Design Of Power Control System Research Articles

Reactor power control system design and dynamic simulation for load maneuvers over full range and entire lifetime of an integrated supercritical CO2 reactor plant

Due to advantage of high efficiency, low carbon, and flexible operation, the integrated supercritical CO2 reactor plant has promising prospect in energy supply. This paper aims to clarify performance of the reactor plant and establish a reactor power control strategy through numerical modeling. Firstly, performance on separated components is evaluated to provide guidance for control strategy development. Secondly, influence of control methods, controller schemes, and saturation models on control strategy are discussed. Thirdly, dynamic response of reactor plant with proposed control strategy is confirmed via load change transients. Results show that passive control method is infeasible at EOL and load demand below 50 %FP, and active control method must be considered. The proposed control strategy adopts coupled temperature-channel and power-channel scheme and soft saturation model. It ensures safe operation of the plant over full load range in whole lifetime. These results can provide helpful guidance on part-load operation for this system.

Adaptive event-triggering mechanism based Takagi-Sugeno fuzzy automatic generation controller design for offshore wind power system

Interconnected offshore wind power system (OWPS) attracts widespread attention due to its special advantage. With the development of wind power technology, higher requirements are put forward for the reliability of networked OWPS. Considering the nonlinear characteristics of OWPS and limited network bandwidth resource, an adaptive multi-event triggering mechanism based distributed Takagi-Sugeno fuzzy robust H∞ control scheme is investigated in this paper. A modeling method for OWPS integrating communication constraints is proposed. By Lyapunov stability theory, the sufficient condition for the asymptotical stability of OWPS has been derived. Compared with traditional control scheme, the proposed Takagi-Sugeno fuzzy controller provides smoother output power, smaller torque oscillation and higher wind energy utilization. Furthermore, the co-design strategy increases the utilization rate of network bandwidth. The feasibility of adaptive multi-event triggering mechanism based Takagi-Sugeno fuzzy controller is demonstrated through a simulation example.

Fractional delay-dependent load frequency controller design for a single-area power system with communication delay

Fractional delay-dependent load frequency controller design for a single-area power system with communication delay

Power Control System Design for Monitoring Active and Standby Power Consumptions of PC Labs

In this study, it was aimed to provide energy saving by informing the user about the power consumption instantly with the power control system (PCS) design and by cutting the energy of the devices in standby mode. The power consumptions of 39 PCs in Lab-1 and Lab-2 in Amasya University Engineering Faculty were examined through the designed system. Lab-1 contains older PCs while Lab-2 contains new generation PCs. The PCs used in the measurements made within the scope of the study were energized via PCS instead of a direct electrical socket. With this method, it has been tried to determine the electrical power consumptions in active work and standby work for calculate the annual electricity consumption and to reflect it on the invoices. The experimental method was carried out on the daily PC staying active for 2 hours and standby for 22 hours. According to the results, it is predicted that 56% lost standby power on an annual basis can be avoided with the use of PCS. The annual invoice cost of this lost power is calculated as 14.116,93 TL and 8.470,12 TL for Lab-1 and Lab-2 respectively. It is thought that the study will make an important contribution to researchers working on this subject.

Hybrid whale optimization algorithm with simulated annealing for load frequency controller design of hybrid power system

Hybrid whale optimization algorithm with simulated annealing for load frequency controller design of hybrid power system

System-level modeling, analysis and coordinated control design for the pressurized water reactor nuclear power system

A flexible operation of the nuclear power system (NPS) over a large operating range is emphasized when it is used as marine power. The current study exposes two bottlenecks in this field: (1) lack of the system-level high-quality dynamic model whose structure is simple enough for control design limits the implementation of the model-based controller; (2) nonlinearity problem due to the large load variation poses challenges for NPS to maintain its performance over a wide operating range. For these reasons, a first-hand simplified nonlinear model is developed and validated for the pressurized water reactor nuclear power system (PWRNPS) through mixed modeling methods of mechanism analysis and data identification. An optimal 50% full-power compromise steady-state operation scheme is first proposed for PWRNPS to balance its primary coolant temperature and secondary steam pressure. Using the simplified nonlinear model as the predictive model, a novel nonlinear model predictive controller (NMPC) is designed to realize the wide-range flexible operation of PWRNPS. Especially, an integrating tracking error is innovatively added to the cost function of NMPC to achieve offset-free control. Two groups of simulations on a complex PWRNPS process developed on the MATLAB/SIMULINK platform demonstrate the effectiveness of the proposed methods.

Power system small-disturbance stability analysis and control design: A characteristic locus method

A characteristic locus method developed from the celebrated generalized Nyquist criterion is proposed for power systems small-disturbance stability analysis and control design in this paper. First, a loop transformation is introduced to re-formulate the familiar Heffron-Phillips model. The new model has a feedback control structure so that the generalized Nyquist criterion is applicable when concluding the stability of the closed-loop system. Subsequently, the relationship between generalized Nyquist curve and characteristic loci is utilized to acquire a new stability margin. The effectiveness of the stability margin is demonstrated using Cassini Oval Theorem. An analytical expression of the stability margin is derived as well. It is convenient to quantify the effects of control loops on stability margin by applying this expression. Moreover, the analytical relationship between stability margin and frequency responses of controllers provides information for the design of the controllers. The utility of the proposed method is confirmed through case studies.

Improved Data-Driven Model-Free Adaptive Damping Controller Design for Interconnected Power Systems With Stochastic Communication Delays

The original model-based wide-area damping control (WADC) is difficult to obtain good damping performance due to the complex structure of interconnected power systems. In this paper, an improved data-driven model-free adaptive control (ID-MFAC) algorithm is proposed to design WADC for interconnected power systems with stochastic communication delays. First, the multiple-input multiple-output power system can be decoupled as multiple single-input single-output subsystems by considering controller interactions and system disturbances. Second, a step-size vector is designed to adjust the pseudo-partial derivative and make the algorithm more flexible by considering both input and output data adequately. Furthermore, an adaptive delay compensator is designed to compensate stochastic communication delays. Last, simulations are conducted to verify that the ID-MFAC algorithm can efficiently suppress multiple inter-area oscillations modes under various stochastic communication delays.

Design of power control system for student dormitory

This design is based on the residential building of boarding school as the research object. The STC89C52RC single-chip microcomputer is used as the main control chip, and the clock chip, temperature chip, smoke collection module, A/D conversion, LED digital tube display circuit, matrix keyboard, infrared wireless remote control and other controllers are used to control the power system and adjust the access control system. This system is applicable to all kinds of colleges and universities that have strict management on students' electricity consumption. It can automatically control the electricity consumption of students' dormitories according to the school management regulations, and can automatically make emergency response to emergencies such as fire.

Resilient Load Frequency Control of Multi-Area Power Systems Under DoS Attacks

Cyber security of modern power systems has become increasingly significant due to their open communication architecture and expanding network connectivity exposed to malicious cyber attacks. Resilient control represents an effective means to preserve the survivability of the power system under cyber attacks. In this paper, we address the resilient load frequency control (LFC) design for multi-area power systems under a new class of time-constrained denial-of-service (DoS) attacks. First, different from the widely-explored duration- and frequency-constrained DoS attack models, we consider a general time-constrained DoS attack model where only the attack durations are confined into some bounds, which represents less a priori knowledge of an attacker’s actions. Second, instead of using a traditional yet conservative time-invariant Lyapunov function (TILF), we develop an attack-parameter-dependent time-varying Lyapunov function (TVLF) approach to enable a resilient LFC design without jeopardizing the desired closed-loop system stability and performance. Furthermore, we provide a formal stability and performance analysis condition as well as a design criterion for the desired DoS-resilient output feedback LFC controller. We also show that the minimum allowable sleeping period and the maximum allowable active period of the attacked LFC system can be explicitly disclosed. Finally, we present two simulation case studies on a two-area LFC system and a three-area LFC system to demonstrate the effectiveness of the obtained results.

Dynamic integral sliding mode control for interconnected delayed power systems

This paper presents the dynamic integral sliding mode control (DISMC) design for interconnected power systems (IPSs). The IPSs consider the effect of time delay related to area control error and the parametric uncertainty. Different from the previous studies, to fully adopt the characteristics of both the system state and control input vector, a novel type of integral sliding surface is defined. Also, a DISMC is designed to assure the system trajectories onto the predefined integral sliding surface despite uncertainties and disturbance. Linear matrix inequality (LMI)-based stabilization criteria are derived for resulting sliding mode dynamics with H∞ performance. Besides that, the control gains and sliding surface matrix are determined. Finally, a numerical example is given to demonstrate the effectiveness and feasibility of the developed DISMC design method.

Hierarchical frequency and voltage control using prioritized utilization of inverter based resources

We propose a novel hierarchical frequency and voltage control design for multi-area power system integrated with inverter-based resources (IBRs). The design is based on the idea of prioritizing the use of IBRs over conventional generator-based control in compensating for sudden and unpredicted changes in loads and generations, and thereby mitigate any undesired dynamics in the frequency or the voltage by exploiting their fast actuation time constants. A new sequential optimization problem, referred to as Area Prioritized Power Flow (APPF), is formulated to model this prioritization. It is shown that compared to conventional power flow APPF not only leads to a fairer balance between the dispatch of active and reactive power from the IBRs and the synchronous generators, but also limits the impact of any contingency from spreading out beyond its respective control area, thereby guaranteeing a better collective dynamic performance of the grid. This improvement, however, comes at the cost of adding an extra layer of communication needed for executing APPF in a hierarchical way. Results are validated using simulations of a 9-machine, 6-IBR, 33-bus, 3-area power system model, illustrating how APPF can mitigate a disturbance faster and more efficiently by prioritizing the use of local area-resources.

A multi-objective energy coordinative and management policy for solid oxide fuel cell using triune brain large-scale multi-agent deep deterministic policy gradient

In this paper, a data-driven multi-objective energy coordinative management policy is proposed in order to enhance the net output power and efficiency of a solid oxide fuel cell (SOFC) and prevent constraint violations. This study focuses on the optimization agent and controller design for a SOFC power system to maintain stable oxygen excess ratio (OER) and fuel utilization (FU) ratio as well as meet the load demand simultaneously. The optimization agent is responsible for output the reference OER and FU, aiming to achieve maximum net output power and operational efficiency as well as dynamic constraint satisfaction times in terms of OER and FU in real time. By applying reference OER and FU settings, the air and hydrogen flow within the SOFC can be effectively controlled by coordination of the air control agent and hydrogen control agent, respectively. In addition, a triune brain large-scale multi-agent deep deterministic policy gradient algorithm (TBL-MADDPG) is proposed. In order to improve the robustness of the proposed policy, the design of TBL-MADDPG entails curriculum learning, imitation learning and a large-scale multi-agent training framework. The performance of this proposed method is verified by the experiment.

A modified Grey Wolf Optimization with Cuckoo Search Algorithm for load frequency controller design of hybrid power system

This paper proposes a novel strategy by consolidating the Modified Grey wolf optimization algorithm and the Cuckoo search algorithm, termed as MGWO-CS algorithm. The superiority of the proposed modified hybrid algorithm over the original algorithm in terms of implementation time and solution quality is compared by taking several benchmark test functions. Further, the genuine utilization of the proposed algorithm is tried by designing a TID controller for frequency regulation of a two-area power system with the application of a photovoltaic system. The matchless quality of the MGWO-CS based TID controller is presented by contrasting with some current methods. Finally, the robustness of the hybrid algorithm-based controller is tested in a multi-area multi-source hybrid power system with the PV-Thermal environment and it is observed that the proposed hybrid algorithm based TID controller is more effective for the load frequency control of the hybrid system compared to the conventional controller.

Neural Lyapunov Control for Power System Transient Stability: A Deep Learning-Based Approach

Power system control and transient stability analysis play essential roles in secure system operation. Control of power systems typically involves highly nonlinear and complex dynamics. Most of the existing works address such problems with additional assumptions in system dynamics, leading to a requirement for a complete and general solution. This paper, therefore, proposes a novel control framework for various power system control and stability problems leveraging a learning-based approach. The proposed framework includes a two-module structure that iteratively and jointly learns the candidate Lyapunov function and control law via deep neural networks in a learning module. Meanwhile, it guides the learning procedure towards valid results satisfying Lyapunov conditions in a falsification module. The introduced termination criteria ensure provable system stability. This control framework is verified through several studies handling different types of power system control problems. The results show that the proposed framework is generalizable and can simplify the control design for complex power systems with the stability guarantee and enlarged region of attraction.

Optimal controller design for non-affine nonlinear power systems with static var compensators for hybrid UAVs

A generalized non-affine nonlinear power system model is presented for a single machine bus power system with a Static Var Compensator (SVC) or State Var System (SVS) for hybrid Unmanned Aerial Vehicles (UAVs). The model is constructed by differential algebraic equations on the MATLAB-Simulink platform with the programming technique of its S-Function. Combining the inverse system method and the Linear Quadratic Regulation (LQR), an optimized SVC controller is designed. The simulations under three fault conditions show that the proposed controller can effectively improve the power system transient performance.

Improved Salp Swarm Optimization Algorithm for Damping Controller Design for Multimachine Power System

This paper proposes an improved salp swarm algorithm (ISSA) as an effective metaheuristic method for tackling global optimization issues and damping power system oscillations. In the suggested ISSA, new equations are introduced to update the location of the leader and followers. This modification improves the method’s exploration possibilities while also preventing it from converging prematurely. Benchmark test functions are used to confirm the proposed algorithm’s performance, and the results are compared to SSA and other effective optimization algorithms. According to the extensive comparisons, the enhanced ISSA algorithm has higher convergence accuracy and stability than the original SSA and other researched algorithms. Furthermore, the feasibility and efficiency of the proposed method were demonstrated by the simultaneous coordinated design of UPFC based damping controllers. For the two-area, four-machine system, the experimental findings are provided. Simulation experiments reveal that ISSA designed controllers outperform those created using other methods.

Pi Power System Controller: Eigenstructure – Based Design and Sensitivities

Significant advances in power system control design techniques that can take into consideration plants linearized around a number of operating conditions. Most of these techniques are based on eigenspectrum analysis which has numerous advantages. A wealth of applications of eigenstructure assignment are available in the literature and showed that new applications have been found and parametric solution of eigenspectrum assignment can be used successfully to design feedback controllers. The use of supplementary controller added to the automatic voltage regulator (AVR) is a practical effective way to supply additional positive damping to system oscillations via power system stabilizers. The present paper utilizes eigenspectrum analysis in the practical design of proportional integral (PI) type power system stabilizers, in order to achieve good steady state as well as transient response characteristics. Eigenspectrum analysis is attractive since it takes into account freedom in determining feedback gains and provides the frequencies and the damping at each frequency for the entire system in a single calculation. Moreover sensitivity of eigenvalues and eigenvectors with respect to parameter variations are assessed so as to provide information to improve setting parameters for power system damping and stability, without ignoring the operating conditions. The results of eigenvalue/eigenvector sensitivity are tangible for analysis with a wide range of parameter variations and is presented through the right and left eigenvectors of the system matrix and also through Taylor series analysis.

An iterative identification algorithm and its convergence analysis of closed-loop power system based on ambient signals

Identification and control are important problems of closed-loop power system. At present, most studies are separate identification methods. This paper studies an online and real-time integrated identification method, which can solve the problems of model set and controller design of closed-loop power system. This paper investigates a new iterative identification algorithm and its convergence problem of closed-loop power system based on ambient signals. Firstly, the whole algorithm procedure is given. This algorithm uses the iterative process under the closed-loop condition, which combines system model identification with controller design. Then the complementary of model identification and control design has been realized. Secondly, because of the dynamic performance of the iterative identification algorithm, it has characteristics described from the perspective of a partitioned dynamic system. Regard each iterative identification step as a state node. In this situation, the algorithm guarantees all the state nodes converge to the Lyapunov stable equilibrium. Finally, the simulation results show the correctness and effectiveness of the proposed method through the simulation of a power system with four-machine-two-region.

Robust decentralized model predictive load-frequency control design for time-delay renewable power systems

Abstract A robust decentralized model predictive control (DMPC) design is proposed for frequency stability of hybrid renewable power systems considering high renewables energy penetration and nonlinearity effects. The Egyptian power system (EPS) considered as a test system comprises both traditional power stations (i.e., steam, gas, combined cycle, and hydraulic power plants) and renewable energy sources (RESs). Where the considered RESs contain both the wind power generated from Zafarana and Gabel El-Zeit wind farms and the solar power generated from Benban solar park, which is considered one of the world’s largest photovoltaic (PV) plants. To obtain an accurate insight into a real modern power system, this research takes into account the effects of the important nonlinearity such as generation rate constraints (GRCs), governor deadband (GDB), and communication time delay (CTD). The designed control is set based on the DMPC for each subsystem independently to ensure the frequency stability of the whole system as each subsystem has different characteristics and operating constraints than the others. Moreover, the decentralized control scheme has become imperative for large power systems due to the high cost of transmitting data over long distances and the probability of error occurrence with the centralized control scheme. To verify the effectiveness and robustness of the proposed DMPC for the EPS, it is compared with the centralized MPC (CMPC) scheme in different operating conditions. The simulation results, which are conducted using MATLAB/SIMULINK® software, emphasized that the proposed DMPC scheme can effectively handle several load disturbances, high uncertainty in the system parameters, and random communication delays. Hence, it can regulate the grid frequency and ensure the robust performance of the studied renewable power system with high RESs penetration and maximum communication delays in the system.