scholarly journals A Distributed AGC Method considering Two-Channel Random Delays and Their Difference between Interconnected Power Systems

2019 ◽  
Vol 2019 ◽  
pp. 1-14
Author(s):  
Xilin Zhao ◽  
Zhenyu Lin ◽  
Bo Fu ◽  
Yang Yang ◽  
Jimin Ma
Keyword(s):  
Power Systems ◽  
Time Delays ◽  
Frequency Control ◽  
Control Variable ◽  
Automatic Generation ◽  
Control Sequence ◽  
Negative Effects ◽  
Random Load ◽  
Sequence Selection ◽  
The Difference

With the emergence of the concept of smart grid, the networked automatic generation control (AGC) method has been more and more important for secondary frequency control due to its characteristics such as openness and flexibility. However, the networked AGC system also presents some defects such as time delays and packet dropouts. The existence of time delays makes the traditional AGC strategies more challenging. A novel AGC method is proposed in this paper to mitigate the negative effects of time delays. Firstly, a multiarea power system model is built under the consideration of two-channel time delays: from controller to actuator and from sensor to controller. More practically, the difference of delays between areas is also exhibited in the model. Thus, from the predictive characteristics of model predictive control (MPC), a method of selection with optimization is presented to obtain the appropriate control variable when delays exist. Furthermore, three cases, (a) no processing for delay, (b) control sequence selection, (c) control sequence selection with optimization, are analyzed. The frequency and area control error (ACE) performance are evaluated with step load perturbation and random load perturbation. The simulation results indicate that the system controlled by the proposed method has desired dynamic performances. Consequently, the feasibility and effectiveness of the proposed method are verified.

scholarly journals Optimal Array Reconfiguration of a PV Power Plant for Frequency Regulation of Power Systems

2021 ◽  
Vol 9 ◽  
Author(s):  
Tingyi He ◽  
Shengnan Li ◽  
Yiping Chen ◽  
Shuijun Wu ◽  
Chuangzhi Li
Keyword(s):  
Power Plant ◽  
Power Systems ◽  
Pareto Front ◽  
Frequency Control ◽  
Storage System ◽  
Energy Storage System ◽  
Automatic Generation ◽  
Frequency Regulation ◽  
Nsga Ii ◽  
Partial Shading

This paper establishes a novel optimal array reconfiguration (OAR) of a PV power plant for secondary frequency control of automatic generation control (AGC). Compared with the existing studies, the proposed OAR can further take the AGC signal responding into account except the maximum power output, in which the battery energy storage system is used to balance the power deviation between the AGC signals and the PV power outputs. Based on these two conflicted objects, the OAR is formulated as a bi-objective optimization. To address this problem, the efficient non-dominated sorting genetic algorithm II (NSGA-II) is designed to rapidly obtain an optimal Pareto front due to its high optimization efficiency. The decision-making method called VIKOR is employed to determine the best compromise solution from the obtained Pareto front. To verify the effectiveness of the proposed bi-objective optimization of OAR, three case studies with fixed, step-increasing, and step-decreasing AGC signals are carried out on a 10 × 10 total-cross-tied PV arrays under partial shading conditions.

Optimal Power-Frequency Control in Deregulated Thermal, Hydro and Hydrothermal Power Systems with AC-DC Links

2019 ◽  
Vol 12 (5) ◽  
pp. 414-424
Author(s):  
Yogendra Arya ◽  
Sushil K. Gupta ◽  
Nisha Singh
Keyword(s):  
Power Systems ◽  
Frequency Control ◽  
Dynamic Performance ◽  
Automatic Generation ◽  
Dynamic Responses ◽  
Automatic Generation Control ◽  
Power Sources ◽  
Power Frequency ◽  
Comparative Stability ◽  
Generation Control

Background: A comparative analysis of Automatic Generation Control (AGC) of two-area electric power systems interconnected by AC and AC-DC links under deregulated environment is conducted. Each area has Thermal-Thermal (TT), Thermal-Hydro (TH) and/or Hydro-Hydro (HH) multiple power sources. A maiden attempt is made to study the demeanour of HH power system under restructured mode. Methods: The state space models of the power systems have been developed to simulate all market transactions probable in a deregulated power environment and optimal proportional integral structured controller is applied to improve the dynamic performance. The concept of DISCO participation matrix is harnessed to simulate the transactions. Results: Eigenvalue analysis is carried out to assess the comparative stability analysis of the power systems with/without AC-DC links. Further, the dynamic responses of TT, TH and HH power systems are contrasted in the presence of AC link and AC-DC links. The inclusion of AC-DC links improves the dynamic performance of all the systems remarkably, however, the responses of HH system are sluggish/poor with large undershoots in comparison to TT and TH systems. Also, TH system exhibits degraded dynamic performance compared to TT system. Conclusion: Moreover, optimal controller is found competent to demonstrate the matching of generation with power demand under different market transactions.

scholarly journals Design and analysis of two degree of freedom tilt integral derivative controller with filter for frequency control and real time validation

2020 ◽  
Vol 71 (6) ◽  
pp. 388-396
Author(s):  
Jagan Mohana Rao Chintu ◽  
Rabindra Kumar Sahu ◽  
Sidhartha Panda
Keyword(s):  
Power Systems ◽  
Real Time ◽  
Thermal Model ◽  
Search Algorithm ◽  
Frequency Control ◽  
Automatic Generation ◽  
Degree Of Freedom ◽  
Suggested Approach ◽  
Bee Colony ◽  
Two Degree Of Freedom

AbstractTo deliver steady electric power with decent quality, intelligent and healthy control schemes are greatly necessary for automatic generation control (AGC) of power systems therefore, this work presents the design of two degree of freedom based tilt integral derivative controller with filter for AGC. Firstly, a two-area reheat thermal model is considered, and the gain of the controller are optimized by adaptive differential evolution method. The advantage of the suggested approach is validated by equating results with latest published approaches such as symbiotic organism search algorithm and articial bee colony tuned PID controller. Further, the suggested method is extended to a three unequal area thermal model and the performance of results are equated with teaching-learning based optimization-PIDD and firey algorithm-PID for the identical model. Lastly, the experiment of the proposed scheme has been employed in real-time simulation using OPAL-RT, for validation of its viability and cogency.

Fuzzy Based Intelligent Approach to AGC of Multi-Area Multi-Unit Power System with SMES under Random Load Disturbances

2014 ◽  
Vol 492 ◽  
pp. 431-438
Author(s):  
Sathans Suhag ◽  
A. Swarup
Keyword(s):  
Power Systems ◽  
Power System ◽  
Intelligent Control ◽  
Control Strategy ◽  
Magnetic Energy ◽  
Thermal Power ◽  
Automatic Generation ◽  
Pi Controller ◽  
Random Load ◽  
Thermal Power System

In reality, load variations in power systems are random in nature. Therefore, the automatic generation control (AGC) performance of the power system needs to be investigated under random load disturbances so as to have a realistic evaluation of the control strategy. This paper reports results for one such investigation. The intelligent control strategy, based on fuzzy gain scheduling of a proportional-integral (PI) controller, is developed and implemented for a multi-area multi-unit thermal power system with reheat nonlinearity. The paper also investigates the effect of superconducting magnetic energy storage (SMES) system on the AGC performance. For the sake of comparison, the behavior of the system for the same load disturbance is also investigated with a conventional PI controller. Simulation studies indicate that the proposed intelligent control strategy is very effective under random load disturbances and provides significant improvement over the conventional PI controller.

Design an optimal fuzzy fractional proportional integral derivative controller with derivative filter for load frequency control in power systems

2019 ◽  
Vol 41 (9) ◽  
pp. 2563-2581 ◽  
Author(s):  
Meysam Gheisarnejad ◽  
Mohammad Hassan Khooban
Keyword(s):  
Power Systems ◽  
Power Plants ◽  
Frequency Control ◽  
Thermal Power ◽  
Automatic Generation ◽  
Load Frequency Control ◽  
Fine Tuning ◽  
Proportional Integral Derivative ◽  
Proportional Integral ◽  
Test Systems

In this article, a novel fuzzy proportional integral derivative (PID) controller with filtered derivative action and fractional order integrator (fuzzy PIλDF controller) is proposed to solve automatic generation control (AGC) problem in power system. The optimization task for fine-tuning parameters of the proposed controller structure is accomplished by cuckoo optimization algorithm (COA). To appraise the usefulness and practicability of proposed COA optimized fuzzy PIλDF controller, four extensively used interconnected test systems, that is, two-area non-reheat thermal, two-area multi-source, three-area thermal and three-area hydro-thermal power plants, are considered. Different nonlinearity such as generation rate constraint (GRC) and governor dead band (GDB) as a source of physical constraints are taken into account in the model of the three-area power systems to examine the ability of the proposed technique to handle practical challenges. The acceptability and novelty of COA-based fuzzy PIλDF controller to solve aforesaid test systems are evaluated in comparison with some recently reported approaches. The consequences of time domain simulation reveal that designed secondary controllers provide a desirable level of performance and stability compared with other existing strategies. Additionally, to explore the robustness of the proposed technique, sensitivity analysis is conducted by varying the operating loading conditions and system parameters within a specific tolerable range.

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