Control Method For Systems Research Articles

Review of methods for modeling and control of cyber-physical systems in multi-energy microgrids

The article analyzes the development of methods for modeling and control of multi-energy microgrids through cyber-physical systems. We used the methods of literature review and meta-analysis based on publications from international databases Scopus and Web of Science, Russian database eLibrary, digital platform IEEEXplore et al. According to the analysis, Smart Grid implementation drives the development of cyber-physical systems. As summarized in this study, control interfaces, data transmission channels, and remote debugging ports are vulnerable parts of IoT devices that can possibly be attacked by intruders. A review of the recent publications in this field finds multi-agent technologies to be an effective approach not only for the operational control of multi-energy microgrid modes, but also for the construction of its reliable information network at the level of medium and low voltage systems. In the field of distributed energy systems, literature review of information technology indicates that the more capabilities are added to receive and process various kinds of information (transaction data, mode parameters, status of controllers, etc.) from external sources, the more vulnerable a multi-energy microgrid is to any cyber threats. Modern mathematical methods such as artificial intelligence, dynamic optimization, and multi-agent approaches should be used to effectively solve the problem of load distribution between different energy sources with cost minimization.

Risk control of hydropower-photovoltaic multi-energy complementary scheduling based on energy storage allocation

The complementary scheduling of hydropower with wind and photovoltaic (PV) power is an effective way to promote new energy consumption. However, previous studies have disregarded the operational risks of hydropower plants due to their physical constraints when complementing new energy sources. This study proposes a risk control method for a hybrid hydro-PV power system by adding electrochemistry energy storage (EES). A “day ahead–intraday–real-time” three-layer nested model is developed to guide the joint operation of the hydro-PV-EES hybrid system. The complementary flexibility of hydropower and EES is quantified and utilized to minimize unfavorable operating conditions of hydropower units when regulating PV forecast deviations. A case study of China's Longyangxia hydro-PV complementary project shows that after EES is connected to the system: (1) the total power generation of the system is improved 3.04%, and no power curtailment or shortage occurs; (2) the number of startups and shutdowns, and crossing the vibration zone of hydropower units are reduced by 12.87% and 12.17%, thereby improving the safety and operational stability of the hydropower plant; (3) the regulation flexibility supply of the complementary system is considerably improved; and (4) EES achieves flexible and safe control itself, with over 90% of the scheduling periods being in a healthy SOC range.

A new control method of hybrid energy storage system for DC microgrid application

AbstractEnergy storage system play a crucial role in safeguarding the reliability and steady voltage supply within microgrids. While batteries are the prevalent choice for energy storage in such applications, their limitation in handling high‐frequency discharging and charging necessitates the incorporation of high‐energy density and high‐power density storage devices to enhance power quality, maintain power balance, and reduce fluctuations. In this study, we introduce a hybrid energy storage system (HESS) solution, combining a battery and a supercapacitor, to address intermittent power supply challenges. The effective management of this HESS is pivotal for constant DC voltage and sustaining microgrid stability. To achieve this, we propose an innovative control strategy called the Adaptive Filter‐Based Method (AFBM) for DC microgrid operation, which prioritizes stable and smooth performance while addressing safety and degradation concerns related to the storage devices. Our control strategy determines the distribution of charging and discharging currents for each storage device within the DC microgrid based on their state of charge. We conducted simulations in MATLAB/Simulink, comparing the proposed AFBM method with the conventional filter‐based approach using identical configurations, parameters, and operational modes. The results demonstrate the superior performance of our proposed system, showcasing improved voltage stability, more equitable load distribution, and efficient charging and discharging of storage devices compared to the traditional method. This research contributes to the advancement of microgrid energy storage solutions, enhancing their reliability and performance.

An event‐triggered subspace predictive control method for partially unknown linear parameter‐varying systems

AbstractThis article develops a novel event‐triggered subspace predictive control (ET‐SPC) method for discrete‐time linear parameter‐varying (LPV) systems with partially unknown system parameters. An event‐triggered law is developed to alleviate the heavy load of data transmission and computation in the conventional subspace predictive control methods for the LPV systems. The design of the event‐triggered law relies on the input‐to‐state stability (ISS) theory and applies the robust stability condition based on linear matrix inequalities (LMIs), which guarantees the stability of the proposed method. Consequently, the input component can be directly transmitted to the system without receding horizon optimization when the event‐triggered law evaluates that the system satisfies the stability condition. The simulation results illustrate its satisfactory performance, which indicates its potential application involving a considerable amount of data transmission and computation such as the network control systems (NCSs).

Event-triggered sliding mode control for networked control systems with actuator faults: Application to gas turbine system

This paper presents an event-triggered sliding mode fault-tolerant control method for networked control systems with actuator faults and external disturbance. First, an event-triggered scheme in the networked control systems is proposed to reduce the number of data transmission. In addition, considering the event-triggering, a sliding mode surface based on the system structure is constructed. Besides, to obtain the controller parameters that meet the [Formula: see text] performance, the bounded real lemma in the form of linear matrix inequality is obtained using the Lyapunov functional. In addition, a sliding mode fault-tolerant control is designed to guarantee that the system can still run stably under the condition of faults and disturbances. Finally, the simulation results of gas turbine system are given to verify the feasibility of the theoretical method.

A Communication-Free Fast Constant Current and Voltage Control Method for Dynamic Wireless Power Transfer System

A Communication-Free Fast Constant Current and Voltage Control Method for Dynamic Wireless Power Transfer System

Voltage control method for multi-energy system based on the coupling of renewable energy hydrogen production and storage

Renewable energy power generation combined with hydrogen storage, is an important way to realize the deep integration of hydrogen energy and renewable energy in multi-energy systems. In the multi-energy system of renewable energy power generation and hydrogen production in AC/DC hybrid. Due to the fluctuation of heat load and electric hydrogen production load in the system and the multi-time scale characteristics of energy flow transmission of heat storage and hydrogen storage. It will lead to the difficulty of power coordination in the whole Multi Energy System (MES). In order to solve the problem of power imbalance in MES, this paper first establishes the hybrid power flow equation of MES cluster composed of AC/DC and hydrogen energy transmission channels. The reactive voltage fluctuation characteristics of the AC/DC system under the fluctuation of energy exchange, system energy conversion, and renewable energy output of the MES cluster interconnection channel are analyzed. Secondly, a multi-energy flow model of the multi-energy system is established. The main factors affecting the voltage-reactive power of the AC system are analyzed. A reactive power model based on electro-thermal conversion, hydrogen storage, and multi-energy transmission channels is established. Then, a generation algorithm of the safe and stable boundary of pipeline pressure is proposed to maintain the pressure of hydrogen production and storage system within a safe range. The robust optimization control method is used to control the coupling of multi-energy sources. Finally, based on the actual operation data of the multi-energy power system. The simulation model of reactive power dynamic optimization control for multi-energy interconnected systems is established. The simulation results show that the control method proposed in this paper is adopted. Through the coordinated distribution of energy among multi-energy systems, the voltage stability level of the system can be effectively improved.

Distributed Adaptive Flocking Control for Large-Scale Multiagent Systems.

This article presents a novel distributed flocking control method for large-scale multiagent systems (LS-MASs) operating in uncertain environments. When dealing with a massive number of flocking agents in uncertain environments, existing flocking methods encounter the problem of communication complexity and "Curse of dimensionality" caused by the exponential growth of agent interactions while solving PDE-based optimal flocking control for large-scale systems. The mean field game (MFG) method addresses this issue by transforming interactions among all agents into the interaction of each individual agent with average effects represented by a probability density function (pdf) of other agents. However, relying solely on a pdf term to consider other agents' states can result in inefficient flocking performance due to the absence of a proficient coordination mechanism encompassing all agents involved in flocking. To overcome these difficulties and achieve the desired flocking performance for LS-MASs, the agents are decomposed into a finite number of subgroups. Each subgroup comprises a leader and followers, and a hybrid game theory is developed to manage both inter-and intragroup interactions. The method incorporates a cooperative game that links leaders from different groups to formulate distributed flocking control, a Stackelberg game that teams up leaders and followers within the same group to extend collective flocking behavior, and an MFG for followers to address the challenges of LS-MASs. Furthermore, to achieve distributed adaptive flocking using the hybrid game structure, we propose a hierarchical actor-critic-mass-based reinforcement learning technique. This approach incorporates a multiactor-critic method for leaders and an actor-critic-mass algorithm for followers, enabling adaptive flocking control in a distributed manner for large-scale agents. Finally, numerical simulation including comparison study and Lyapunov analysis demonstrates the effectiveness of the developed method.

A Voltage Minimization Control Method for Magnetic Navigation Systems to Enhance the Rotating Magnetic Field

A Voltage Minimization Control Method for Magnetic Navigation Systems to Enhance the Rotating Magnetic Field

Frequency stability control method for multi-energy system considering storage characteristics and transmission inertia of hot and gas pipeline network

The grid-connected capacity of renewable energy generation in multi-energy microgrid is increasing. This leads to a decrease in the inertia level in the microgrid, which has a great impact on the frequency stabilization control. This article proposes an adaptive control method for frequency control of inertia in multi-energy microgrids. Firstly, the system frequency fluctuation problem is addressed. Analyze the response characteristics of virtual inertia and the influence of physical inertia of rotating equipment on system frequency dynamics in multi-energy microgrid. Secondly, study the energy transfer characteristics of electric, thermal and gas systems in multi-energy microgrids. The energy coupling model between the subsystems in the multi-energy microgrid is established. And according to the difference of energy transmission time inertia of electric, heat and gas subsystems, the microgrid inertia response time model of different energy systems is established. Then, according to the energy balance stability criterion of multi-energy microgrid, combined with the current operating state of the system and the state of the higher-level distribution network, the fast response adaptive over-compensation control of multi-energy microgrid cluster is carried out to realize the inertia allocation in multi-energy microgrids. Finally, the proposed advanced frequency control method of multi-energy microgrid considering inertia demand is verified by simulation.

A Projected Gradient Descent-Based Distributed Optimal Control Method of Medium-Voltage DC Distribution System Considering Line Loss

A Projected Gradient Descent-Based Distributed Optimal Control Method of Medium-Voltage DC Distribution System Considering Line Loss

Deterministic and Robust Volt-var Control Methods of Power System Based on Convex Deep Learning

Deterministic and Robust Volt-var Control Methods of Power System Based on Convex Deep Learning

A Separation and Rendezvous Control Method for the UAV-USV System Based on Distributed NMPC

A Separation and Rendezvous Control Method for the UAV-USV System Based on Distributed NMPC

Energy saving control method for central air conditioning systems in public buildings based on improved particle swarm optimisation

Energy saving control method for central air conditioning systems in public buildings based on improved particle swarm optimisation

A Stackelberg Differential Game-based Optimal Fault-tolerant Control Method for Over-actuated Systems

This paper focuses on the optimal fault-tolerant control problem for over-actuated systems with actuator faults. Based on Stackelberg differential game, a novel integrated method is put forward where the optimal High-level motion controller serves as the leader to give the virtual control input, and the optimal Low-level fault-tolerant allocation strategy acts as the follower to allocate the virtual control input to actuators. Adaptive Dynamic Programming is used to realize the online solution of such an integrated method. A numerical simulation is presented to verify its feasibility.

Industrial Metaverse-Powered Interactive and Self-Healing Control Method for Combustion System

Industrial Metaverse-Powered Interactive and Self-Healing Control Method for Combustion System

Active damping control method for suspended gravity offloading system

Active damping control method for suspended gravity offloading system

Reinforcement Learning Based Motion Control Method for Electrical-hydraulic Valve-Controlled System

Reinforcement Learning Based Motion Control Method for Electrical-hydraulic Valve-Controlled System

System Control Methods for Energy Efficiency Improvement of Parallel Pump Systems: A Review

System Control Methods for Energy Efficiency Improvement of Parallel Pump Systems: A Review

A DOD-SOH balancing control method for dynamic reconfigurable battery systems based on DQN algorithm

This article presents a DOD-SOH equalization method for a DRB system based on the Deep DQN algorithm. The proposed method utilizes DQN to learn the operational processes of the system. By integrating the advantages of DRB with SOH equalization theory and the DQN algorithm from the perspective of DOD, our method significantly improve battery performance and ensure cell balancing. To begin with, we present a dynamic reconfigurable battery system with a simple topological structure and outline its switching control process. Additionly, we provide an analysis of the SOH balancing principle and elaborate on the control process of DQN algorithm. Finally, subsequent simulations are carried out, and the simulation results demonstrate outstanding performances in reducing the variance of SOHs, which indicates an enhancement in the level of SOH balancing as well.