control and reference generation A simple power system model with B2B converters, connected to multiple microgrids is shown in Fig. 1. Each of the microgrids has their own micro-sources and loads. The utility loads and line impedances (z) are also incorporated as the connection of the B2Bs are not very close to each other. A simple microgrid with two sources and one load connected through the B2B connection is shown in Fig. 2. The B2B converters (VSC-1 and VSC-2) are supplied by a common DC bus capacitor with voltage of VC. The converters can be blocked with their
In this section the control scheme and reference generation for the VSCs are described. The control can work in two different modes. In mode one, with low power demand and contractual scenario with utility, the utility can supply a fixed amount of power to the microgrid while the microgrid DGs shares the rest of the power demand through droop control. In mode two, with a high load demand, the microgrids DGs supply their maximum power and the utility provides the deficit power through B2B to the microgrid.
Fig. 1. The microgrids and utility system.
488
R. Majumder, G. Bag / Electrical Power and Energy Systems 55 (2014) 486–496
It is assumed that, in case of a very high power demand in the microgrid, loads are switched out. In either case control of VSC-1 (Fig. 2) is same and described first with the proposed control methods. The control of VSC-2 and the DGs are described subsequently. 3.1. VSC-1 reference generation and proposed capacitor voltage control Both the VSCs of B2B are supplied from a common capacitor of voltage VC as shown in Fig. 2. First the fixed capacitor voltage control VSC-1 is described and then the proposed controls are shown. 3.1.1. Control-1: Fixed capacitor voltage reference In this case reference angle for VSC-1 is generated as shown in Fig. 3a. First the measured capacitor voltage VC is passed through a low pass filter to obtain VCav. This is then compared with the reference capacitor voltage VCref. The error is fed to a Proportional Integral (PI) controller to generate the reference angle dref. VSC-1 reference voltage magnitude is kept constant, while angle is the output of the PI controller. The instantaneous voltages of the three phases are then derived from the references. This controller works well with a microgrid connected to the utility, however with multiple microgrids connected as shown in Fig. 1, it can lead to system instability (shown in simulation section) due to low system damping. This low system damping arises from the connection of the parallel B2B converters. The B2B provides the much needed isolation between the utility and microgrid for superior control but has some disadvantages. The inherent system damping due to utility line resistance is lost at the microgrid side due to B2B connection. The output voltage angle control of the second VSC (VSC-2) through droop also create system stability problem similar to parallel operation of converters. Moreover, the fixed value control of capacitor voltage from utility side converter leads to large power circulation in the utility side line during a small disturbance (as the DC capacitor voltage is used for output voltage angle calculation of the converter).
3.1.1.1. Mathematical model and eigen value analysis. A mathematical model of the B2B converter is developed as shown in Appendix A. A system with four B2B connections (Fig. 1) is considered for the analysis. The effect of DC voltage controller gains (VSC-1) and droop gains (VSC-2) are shown in Fig. 4 at nominal operating point with different number of B2B connections. Fig. 4 shows the eigen value trajectory of the dominant modes with change in power controller gain with two, three or four parallel B2B connections. It can be seen that increased number of connections lead the system to instability for the same value of the feedback gains. A selection of lower value of controller gain would result in an inferior DC voltage dynamics (VSC-1) and slower droop characteristic (VSC-2). In this paper control methods are proposed to improve the system stability with acceptable feedback gains. 3.1.2. Control-2: Drooping capacitor voltage reference As the DC capacitor supplies VSC-1 and VSC-2, regulating the capacitor voltage will result in improving dynamic response of the B2B converters. The reference capacitor voltage is then drooped from the rated value based on the power flow from utility to microgrid. The control scheme is shown in Fig. 3b. However, this controller fails to ensure a stable system condition with two close B2B connections and /or reverse power flow (from microgrid to utility) in some of the B2B connections. 3.1.3. Control-3: Improving damping with voltage angle measurement The system damping can be further improved by adding a secondary loop based on the measured voltage angle difference as shown in Fig. 3c. The measured angle is passed through a low pass filter and the output is used to rectify the angle reference as shown in Fig. 3c. However the angle information can be derived from the real and reactive power flow which is discussed in the next section. 3.1.4. Control-4: Improving damping with communication It can be seen in controller 3 that, modulating the angle would result in a much better system damping. However we need the
Fig. 3. Angle controller.
R. Majumder, G. Bag / Electrical Power and Energy Systems 55 (2014) 486–496
489
Fig. 4. Eigen value trajectory with parallel back to back connections.
angle information referred to a common frame. Hence it would be effective if we can use controller-2 (Fig. 3b) but modulate the Vcrated based on the common angle information. The angle information can be derived from the real and reactive power flow in the lines. To derive the angle information from the real and reactive power flow, let us consider the system shown in Fig. 1. It is assumed that four microgrids with their own DGs and loads are connected through B2B and loads. The utility loads are representing the main outgoing feeders. If the line impedance Zi has resistance Ri and reactance Xi. The power flow equations over the line for small angle differences can be written as
d11 d22 ¼ R11 Q M1R þ X 11 PM1R R22 Q M2L þ X 22 PM2L
ð1Þ
where R11 = R1/(V11V), R22 = R2/(V22V), X11 = X1/(V11V) and X22 = X2/(V22V). Similarly, the Point of Common Coupling (PCC) voltage angle of B2B3 and B2B4 can also be represented with respect to d22 as,
d33 d22 ¼ R22 Q M2R þ X 22 PM2R R33 Q M3L þ X 33 PM3L d44 d22 ¼ R33 Q M3R þ X 33 PM3R R44 Q M4L þ X 44 PM4L The output voltage angle with respect to a common reference is derived from the power flow and then used to control the capacitor voltage as
V Cref ¼ V cr KP:PG K FL ðddiff Þ The reference voltages of the B2Bs are then derived as,
V Cref 1 ¼ V cr1 KP1:P G1 K FL1 :ðd11 d22 Þ
ð2Þ
V Cref 2 ¼ V cr2 KP2:PG2 K FL2 :ðd22 Þ
ð3Þ
V Cref 3 ¼ V cr3 KP3:PG3 K FL3 :ðd33 d22 Þ
ð4Þ
V Cref 4 ¼ V cr4 KP4:PG4 K FL4 :ðd44 d22 Þ
ð5Þ
The controller is shown in Fig. 3d. The primary loop is shown with PG while the secondary control based on (2) is shown as VCpq . It is to be noted that in (1) the power flow data from one point of the network need to be communicated to other part. In smart grid scenarios, communication of these power flow data can be implemented. Here a switched Ethernet network is considered. It is to be noted that in (2)–(5), the first primary control loops based on local power measurements PGi , and will ensure system stability in most of the cases. The microgrids operations do not need any frequent change of capacitor voltages and hence a low bandwidth communication would be sufficient. As evident from Eqs. (2)–(5)(where the reference voltages of the B2B converter capacitor are generated) the first term is a constant and the second term is derived from the local power measurement. The communication is needed for the last part. Hence the impacts of communication delay or errors are only in part of the reference generation. However a limiter is placed to limit the communicated measurement in case of communication error. In general, the B2B control performance is not sensitive to communication delay in most of the scenarios. However, in multiple parallel operations with continuous change in power requirement and power flow direction, a large delay can fail to meet the control requirement. In that case, the particular B2B can be switched to fixed power supply mode, to improve the system stability.
490
R. Majumder, G. Bag / Electrical Power and Energy Systems 55 (2014) 486–496
During fault, both the converters of the B2Bs are blocked by their protection functions and the capacitor voltages are held. During fault, the secondary control loop (with angle) is also bypassed. The communication network is shown in Fig. 5. The communication network is simulated in MATLAB–SIMULINK based communication network simulator TrueTime as switched Ethernet network [22]. The detail parameters are given in Table 1.
In case of high power demand, the DGs supply their maximum available power while utility needs to supply any deficit in the power requirement through B2B converters. Let the maximum rating of the B2B converters are given by PTmax, QTmax. Then the voltage magnitude and angle reference of VSC-2 is generated as
3.2. VSC-2 reference generations
where VTmax and dTmax are the voltage magnitude and angle, respectively, when VSC-2 supplies the maximum load.
VSC-2 of Fig. 2 is connected with PCC through an output inductance LG and controls the real and reactive power flow between the utility and the microgrid. As mentioned before the B2B can supply a fixed amount power to the microgrid or the power deficit. Let us assume that in fixed power supply mode the references for the real and reactive power be PTref and QTref respectively and the VSC-2 output voltage be denoted by VT\dT and the PCC voltage by VP\dP. Then the reference VSC-2 voltage magnitude and its can be calculated as
VT ¼
V 2P þ Q Tref X G V P cosðdT dP Þ
dT ¼ tan1
PTref X G V 2P þ Q Tref X G
ð6Þ ! þ dP
ð7Þ
dT ¼ dTmax mT ðPT PTmax Þ V T ¼ V Tmax nT ðQ T Q Tmax Þ
ð8Þ
3.3. Reference generation for DG sources In this section, the reference generation for the DGs is presented. It is to be noted that in this paper the DGs are assumed as constant DC sources and the converters are controlled as VSC. The DG could be a fuel cell or Photovoltaic, and DC chopper maintains the output DC voltage of the DG as [23]. The DG interfacing converter can run in two different modes as stated in [24]. One mode is PQ converter control where the converter is used to supply a given active and reactive power set-point. The other mode is VSC control where the converter is controlled to ‘‘feed’’ the load with pre-defined values for voltage and frequency. In this paper, the interfacing converters are controlled as VSCs. The voltage and frequency are then controlled with the load frequency control based on the real and reactive power output. The control strategy for both the DGs is the same and hence only DG-1 reference generation is discussed here. It is assumed that when the utility supplies a part of load demand in microgrid by a fixed amount power through the B2B converters, rest of the power demand in the microgrid is supplied and regulated by the DGs. The output voltages of the converters are controlled to share this load proportional to the rating of the DGs. The power requirement can be distributed among the DGs, similar to a conventional droop by dropping the voltage magnitude and angle as
d1 ¼ d1rated m1 ðP1 P1rated Þ V 1 ¼ V 1rated n1 ðQ 1 Q 1rated Þ
ð9Þ
where V1rated and d1rated are the rated voltage magnitude and angle respectively of DG-1, when it is supplying the load to its rated power levels of P1rated and Q1rated. The coefficients m1 and n1 respectively indicate the voltage angle drop vis-à-vis the real power output and the magnitude drop vis-à-vis the reactive power output. These values are chosen to meet the voltage regulation requirement in the microgrid. In high loading condition, the DGs supply their maximum available power and the utility supplies the deficit power. Let us denote the available active power as P1avail. Then based on this and the current rating of the DG the reactive power availability Q1avail of the DG can be determined. Based on these quantities, the voltage references is calculated as
Fig. 5. Communication network structure.
V1 ¼
V 2P1 þ Q 1av ail X 1 V P1 cosðdP1 dP Þ 1
d1 ¼ tan
Table 1 Communication network. Wired
Ethernet
Network type Data rate Minimum frame size Total switch memory Switch overflow behavior
Switched Ethernet 1,000,000 bits/s 512 80,000 Retransmit
P1av ail X 1 V 2P1 þ Q 1av ail X 1
ð10Þ ! þ dP1
ð11Þ
The references for the other DGs are generated in a similar way. It is to be noted that there could be non-linear and unbalanced loads. The reference for the DGs then needs to be compensating [25]. In [26], design aspects of various passive components and switching dynamics of a voltage source inverter (VSI) for compensating unbalanced and nonlinear load are presented. A novel
491
R. Majumder, G. Bag / Electrical Power and Energy Systems 55 (2014) 486–496
method is proposed for VSI to track desired reference currents smoothly. In case of a DSTATCOM (Distributed Static Compensator), any change in the load affects the dc-link voltage directly [27]. A novel fast-acting dc-link voltage controller based on the energy of a dc-link capacitor is proposed. For a microgrid connection through B2B connection, we need to modulate the DC capacitor reference voltage to improve the system damping. This has been the main focus of the proposed controllers and the performances of the controllers are described in next subsections. It must be noted that parallel operation of converter interfaced sources has many challenges [25,28–30]. Different control techniques and synchronization method is proposed by many authors [25,28–30]. However the proposed method in this paper of B2B converter interfaced multiple microgrids is not directly related to the number of microgrid microsources and can be extended to more number of microgrid connection or DGs. The main reason of taking a small test microgrid (Fig. 2) is the limitation of the computer and software capability. With the each B2B converter also has two VSC converters, for multiple microgrid case microsource number in each microgrid is limited. A real microgrid will have many more microsources and the proposed method can be applied to such system as the main controllability issues are at the microgrid PCC with voltage, frequency and power exchange. The generalized concept and control result of multiple converter sources microgrid with B2B converter interfaced is shown in [31]. In this paper the control approach for parallel back to back connections is proposed.
Table 2 System and controller parameters. System Quantities
Values
Systems frequency Source voltage (Vs) Feeder impedance
50 Hz 11 kV rms (L–L) Rs = 3.025 X, Ls = 57.75 mH
Load Impedance (Balanced) or Induction motor
RL = 100.0 X, LL = 300.0 mH Rated 40 hp, 11 kV rms (L–L)
DGs and VSCs DC voltage (Vdc1, Vdc2) Transformer rating VSC losses (Rf) Filter capacitance (Cf) Inductances (L1, L2) Inductances (LG) Hysteresis constant (h)
3.5 kV 3 kV/11 kV, 0.5 MVA, 2.5% reactance (Lf) 1.5 X 50 lF 20 mH and 16.0 mH 28.86 mH 105
Angle controller Proportional gain (Kp) Integral gain (KI)
0.2 5.0
Droop coefficients Power-angle m1 m2 Voltage-Q n1 n2
0.3 rad/MW 0.24 rad/MW 0.15 kV/MVAr 0.12 KV/MVAr
4. Simulation studies Simulation studies are carried out in PSCAD/EMTDC (version 4.2) with converter model for all the cases except case 4. In case 4, the power network and communication network are simulated in closed loop in MATLAB SIMULINK. The power network is modeled in SimPower, with VSC bridges while the communication network is modeled in TrueTime. The close loop simulation structure is shown in Fig. 6. Different configurations of load and its sharing are considered. The DGs are considered as inertia-less dc source supplied through a VSC. The system data are given in Table 2. 4.1. Case 1: Control 1-fixed capacitor voltage First it is assumed that only one B2B is connected to the utility shown in Fig. 1. It is desired that B2B-1 supplies 50% of the load power requirement in microgrid-1 and rest of the power requirement is supplied by the DGs. With the system running in steady state, the load power demand is changed from 1 MW to 0.525 MW at 0.1 s. The system response is shown in Fig. 7a. It can be seen that B2B continues to supply 50% of the load power demand. Rest of the power requirement is shared by the
Fig. 7. Power output of back-to-back converters.
DG proportional to their ratings. At 0.35 s system is revert back to initial condition and DGs, B2B power go back to initial condition. This validates individual B2B operation. To investigate the parallel operation of the B2Bs, B2B-1 and B2B-2 are then connected to each other at 0.1 s (an utility breaker between the two microgrids is used). The power flows through the B2Bs are shown in Fig. 7b. It can be seen that system oscillation increases and the system becomes unstable. The DC capacitor voltage is shown in Fig. 8a. The PCC voltage, DG output power and DG output current is also shown in Fig. 8. The DG output power starts oscillating and also PCC voltage. Then the system becomes unstable. 4.2. Case 2: Control 2-drooping capacitor voltage
Fig. 6. Close loop simulating of power and communication network.
To improve the system damping, the DC capacitor reference voltage is drooped with the power flow through B2B as shown in Fig. 3b. While both microgrids connected in parallel and utility is supplying, system is operated as case 1. Fig. 9 shows the system response. The stable DC capacitor voltage is shown in Fig. 9a. The
492
R. Majumder, G. Bag / Electrical Power and Energy Systems 55 (2014) 486–496
Fig. 8. System instability.
Fig. 9. Capacitor voltage and DG output.
PCC voltage is also stable and the DG output powers share the load as desired (case 1). DG output current shown in Fig. 9 also ensures a stable system operation. To further verify the controller ability and system stability, the power flow through the B2B 2 is reversed and microgrid-2 start supplying power to the utility at 0.1 s. The system response is shown in Fig. 10. The DC capacitor voltage and angle controller output are also shown in Fig. 10. The voltage and angle oscillations lead the system to instability. Thus only drooping the DC capacitor voltage is not sufficient to ensure stable system operation.
4.3. Case 3: Control 3-voltage angle measurement To further improve the system stability, the PCC voltage angle difference is measured and passed through a low pass filter as shown in Fig. 3c. The system is simulated with this controller in same operating condition as in previous case. Fig. 11 shows the power flow through the B2Bs and it can be seen that a stable system operation is achieved. The B2B supplies (absorb) power to (from) microgrids as desired. The DC capacitor voltage and angle controller output are shown in Fig. 11b and c. A stable system
Fig. 10. Power flow through back-to-back converters and angle controller output: Unstable Case.
condition is apparent. Thus including the voltage angle information improves the system stability.
R. Majumder, G. Bag / Electrical Power and Energy Systems 55 (2014) 486–496
493
4.4. Case 4: Control 4-with communication
Fig. 11. Power flow through back-to-back converters and angle controller output: Stable Case.
Fig. 12. Power flow through the B2Bs and PCC voltage.
In the next section the angle information for a multiple microgrid scenario is derived from the real and reactive power flow in the network. Communication is used to carry the power flow measurement from one part of the network to the B2Bs.
In this case, system shown in Fig. 1, with four microgrid connected through B2B connections are considered. The aim is to improve the system stability by modulating the DC capacitor voltage based on the power flow through the B2B and PCC voltage angle. To calculate the angle with same reference, real and reactive power flow in the network is used as (2)–(5). The communication network shown in Fig. 5 is used in this case. This is a TrueTime communication network, which has four send and four receive ports. The measured data are fed to send port and received at the receive port as shown in Fig. 5. The data communications are controlled through the trigger signal. When a node tries to transmit a message, a triggering signal is sent to the network block on the corresponding input channel. At the end of the simulated transmission (in communication network) of the message is finished, the network block sends a new triggering signal on the output channel corresponding to the receiving port. The transmitted message is put in a buffer at the receiving port. A message contains information about the sending and the receiving computer port, measurement signals or control signals, the length of the message, and optional real-time attributes such as a priority or a deadline. In this case, the power flow data at PCC of the B2B converters are communicated to other B2B connections to calculate the converter output voltage angle difference as in (1)–(5). The network parameters are given in Table 1. It is assumed that utility is connected to microgrids 1, 2 and 3 through the B2Bs and supply power. Microgrid 4 is connected to the grid at 0.5 s. The system response (power flows through the B2Bs) is shown in Fig. 12a. PCC voltage and current through the B2B-4 are shown in Fig. 12b and c. It can be seen a stable PCC voltage is maintained and the current becomes balanced within 2–3 cycles. The power flow of the utility network is communicated through the communication network as shown in Fig. 5. The network has four send ports and four receive ports. The scheduling of the network is shown in Fig. 13a. The power flow in the network, as shown in Fig. 5, is measured and communicated. Fig. 13b and c show the measured power and the power data received through the network. It can be seen that they are close and moreover, the proposed control has the primary term based on local power measurement ((2)–(5)). The control will work even with a much slower sampling of this secondary term. The data rate could be chosen based on communication infrastructure available.
Fig. 13. Network schedule and communicated power signals.
494
R. Majumder, G. Bag / Electrical Power and Energy Systems 55 (2014) 486–496
Fig. 14. Change inflow in B2B4 with different communication bandwidth.
In this paper, the coordination of B2B connections of multiple microgrids is demonstrated with switched Ethernet communication. To investigate the effect of communication delay, the bandwidth is varied for this particular operating condition. It is found the control performance deteriorates significantly below 200 kbps. However, this would vary with measurement data precision, number of port, switched memory and scheduling topology. The control performances with different bandwidth are given in Fig. 14, where the change in power flow for B2B4 is shown for various communication bandwidths. It must be noted that the communication of the power flow measurement for control is done with low bandwidth communication network with acceptable system response as mentioned. The fault data (converter blocking)/outage are communicated with high priority for shorter time delay and deactivation of the secondary control.
with five parallel microgrids (for limitation in computing ability number of DGs in each microgrid is limited to two). With the connection of microgrid 4, the power sharing is shown in Fig. 15b. The stable system operation with expansion within a microgrid or a new microgrid verifies the dynamic system growth support of the proposed control method. 5. Conclusions This paper demonstrates the possibility of connecting multiple microgrids to utility through B2B converters connections. The system stability with multiple B2B connections is addressed. The proposed decentralized controller modulates the DC capacitor voltage based on power flow through B2B. A secondary control loop based on real and reactive power flow in the network through communication is also proposed. The power network and communication network is simulated in closed loop. The proposed control schemes show stable system operations in different operating conditions.
4.5. Case 5: Control 4 and system expansion validation Acknowledgement In this case the expansion of microgrid is tested to ensure the proposed control can handle dynamic system growth. First three parallel microgrid (Fig. 1 without microgrid 4) each having 4 DGs is simulated. The power sharing and stable system operation (Fig. 15a) validate the expansion of individual microgrid with the proposed control method. Then the microgrid in Fig. 1 is modified
The authors would like to thank ABB Corporate Research, Sweden. Appendix A The equivalent circuit of a B2B converter is shown in Fig. A.1. From equivalent circuit shown in Fig. A.1, the following equations are obtained for each of the phases of the three phase system For VSC-1.
ðv cf 1 þ u1 :V dc Þ di11 RT1 ¼ i11 þ dt LT1 LT1
ðA:1Þ
dv cf 1 ði11 i21 Þ ¼ Cf 1 dt
ðA:2Þ
v cf 1 v t1 ¼ Lf 1
di21 dt
ðA:3Þ
For VSC-2
Fig. 15. System expansion with the proposed control method.
ðv cf 2 þ u2 :V dc Þ di12 RT2 ¼ i1 þ dt LT2 LT2
ðA:4Þ
495
R. Majumder, G. Bag / Electrical Power and Energy Systems 55 (2014) 486–496
Fig. A.1. Equivalent circuit.
dv cf 2 ði12 i22 Þ ¼ Cf 2 dt
ðA:5Þ
The current references can be expressed in terms of voltage references as
v cf 2 v t2
di22 ¼ Lf 2 dt
ðA:6Þ
Pdc
d V2 ¼ V dc C dc ðV dc Þ þ dc dt Rdc
ðA:7Þ
Pac ¼ ðv 1d i12d þ v 1q i12q Þ ¼ ðv cf 1d i21d þ v cf 1q i21q Þ
ðA:8Þ
Equating the power we get,
¼ ðv cf 1d i21d þ v cf 1q i21q Þ
ðA:9Þ
Taking Vdc2 as a state, we get,
1 1 ðV 2 Þ þ ðv cfd i21d þ v cfq i21q Þ Rdc C dc dc C dc
xi1 ¼ ½i11d
i11q
i21d
i21q
v cf 1d v cf 1q T
xi2 ¼ ½i12d
i12q
i22d
i22q
v cf 2d v cf 2q T
ðA:10Þ
ðA:11Þ
It is assumed here that the tracking is perfect and hence, in the limit, switching function u can be represented by uc. From (A.11), ucdq can be expressed as
udq1 ¼ k2 i11dq þ ðk2 k1 Þi21dq k3 v cfdq1 þ k1 i21refdq þ k2 icf 1refdq þ k3 v cf 1refdq
ðA:12Þ
The above equation can be written in matrix form as
¼ Gi1 xi1 þ Hi1 yrefdq1
ðA:13Þ
where
i21refq
icf 1refd
icf 1refq
¼4
1
0
xLf
x1L
0
f
3 5
2
v cf 1refd 4 0 þ v cf 1refq x1L
1
x Lf f
0
3 v 5 t1d
v t1q
x_ i1 ¼ ACONV1 xi1 þ BT1 v cf 1refdq þ BBUS1 v t1dq
ðA:15Þ
where ACONV = Ai + B1Gi and BCONV = BiHi. A.2. Converter output voltage controller
Ki d1 ¼ dref ¼ ðV dcref V dc Þ K p þ s
v cf 1refd v cf 1refq
du ¼ ðV dcref V dc Þ dt The converter voltage angle is
½d1 ¼ ½K i ½u þ ½K p ½V dcref
x_ i1 ¼ Ai1 xi1 þ B11 ucdq1 þ B21 v tdq1
yrefdq1 ¼ ½i21refd
2
v cf 1refd v cf 1refq
We can write linearized state equation and output converter voltage angle equation as,
The state equation in the d–q frame is given by (for VSC-1)
ud1 uq1
xC f
Assuming a state u, where
The Eqs. (A.1)–(A.6) are translated into a d–q reference frame of converter output voltages, rotating at system frequency x. Defining a state vector as for VSC-1 and VSC-2
xC f 0
0
For VSC-1, the voltage magnitude is kept constant while voltage angle is controlled as (assuming tracking is perfect)
d V2 V dc C dc ðV dc Þ þ dc ¼ ðv 1d i12d þ v 1q i12q Þ dt Rdc
¼
¼
The converter model can be written as,
In ac side the power can be expressed as (neglecting the resistance)
ðV 2dc Þ
i21refd i21refq
The power consumed by the DC side can be expressed as
icf 1refq
A.1. DC voltage
icf 1refd
½Du ¼ ½0½Du þ ½1½DV dc þ ½1½DV dcref
ðA:16Þ
½Dd1 ¼ ½K i ½Du þ ½K p ½DV dcref
ðA:17Þ
For VSC-2, the converter output voltage magnitude is controlled as
v cf 2refd ¼ V cf 2ref
¼ V rated2 n2 ðQ 2 Q rated2 Þ
ðA:18Þ
where the reference voltage is aligned in d axis. The output angle is controlled as,
d2 ¼ d2ref ¼ d2rated m2 ðP2 Prated2 Þ
ðA:19Þ
From (A.18) and (A.19), the linearized voltage controller equation can be written as
Dd2 ¼ m2DP2 Dv cfrefd ¼ nDQ
2
The power output is measured through a low pass filter and can be derived as,
T
xC
ðv cf 2d i22d þ v cf 2q i22q Þ
P2 ¼
x_ i1 ¼ ðAi1 þ B1 G1 Þxi þ B11 Hi1 yrefdq1 þ B21 v tdq1
xC xC q ¼ ðv cf 2d i22q v cf 2q i22d Þ Q2 ¼ s þ xC 2 s þ xC
ðA:14Þ
s þ xC
p2 ¼
xC
Substituting (A.13) into (A.11) we get
s þ xC
496
R. Majumder, G. Bag / Electrical Power and Energy Systems 55 (2014) 486–496
Linearizing we get,
"
DP_ 2 DQ_ 2
#
¼
xC
0
0
xC
Dv cf 2dq DP 2 þ BP Di22dq DQ 2
ðA:20Þ
A.3. Model of B2B converter The model of the B2B converter is then derived by linearzing (A.10), (A.15) and then combining with (A.16) and (A.20) as
Dx_ ib2b1 ¼ Aib2b1 Dxib2b1 þ Bb2b1 Dv cf 1refdq þ BBUSb2b1 Dv t1dq where
Dxib2b1 ¼ ½DV 2dc Du Dxi1 Dxi2 DP2 DQ 2
T
Considering there is Z B2B connection to the utility network, the total state space
Dx_ Z ¼ AZ DxZ þ BZ Dv tZdq where
AZ ¼ diagð Aib2b1
Aib2b2
Aib2bZ Þ
References [1] Lasseter RH. MicroGrids. IEEE Power and Energy Society General Meeting; 2002, p. 305–8. [2] Katiraei F, Iravani MR. Power management strategies for a microgrid with multiple distributed generation units. IEEE Trans Power Deliv 2006;21(4):1821–31. [3] Reza M, Sudarmadi D, Viawan FA, Kling WL, Van Der Sluis L. Dynamic stability of power systems with power electronic interfaced DG. In: IEEE power systems conference and exposition; 2006, p. 1423–8. [4] Dai M, Marwali MN, Jung JW, Keyhani A. Power flow control of a single distributed generation unit with nonlinear local load. In: IEEE power systems conference and exposition; 2004, p. 398–403. [5] Guerrero JM, de Vicuna LG, Matas J, Castilla M, Miret J. A wireless controller to enhance dynamic performance of parallel inverters in distributed generation systems. IEEE Trans Power Electron 2004;19(1):1205–13. [6] Lasseter RH, Paigi P. Microgrid: a conceptual solution. In: IEEE power electronics specialists conference; 2004, p. 4285–90. [7] Yunwei L, Vilathgamuwa DM, Poh CL. Design, analysis, and real-time testing of a controller for multibus microgrid system. IEEE Trans Power Electron 2004;19(5):1195–204. [8] Chen C, Duan S, Cai T, Liu B, Hu G. Smart energy management system for optimal microgrid economic operation. IET Renew Power Generat 2011;5(3):258–67. [9] Ross M, Hidalgo R, Abbey C, Joós G. Energy storage system scheduling for an isolated microgrid. IET Renew Power Generat 2011;5(2):117–23.
[10] Bevrani H, Ise T, Miura Y. Virtual synchronous generators: a survey and new perspectives. Int J Electric Power Energy Syst 2014;54:244–54. [11] Aghamohammadi MR, Abdolahinia H. A new approach for optimal sizing of battery energy storage system for primary frequency control of islanded microgrid. Int J Electric Power Energy Syst 2014;54:325–33. [12] Serban I, Marinescu C. Battery energy storage system for frequency support in microgrids and with enhanced control features for uninterruptible supply of local loads. Int J Electric Power Energy Syst 2014;54:432–41. [13] Sigrist L, Lobato E, Rouco L. Energy storage systems providing primary reserve and peak shaving in small isolated power systems: an economic assessment. Int J Electric Power Energy Syst 2013;53:675–83. [14] Kumar L, Jain S. A multiple source DC/DC converter topology. Int J Electric Power Energy Syst 2013;51:278–91. [15] Wang Y, Li W, Lu J. Reliability of wide area measurement system. IEEE Trans Power Deliv 2010;25(3):1483–91. [16] Bose A. Smart transmission grid applications and their supporting infrastructure. IEEE Trans Smart Grid 2010;1(1):11–9. [17] Madureira AG, Pecas Lopes JA. Coordinated voltage support in distribution networks with distributed generation and microgrids. IET Renew Power Generat 2009;3(4):439–54. [18] Jupe SCE, Taylor PC. Distributed generation output control for network power flow management. IET Renew Power Generat 2009;3(4):371–86. [19] Abdulwahid U, Manwell JF, Mcgowan JG. Development of a dynamic control communication system for hybrid power systems. IET Renew Power Generat 2007;1(1):70–80. [20] Soultanis NL, Papathanasiou SA, Hatziargyriou ND. A stability algorithm for the dynamic analysis of inverter dominated unbalanced LV microgrids. IEEE Trans Power Syst 2007;22(1):294–304. [21] Hadjsaid N, Caire R, Raison. Decentralized operating modes for electrical distribution systems with distributed energy resources. IEEE Power & Energy Society General Meeting; 2009. p. 1–4. [22] TrueTime 2.0 beta 5 – Reference manual, Department of Automatic Control, Lund University, Sweden; June 2010. [23] Shahnia F, Majumder R, Ghosh A, Ledwich G, Zare F. Operation and control of a hybrid microgrid containing unbalanced and nonlinear loads. Electric Power Syst Res 2010;80(8):954–65. [24] Pecas Lopes JA, Moreira CL, Madureira AG. Defining control strategies for microgrids islanded operation. IEEE Trans Power Syst 2006;21(2):916–24. [25] Majumder R, Ghosh A, Ledwich G, Zare F. Load sharing and power quality enhanced operation of a distributed microgrid. IET Renew Power Generat 2009;3(2):109–19. [26] Mishra MK, Karthikeyan K. An investigation on design and switching dynamics of a voltage source inverter to compensate unbalanced and nonlinear loads. IEEE Trans Ind Electron 2009;56(8):2802–10. [27] Mishra MK, Karthikeyan K. A fast-acting DC-link voltage controller for threephase DSTATCOM to compensate AC and DC loads. IEEE Trans Power Deliv 2009;24(4):2291–9. [28] Xiaonan L, Guerrero J, Teodorescu R, Kerekes T, Kai Sun S, et al. Control of parallel-connected bidirectional AC–DC converters in stationary frame for microgrid application. IEEE Energy Convers Cong Expos (ECCE) 2011:4153–60. [29] Sao CK, Lehn PW. Control and power management of converter fed microgrids. IEEE Trans Power Syst 2008;23(3):1088–98. [30] Majumder R, Ghosh A, Ledwich G, Zare F. Control of parallel converters for load sharing with seamless transfer between grid connected and islanded modes, IEEE power and energy society general meeting – conversion and delivery of electrical energy in the 21st century; 2008. p. 1–7. [31] Majumder R, Ghosh A, Ledwich G, Zare F. ‘Power management and power flow control with back-to-back converters in a utility connected microgrid. IEEE Trans Power Syst 2010;25:821–34.