Two-area Reheat Thermal System Research Articles

AGC of two-area electric power systems using optimized fuzzy PID with filter plus double integral controller

The incessant swell in size, complexity, nonlinearity and structural variations in modern electric power systems, as well as rise in power demand has entailed the use of intelligent control strategies for the real-time satisfactory operation of power system. Hence, in this paper, a novel fuzzy PID with filter plus double integral (FPIDF-II) controller is proposed for automatic generation control (AGC) of two-area interconnected power systems. Initially, a well accepted two-area non-reheat thermal system is considered and the output scaling factors (SF) of FPIDF-II controller are optimized using imperialist competitive algorithm (ICA) employing an integral squared error (ISE) criterion. The supremacy of the proposed approach is demonstrated by contrasting the results with recently published optimal and various modern heuristic optimization techniques based controllers. To demonstrate the efficacy and scalability of the approach over other prevalent intelligent control techniques, the study is further extended to two-area non-reheat thermal system with governor deadband nonlinearity, two-area reheat thermal system, recently appeared two-area photovoltaic (PV)-reheat thermal system and two-area multi-source hydrothermal system. Finally, a sensitivity analysis is carried out to demonstrate the robustness of the proposed controller under broad variations in the system parameters from their nominal values.

Fuzzy Gain Scheduling Controllers for Automatic Generation Control of Two-area Interconnected Electrical Power Systems

In this study, fuzzy gain scheduling controllers are proposed for automatic generation control of interconnected electrical power systems. Primarily, the study is done for automatic generation control of a two-area non-reheat thermal power system, and the parameters of fuzzy gain scheduling controllers are optimized by a genetic algorithm. Simulation results show the performance of fuzzy gain scheduling controllers is superior compared to the optimal and controllers based upon the gravitational search, the bacteria foraging optimization, and the hybrid bacteria foraging optimization–particle swarm optimization algorithms for an identical power system. The proposed approach is further protracted to a two-area reheat thermal system; the benefits of the fuzzy gain scheduling approach are demonstrated over optimal, conventional proportional-integral, and genetic algorithm-based integral controllers. Next, a multi-source multi-area hydro thermal system is considered, and the superiority of fuzzy gain scheduling controllers is established by comparing the results to the genetic algorithm and best claimed hybrid firefly algorithm–pattern search technique-based controllers. Finally, the effectiveness of the proposed approach is established for a two-area restructured reheat thermal power system. The simulation results indicate that the proposed fuzzy gain scheduling controllers work efficiently and provide better dynamic performance without being redesigned for separate systems.

Variable structure control strategy to automatic generation control of interconnected reheat thermal system

The paper deals with the analysis of automatic generation control (AGC) of a two-area reheat thermal system considering a variable structure controller (VSC) based on the sliding mode concept. A systematic method is suggested for obtaining switching hyperplanes. Optimum gain settings of the variable structure controller are obtained, both in the unconstrained (neglecting generation rate) and the constrained (considering generation rate constraint) modes, using the integral squared error (ISE) technique. Investigation reveals that there is a significant improvement in system dynamic performance with a VSC over that with an integral controller. Moreover, the variable structure controller is found to be quite insensitive to wide variations of system parameters.

Discrete-mode automatic generation control of a two-area reheat thermal system with new area control error

Most of the work reported in the literature pertaining to Automatic Generation Control (AGC) of interconnected power systems is centered around tie-line frequency bias control strategy. Supplementary controllers are designed to regulate the area control errors to zero effectively. Several modern design techniques have been used to optimize the parameters of the supplementary controllers. Supplementary controllers regulate the generation to match the load variation. As the generation change chases the load variation, the frequency and tie-power deviate from the scheduled values. This would result in accumulations of time error and inadvertent interchange. They would also occur due to various measurement errors or intentional offsets in scheduled settings. It is expected that individual areas will make all reasonable efforts to minimize time error and inadvertent interchange accumulations by minimizing or eliminating source causes. There is a need for correcting these accumulations. Such corrections are achieved by making appropriate offsets in system frequency schedules to compensate for time error accumulations and offsets in area net interchange schedules to compensate for inadvertent interchange accumulations. Detailed literature survey clearly shows that the two-step correction scheme, mentioned above, has been used by utilities inspite of some practical difficulties. To avoid those difficulties they are looking forward for a suitable control strategy that not only maintains constancy of system frequency and desired tie-power flow but also achieves zero steady state time error and inadvertent interchange. It is essentially in this area, the investigations are carried out in this paper.

Sampled-Data Automatic Generation Control of Interconnected Reheat Thermal Systems Considering Generation Rate Constraints

This paper deals with some aspects of sampled-data Automatic Generation Control (AGC) of a two-area reheat thermal system provided with classical controllers. Discrete mode optimization of such controllers using margin of stability and Integral Squared Error concepts have been attempted. Investigations rev eal that the optimal integral gain achieved through the continuous mode analysis is totally unacceptable in the discrete mode for the sampling periods used in practice Moreover, for all practical purposes the optimum integral gain in the discrete mode can be achieved by neglecting the generation rate constraints from the mathematical model unlike in the continuous mode. Performances of discrete optimum integral and optimum proportional-integral controllers have also been examined. Recommendation to optimum sampling period selection has also been attempted.