scholarly journals Load Frequency Control of HVDC Link Interconnected Power System Using Genetic Algorithm

MENDEL ◽  
2019 ◽  
Vol 25 (1) ◽  
pp. 131-138
Author(s):  
Saurabh Chanana ◽  
Saurabh Kumar

Advances in power electronics have improved grid support functions such as tie-line power control and frequency control, making renewable generation and High Voltage DC (HVDC) links more common in power system applications. Load Frequency Control (LFC) systems handle the complex interactions between the distributed generator and the control area with the HVDC link. In this work, LFC of a two-zone system including parallel AC/DC transmission links has been analysed. The parameters of this system are optimised using advanced genetic algorithm resulting in improved performance of system in terms of reduction in peak overshoots and settling time of frequency measurement, tie line power flow and area control error signals in an interconnected power system. The advantage of having parallel HVDC links is also demonstrated when performance is compared to system interconnected with only AC tie line.

Load frequency control (LFC) in interconnected power system of small distribution generation (DG) for reliability in distribution system. The main objective is to performance evaluation load frequency control of hybrid for interconnected two-area power systems. The simulation consist of solar farm 10 MW and gasifier plant 300 kW two-area in tie line. This impact LFC can be address as a problem on how to effectively utilize the total tie-line power flow at small DG. To performance evaluation and improve that defect of LFC, the power flow of two-areas LFC system have been carefully studied, such that, the power flow and power stability is partially LFC of small DG of hybrid for interconnected two-areas power systems. Namely, the controller and structural properties of the multi-areas LFC system are similar to the properties of hybrid for interconnected two-area LFC system. Inspired by the above properties, the controller that is propose to design some proportional-integral-derivative (PID) control laws for the two-areas LFC system successfully works out the aforementioned problem. The power system of renewable of solar farm and gasifier plant in interconnected distribution power system of area in tie – line have simulation parameter by PID controller. Simulation results showed that 3 types of the controller have deviation frequency about 0.025 Hz when tie-line load changed 1 MW and large disturbance respectively. From interconnected power system the steady state time respond is 5.2 seconds for non-controller system, 4.3 seconds for automatic voltage regulator (AVR) and 1.4 seconds for under controlled system at 0.01 per unit (p.u.) with PID controller. Therefore, the PID control has the better efficiency non-controller 28 % and AVR 15 %. The result of simulation in research to be interconnected distribution power system substation of area in tie - line control for little generate storage for grid connected at better efficiency and optimization of renewable for hybrid. It can be conclude that this study can use for applying to the distribution power system to increase efficiency and power system stability of area in tie – line.


2014 ◽  
Vol 63 (2) ◽  
pp. 161-175 ◽  
Author(s):  
S. Selvakumaran ◽  
V. Rajasekaran ◽  
R. Karthigaivel

Abstract A new design of decentralized Load Frequency Controller for interconnected thermal non-reheat power systems with AC-DC parallel tie-lines based on Genetic Algorithm (GA) tuned Integral and Proportional (IP) controller is proposed in this paper. A HVDC link is connected in parallel with an existing AC tie-line to stabilize the frequency oscillations of the AC tie-line system. Any optimum controller selected for load frequency control of interconnected power systems should not only stabilize the power system but also reduce the system frequency and tie line power oscillations and settling time of the output responses. In practice Load Frequency Control (LFC) systems use simple Proportional Integral (PI) or Integral (I) controller. The controller parameters are usually tuned based on classical or trial-and-error approaches. But they are incapable of obtaining good dynamic performance for various load change scenarios in multi-area power system. For this reason, in this paper GA tuned IP controller is used. A two area interconnected thermal non-reheat power system is considered to demonstrate the validity of the proposed controller. The simulation results show that the proposed controller provides better dynamic responses with minimal frequency and tie-line power deviations, quick settling time and guarantees closed-loop stability margin.


Author(s):  
Dao Thi Mai Phuong

The crucial objectives of load-frequency control (LFC) to a multi-area interconnected power system are to maintain the system frequency at a nominal value (50 Hz or 60 Hz) and the tie-line power flows at predetermined values. Based on tie-line bias control strategy, conventional regulators, such as I, PI and PID, were initially used for solving the LFC problem. Due to the complexity, nonlinearity and uncertainty of a multi-area power system in practice, the conventional regulators may not obtain the control performances good enough to bring the network back to the steady state as soon as possible. Meanwhile, intelligent controllers, such as fuzzy logic (FL)-based controllers, are able to completely replace these conventional counterparts. The superiority of the FL-based LFC controllers over the conventional ones for a typical case study of five-area interconnected power grids is validated in this paper through numerical simulations implemented in Matlab/Simulink package. It should be apparent from this comparative study that the LFC controller based on FL technique is a feasible selection in dealing with the LFC problem of a multi-area power network.


Energies ◽  
2021 ◽  
Vol 14 (6) ◽  
pp. 1581
Author(s):  
Deepak Kumar Gupta ◽  
Amitkumar V. Jha ◽  
Bhargav Appasani ◽  
Avireni Srinivasulu ◽  
Nicu Bizon ◽  
...  

The automatic load frequency control for multi-area power systems has been a challenging task for power system engineers. The complexity of this task further increases with the incorporation of multiple sources of power generation. For multi-source power system, this paper presents a new heuristic-based hybrid optimization technique to achieve the objective of automatic load frequency control. In particular, the proposed optimization technique regulates the frequency deviation and the tie-line power in multi-source power system. The proposed optimization technique uses the main features of three different optimization techniques, namely, the Firefly Algorithm (FA), the Particle Swarm Optimization (PSO), and the Gravitational Search Algorithm (GSA). The proposed algorithm was used to tune the parameters of a Proportional Integral Derivative (PID) controller to achieve the automatic load frequency control of the multi-source power system. The integral time absolute error was used as the objective function. Moreover, the controller was also tuned to ensure that the tie-line power and the frequency of the multi-source power system were within the acceptable limits. A two-area power system was designed using MATLAB-Simulink tool, consisting of three types of power sources, viz., thermal power plant, hydro power plant, and gas-turbine power plant. The overall efficacy of the proposed algorithm was tested for two different case studies. In the first case study, both the areas were subjected to a load increment of 0.01 p.u. In the second case, the two areas were subjected to different load increments of 0.03 p.u and 0.02 p.u, respectively. Furthermore, the settling time and the peak overshoot were considered to measure the effect on the frequency deviation and on the tie-line response. For the first case study, the settling times for the frequency deviation in area-1, the frequency deviation in area-2, and the tie-line power flow were 8.5 s, 5.5 s, and 3.0 s, respectively. In comparison, these values were 8.7 s, 6.1 s, and 5.5 s, using PSO; 8.7 s, 7.2 s, and 6.5 s, using FA; and 9.0 s, 8.0 s, and 11.0 s using GSA. Similarly, for case study II, these values were: 5.5 s, 5.6 s, and 5.1 s, using the proposed algorithm; 6.2 s, 6.3 s, and 5.3 s, using PSO; 7.0 s, 6.5 s, and 10.0 s, using FA; and 8.5 s, 7.5 s, and 12.0 s, using GSA. Thus, the proposed algorithm performed better than the other techniques.


Sign in / Sign up

Export Citation Format

Share Document