Control Strategy For DC Microgrid Research Articles

Secondary Control Strategies in the DC Microgrids

Now, DC microgrids have become more popular for several reasons, including the lack of issues related to reactive power and frequency control, the direct integration of energy storage devices and solar photovoltaic, and the higher utilization of DC loads. A DC microgrid using several sources (distributed generation) is a popular research area. The main issue in such a DC microgrid is to provide good voltage regulation and proportional power sharing among all sources. Control strategy is very important to solve the above issue in order to maintain the reliability and stability of DC microgrids. Hence, a comprehensive review of DC microgrid control techniques is essential. Compared to other methods, hierarchical control is widely used to solve the aforementioned issue. It consists of three layers of control: primary control, secondary control, and tertiary control. At the primary level, to improve current sharing performance, droop control is usually applied. Secondary control is used for voltage regulation of the DC bus. A tertiary control is a higher-level control to achieve Optimization and economical grid operation. In traditional primary control, it is not possible to attain accurate power sharing and voltage regulation simultaneously. Thus, secondary control is required. So, this paper reviews the secondary level control techniques in the hierarchical control strategy for DC microgrids. Precisely, Centralized, distributed, and decentralized approach-based secondary control are reviewed. Several secondary control techniques have been thoroughly examined in terms of their advantages and disadvantages making this an excellent resource for both academics and business executives.

Retracted

Retracted

Edge computing and hybrid control technology for microgrids based on activity on edge networks

AbstractEdge‐side services provide new ideas for microgrid operational control, but as the microgrid control structure becomes increasingly large, the cost of configuring edge‐side services also grows. In this context, it is necessary to find a modelling approach that can unify the mathematical models involved in microgrid control systems. First, a microgrid control structure with edge‐computing services based on hybrid control theory is proposed, which can exploit the hybrid characteristics of the microgrid control and reduce the amounts of communication using event‐triggered technology. Then, a hybrid control modelling method based on activity‐on‐edge networks is proposed, along with a standardised control strategy configuration method. The texts entered by the configurator can be parsed in an intuitive way. Complex control strategies can be configured with low‐code input while improving the reliability of the strategies. Finally, a distributed control strategy for DC microgrids was studied and modelled using the hybrid control modelling approach based on activity‐on‐edge networks. The superiority of edge‐computing services based on hybrid control theory and event‐triggered technology in reducing communication and improving control in real time is demonstrated through the case study.

The coordinated control strategy of DC microgrid based on multiple energy storage units

Recently, the DC microgrid (MG) has caught people’s attention because of its simpler control system than the AC microgrid. In this paper, the bus voltage layering control method based on droop control is used for DC microgrid coordination control. According to the working characteristics of the DC bus, the voltage of the DC bus is divided into five sections, corresponding to 5 operating modes respectively. Inside the DC microgrid, each unit converts the operation mode by local control according to voltage amplitude. The photovoltaic power generation unit adopts MPPT control and constant voltage control to adjust the running point tracking, so as to realize changing-over smoothly between voltage regulator mode and MPPT. The battery system adopts a hierarchical operation control method of several batteries on the basis of the state of charge (SOC). To realize the target, which means getting rational active power allocation and SOC equilibrium of each battery unit, as well as different batteries changing-over the charge and discharge modes on the basis of SOC size, so as to adjust the droop curve according to the power size. Finally, the balance between the three objectives of the highest photovoltaic energy utilization rate, energy storage SOC balance, and stable bus voltage is achieved.

Distributed Data-Driven Secondary Regulation for the Conflict Between Voltage Recovery and Accurate Current Sharing in DC Microgrids

The problem of voltage restoration and current balancing has been a hot topic in the study of DC microgrids (MGs), and how to engineer a secondary controller to solve the conflict between these two is the concern of this paper. With the above consideration, an optimal distributed data-driven secondary control strategy is proposed in this paper, which relies entirely on the input and output (current measurements) data of DC MGs. The proposed framework completes the design of a secondary control strategy for DC MGs based on a data model for the first time, which incorporates the physical coupling relationship between voltage and current into the controller design and is independent of the global circuit parameters and topology information. As a result of the proposed cost function with future current prediction, the designed secondary control strategy not only retains the advantages of consensus control, such as facilitating the plug-and-play of generation units, but also enables DC MGs to achieve better output current quality at steady state, fast dynamic response and improves robustness to external disturbances. Unlike the existing schemes based on average voltage observer, this paper resorts to a combination of limiting the voltage reference value generated by the secondary controller and a current cooperative strategy based on the learned data model to achieve an easy-to-use trade-off between the two objectives of voltage regulation and current sharing in DC MGs. From the design and implementation point of view, the solution proposed in this paper is going to be simpler. Then, an analytical model of a closed-loop DC MG system under the proposed control scheme is developed, and the analysis of stability and consensus of weighted output current is given accordingly. Finally, the proposed control strategy is tested on a hardware DC MG system with solar panels and an MPPT controller to verify its feasibility.

Power pool‐based supervisory coordinate control strategy for DC microgrids

SummaryStandalone DC microgrids are progressively becoming explored in the modern power system. Proper voltage regulation and effective power distribution among sources are the main challenges for DC microgrid operation. A supervisory coordinated control strategy for proportionate power‐sharing and enhanced voltage regulation is presented in this paper to overcome these challenges. The formation of multiple power pools on the basis of available power from each renewable energy source (RES) is a crucial element of this approach. It modifies the power sharing between power pools and individual sources based on the amount of power available in the sources. In addition, for effective power management, it coordinates the operation of all power pools with all RESs. Also, by reducing the charging and discharging cycle of energy storage systems (ESSs), it is possible to make effective use of ESSs. The proposed control adapts to intermittent RESs and changes in the microgrid network. The proposed method's capabilities are validated by experimental results.

Distributed Autonomous Economic Control Strategy for DC Microgrid

A distributed autonomous economic control strategy is proposed to realize the economic operation of the DC microgrid in the islanded state. The control strategy first introduces incremental cost in primary control, but due to the influence of line impedance, it is not possible to precisely achieve the consensus of incremental cost at each unit, and it generates a steady-state error. To overcome this problem, a distributed secondary control based on a dynamic consensus algorithm is designed on the basis of primary control, which makes each distributed generator operate under equal incremental cost. The two layers of control strategies cooperate work together to realize the hierarchical-distributed autonomous economic operation of the DC microgrid. Finally, the simulation model of the DC microgrid is constructed, which verifies the effectiveness of the proposed method.

Multi-layer Voltage Control Strategy for DC Microgrid without Communication

This paper presented a multi-layer voltage control strategy for a stand-alone DC Microgrid. The unbalanced power of the system is compensated by the hybrid energy storage. The bus actual voltage is used as a message to implement the coordination of various terminals. By dividing the bus voltage, different voltage layers correspond to different working modes of each terminal of the system. The novelty of the presented control strategy is that the energy management performance of the DC Microgrid is improved, which is independent of the communication link. The DC Microgrid model is established in MATLAB/Simulink environment, and the simulation result shows that the presented strategy is feasible under different setting scenarios.

Energy management and control strategy of DC microgrid based hybrid storage system

In this paper, a method of energy management shared with storage devices in a standalone DC microgrid is presented. The objective of management is to satisfy the energy demand in addition to guaranteeing a production/consumption balance with good regulation and stability of DC bus voltage. Another advantage of the energy management method lies in the consideration of losses in the static converters by calculating the effective power available on the common DC bus. The proposed control strategy takes advantage of non-linear control by combining fuzzy logic control for the extraction of the maximum power from the photovoltaic and wind sources, while sliding mode control is used for the control of the storage power converters. The control of the power flow of the common DC bus allowed good stability of the bus voltage with small deviations around the desired value, limiting the battery stress since the low-frequency current component is sent to the battery while the higher-frequency power component is directed to the supercapacitor. The simulation results show the validity of the proposed energy management and control strategy.

Research on Virtual DC Generator-Based Control Strategy of DC Microgrid with Photovoltaic and Energy Storage

With the penetration of a large number of photovoltaic power generation units and power electronic converters, the DC microgrid shows low inertia characteristics, which might affect the stable operation of the microgrid in extreme cases. In order to enhance the “flexible features” of the interface converter connected to the DC bus, a control strategy of DC microgrid with photovoltaic and energy storage based on the virtual DC generator (VDCG) is proposed in this paper. The interface converters of the photovoltaic power generation system and the energy storage system simulates the inertia and damping characteristics of the DC generator to improve the stability of the DC bus voltage. The impedance ratio of DC microgrid was obtained by establishing the small-signal model of photovoltaic power generation system and energy storage system, and the Nyquist curves was applied to analyze the small-signal stability of the system. Finally, the simulation results were verified with MATLAB/Simulink. The results show that the proposed control strategy can slow down the fluctuation of bus voltage under the conditions of photovoltaic power fluctuation and load mutation, thus enhancing the system stability.

A Robust Cooperative Distributed Secondary Control Strategy for DC Microgrids With Fewer Communication Requirements

This article proposes a robust cooperative distributed secondary control strategy for dc microgrids, with the main focus on reducing communication burdens. To this end, we adopt a sparsity-promoting consensus-based distributed secondary control framework for converter-interfaced dc microgrids consisting of multiple distributed generation (DG) units. The proposed control strategy relies on less (sparse) information exchange over a communication network and does not require exchanging voltage signals or their estimated values amongst neighboring DG units. Rigorous Lyapunov-based stability certificates for dc microgrids are derived. The stability conditions can be verified without the knowledge of distribution lines connecting different DG units. The effectiveness of the proposed secondary control approach is verified by experimental results and a comparative simulation case study on a multiple-DG dc microgrid.

Decentralized composite generalized predictive control strategy for DC microgrids with high PV penetration

AbstractHigh PV penetration into DC microgrids could bring serious stabilization challenges for power electronics engineers, as renewables are accessible to DC bus voltage oscillation, hence leading to degradation of power quality and even system collapse. This article addresses the stabilization issue for a DC microgrid with high PV penetration rate, in which a decentralized composite generalized predictive control strategy is designed. First, a disturbance observer is designed to deal with the lumped uncertainties of both PV intermittency and variation of constant power loads, which is subsequently integrated into the control design through feedforward compensation loops. Second, an offset‐free generalized predictive controller is designed by employing the receding‐horizon optimization process. In this regard, the new method could endow the DC microgrid system of two main distinguishable features: (1) large‐signal stability for global system; (2) optimized transient‐time control performance based on an offset‐free voltage regulation objective. The effectiveness and performance improvement of the proposed methodology are verified by comparative experimental studies on a DC microgrid platform with 50% PV integration.

Distributed control strategy of DC microgrid based on consistency theory

In order to solve the cooperative control problem among multiple distributed units in a distributed DC microgrid, a distributed control based on a consensus algorithm is firstly proposed, which can realize power distribution among distributed units. The distributed voltage control of the observer will generate steady-state errors due to problems such as time delay initial value of the observer. A voltage optimization control strategy based on the PI consistency algorithm is further proposed, which converts the voltage control problem into an optimization problem, and the optimization goal is to ensure the deviation sum of each busbar from the rated value is the smallest, and the stability of this method is proved. Finally, the effectiveness of the proposed method is verified by MATLAB/Simulink software.

Research on Coordinated DC voltage Control Strategy of DC Microgrid based on Photovoltaic Power Generation System

DC microgrid system is a flexible and commonly used renewable power generation system. Among them, the energy storage system (ESS) can reduce the waste light of the photovoltaic (PV) power generation system and provide stable power output for the power grid. However, a reasonable control strategy is needed to realize the energy balance of PV, grid-connected converter and ESS, so as to ensure the safe and stable operation of DC microgrid. Therefore, this paper proposes a DC voltage coordination control strategy without communication. The control strategy can automatically coordinate the working state of each converter of DC microgrid, which according to the change of DC voltage and the ESS’s state of charge (SOC), At the same time, the inertia of DC voltage in each working state is analyzed, and the stability of DC microgrid is improved through the backup inertia support of ESS. Finally, the effectiveness of the proposed method is verified by simulation and experiments.

Adaptive Droop based Control Strategy for DC Microgrid Including Multiple Batteries Energy Storage Systems

In a microgrid architecture that includes energy storage systems based on parallel batteries, the inequalities in the batteries’ state of charge may cause inconsistency in the residual capacity of each battery. As a consequence, the battery cells may be degraded owing to overcharging or deep discharging. This paper presents an optimized load-sharing approach-based droop control strategy for parallel batteries operating in a DC microgrid. The main aim of the proposed control approach is to include the real battery capacity, which may be affected during its lifecycle, in the control algorithm in order to prevent non-matching conditions. As a result, proportional power-sharing will be allowed according to the actual capacity. In addition, all the SoCs will be equalized and the parallel batteries, present in the system, will operate equally in terms of SoC when delivering or absorbing power. Hence, the batteries lifecycle will be extended while power-sharing is performed in the best way. To this end, the identification of the actual battery capacity has been carried out using a metaheuristic optimization algorithm called Salp Swarm Algorithm (SSA). Each battery output is controlled by bidirectional DC/DC converters that ensure the charging and discharging process. The control approach has been evaluated under different scenarios such as similar and different capacities and a sudden disconnection of a battery. The obtained results prove the ability of the proposed control strategy to ensure proportional power-sharing while handling the inconsistency of residual energy between battery cells and improve the battery state of health.

Review on operation control strategy of DC microgrid with electric-hydrogen hybrid storage system

Review on operation control strategy of DC microgrid with electric-hydrogen hybrid storage system

A survey on cooperative control strategies for DC microgrids

Distributed generators have been widely used in modern power systems, and microgrids are becoming a key concept for the integration of multiple distributed generators and clusters of loads with great efficiency and high system reliability. In a microgrid, the control strategy is one of the most important issues. Various control schemes have been proposed to achieve the cooperation of distributed generators in a microgrid. This paper surveys cooperative control strategies for multiple distributed generators in DC microgrids. The three popular coordinated control strategies are presented: decentralized control, centralized control, and distributed control. The advantages and drawbacks of the control strategies are compared. Some intelligent control methods such as fuzzy logic control and neural network approaches are also briefly introduced in the context of microgrids. Further research trends and challenges in this area are also discussed.

A grid interface current control strategy for DC microgrids

In this paper, a grid interface current control strategy is presented for a DC microgrid, which aims to reduce the disturbance from PV generation and the load variation to the main grid without a grid interface converter. The grid interface current is directly controlled by a battery DC-DC converter within the DC microgrid. Based on a comprehensive analysis of the battery DC-DC converter and interface current control, the control system has been mathematically modelled. This enabled two transfer functions to be derived that reflect the dynamic response of the inductor current to the duty cycle variation (inner loop), and the dynamic response of the grid interface current to the inductor current variation (outer loop). Experimental study has been done to assess the effectiveness of the proposed control strategy. The experimental results indicate that the proposed control strategy has a good performance to control the grid interface current without an interface converter, regardless the variations of both PV and the load conditions.

Distributed control strategy for DC microgrids based on average consensus and fractional‐order local controllers

Distributed control strategy for DC microgrids based on average consensus and fractional‐order local controllers

Forecast-Based Consensus Control for DC Microgrids Using Distributed Long Short-Term Memory Deep Learning Models

In a microgrid, renewable energy sources (RES) exhibit stochastic behavior, which affects the microgrid continuous operation. Normally, energy storage systems (ESSs) are installed on the main branches of the microgrids to compensate for the load-supply mismatch. However, their state of charge (SoC) level needs to be balanced to guarantee the continuous operation of the microgrid in case of RES unavailability. This paper proposes a distributed forecast-based consensus control strategy for DC microgrids that balances the SoC levels of ESSs. By using the load-supply forecast of each branch, the microgrid operational continuity is increased while the voltage is stabilized. These objectives are achieved by prioritized (dis)charging of ESSs based on the RES availability and load forecast. Each branch controller integrates a load forecasting unit based on long short-term memory (LSTM) deep neural network that adaptively adjusts the (dis)charging rate of the ESSs to increase the microgrid endurability in the event of temporary generation insufficiencies. Furthermore, due to the large training data requirements of the LSTM models, distributed extended Kalman filter algorithm is used to improve the learning convergence time. The performance of the proposed strategy is evaluated on an experimental 380V DC microgrid hardware-in-the-loop test-bench and the results confirm the achievement of the controller objectives.