Hierarchical structure and bus voltage control of DC ...

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Hierarchical structure and bus voltage control of DC microgrid ⁎

Zhikang Shuaia, , Junbin Fanga, Fenggen Ninga, Z. John Shenb a b

National Power Transformation and Control Engineering Technology Research Center, Hunan University, Changsha 410082, China Electrical and Computer Engineering, Illinois Institute of Technology, Chicago, IL 60616, USA

A R T I C L E I N F O

A B S T R A C T

Keywords: DC microgrid Primary control Secondary control Tertiary control Hierarchical control scheme

Compared to AC microgrids, DC microgrids have the advantage of higher reliability and efficiency and are convenient to connect with various distribution energy resources (DERs). Concentrated in different time-scale control objectives, a multi-level control structure can guarantee that none of the control objectives affect each other. Considering this, an extensive review on the hierarchical structure of the DC microgrid is applied, and two typical control structures are presented in detail: two-level control architecture and three-level control architecture. Furthermore, the primary, secondary, and tertiary control levels are systematically analyzed and classified according to different control objectives. In order to improve the control capability of the primary control level, an energy efficiency improved DC bus voltage control strategy is proposed to increase the energy efficiency and system reliability. Finally, a distributed DC microgrid model is established and simulated in the RT-LAB to verify the effectiveness of the proposed control strategy.

1. Introduction Since the concept of microgrids was proposed [1], distribution DC microgrids have been attracting increasing attention. Integrated using various technologies including distributed renewable energy sources (RES), energy storage system (BES), loads, grid-connected voltage source converter (G-VSC), and control devices, and so forth, as shown in Fig. 1, the DC microgrids have become important in coping with energy shortage and environmental pollution [2]. Compared to AC microgrids, DC microgrids have many advantages such as high efficiency and reliability, while having no frequency, reactive issues [3], and it is easy to connect to DC micro-sources. Consequently, DC microgrids can be applied in a wide range of areas including residential buildings, data centers, island power supplies, communication systems, electric vehicles, and metro tractions [4–10] etc. Taking into consideration the wide application possibilities of DC microgrids, many researches have been conducted in various aspects, such as power topology, network planning, operational control, stability analysis, fault and protection [11–17]. In recent times, operational control has been the focus of the researches conducted on DC microgrids. As a result, many different operational control methods for the converters are proposed, and can be classified as the following: centralized control [18], master-slave control [19], multi-agent control [20], and distributed autonomous control [21]. From the research results [22], it can be concluded that the distributed autonomous control is the most suited method as the primary control for converters in the ⁎

DC microgrids. The reasons are as follows: (1) Less reliance on communication; (2) more autonomous; (3) more suitable for plug and play (PnP); (4) more flexible control configuration; Depending on the local conditions, the normal operation of a DC microgrid is a reasonable set of compromises on multiple control objectives. Thus, a hierarchical control structure was proposed to optimize the control of the DC microgrid [23], which is used for coordinating with multiple control objectives or optimal operation of the DC microgrid in various time-scales. Many scholars have made great efforts on the hierarchical control structure of the DC microgrid. However, as to the most appropriate hierarchical control structure for DC microgrids, there was no consensus reached. In general, hierarchical control structures can be classified into two major types: two-layer control structure and three-layer control structure. As described in [14], a typical three-level hierarchical control structure is as shown in Fig. 2. The definitions of each control level are as follows: (1) Primary control: It is the lowest level in the control structure, and it adjusts the voltage reference provided to the inner current and voltage control loops. (2) Secondary control: It is on the top of the primary control, and it mainly focuses on solving the problem of the voltage or current deviation. (3) Tertiary control: It is on the top of the control structure and is mainly responsible for the optimal operation of microgrid at the

Correspondence to: College of Electrical and Information Engineering, Hunan University, No. 2, South Lushan Road, Changsha City, Hunan Province, China. E-mail addresses: [email protected] (Z. Shuai), [email protected] (J. Fang), [email protected] (F. Ning), [email protected] (Z.J. Shen).

https://doi.org/10.1016/j.rser.2017.10.096 Received 23 October 2016; Received in revised form 8 August 2017; Accepted 28 October 2017 1364-0321/ © 2017 Elsevier Ltd. All rights reserved.

Please cite this article as: Shuai, Z., Renewable and Sustainable Energy Reviews (2017), http://dx.doi.org/10.1016/j.rser.2017.10.096

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Fig. 1. Diagram of a DC microgrid.

control manner at the global level [26–28]. As a consequence, the communication line is required in upper control level to collect the operation information from basic composition unit [29,30]. In this paper, a review of the hierarchical control structure of the DC microgrids is provided, and the primary, secondary, and tertiary control levels are systematically analyzed and classified according to the different control objectives in different hierarchical control schemes. For the existing problems in the DC bus voltage control method, a brief solution was also proposed. This paper is organized as follows. In Section Ⅱ and Ⅲ, the two-layer and three-layer control structures are reviewed, respectively. Section Ⅳ presents a summary of the autonomous control in primary control. A brief review of the DC bus voltage control strategy and improved DC bus control method is presented in Section Ⅴ, and the simulation results are presented in Section Ⅵ. SectionⅦ presents the conclusions and future trends of the hierarchical control structure.

Fig. 2. . Hierarchical control levels of a DCmicrogrid.

system level. In the hierarchical control structure, the main objective of the primary control is to ensure a normal and stable operation of each converter unit. The voltage versus current (V–I) Droop control [24] and DC bus signal (DBS) [25] control are the most commonly used control methods for primary control. Compared to other control methods, droop control and DBS control use the DC bus as a communication line, which could make the DC microgrid operation normal even under the failed communication or non-communication conditions. Under the premise of the basic function of converters is achieved, the secondary and tertiary control level are realized in a concentrated or distributed

2. Research of primary control In the hierarchical control structure, the distributed autonomous primary control can maintain the voltage stability of the DC bus without the communication line. As previously mentioned, the primary control level mainly focused on small time scale control problems, such as transient current /voltage control, instantaneous power sharing. For the requirement of a very short control response time, the primary control level is integrated with general of current and voltage control, and located in local converters. As shown in Fig. 3, the droop based 2

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vo = vref − RD⋅io − RL⋅io

From (1) and (2), we have to accept that the voltage deviation always exists in droop control, for the reason of unavoidable errors caused by the droop coefficient RD and line resistor RL . Besides, the load sharing accuracy and system stability have a direct correlation with the droop coefficient. The higher the droop coefficient, the better is the accuracy of current sharing and the larger is the voltage deviations [39]. In [40] the design of RD is discussed in detail. Using an analysis tool, literature [41] puts forward the idea that a tradeoff has to be made between the power sharing and DC voltage deviation. Even so, the conventional droop method still suffers from the drawback of poor current sharing and voltage regulation [42]. In addition, to solve the optimal droop coefficient, there are two additional approaches to enhance the performance of droop control.

Fig. 3. Primary control diagram.

primary control adjusts the voltage reference provided to the inner control loops, to maintain autonomous control for parallel operation control of converters. For different operating environments, different distribution autonomous control methods are used for primary control such as droop control [24], frequency allocation approach [24], and DC bus voltage method [25].

2.1.1. Nonlinear droop control The droop curve in the conventional droop control mentioned above is linear. However, many researchers propose to introduce a nonlinear droop curve to improve performance. In order to lower the influence of cable resistance, a nonlinear droop method is proposed [43], in which the value of droop resistance is a second-order function of the output current. In [44], a kind of droop control strategy based on the hysteresis characteristics is proposed to improve load power distribution accuracy. A nonlinear droop function that minimizes the operating cost of the microgrid and shares the reactive power effectively among the sources was proposed in [45]. Literature [46] proposes a robust droop control approach, which promotes the power sharing accuracy and minimizes the circulating current. In literature [47] and [48], an increasing DC-bus voltage and current feedback droop control method are proposed respectively, in which the DC-bus voltage and current signal are transferred to the droop controller to improve the accuracy of the power sharing. Generally, as reviewed in [49], nonlinear droop control can ensure a higher droop gain at heavy loads and lower values at lighter load conditions.

2.1. Droop method The application of the droop control method in multi-terminal DC systems was first seen in the literature [31]. As shown in Fig. 4, the V–I droop control method is realized by linearly reducing the output voltage as the output current increases, in order to compensate for instantaneous mismatch between scheduled power and power demanded by the loads without any communication technology. The output characteristics of the droop control scheme can be equivalent to a virtual resistor at the output of the converter [32]. This operational feature makes the droop method fit nicely to the primary control to achieve the autonomous operation of parallel-connected converters, especially, during the absence of communication lines. In addition, this feature makes it easy to realize the PnP capability. Moreover, the power versus voltage (P-V) droop method is also one of the common forms of primary control [33]. For specific control objects, a state-of-charge (SoC)-based droop method [34], in which SoC and droop coefficients are specifically correlated, was also adopted in the primary control. Typically, in the V–I droop control method, a virtual resistance or droop coefficient is adopted. Then, the output voltage vo is determined by the magnitude of the output current io and droop coefficient RD .

vo = vref − RD⋅io

(2)

2.1.2. Adaptive droop control Instead of a fixed droop coefficient value adopted in the conventional droop control, an adaptive variable droop coefficient was proposed. In this method, the droop resistance was adjusted to track the variation of the load current or power supply. An adaptive droop method was proposed to vary the virtual resistance in order to track the variation of the load current [50] between parallel-connected DC-DC converters. To enhance the effect of the power sharing for DC-DC converters, an instantaneous droop calculation algorithm is proposed [51]. In this method, the virtual resistance value instantaneously hinge on the converters output voltage deviation. However the introduction of negative resistance can lead to system instability [52]. In order to optimize the power distribution of a DC microgrid, a coordinated adaptive droop control is proposed [53], in which the droop coefficients hinge on the available headroom of each converter station. In addition, many other adaptive droop control methods are proposed such as fuzzy logic-based adaptive droop control [54], consensus algorithm-based adaptive droop control [55], and impedance-based adaptive droop method [56]. The adaptive droop control method is more flexible and more applicable, and suffers from less voltage deviations and power sharing errors, related to the conventional droop control. Therefore, as the droop control adopted in primary control, an upper control level is still needed to increase the control accuracy of the primary control, particularly when the distribution line impedances are not negligible [57]. On this occasion, an upper control level with a low-bandwidth communication line is needed to provide the voltage-regulated signal to eliminate the control deviation caused by the droop control [58].

(1)

Here vref is the output voltage reference at open circuit. As shown in (1), RD⋅io causes an output voltage deviation during the operation [35]. Then, in order to obtain better control performance, many scholars pay particularly attention to calculate the optimized parameters of droop coefficient RD , including literature [36,37]. In addition, the accuracy of load sharing is affected by the line impedance of the power system [38]. Taking into consideration the line impedance RL , from the load access point, the output voltage vo can be described as following:

Fig. 4. Principle of droop control.

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2.2. Frequency based control The conventional voltage droop control mainly aims at static power flow regulation, with no frequency-response based power flow control. However, in a DC microgrid, there are many distribution generations and energy storage system (ESS) integrated, and therefore, the dynamic behaviors of each unit are variable for different time scales [59]. In a battery and ultra-capacitor parallel-connected system, the battery and ultra-capacitor can be considered as a high energy density storage and high power density storage, respectively [60]. Based on this, a frequency-coordinating virtual impedance based control method for DC microgrid was proposed in [61], wherein the virtual output impedances were modified in different frequency-domains, the battery and super capacitor units are scheduled to absorb low-frequency and high-frequency power fluctuations.

Fig. 6. Operation modes of DC microgrid.

form of this method is called the mode-adaptive decentralized control, as shown in Fig. 6. The normal operating DC bus voltage range is divided into several sections or levels. Then, different control strategies are formulated in different sections for different micro sources. Thus, the key to the DBS method is to set reasonable control strategy rules for different voltage sections. Similarly, different scholars have their own comprehension on different bus voltage classifications. Usually, to get more flexible control targets, the bus voltage range is divided into several different intervals. As the DBS method is adopted in the DC microgrid, the different voltage levels are equal to different system operation modes [66]. In [64], a mode adaptive decentralized control strategy is proposed for the power management of a DC microgrid, in which the DC bus voltage signal is utilized to determine the mode conversion. In the method, three operation modes are set for the converters according to different voltage ranges. In different voltage layers, the pilot converters are switched to maintain the normal operation of the microgrid [67]. In general, the more the voltage level is formulated, the more flexible are the control options of the microgrid, and vice versa. In general, the DBS control method has the advantage of low cost and simple control, and it requires only non-communication techniques. However, there are several drawbacks of the DBS control strategy [63]. On the one hand, the normal range of voltage is limited and the voltage levels cannot be divided unlimitedly for sources and storages. In other words, the control modes of converters are rather few in number. On the other hand, voltage bus signaling can only be suitable for a small-scale microgrid with a limited number of sources and storages [25].

2.3. DC bus signal based control In a DC microgrid, various micro sources, loads, and energy storage units are connected to the DC bus in parallel. With the line resistance ignored, the voltage of the DC bus can be regarded to be equal everywhere. Thus, all the parallel-connected converters can get the same voltage reference. By detecting the DC bus voltage signal, the working status of each converter can be derived [62]. The implementation of the DBS method can be achieved without the need for the communication lines. It uses the DC cable as a communication carrier. In the DBS control method, the ranges of the operating voltage are generally divided into pre-defined sections, which are named as voltage level or operation mode. As presented in [63], different DC bus voltage levels can be regarded as an information carrier and they can dictate different operation modes. Particularly, with the pre-specified control rules, the DBS method can realize the autonomous control for each parallelconnected converter. Fig. 5 is the current distribution diagram with equivalent powers of the DC microgrid. According to Kirchhoff's current law (KCL), (3)

IC = Is − IL The deformation of (3) can be

IC = C⋅

dVC dt

(4)

Eq. (3) can be rewritten as:

dVC 1 = ⋅(IS − IL) dt C

3. Two-level control structure

(5)

From the voltage change ratio in Fig. 5 and Eq. (5), the balance of the power in the microgrid can be observed. When the load power is greater than the output power of micro sources, the voltage decreases and vice versa [64]. An improved DBS method is proposed in [65], the switching frequency of a grid-connected DC/DC converter was used as the operating information for the DC microgrid components. Another

Hierarchical control for power distribution has been widely applied in traditional AC power systems [68]. However, in power electronic converter-based DC microgrids, there is no frequency, reactive power and phase problem They are often ignored in dynamic stability [69], and these advantages make the traditional AC hierarchical control structure to be modified to meet the DC microgrid. In the two-level control structure, proportional load sharing, voltage regulations, circulating current avoidance, SoC equalization, and charge/discharge management are the main control objectives in the primary control level. Generally, various droop control methods and DBS methods are applied in the primary control. However, as mentioned above, the voltage deviation and current sharing errors inevitably exist [70]. In order to rectify these problems, an upper level controller, usually named as secondary control level was adopted. As shown in Fig. 1, load sharing and voltage regulation between parallel converters are achieved by the primary controller without a communication line. For getting better control effect, a secondary control level is introduced into the control structure, which sets the reference to the primary control and maintains the controlled parameter within an optimization range, As showing in Fig. 7. Fig. 7 Typical two-level control structure.

Fig. 5. Powerflow of DC microgrid.

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Fig. 7. Typical two-level control structure.

with constant power loads (CPL). A secondary controller is then set to compensate the voltage deviation without affecting current sharing accuracy. To overcome the drawbacks of the conventional droop control method in the DC microgrids, a secondary control level is proposed to restore the DC voltage deviation and to improve the current sharing accuracy by adjusting the droop coefficient [81]. In addition, [82] proposes a two-level control strategy of the grid connected DC microgrids, in which a DBS and SoC-based droop method is applied in the primary control, and then, by shifting the droop curve, the secondary controller can restore the DC bus voltage and SoC to the nominal value.

Generally, as an upper control level, the secondary controller can be divided into two forms. The first one is integrated with the primary control and is located in the power converter and the other is located remotely [71,72]. In comparison, based on the primary control，the control objective of the secondary control is more flexible and diverse than the primary control. The main optimization objective of the secondary control can be described as follows. 3.1. Voltage deviation restoration In the existing studies, many scholars hold that the main task of the secondary control level is to cover the voltage deviation, which is caused by the virtual impedance based droop control [73]. As shown in Fig. 2, the secondary control level in the microgrid set the voltage regulation factor δvo to all units connected to the DC microgrid [74]. Then, Eq. (1) can be rewritten as:

vo = vref − RD⋅io + δvo

3.1.1. Optimal power flow In a DC microgrid, an optimal power flow (OPF) between converters is also the pursuit of many researchers. The optimal power flow algorithm can be considered originating from the AC power system [83]. Generally, the OPF algorithm in the secondary control depends on the grid's conductance matrix and load distribution matrix [84]. In this control architecture, different objective functions can be adopted in the secondary control, such as transmission loss minimization [84,85], minimal power losses [86], and maximum loadability [87]. As the voltage droop-based primary control is adopted in the multi-terminal DC (MTDC) grid, an OPF algorithm is executed at the secondary control level [85], and the converters update the voltage regulator set point to improve the power flow sharing. In such a case, the voltage-droop characteristics curve of the primary control could be modified according to the OPF results [88]. In multi-terminal DC transmission systems, the power balancing between converters is controlled by a voltage-droop controller. However, the control effect of primary control is easily affected by the DC microgrid topology and line resistances. Aimed at this issue, [89] proposes a secondary control strategy to restore power flow at certain converters to presuppose operating points. In a renewable energy source (RES) integrated HVDC transmission system, to keep the power flows in the transmission cables within the thermal limits after disturbance, a secondary controller is set to change voltage and power settings of the primary controllers [90]. To minimize the transmission loss of a DC microgrid, [91] proposes a power flow sharing and voltage regulation control based hierarchical structure. Herein a voltage-droop based primary control is utilized to improve the stability and reliability of the grid, after which two voltage regulation signals generated by the secondary control layer are sent to the primary controller to regulate the power flow of the DC microgrid to the optimal condition. However, under this condition, the complexity of this control method increased.

(6)

As described in Eq. (6), by introducing the variable δvo , the output voltage vo can be improved significantly, to achieve the objective of voltage restoration. In a droop control based high voltage direct current (HVDC) grid [75], current sharing is achieved by the droop-based primary control, and to restore the DC bus voltage deviation, five different schemes for secondary control level are proposed and compared. To realize the DC bus voltage regulation with low reliance on communications in a dedicated paralleled flywheel-based energy storage system, the DBS method is employed in the power coordination of the grid and flywheel converters as primary control. Then, through a dynamic consensusbased voltage observer, the secondary controller generates the DC bus restoration signal to adjust the voltage set-point [76]. In order to avoid the single point of failure problem, a consensus algorithm-based distributed secondary control method was proposed in [77], in which, the compensations of current and voltage are send to the droop-based primary control. Specific to the single point of failure, an interesting solution was proposed in [78], in which the fault current was well restricted. To avoid the over-charging and over-discharging states of the ESS in the islanded DC microgrid, based on the bus-signaling method-based primary control, an additional secondary control is employed to eliminate the steady state bus voltage deviation [79]. In [80], a voltage droop based primary controller is utilized to implement the current sharing of the parallel-connected buck converters in a DC microgrid 5

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Fig. 8. Typical three-level control structure.

uppermost shortage is that complex or multi system-level control target cannot be realized, because of the limited control level. As a consequence, the most common objective of the secondary control is to bring the controlled converter back to scheduled operating conditions. However, the restoration of voltage and power deviation helps in the normal operation of the DC microgrid. However, this does not mean optimal operation [84], but the two control objectives can easily be achieved if an extra control level is provided.

3.1.2. Power sharing and management Many scholars consider that the objective of the secondary control is to achieve accurate power sharing and optimal management among parallel-operated converters in a DC microgrid. As stated in [92]，the energy management system (EMS), which is the brain of the DC microgrid, can comprehend operation status, load forecasting, operating cost, and optimal schedules based on the output power information. In [92], a series of functions and constraints is calculated in the secondary control, decisions about powers and the exchange between distribution networks are transferred to the lower level. The same control idea is adopted in [72], the secondary controller shares its reference power/ current signals to the droop controller, then the droop coefficient is dynamically adjusted to improve the power sharing in DC microgrid. For example, in a RESs integrated DC microgrid, a sliding mode control (SMC) and a supervisory controller are scheduled in order to maximize the use of the RES and minimize the connection to the grid [84]. In the control process, the sliding surfaces, and set point of SMC are optimally changed by the supervisory controller according to the operating conditions. However, the utilization of the SMC as the primary control greatly increases the control complexity. [93] Presents a generalized voltage droop control strategy for a VSC-based DC microgrid. To improve the power-sharing capabilities of primary control, a centralized secondary controller is implemented to regulate the droop characteristics. To eliminate the influence of line resistance and improve the accuracy of power distribution in a bipolar-type DC microgrid, the droop-based primary control is utilized to achieve parallel operation of converters then a distributed secondary control provides the voltage and current restoration signal to improve the power distribution [94]. Furthermore, except for the abovementioned applications, the twolevel control structure is also applied to hybrid energy storage systems (HESS). In a multiple-parallel energy storage system [95], based on charge/discharge monitoring and SoC detection, the distributed secondary controller alters the virtual droop resistance of each storage unit according to the difference between the unit SoC and the microgrid average SoC. However, the biggest difficulty that lies in this control structure is the precise estimation of SoC for each storage unit. Based on the primary control, a secondary control is implemented to obtain a better control performance, such as restoration of the voltage deviation caused by primary control, better current and power sharing, and power flow optimization. To connect the primary control with secondary control, a communication line was required [96], whether in concentrated or distributed secondary control level. As to the disadvantages of a two-level control structure, the

4. Three-level control structure According to the hierarchical intelligent control theory [97], a three-level intelligent control structure with the organization, coordination, and execution level was developed. By combining the hierarchical intelligent control theory and conventional hierarchical control of the AC grid with the inherent characteristics of the DC microgrid, many researchers have proposed various three-level hierarchical control structures for the DC microgrid. Considering the weakness of a single optimization objective, in twolevel control structure, many intellectuals put forward a three-level control structure for a DC microgrid, a typical three-level control structure is proposed and shown in Fig. 3. As shown in the figure, the main objective of the primary control is to realize power sharing and to improve stability of the parallel-connected converters. Based on this, a secondary controller is used to deal with the voltage deviations caused by primary control, and power-sharing accuracy improves simultaneously. After this, a third-level or tertiary control was applied into the control structure, which adjusts the set points for the secondary controller to achieve an optimal, economic, and efficient operation of the DC microgrid. Fig. 8 Typicalthree-level control structurent. Based on the primary and secondary control level, for different situations, various control objects for the tertiary control are proposed including economic and efficient operation, global energy management, optimal power flow, and other system-level objectives. 4.1. Optimal or efficiency operation Similar to a conventional AC grid, the economic and efficient operation of a DC microgrid is an objective many researchers generally pursue. To explore a feasible DC control system for enhancing economic efficiency and the resilient operation of a DC microgrid [98], three-level hierarchical control architecture is proposed and tested. As mentioned before, V–I droop is utilized as the primary control, a secondary control level is used to compensate the voltage deviations, and the economic 6

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4.3. Energy management between grids

operations of DC microgrids is realized by the tertiary control by setting the operating point for the secondary control. As described in [83], the secondary control is disabled in the grid-connected mode since the voltage is maintained by the utility grid. However, it does not mean that the voltage deviations in the grid-connected mode are nonexistent. The same control architecture is also utilized in [99] aimed at the parallel operation of distribution energy resources. As mentioned above, based on the droop-based primary control and voltage deviations compensated by the secondary control, the tertiary controller worked simultaneously in the one-day-ahead dispatch and real-time-operation dispatch to achieve an economic and optimal operation of the microgrid. However, both the secondary and tertiary controller work in realtime mode, and therefore, a high-speed communication is required. To maintain system power balance in hybrid AC/DC microgrids, [100] proposes three-level control architecture with different control strategies for AC and DC subgrid. In this method, voltage and frequency droop-based autonomous control is scheduled for AC and DC subgrid as the primary control respectively. Then, the secondary control is used to recover the deviations of the bus voltage and frequency, based on the comparison of marginal costs. The optimal power references of system units are generated in tertiary control to achieve the power balancing. However, with the secondary and tertiary control connected in parallel, conflicting priorities may exist. Similar control strategies are also applicable in multi-terminal energy storage systems. In [101], a multilevel energy management system (EMS) is proposed to achieve a superior performance for DC microgrids. In addition, stable operations of the microgrid and compensation controls are realized by the primary and secondary control, respectively. On this basis, the optimal economic dispatch signals are generated in the tertiary control level according to the comparison of marginal costs of the system operation. Thus, the operation costs of DC microgrids can be minimized.

With the development of DC microgrids, there is an increasing need for managing the power flow between DC microgrids and other stiff grids or microgrids. As a representative three-level control structure [106], a droop method-based primary control is adopted to make the system stable and more damped. The secondary control level is used to restore the deviations that are caused by the primary control. Finally, the power flow between the microgrid and other distribution systems is conducted by the tertiary control. Owing to the introduction of tertiary control level, the optimal energy flow of the DC microgrid is assured. In an AC and DC hybrid microgrid, the same primary and secondary control strategy mentioned in [106] is implemented, and the tertiary control is adopted to improve the performance considering the connection to a stiff AC or DC source by providing a compensating parameter to the secondary control level [31]. In an AC and DC bus hybrid microgrid, with the same primary and secondary control strategy mentioned above, the tertiary control is scheduled to deal with the connection with an external DC system [107]. Aiming at a community microgrid with multiple AC and DC sub-microgrids, the hierarchical control structure is proposed to achieve the economic and coordinative control.especially, the tertiary control is implement to ensure the optimal coordination of an islanded community microgrid [108]. As mentioned above, the tertiary control level conducts the power flow according to the system requirements; however, the energy interactions with other micogrids are neglected. To resolve this problem, a three-level control method is proposed to improve the load sharing among microgrids within a microgrid cluster [109]. In the control scheme, the load sharing among various sources within the DC microgrid is managed by primary and secondary control. A tertiary control is applied to adjust the voltage set point for each sub-microgrid, and then the power sharing between multiple DC microgrids within a cluster is achieved. Compared to a two-level control structure, the three-level control structure has inherent advantages that enable it to achieve more complex control targets, especially the optimal control for DC microgrid at the system level and the power flow management between microgrids. In the two-level and three-level control scheme, the same primary and secondary control objects exist, such as power sharing, stable operation in primary control, voltage restoration, and energy management in secondary control. Generally, an autonomous distributed control strategy is universally adopted in the primary and integrated with local converters. The secondary and tertiary control can be divided into decentralized and centralized, wherein one integrates with the primary control in a decentralized way, and the other uses the communication line connected to each converter in a centralized way [110]. In masterslave and multi-agent control, the operation of the microgrids depends on the fast communication technique. The failure of communication results in the collapse of the whole microgrid. However, in the failure of communication, the fundamental function of hierarchical control will be guaranteed by the autonomous decentralized primary control. This is the main difference between the hierarchical control and conventional control method.

4.2. Energy management among converters In addition, for that the multiple renewable and micro energy sources are installed at different locations, the energy management among converters within a DC microgrid in the system level is also a concern for many scholars. In [102], a three-level control strategy that fits the smart house is proposed, based on the droop-based primary control and the voltage deviation compensation in the secondary control. To provide a better control performance for renewable energy generation and load sharing, the tertiary controller provides optimal power flow control by changing the voltage reference to the secondary control level. In general, the control architecture in [102] is widely used in many literatures. However, it can be observed from analyzing the function that better use of the tertiary control level can be achieved. A similar control structure is also introduced to the hybridization of energy storages system (HESS) to minimize system bus voltage variation and extend the ESS lifetime in a DC microgrid [103]. Based on distributed primary control, a bus voltage restoration is implemented in the secondary control, after which the tertiary control is used to recover the SoC autonomously. However, the energy management of HESS is just a part of the entire DC microgrid. With the same primary and secondary control structure applied to DC microgrids, [66] holds that the tertiary control could be used to deal with extreme operational conditions such as sudden load, load shedding, or ballast. However, within this control framework, it places greater demands on on-line real-time processing. In [104] and [105], a hierarchical power management scheme is proposed for a typical DC microgrid, in which the primary control is used to implement distributed operation. Then the voltage restoration is achieved in the secondary, and the tertiary control is adopted to manage the battery charge and discharge or system energy management. However, in this scheme, the secondary control is connected in parallel with the tertiary control, which indicates they are operated at the same precedence level.

5. Energy efficiency improved DC bus voltage control 5.1. Research of DC bus voltage in primary control As mentioned above, in a hierarchical control structure the normal work of secondary and tertiary control depends on the communication line. In order to ensure the safety and stability of the DC microgrid, decentralized autonomous control in the primary control is required [110]. Without regard for phase, frequency, symmetrical and asymmetrical [111] problems of the DC bus voltage, the power balance management can be considered as the DC bus voltage adjustment. To ensure normal operation of the DC microgrid, the value of the DC bus 7

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voltage must be kept within a reasonable range [112]. In a DC microgrid，there are two main selections for the DC bus voltage base value: 380 V [113] and 400 V [114], and the normal operating range is defined as a deviation of less than 10% [115]. Generally, DC microgrids comprise of GVSC, new energy power generator, auxiliary power generator, energy storage system, and load. There are multiple possibilities as to which of these components mainly controls the DC bus voltage. In grid-connected states, there is an emerging consensus that the GVSC unit is supposed to maintain the DC bus voltage. However, in the island mode, there are a number of solutions to realize the stability of DC bus voltages. During the operation of a DC microgrid, over-voltage and under-voltage is a key issue in the DC bus voltage control, which indicates the power balance between the source and the load. In the case of over-voltage, new energy power generation has to be restricted and then combined with DER to maintain the DC bus voltage balance in a normal range [115]. However this decreases the utilization of new energy. In the case of under-voltage, non-critical load is disconnected according to the DC bus voltage. As proposed in [116], a controllable DC load is utilized for dc-bus voltage regulation for a dc distribution system with providing the demand response requirements. In this process, a BES is usually adopted to balance the power supply and demand. However, based on the current technical conditions, there is still the possibility that the BES can run out of its capacity easily [117]. Another limitation of conventional control strategy is that the capability for peak clipping of BES is seriously affected by the SoC [46,118].

Fig. 9. Threshold of each mode.

voltage range of 1.0 p.u–1.05 p.u. Mode 4: In the grid-connected mode, the DC bus voltages are maintained by GVSC. In the off-connected mode, the bus voltage drops into Mode 5. Mode 5: In this mode, the DC bus voltage is maintained by DER and BES. Overall, the improved DC bus voltage control method is summarized as follows: In the high DC bus voltage, the DER, TSS, and the G-VSC are employed to absorb the excess energy. During the process, renewable energy units continue working in the MPPT state. With the insufficient power supply, the G-VSC and BES are employed to provide energy in grid-connected mode. However, in the island mode, the BES units are responsible for the energy deficient, and the operation voltage is decreased properly to lower the power consumption of resistive loads. To prolong the time of the power supply under the off-connected condition, the BES is set to keep charging in Mode 3.

5.2. Energy efficiency improved DC bus voltage control In this section, an improved DC bus control method is proposed, in which a thermal storage system (TSS) is introduced and connected to the DC bus by a buck converter to achieve the peak clipping operation. By detecting the DC bus voltage, the variable duty cycle control for buck converter is achieved, and then the equivalent resistance of TSS that is connected to the DC bus is mutable. In this case, even in the situation of high bus voltage, the TSS and BES could achieve the peak clipping for DC microgrid. Hence the new energy resources could work in the MPPT state all the time and enhance the utilization of new energy. On the contrary, the TSS is off-connected to the DC bus in the condition of low DC bus voltage, which contributes to the restoration of the DC bus voltage. In the DBS method, a different voltage level is employed as an indicator to different control modes. In this paper, the voltage of Vn ± 10% is considered within normal limits [115], and the voltage range is divided into five layers. To distinguish each voltage layer, they are named as mode I (M1), mode II (M2)…mode V (M5), from high to low, and correspond to voltage ranges of: 1.1 p.u–1.075 p.u, 1.075 p.u–1.05 p.u, 1.05 p.u–0.95 p.u, 0.95 p.u–0.925 p.u, 0.925 p.u–0.9 p.u, as shown in (Fig. 9). In each voltage mode, different priorities of converters are presented in Fig. 9. Furthermore, the higher priority of the converters implies that the unit response to the DC bus in a lower voltage deviation (Fig. 10). Combined with Fig. 9 and Fig. 10, the following control strategy can be derived.

6. Experimental validation To verify the proposed improved DC bus signal control method, a model of DC microgrid is built by the RT-LAB. As shown in Fig. 11, leadacid battery, photovoltaic array, wind power generation, thermal storage system, and loads are adopted to the system. Particularly, we introduce a 2 kW constant power load, which accounts for 20% of the total load and the remaining 80% is resistive load. Besides, the normal range of the DC bus voltage is set in the range of 400 ± 10% V. This article selects the off-connected microgrid as the subjects of the simulation because it is a more challenging job to maintain the DC bus voltage without the support of the stiff grid. 6.1. Island state with maximum load In this case, the total load of the DC microgrid is composed of resistive and constant power load to test the maximum power output of 10 kW at the off-connected mode. Fig. 12(a) shows the DC bus voltage variation with output fluctuations of new energy generations. With the maximum load connected, the DC bus voltage is below the rated voltage, but remains in the normal voltage range. Fig. 12(b) shows the output fluctuations of the wind power and the photovoltaic. By detecting the DC bus voltage, the control signals for the converters are given in Fig. 12(c). As a response to the control of the reference signal, the output curve of TSS and BES is given in Fig. 12(d). Through the analysis of Fig. 12, when the bus voltage is above 400 V, the BES is set to charging mode. With an increase in the DC bus voltage, the TSS and BES are whipped into service. With the insufficient new energy power supply, DC bus voltage drops to Mode 5, and then the BES coordinated

Mode 1: A relative high voltage deviation exists and new energy generations are operated in the MPPT mode, with the cooperative operation of DER, TSS, and G-VSC. The DC bus voltage is restricted to 1.1 p.u. Mode 2: The new energy generation is operated in the MPPT mode, with the cooperative operation of BES and TSS. The DC bus voltage is restricted to 1.075 p.u. Mode 3: The voltage range is divided into two parts. In order to maintain a high SoC, the BES is kept at a charging state in the 8

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Fig. 10. Control strategy for converters.

structures of the DC microgrid and DC bus voltage control. By reviewing the existing literatures, the primary, secondary, and tertiary control is systematically analyzed and classified. In the hierarchical control structure, various control objectives can be set flexibly in each control level, according to the different application fields. Finally, based on the previous analysis, we can still draw some general conclusions:

with the DER is responsible for the voltage restoration. 6.2. Island state with step load In this case, DC microgrid started with a 4-kW resistive load and 2kW constant load. To test the disruption recovery, at 10 s, a 4-kW resistive step load was connected to the DC bus. Fig. 13(a) shows the voltage change when the step load is connected to the DC bus. Before it is accessed, the DC bus voltage is in a relatively high level with the light load, and after that, the DC bus voltage drops when the step load is connected. Fig. 13(b) shows the output fluctuations of new energy. The control signals for converters are given in Fig. 13 (c), according to the DC bus voltage signal. The output curve of TSS and BES is shown in Fig. 13(d). With a sufficient electric energy supply, the TSS and BES are implemented to the balance in the power. As soon as the DC bus voltage sags are detected, the TSS disconnects from the DC bus and BES switches to the discharge mode. From Fig. 13(c) and (d) it can be inferred that, in a light load, DC bus voltage is relatively higher than Fig. 13(a) showed, and then the BES and TSS absorbs more energy from the DC bus. When the step load is connected to the DC bus at 4 s, the TSS reduces the power absorption instantly.

(1) In hierarchical control structures, a communication line is required in both two-level and three-level control structures. Limited to the existing communication rate and reliability, the real-time control of different time scales in the DC microgrid is difficult to realize simultaneously. With the development of communication, the boundary of each control level shows a weakening tendency. (2) When the performance of the micro-programmed control unit (MCU) is improved, more control goals can be achieved in the local converter, the requirement of distributed optimization techniques is achievable. The development possibility of the DC microgrid control structure is flattening, digitalization, and integration. (3) In a DC microgrid, instantaneous DC bus voltage signals contain useful information for the operating states prediction. In the process, the intelligent estimation method can be adopted. (4) With the development of artificial intelligent technology, optimization of DC microgrid operation will obtain better control results. (5) To improve the distributed energy resource utilization efficiency,

7. Conclusions and future trends This paper provides an extensive review on hierarchical control

Fig. 11. Configuration of the experiment.

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Fig. 12. Simulation results with maximum load. (a) DC bus voltage. (b) Output of new energy. (c) Power reference signal. (d) Power response of converter.

Fig. 13. Simulation results with step load. (a) DC bus voltage. (b) Output of new energy. (c) Power reference signal. (d) Power response ofconverter.

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combined cooling, heating, and power system is a feasible and reasonable solution.

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Fenggen Ning received the B.S degree in electronic and information engineering from Hunan University, Changsha, China, in 2014, where he is currently pursuing the M.S degree in power electronics in the College of Electrical Engineering. His research interests include voltage control and droop control in dc microgrids.

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Z. John Shen (S′89-M′94-SM′01-F′11) received BS from Tsinghua University, China, in 1987, and M.S. and Ph.D. degrees from Rensselaer Polytechnic Institute, Troy, NY, in 1991 and 1994, respectively, all in electrical engineering. He was on faculty of the University of Michigan-Dearborn between 1999 and 2004, and the University of Central Florida between 2004 and 2012. He joined the Illinois Institute of Technology in 2013 as the Grainger Chair Professor in Electrical and Power Engineering. He has also held a courtesy professorship with Hunan University, China since 2007; and with Zhejiang University, China since 2013. His research interests include power electronics, and power semiconductor devices, etc. Dr. Shen has been an active volunteer in the IEEE Power Electronics Society, and has served as VP of Products 2009–2012, Associate Editor and Guest Editor in Chief of IEEE Transactions on Power Electronics, technical program chair and general chair of several major IEEE conferences.

Zhikang Shuai (S′09-M′10-SM′17) received the B.S. and Ph.D. degree from the College of Electrical and Information Engineering, Hunan University, Changsha, China, in 2005 and 2011, respectively, all in electrical engineering. He was with the Hunan University, as an Assistant Professor between 2009 and 2012, and an Associate Professor in 2013. Starting in 2014, he became a Professor at Hunan University. His research interests include power quality control, power electronics, and Microgrid stability analysis and control. Dr. Shuai is a recipient of the 2010 National Scientific and Technological Awards of China, the 2012 Hunan Technological Invention Awards of China, the 2007 Scientific and Technological Awards from the National Mechanical Industry Association of China.

Junbin Fang received his B. S. and M. S. from the College of Information Engineering, Xiangtan University, Xiangtan, China, in 2012 and 2015, respectively. He joined the Hunan University as a Ph.D. student in 2015, where he is currently pursuing the Ph.D. degree in the College of Electrical and Information Engineering. His current research interests include renewable energy, DC power systems and energy management in distribution systems.

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