Hydro Area Research Articles

A hybrid metaheuristic optimisation technique for load frequency control

This paper investigates the problem of load frequency control by the application of metaheuristic optimisation techniques. In order to analyse the effect of the system model on the performance of the algorithm, two different two-area systems are considered, modelled using the Matlab/Simulink package. The first one consists of a reheat thermal area and a hydro area while the second one is made up of identical reheat thermal areas. To take into consideration the effects of practical constraints, nonlinearities such as Generation Rate Constraint, Governor Deadband and Boiler Dynamics are introduced. The Shuffled Frog Leaping Algorithm and Teaching Learning Based Optimisation are applied followed by a proposed hybrid of both algorithms to tune Proportional-Integral-Derivative (PID) controllers for the different areas of the systems, taking into account step load changes as inputs. The aim of this proposed algorithm is to merge the qualities of the individual algorithms to provide a more efficient one, converging faster to the optimal gains of the controllers. The results obtained proved the satisfactory performances of all algorithms and superiority of the hybrid Shuffled Frog Leaping Algorithm -Teaching Learning Based Optimisation technique in controlling frequency level in both systems investigated, where the main control measures such as peak values, settling times and steady-state values have been considered.Article HighlightsWhen considering a system of electrical mechanisms installed to produce, distribute and use electric energy, it is important to match supply with demand in order to keep frequency almost constant so as to ensure the safe and reliable use of equipment and maintain stability.The combination of two different algorithms efficiently improved the performance of the control system since the new system benefitted from the qualities of both strategies.Algorithm-based controllers provided robust and reliable frequency control and may be used to increase the quality of electrical energy under increasing and constantly changing demand.

Performance of CSA optimized controllers of DFIGs and AGC to improve frequency regulation of a wind integrated hydrothermal power system

In the event of availability of wind and hydro power resources in a predominantly thermal power system, the wind power utilization policy may be chosen judiciously so that the frequency regulation capability of the system improves. The main objective of the work is to analyze the effects of integrating Double Fed Induction Generator (DFIG) based wind power to a standard two area power system in terms of the frequency regulation capability of the system. Wind power integration is done in the conventional Automatic Generation Control (AGC) models of two area interconnected power system, first when both the areas have thermal generation (Thermal-thermal) and then replacing hydro power in one of the areas (Hydro-thermal). The effects of variations of system load power on the frequency regulation is studied in both thermal-thermal and hydro-thermal environment within AGC. The work proposes a simultaneous optimization of controller parameters of AGC and DFIG controllers with the help of Cuckoo Search Algorithm to improve the frequency regulation of the system. It was further found that it is more beneficial to utilize the available wind power resources in the hydro area instead of thermal area in a hydro-thermal power system.

Optimizing the AGC system of a three-unequal-area hydrothermal system based on evolutionary algorithms

This paper focuses on expanding and evaluating an automatic generation control (AGC) system of a hydrothermal system by modelling the appropriate generation rate constraints to operate practically in an economic manner. The hydro area is considered with an electric governor and the thermal area is modelled with a reheat turbine. Furthermore, the integral controllers and electric governor parameters are optimized using integral squared error (ISE) criterion. Also, a novel Teaching-Learning-Based Optimization (TLBO) algorithm, Particle Swarm Optimization (PSO), and Gravitational Search Algorithm (GSA) with controller are proposed for optimizing AGC. Investigations have been conducted for the selection of a suitable value for governor speed regulation parameter R for the hydro and thermal areas, to explore the effect of tie-line power on the dynamic response. The advantages of the proposed approach are demonstrated by comparing the results of optimizing the AGC system of a three-unequal-area hydrothermal system with mentioned algorithms for the first one in comparison with other recently published techniques. The results confirm the flexibility and the suitability of the proposed AGC model for optimizing the different approaches. Moreover, it is more practical to use the proposed method to make a wide variety of changes in the system parameters using sensitivity analysis.

Performance analysis of automatic generation control of interconnected power systems with delayed mode operation of area control error

This study presents automatic generation control (AGC) of interconnected power systems comprising of two thermal and one hydro area having integral controllers. Emphasis is given to a delay in the area control error for the actuation of the supplementary controller and to examine its impact on the dynamic response against no delay which is usually the practice. Analysis is based on 50% loading condition in all the areas. The system performance is examined considering 1% step load perturbation. Results reveal that delayed mode operation provides a better system dynamic performance compared with that obtained without delay and has several distinct merits for the governor. The delay is linked with reduction in wear and tear of the secondary controller and hence increases the life of the governor. The controller gains are optimised by particle swarm optimisation. The performance of delayed mode operation of AGC at other loading conditions is also analysed. An attempt has also been made to find the impact of weights for different components in a cost function used to optimise the controller gains. A modified cost function having different weights for different components when used for controller gain optimisation improves the system performance.

FREQUENCY REGULATION OF DEREGULATED POWER SYSTEM HAVING GRC INTEGRATED WITH RENEWABLE SOURCE.

This paper addresses the automatic generation contr ol of deregulated multi area power system including one of the most important renewable energy resource viz. wind power plant. Th e interconnected two area power system is thermal-h ydro system with two GENCOs in thermal area and one GENCO in hydro area. Generation rate constraint (GRC) is considered in all the GENCOs separately. Integral square error technique is used to optimize the gains of various integral controll ers. It is seen that system response becomes poorer in terms of peak overshoots and sett ling time by considering GRC. DISCO participation m atrix is chosen on the basis of open market strategy which is continuously chang ing. So, effect of changing DPM on dynamic response s is studied, following a step load perturbation. It is revealed that there is no effect of changing DPM on system’s dynamic response s.

A Comparison of PI Tuning by Direct Search and Genetic Algorithm for Optimal Control of AGC in Continuous-Discrete Mode

This paper deals with Automatic generation control (AGC) of interconnected hydrothermal system in continuous-discrete mode using proportional-integral (PI) controller with different tuning approaches. Here the PI controller is initially tuned using local optimization technique such as Fminsearch (Existing MATLAB function) and optimal control strategies were taken as integral square error (ISE), integral time-absolute error (IATE) and integral time square error (ISTE). Then the same PI controller is tuned by using evolutionary algorithm i.e. Genetic Algorithm (GA). For the given system appropriate generation rate constraint (GRC) has been considered both for the thermal and hydro plants. System performances are examined considering 1 % Step Load Perturbation (SLP) in both thermal and hydro area with 1 second sampling period. Finally the performance of both the local and global optimization algorithms is compared in terms of the time domain specifi cations both for frequency deviation in each area, and tie line power.

Simulation study for automatic generation control of a multi-area power system by ANFIS approach

This paper deals with the application of artificial neural network (ANN) based ANFIS approach to automatic generation control (AGC) of a three unequal area hydrothermal system. The proposed ANFIS controller combines the advantages of fuzzy controller as well as quick response and adaptability nature of ANN. Appropriate generation rate constraints (GRC) have been considered for the thermal and hydro plants. The hydro area is considered with an electric governor and thermal area is considered with reheat turbine. The design objective is to improve the frequency and tie-line power deviations of the interconnected system. 1% step load perturbation has been considered occurring either in any individual area or occurring simultaneously in all the areas. It is a maiden application of ANFIS approach to a three unequal area hydrothermal system with GRC considering perturbation in a single area as well as in all areas. The performance of the ANFIS controller is compared with the results of integral squared error (ISE) criterion based integral controller published previously. Simulation results are presented to show the improved performance of ANFIS controller in comparison with the conventional integral controller. The results indicate that the controllers exhibit better performance. In fact, ANFIS approach satisfies the load frequency control requirements with a reasonable dynamic response.

GASA Tuned Optimal Fuzzy Regulator for AGC of an Interconnected Power System

fuzzy AGC regulator design based on GASA tuning technique for interconnected power system is proposed in this paper. The investigations with the GASA tuned optimal fuzzy regulator are carried out on a two area interconnected power system consisting of power plants with different characteristics. Power system area-1 is having plants with reheat thermal turbines whereas area-2 has plants with hydro turbines. The dynamic response plots are obtained for 1% load disturbance in hydro area. The dynamic response plots are obtained for various system states with the implementation of conventional integral, fuzzy logic and GASA based AGC regulators designed in the study. The GASA technique is applied to tune the gains of fuzzy logic based AGC regulators also. The simulation results demonstrate superiority of GASA technique based optimal fuzzy AGC regulators over the others.

Automatic generation control of a multi area hydrothermal system using reinforced learning neural network controller

This paper deals with automatic generation control (AGC) of a three unequal area hydrothermal system. Reheat turbines in thermal areas and electric governor in hydro area are considered. Appropriate generation rate constraints are considered in the areas. Bacterial foraging (BF) technique is used to simultaneously optimize the integral gains ( K Ii ) and speed regulation parameter ( R i ) keeping frequency bias fixed at frequency response characteristics. The integral controller in this case is termed as BFIC. The performance of a multilayer perception neural network (MLPNN) controller using reinforcement learning is evaluated for the system. In this reinforcement learning, the weights are dynamically adjusted online using backpropagation algorithm with error being the area control error (ACE). The performance of the MLPNN controller is compared with that of BFIC. Also, the performance of MLPNN controller over a wide range of system loading conditions and step load perturbations is compared with BFIC. Investigations clearly reveal the superior performance of MLPNN controller over BFIC. Sensitivity analysis subject to wide changes in system loading, inertia constant ( H) and size and location of step load perturbation is carried out to investigate the robustness of the controller with the optimum K Ii and R i obtained at nominal condition.

Some New Findings on Automatic Generation Control of an Interconnected Hydrothermal System With Conventional Controllers

This paper deals with automatic generation control of an interconnected hydrothermal system in continuous-discrete mode using conventional integral and proportional-integral controllers. Appropriate generation rate constraint has been considered for the thermal and hydro plants. The hydro area is considered with either mechanical or electric governor and thermal area is considered with either single or double reheat turbine. Performances of mechanical governor, electric governor, and single stage reheat turbine and two stage reheat turbine on dynamic responses have been explored. Further, selection of suitable value of speed regulation parameter R and sampling period has been investigated. System performance is examined considering 1% step load perturbation in either thermal or hydro area.