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Islanded DC microgrids face challenges in voltage stability and communication overhead due to renewable energy variability. A novel enhanced distributed coordinated control framework, based on adaptive event-triggered mechanisms, is developed for the efficient management of multiple hybrid energy storage systems (HESSs) in islanded DC microgrids (MGs). We propose a hierarchical distributed control framework integrating ANN-based controllers and adaptive event-triggered mechanisms to dynamically regulate power flow and minimise communication. This system utilises a hierarchical coordinated control method (HCCM) with primary virtual resistance droop control integrated with state-of-charge (SoC) management and secondary control for voltage regulation and proportional current distribution through optimised communication networks. The integration of artificial neural network (ANN)-based controllers alongside traditional PI control leads to an improvement in system responsiveness. The control approach dynamically adjusts the trigger parameters to minimise communication overhead with tight voltage regulation. An extensive simulation using MATLAB/Simulink shows how the system can effectively manage variability in renewable energy sources and maintain stable voltage profiles with precise power distribution and minimal bus voltage fluctuations. Simulations confirm enhanced voltage regulation (±0.5% deviation), proportional current sharing (98% accuracy), and 60% communication reduction under load transients (outcomes).

To improve the efficiency of air pollution control, in this research, a systematic air pollution collaborative governance pathway system was developed from a systemic perspective. The sequencing of air pollution control pathways in the system can significantly affect its efficiency, so the order of the sequence was optimized. To develop the system, first, two case studies on coordinated air pollution control in the U.S. and China were conducted to demonstrate the importance of systematic collaborative governance. Next, based on the analysis of these two cases and a review of the related literature, a systematic coordinated air pollution control mechanism was proposed. The priorities of collaborative governance pathways were evaluated using the Analytic Hierarchy Process (AHP) methodology. The input to the AHP was data from in-depth interviews with established scholars and practitioners in air pollution prevention and control. Several policy suggestions are put forward based on the expert ranking of the results of the priorities of the collaborative governance pathways. These policy suggestions include identifying the most critical pathways in the cooperative control of air pollution and their order of implementation as well as measures that can effectively reduce pollution. The theoretical contributions of this research include the establishment of a cooperative governance mechanism and the analysis of governance pathways to help develop an efficient air pollution pathway system. The practical contributions of this research include policy suggestions to improve the efficiency of collaborative air pollution treatment and lower its costs.

Wind turbines (WTs) participate in frequency regulation, which is one of the means to solve the problem of inadequate regulation capacity in power systems with a high proportion of renewable energy. The doubly fed induction generator (DFIG) can reserve part of power to achieve bidirectional regulation capability through rotor over-speed and increasing pitch angle. In this paper, it is pointed out that the available bidirectional regulation power of the WT is constrained by the maximum regulation power under the rotor speed regulation. The regulation power constraints under the pitch regulation considering the time scale are calculated. The adjustment coefficient of WT participating in frequency regulation is designed. Considering the regulation power constraints, the frequency difference interval in which the WT can provide the regulation power according to the adjustment coefficient is analyzed. The rotor speed and pitch coordinated control strategy of DFIG with different wind speeds is designed. Based on 24-hour measured data from a wind farm, the power constraints and their effects of WTs in the wind farm participating in frequency regulation are verified by simulation. The regulation power of the wind farm, frequency quality, and wind power utilization under the different control strategies are analyzed. The results show that the effects of bidirectional power constraints must be taken into account when evaluating the effectiveness of WTs in continuous frequency regulation.

Agents are intelligent entities that act flexibly and autonomously and make wise decisions based on their intelligence and experience. A multi-agent system (MAS) contains multiple, intelligent, and interconnected collaborating agents for solving a problem beyond the ability of a single agent. A smart grid (SG) combines advanced intelligent systems, control techniques, and sensing methods with an existing utility power network. For controlling smart grids, various control systems with different architectures have already been developed. MAS-based control of power system operations has been shown to overcome the limitations of time required for analysis, relaying, and protection; transmission switching; communication protocols; and management of plant control. These systems provide an alternative for fast and accurate power network control. This paper provides a comprehensive overview of MASs used for the control of smart grids. The paper provides a wide-spectrum view of the status of smart grids, MAS-based control techniques and their implementation for the control of smart grids. Use of MASs in the control of various aspects of smart grids—including the management of energy, marketing energy, pricing, scheduling energy, reliability, network security, fault handling capability, communication between agents, SG-electrical vehicles, SG-building energy systems, and soft grids—have been critically reviewed. More than a hundred publications on the topic of MAS-based control of smart grids have been critically examined, classified, and arranged for fast reference.

In order to achieve a state-of-charge (SOC) balance among multiple energy storage units (MESUs) in an islanded DC microgrid, a SOC balancing and coordinated control strategy based on the adaptive droop coefficient algorithm for MESUs is proposed. When the SOC deviation is significant, the droop coefficient for an energy storage unit (ESU) with a higher (or lower) SOC is set to a minimum value when discharging (or charging). The ESU with the higher (or lower) SOC is controlled to discharge (or charge) with the rated power, while the other ESU compensates for the remaining power when the demanded discharging (or charging) power is greater than the rated power of the individual ESU. Otherwise, when the demanded discharging (or charging) power is lower than the rated power of either ESU, the ESU with the higher (or lower) SOC releases (or absorbs) almost all the required power while the other ESU barely absorbs or releases power, thus quickly realizing SOC balancing. When the SOC deviation is slight, the fuzzy logic algorithm dynamically adjusts the droop coefficient and changes the power distribution relationship to balance the SOC accurately. Furthermore, a bus voltage recovery control scheme is employed to regulate the bus voltage, thus improving the voltage quality. The energy coordinated management strategy is adopted to ensure the power balance and stabilize the bus voltage in the DC microgrid. A simulation model is built in MATLAB/Simulink, and the simulation results demonstrate the effectiveness of the proposed control strategy in achieving fast and accurate SOC balance and regulating the bus voltage.

Inverter Based Resources (IBR) are gaining more popularity in modern power systems, leading to decrease in grid inertia. Hydropower Plants with rotating synchronous machines have been excellent source of inertia in existing grids. Adding a frequency converter between the generator and the grid in these hydropower plant would enable to run the hydropower in variable speed leading to enhanced efficiency and more flexibility in operation. These Variable Speed Hydropower Plant (VSHP), having the capability of anciliary services for grid support could be a potential solution for providing synthetic inertia to low-inertia power grids. However, there is a little research done on control of VSHP for grid support. This paper aims at implementing Non-Linear Model Predictive Controller (NLMPC) algorithm for optimal control of VSHPs, and the results are compared with classical PID control method. Explicit comparison under realistic operating condition and analysis of constraint handling capabilities and robustness of MPC have been performed. Advanced model based NLMPC successfully coordinated the hydraulic and electric systems having different time constants by implementing multi-objective optimization and upstream constraints satisfaction. Furthermore, the NLMPC has shown relatively better performance than the classical controllers even during the occurrence of an unanticipated grid-side disturbance. This paper is claimed to be an important work in control domain since it develops the control system for VSHPs using time-domain models which can offer better insights over the nonlinearities that exist within hydropower systems. Apart from the computational complexity, NLMPC is found to be viable for the control of VSHP since it ensured stable operation, as can be seen from the analysis of different operational cases studied implemented in this paper. The key takeaway from this paper is the potential of utilizing advanced model based optimal control strategy for coordination among complex dynamic systems of VSHP for different loading patters and disturbances. Also, the MPC has a scope of providing more robust grid support by addressing overloads and uncertainties during operation.

The problem of the relative position coordinated control for spacecraft formation flying with a leader spacecraft under the obstacle environment is the focus of this paper. To avoid obstacle/collision and maintain the formation configuration, the Null-Space-Based behavioral control architecture is built by defining the priorities of the basic tasks and computing the corresponding velocity vectors. Through the null-space projection, the desired velocity of each follower spacecraft can be calculated by merging the basic tasks. Moreover, due to the partial access to the dynamic leader spacecraft’s states, the distributed estimators are presented for each follower spacecraft. Then, based on the desired velocity, the adaptive coordinated tracking control algorithm incorporated with the barrier Lyapunov function is designed such that the states satisfy the time-varying constraints, even subject to uncertainties and unknown disturbances. Finally, numerical simulations are performed to illustrate the main results.

In modern power systems, conventional energy production units are being replaced by clean and environmentally friendly renewable energy resources (RESs). Integrating RESs into power systems presents numerous challenges, notably the need for enhanced grid stability and reliability. RES-dominated power systems fail to meet sufficient demand due to insufficient inertia responses. To address this issue, various virtual inertia emulation techniques are proposed to bolster power system stability amidst the increased integration of renewable energy sources into the grid. This review article explores state-of-the-art virtual inertia support strategies tailored to accommodate the increased penetration of RESs. Beginning with an overview of this study, it explores the existing virtual inertia techniques and investigates the various methodologies, including control algorithms, parameters, configurations, key contributions, sources, controllers, and simulation platforms. The promising virtual inertia control strategies are categorised based on the techniques used in their control algorithms and their applications. Furthermore, this review explains evolving research trends and identifies promising avenues for future investigations. Emphasis is placed on addressing key challenges such as dynamic response characteristics, scalability, and interoperability with conventional grid assets. The initial database search reveals 1529 publications. Finally, 106 articles were selected for this study, adding 6 articles manually for the review analysis. By synthesising current knowledge and outlining prospective research directions, this review aims to facilitate the current state of research paths concerning virtual inertia control techniques, along with the categorisation and analysis of these approaches, and showcases a comprehensive understanding of the research domain, which is essential for the sustainable integration of renewable energy into modern power systems via power electronic interface.

Purpose. To increase output of traffic network while deriving new dependencies of transport flow characteristics upon control law parameters and using them to develop an algorithm to automate a process of the transport flow coordinated regulation within towns and cities. Methodology. The aggregated simulation model, describing processes of road traffic formation within a local section of urban traffic system, is used for the analysis of dependencies to assess quality of transport flow control upon correcting conditions being parameters of traffic cycles within intersections. The abovementioned should involve a PID controller as well as a negative feedback idea to automate control of the road traffic process. In this context, control criterion is applied to determine critical flow intensity if a traffic jam occurs. The criterion makes it possible to identify changes in the road traffic nature. To determine the optimal settings of the PID controller for different stocks of the stability control system, the standard deviation of the controlled variable from the set value and the mean static control error are defined. The derived dependencies of control quality criteria upon a law of flow regulation have helped develop a new algorithm of the coordinated automated road traffic control within a local section of urban traffic section using standard control action. Simulation experiments made it possible to assess efficiency of the proposed algorithm of control compared with available ones applied in terms of different road conditions. Findings. As a part of the studies, algorithm of the coordinated automated road traffic has been developed. It helps support maximum output of road systems while monitoring changes in the traffic environment characteristics. Originality. For the first time, dependencies of assessment criteria of traffic flow control upon the parameters of a law of flow intensity regulation have been identified if maximum output of road systems is provided. The dependencies have helped substantiate optimum control criteria for different road conditions while automating a process of coordinated traffic flow regulation within local section of urban traffic network. Practical value. The proposed dependencies of assessment criteria of traffic flow control upon the parameters of a law of flow intensity regulation as well as the algorithm of automated coordinated control are the theoretical foundations to solve such an important applied scientific problem as automation of a process of urban traffic flow regulation.

This article presents a coordinated control approach for a tractor-trailer vehicle such that a satisfactory trajectory tracking performance can be achieved, simultaneously guaranteeing vehicle kinematics restriction and dynamics maneuvers. The coordinated control is consisted of multilevel controllers, each of which is constructed by different algorithms to better clarify their specific advantages and defects, thereby establishing the composition principles of this multilevel architecture. In this regard, on the level of kinematics, linear quadratic regulator and model predictive control (MPC) are used to design the posture controller separately; on the level of dynamics, sliding mode control and global terminal sliding mode control (GTSMC) are introduced to design the dynamic controller for the tracking of the desired velocities generated online. The simulation results suggest that the combination by MPC and GTSMC can offer more favorable control performance for such kind of sophisticated vehicle system.