Distributed Control Method Research Articles

A Power Distributed Control Method for Proportional Load Power Sharing and Bus Voltage Restoration in a DC Microgrid

This paper proposes a new power distributed control method for a dc microgrid. This method was developed to share the load power proportionally to the distributed power source ratings and restore the dc bus voltage when the load changes. To achieve this effectively, a shifted voltage technique was developed based on the power rating and the instantaneous power of distributed generators. By adding the shifted voltage, the voltage drop caused by the droop controller is effectively compensated such that the dc bus voltage is constantly regulated regardless of the load change. To realize the method, all the required information to determine the reference voltage is transmitted through low-bandwidth communication. The controller design process is presented in detail along with a system stability analysis. The effectiveness of the method was verified by simulation and experiments, which were carried out using a 2.8-kW prototype of a dc microgrid.

Two-level energy management strategy for PV-Fuel cell-battery-based DC microgrid

With the fast development of DC Microgrid (MG) technology, its operating economy and reliability are getting more and more concern. The traditional distributed control method is aimed at power balance and system stability, and is difficult to meet the requirement of energy management system for multi-source hybrid DC MG. This paper provides a two-level energy management strategy for PV-fuel cell-battery-based DC MG, which is divided into device control level and system control level. At the device control level, the distributed control methods based on MPPT-droop dual-mode control and droop control are proposed to enhance system reliability; at the system control level, the equivalent consumption minimization strategy (ECMS) is used to distribute system net power between battery pack and fuel cell system. A lab-scale DC microgrid platform is developed to verify the proposed energy management strategy in this paper. Moreover, the analysis and compare of the results show that the proposed two-level energy management strategy can achieve lower equivalent hydrogen consumption than classical PI control and state machine control method.

Incognito-authentication for preserving information on cloud with distributed approach control

A new distributed approach control methods which are considered on preserve information repository in clouds in order to back incognito authentication. In the current method, the cloud checks the credibility of the series by not getting the user’s integrity formerly saving the information. In this work we developed a method which include major aspects like approach control for all authentic users who can able to decode the preserved knowledge. This method blocks epitomize barrage along with backing formation, alteration as well as educating information reposted in the cloud. We moreover deal customer repudiation, verification and approach control methods are distributed and vigorous, unlike alternative approach control methods created for clouds which are unify. The conversation, calculation along with repository aloft which is as good as to unify access.

Modified Order-Reduction Method for Distributed Control of Multi-Spacecraft Networks With Time-Varying Delays

This paper studies the order-reduction method for robust distributed control of multi-spacecraft formation problems considering external disturbance and time-varying delays. Two kinds of delay-dependent controllers are designed to achieve accompanying flight and around flight, respectively. Further, a modified order-reduction method is proposed to reduce the order of sufficient conditions in the form of linear matrix inequalities (LMIs), which guarantee the desired relative state between the controlled spacecraft and the reference point subject to $\boldsymbol{H}_{\infty}$ performance. Numerical simulations are provided to illustrate the effectiveness of theoretical results and show that the proposed modified order-reduction method can significantly reduce the numerical complexity of LMIs compared with existing ones.

Vehicle braking force distribution with electronic pneumatic braking and hierarchical structure for commercial vehicle

Brake by wire that allows a number of braking functions exists on commercial vehicles under the name electronic pneumatic braking system, which can improve braking comfort and safety of commercial vehicle. The design of braking force distribution control method has drawn much more attention. Considering structure characteristics of electronic pneumatic braking system, a control method with a three-layer hierarchical structure is proposed. The first layer presents an estimation method towards vehicle mass and centre of gravity combining Kalman filter with recursive least square. The second layer is developed by designing a fixed relationship between the brake pedal displacement and vehicle braking deceleration. A deceleration control method that only uses brake pedal displacement as input is applied to make the vehicle follow the desired deceleration. The third layer includes a braking force distribution control method between the front and rear axles. The vehicle deceleration can be achieved with a smooth axle load transfer process based on linear matrix inequality. In addition, the controllers of wheel slip rate and valve hysteresis compensation are designed to improve control accuracy and efficiency. Utilizing a hardware-in-the-loop simulation test rig of electronic pneumatic braking system, the experiment results show that the control method can improve the braking performance of vehicle.

Hierarchical distributed control for decentralized battery energy storage system based on consensus algorithm with pinning node

A decentralized battery energy storage system (DBESS) is used for stabilizing power fluctuation in DC microgrids. Different state of charge (SoC) among various battery energy storage units (BESU) during operation will reduce batteries’ service life. A hierarchical distributed control method is proposed in this paper for SoC balancing and power control according to dispatching center requirement in DBESS. A consensus algorithm with pinning node is employed to allocate power among BESUs in the secondary control whereas in the primary control, the local controller of BESU adjusts output power according to the reference power from secondary control. Part of BESUs are selected to be pinning node for accepting command from dispatching center while other BESUs as following nodes which exchange output power and SoC information with the adjacent nodes through communication network. After calculating reference power of each BESU by adopting consensus algorithm, the power sharing in DBESS is achieved according to their respective SoC of BESUs. Meanwhile, the total output power of DBESS follows the varying requirements of dispatching center. The stability of DBESS is also improved because of having no center controller. The feasibility of the proposed control strategy is validated by simulation results.

Smart Internet of Things (IOT) System for Performance Improvement of Dual Bridge LLC Resonant Converter by Using Sophisticated Distribution Control Method (SDC)

A resonant converter is a kind of electric power converter that contains a system of inductors and capacitors called a resonant tank, tuned to resonate at a particular frequency in this work recommends a better-quality dual bridge LLC resonant converter with a novel controller technique. The resonant converters include the serial or parallel connections of inductors and capacitors to activate the switch to realize the Zero Current Switching (ZCS) and Zero Volt Switching (ZVS) under resonance conditions. The resonant effects are switching sufferers, turning strain and electromagnetic interference problems the switching resonant converter controls the output voltage through changing frequency and generally can be sub classified in ZCS converter and ZVS converter. This scheme had combined wireless monitoring for dual bridge LLC resonant converter for dc distribution applications based on sophisticated distribution controller (SDC) through the internet of things and embedded structure access and other mechanisms. The consequence of our exhibition demonstrates that the framework can monitor and store the manipulate data from the converter. Thus, the wireless monitoring functions are realized in real-time. This converter permits both forward and reverses power exchange between the source and the load, to keep up the output voltage consistent, regardless of load and line unsettling influences, it is important to work the converter as a closed loop system. The proposed SDC based dual bridge resonant converter has validated through simulation in Matlab Simulink environment. A hardware setup is also developed to validate the simulation. General 97% effectiveness accomplished at full load condition in light of the dual bridge resonant converter.

Distributed secondary and tertiary controls for I–V droop‐controlled‐paralleled DC–DC converters

A hierarchical distributed control method for I-V droop-controlled-paralleled DC-DC converters in DC microgrid is proposed. The control structure includes primary, secondary, and tertiary levels. The secondary control level is used to remove the DC voltage deviation and improve the current sharing accuracy. An improved dynamic consensus algorithm is used in the secondary control to calculate the average values of bus voltage and voltage restoration in distributed control. In the tertiary control level, as the main contribution in this study, the system conversion efficiency is enhanced by using the average restoration value obtained in the secondary control level, instead of using the total load current which needs more communication traffic. When the converters are connected to batteries, the method for the state of charge (SoC) management is proposed so that the SoC balance can be guaranteed. The effectiveness of the proposed method is verified by detailed experimental tests based on four 0.7 kW DC-DC converters.

Stability analysis of DC microgrids with constant power load under distributed control methods

Constant power loads (CPLs) often cause instability due to its negative impedance characteristics. In this study, the stability of a DC microgrid with CPLs under a distributed control that aims at current sharing and voltage recovery is analyzed. The effect of the negative impedance on the behavior of distributed controller is investigated. The small-signal model is established to predict the system qualitative behavior around equilibrium. The stability conditions of the system with time delay are derived based on the equivalent linearized model. Additionally, eigenvalue analysis based on inertia theorem provides analytical sufficient conditions as a function of the system parameters, and thus it leads to a design guideline to build reliable microgrids. Simulations are performed to confirm the effectiveness and validity of the proposed method.

Prescribed-Time Consensus and Containment Control of Networked Multiagent Systems.

In this paper, we present a new prescribed-time distributed control method for consensus and containment of networked multiple systems. Different from both regular finite-time control (where the finite settling time is not uniform in initial conditions) and the fixed-time control (where the settling time cannot be preassigned arbitrarily), the proposed one is built upon a novel scaling function, resulting in prespecifiable convergence time (the settling time can be preassigned as needed within any physically allowable range). Furthermore, the developed control scheme not only ensures that all the agents reach the average consensus in prescribed finite time under undirected connected topology, but also ensures that all the agents reach a prescribed-time consensus with the root's state being the group decision value under the directed topology containing a spanning tree with the root as the leader. In addition, we extend the result to prescribed-time containment control involving multiple leaders under directed communication topology. Numerical examples are provided to verify the effectiveness and the superiority of the proposed control.

Interference Compensation for Smart Grid Communications: A Distributed Power Control Approach

The co-tier and cross-tier interferences become serious when the electric power communication networks are deployed densely in the coverage area of the primary network base station (PBS). To reduce the co-tier interference in the electric power communication networks and guarantee the quality of service of the primary networks users (PUEs), we propose a distributed power control method. First, a reasonable interference threshold of the PBS is chosen to guarantee the PUE’s transmission requirement. Then, a fictitious power-price game with interference compensation is employed to update the power of gateways in smart grid on the condition of the interference threshold. Finally, a modified distributed power control method is proposed to protect the primary network link. Simulation results show that the co-tier interference among gateways is reduced efficiently, the target signal-to-interference plus noise ratio of the PUEs can be achieved, and the network performance is improved.

Distributed Model Predictive Control and Implementation for Vehicle Active Suspensions

This paper proposes a distributed model predictive control (DMPC) method for a half-vehicle system with active suspensions. First, the half-vehicle system is divided into three subsystems to reduce the system dimension. Considering the distribution characteristics of suspension control systems, a DMPC controller is designed for each suspension subsystem in order to inhibit the vehicle vertical and pitch motion. To evaluate the proposed control system, controllers with low cost micro-control units (MCU) are implemented, where a fast MPC method for real-time optimization based on continuation/general minimum residual (C/GMRES) method is realized and in-vehicle network FlexRay is used to exchange control information among these controllers. Finally, the implementation of DMPC controllers in MCUs is finished and the results show that vehicle comfortability can be improved by the proposed controllers.

配電系統分散電圧制御における系統構成変化および電圧制御機器群の無駄動作への対応

This paper proposes a new method for distributed voltage control, which is effective on system re-configuration and improper motion of voltage control devices for distribution networks. The authors have so far proposed a distributed voltage control method for distribution networks by means of multi-agent framework, which is an optimal control both for minimizing tap changes and voltage deviations. In this paper, several effective ideas and functions are introduced to the proposed method to enhance the performance. The re-configuration is executed by management of system data using the management agent and blackboard memory and the improper motion is prevented by providing a new index to the agent. The effectiveness of the proposed scheme is demonstrated through numerical simulations with successful results.

Distributed control method for swarm robot to emerge cohesive behavior

Distributed control method for swarm robot to emerge cohesive behavior

Distributed Control Method for Economic Dispatch in Islanded Microgrids With Renewable Energy Sources

The economic dispatch in islanded microgrids (MGs) is a thorny problem due to the low equivalent inertia and the uncertainty of environmental conditions. In this paper, a two-layer model is proposed for economic dispatch in islanded MGs, in which an MG is considered as the lower layer, while a communication network is considered as the upper layer. Furthermore, a systematic method is presented to derive fully distributed control laws from any given communication network. On the communication network, there are two subgraphs, G̃ and Ĝ, one of which consists of all agents, while the other of which consists of only controllable agents. Correspondingly, two sets of control laws are derived from the two subgraphs, where the control laws from the subgraph G̃ ensure the supply-demand balance in the MG, while the control laws from the subgraph Ĝ realize the economic dispatch. Moreover, the economic operation in MGs can be satisfied, only if agents on the communication network regulate distributed generators iteratively according to the control laws. Finally, three cases are designed to evaluate the performance of the method, and the simulation results verify the effectiveness of the proposed method.

Power Flow Coloring System Over a Nanogrid With Fluctuating Power Sources and Loads

Due to the excessive increase in environmental costs of nonrenewable energy resources, there have been government legislation, policies, and new technologies to control carbon emissions. The increase in renewable resources requires new strategies for the operation and management of the electricity. This paper presents the power flow coloring system, which gives a unique ID to each power flow between a specific power source and a specific power load. It allows us to design multiple power flow patterns between distributed and fluctuating power sources and loads taking into account energy availability, cost, and carbon dioxide emission. For implementation, this paper proposes a cooperative distributed control method, where a master–slave role assignment scheme of power sources and a time-slot-based feedback control are introduced to cope with power fluctuations, while keeping the voltage stable. The experimental results clarify the practical feasibility of our proposed method in managing distributed fluctuating power sources and loads.

Guest Editorial Distributed Control and Efficient Optimization Methods for Smart Grid

Smart grid proactively uses the state-of-the-art technologies in communications, computing, and control to improve efficiency, reliability, sustainability, and stability of the electrical grid. In particular, distribution networks are expected to undergo dramatic changes by incorporating a large number of sensors and thousands of controllable devices such as distributed generators, batteries and flexible loads. To be able to efficiently operate such complex large-scale systems, new sets of control and optimization tools should be developed. On a slow time scale, optimization theory plays a major role in solving various large-scale decision-making problems for future power transmission and distribution systems. One major challenge is the design of computational methods for handling fairly detailed power system models that often include continuous and discrete nonlinearities. It is also important to develop distributed computation techniques to shift the computation from a centralized platform to many computing devices.

Decentralised secondary voltage and frequency control scheme for islanded microgrid based on adaptive state estimator

This study proposes a decentralised secondary voltage and frequency control based on the state estimation principle and cooperative strategy in an islanded microgrid. Following the establishment of a large signal model of microgrid, an adaptive sliding mode observer is allocated to each distributed generation unit to estimate the transient responses of the other units based on the coupling of the physical system. In this way, the proposed secondary control is implemented in a fully decentralised structure such that each distributed generation requires its own information only; unlike conventional centralised or distributed control methods, this scheme obviates any requirement for communication network and remote measurements, which leads to improved system reliability, flexibility and scalability. Simulation results are presented to verify the effectiveness of the proposed secondary control for a typical microgrid system.

Coordination control for distributed energy based on multi-agent system

In the future, energy utilization structure will be centralized plant combining with decentralized and distributed energy resources. With the development of clean and renewable energy, much more difficult control problem occurs simultaneously. Centralized control is suitable for existing system while not sufficient to future. We propose a multi- agent system to control distributed energy resources, which is a typical idea that information can exert influence on physical system. The most important design of the control system is communicating protocol between two energy points. Traditionally in multi-agent system, the communicating protocol is used to get to emergence of consensus, which means all the state of agent become the same. However, in energy system, what we considered is not the consensus but optimal allocation. We rewrite the multi-agent protocol to make it suitable for our demand: to get optimum not consensus and we make it under some specific assumption. In this paper firstly, we demonstrate the convergence and optimum of the algorithm whereby detailed mathematic calculation. Secondly, an ideal 8 distributed energy systems model is used to study the process generated by the protocol. Besides, different topology of distributed energy points is considered carefully and the detailed reason why the efficiency can be improved is discussed. Finally, we apply this method to a realistic system to make further study. Both the mathematic demonstration and simulation results show that the distributed algorithm can be successfully used to improve efficiency of the system. In mathematic demonstration, we use induction to prove that final result must be better than the origin only by every two points′ communication. Without centralized control, the system will evolve into a better allocation. Then in simulation, we study the process detailly. A typical overload working condition is studied. There are 8 points in the system and each point has its own load and load curve. When we set a point′s load increasing by 50%, we get the synergy of the whole system. Traditionally, centralized control will dispatch the load to other points to make sure that the overload one is not so bad. Here, without any external command, the system regulates itself automatically. The overload is shared by other points around the broken one and how much other points share depends on its ability. Furthermore, we study the influence of the topology of system. The conclusion is that with more complete information topology, which means there are connection between every two points as much as possible, the convergence speed will be faster but the final convergence point is the same. However, if the topology is unconnected, the final result is totally different with connected one. Finally, the algorithm is applied to a distributed energy system with generation, energy storage and users. The result shows even the load curve of each point is much more difficult than ideal one, the algorithm still works and the average efficiency is improved. In this paper, the most creative idea is switching multi-agent consensus algorithm to distributed control method. Although some characteristics are neglected, the result can assure the essential validity of the algorithm.

Distributed trajectory optimization for multiple solar-powered UAVs target tracking in urban environment by Adaptive Grasshopper Optimization Algorithm

Aiming at the trajectory optimization of the solar-powered UAVs (SUAVs) cooperative target tracking in urban environment, the distributed model predictive control (DMPC) method based on Adaptive Grasshopper Optimization Algorithm (AGOA) is proposed in this paper. Firstly, the cooperative target tracking problem in urban environment is modeled by formulating the SUAVs kinematic and target models, the urban environment constraints, solar power harvesting and consumption models for SUAV, and sight occlusions by constructions. Especially, the sight occlusions in urban environment for SUAV are taken into consideration for the first time in this paper. A judgment method of sight occlusions for SUAV is proposed to make the calculation of the energy index more precise. Second, based on the precise modeling, the DMPC method is adopted as the framework for trajectory optimization in real time. Third, AGOA, a novel intelligent algorithm to mimic the behaviors of grasshoppers, is proposed to be the DMPC solver. The proposed AGOA has a better searching ability than the traditional GOA and some other intelligent algorithms by introducing some improvement measures e.g. the natural selection strategy, the democratic decision-making mechanism, and the dynamic feedback mechanism based on the 1/5 Principle. Finally, the effectiveness of the proposed method is demonstrated by the simulations.