AUTOMATIC GENERATION CONTROL OF INTERCONNECTED MULTI AREA POWER SYSTEM

Abstract

Currently, power system operation and control with AGC are undergoing fundamental changes due to rapidly increasing amount of renewable sources, energy storage system, restructuring and emerging of new types of power generation, consumption and power electronics technologies. Continuous growth in size and complexity, stochastically changing power demands, system modeling errors, alterations in electric power system structures and variations in the system parameters over the time has turned AGC task into a challenging one. Infrastructure of the intelligent power system should effectively support the provision of auxiliary services such as an AGC system from various sources through intelligent schemes. Literature survey shows that performance of AGC of interconnected power system with diverse sources gets improved by changing in controller structure, using intelligent optimization techniques for controller parameters, adding storage system and by considering different participation of diverse sources in multi area power systems. Hence, proposing and implementing new controller approaches using high performance heuristic optimization algorithms to real world problems are always welcomed. Researchers are devising various optimization Algorithms with different behaviors in various systems. Widespread review of the taxonomy of optimization algorithms in power system is explored in this study. Most popular nature inspired algorithm is population based algorithm which has a set of solution which moves towards the goal all together. Meta Heuristic Algorithm is divided into two important groups as trajectory based and population based. Population based algorithm are further divided into six groups depending on bio-inspired, physics, chemistry, social human behavior, plant vi characteristics. Review of various population based algorithm in application to frequency control is studied. Also, critical review of AGC schemes in interconnected multi area power system with diverse sources is done. Performance of many controllers depends on proper selection of certain algorithms and specific control parameters. Hence, the goal of the present study is to propose different types of new supplementary controller to achieve better dynamic performances in multi-area interconnected power system with diverse sources. Based on the extensive literature review on the control designs of AGC of interconnected power system, it has been felt that new control techniques for design of AGC regulators for interconnected power system especially for renewable sources is always welcome and challenging for researchers. The problem of nonlinearity in interconnected power system with diverse sources has also been addressed with suitable control algorithms. The study is conducted by proposing novel human based nature inspired artificial intelligence (AI) technique - Jaya for AGC of two area interconnected thermal-hydro-gas power system with varying participation of sources. Comparative analysis of proposed Jaya based AGC with bio-inspired AI technique like BAT and recently published Bacterial Forging Optimization (BFO) technique justify the stability of controller. The controllers are compared in terms of dynamic response, performance index value and performance. Regular increase in energy demand made the researchers to work towards the realistic hybrid interconnected multi source power system. Undesirable behavior of renewable sources likes hydro and wind is regularly amended by researchers through incorporating different artificial techniques, energy sources, varying participation of sources etc.To make the system realistic, researchers studied nonlinearities and participation factors incorporation in power system. Novel Jaya vii based AI technique is further employed on realistic power system by considering non linearities like Governor Dead band (GDB), Generation Rate Constraint (GRC) and Boiler dynamics. The study is done on Jaya based AGC of two area interconnected thermal-hydro-wind and thermal-hydro-diesel power system with and without nonlinearities by considering step load and random perturbation at different control areas. By proper selection of AI technique based controller for AGC of interconnected multi area multi source power system gives the opportunity to works well with nonlinearities also. Using novel Jaya based PID parameter values, two area interconnected multi source power system without nonlinearities are simulated and set against other bio-inspired based AI techniques like bio inspired IPSO, PSO and BFA and social human behavior based TLBO algorithm. Modern control theory helps in achieving the main objectives of AGC by effective design strategy. Design of optimal AGC regulator is explored for three area interconnected multi source power system with suitable structures of weighting matrices. Linear quadratic regulator (LQR) owns the top spot for Optimal AGC regulator design. The choice of weighting matrices propels the improvement in dynamic performance and stability of system. Designing of optimal AGC regulator for three different three-area interconnected multi source power systems has been planned. In each power system, optimal AGC regulators have been designed by using different structures of cost weighting matrices (Q an R). Three different structures of cost weighting matrices have been inspected for the design of optimal AGC regulators. One of the novel approaches for design of cost weighting matrices is based on the scaling method. To validate the effectiveness of optimal AGC regulator with structures of control and state cost weighting matrices, dynamic response of system for frequency viii and tie line power deviation is procured with 1% slp in each area. Optimal feedback gain matrix, eigen values, dynamic response characteristics and dynamic responses are the assessment to examine the stability of power system. The investigation carried out reveal that optimal AGC regulator based on structures of control and state cost weighting matrices with scaling method offer remarkable improvement in dynamic stability as compared to other designed regulators. Implementation of Superconducting Magnetic Energy Storage System (SMES) in operation and control of AGC of three-area multi source power systems has been studied. Analysis of PSO tuned Integral controller for AGC of three area interconnected multi source power systems with and without SMES by considering step load perturbation at different control areas has bee done. Comparative performance of different bio-inspired artificial technique has been presented on AGC of three area interconnected power system with SMES. With the use of SMES in power system, significant improvement in the dynamic responses of power system has been observed .Degradation of system due to the presence of hydro sources in interconnected multi source power system with SMES is noticeably reduced by considering 1% slp in all area as compared to 1% slp in individually areas. Battery Energy Storage System (BESS) has the feature are to provide and absorb power at the time of load disturbances and have ability to charge and discharge in short span. AGC of three area multi source interconnected power systems by including and excluding Battery Energy Storage System (BESS) at step load perturbation in different control areas has been studied. Application of BESS in power system certainly helps the power system to achieve AGC objectives in astonishingly quick response time even with reneweable sources.