Tie-line Power Flow Research Articles

Optimal design of model predictive control with superconducting magnetic energy storage for load frequency control of nonlinear hydrothermal power system using bat inspired algorithm

This paper proposes bat inspired algorithm (BIA) as a new optimization approach of a model predictive control (MPC) and superconducting magnetic energy storage (SMES) for load frequency control (LFC) of a two-area interconnected hydrothermal system. The proposed power system model includes generation rate constraint (GRC), governor dead band, and time delay. Conventionally, the parameters of MPC controller and SMES are obtained by trial and error method or experiences of designers. To overcome this problem, the BIA is applied to simultaneously tune the parameters of MPC controller and SMES to minimize deviations of frequency and tie-line power flow of the interconnected power system against load disturbances. Simulation results show that the performance of the proposed BIA based MPC controller with SMES is superior to the conventional proportional-integral (PI) controller based integral square error technique and BIA based MPC controller without SMES in terms of the overshoot settling time and robustness.

A New Load Frequency Control Method of Multi-Area Power System via the Viewpoints of Port-Hamiltonian System and Cascade System

The existed control methods of the multi-area load frequency control (LFC) system fail to decouple the total tie-line power flow. This defect can be addressed as a problem on how to effectively utilize the total tie-line power flow. To improve that defect, the energy and structure of multi-area LFC system have been carefully studied, such that, the energy goes through the systemic cascade parts and the systemic structure matrix is partially skew symmetry. Namely, the energy and structural properties of the multi-area LFC system are similar to the properties of Port-Hamiltonian (PH) system and cascade system. Inspired by the above properties, a new method based on the PH system and cascade system that is proposed to design some PID control laws for the multi-area LFC system successfully works out the aforementioned problem. Compared with the existed PID methods for the multi-area LFC system, the proposed method has two advantages, which are the decoupling of total tie-line power flow and the robust disturbance rejection. At last, simulations results demonstrate the validity and advantages of the proposed method.

Decentralised method for solving multi‐area stochastic dynamic economic dispatch problem

This study discusses the implementation of a decentralised optimisation method for the multi-area stochastic dynamic economic dispatch (MASDED) of power systems with wind power integrated. Firstly, the volatility of wind power is represented by sampling wind scenarios, and the consensus constraints of tie-line power flows among the forecast scenario and sampling scenarios are built. Secondly, the multi-area power system is decomposed into different areas by creating a coordination centre and duplicating boarder variables. Finally, analytical target cascading method is applied to solve the MASDED in a decentralised way. The master problem of the coordination centre, the forecast scenario subproblems, and the sampling scenario subproblems of each area are solved iteratively. In order to increase computation speed, the decentralised deterministic optimisation is implemented before the decentralised stochastic optimisation. The three-area IEEE reliability test system is tested to demonstrate the effectiveness of the proposed method.

Using differential search algorithm for solving optimal frequency regulation problem in interconnected power system

In order to improve the frequency stability and control in an interconnected power system including various power generating units, the automatic generation control (AGC) needs to be more robust and efficient. On the other hand, the difficulties in AGC are not only to design a robust controller but it also to optimise its parameters effectively for a robust optimal solution. In this paper, an application of a new efficient optimisation method called the differential search algorithm (DSA) was proposed to solve the AGC problem. The proposed approach was applied to reach the proportional-integral-derivative (PID) controller parameters. This latter was used to maintain the frequency at nominal value using the integral time multiplied by absolute error (ITAE) as fitness function. To show the robustness of the proposed strategy, a four area interconnected electrical network was investigated for the simulation. The obtained DSA results were compared to other approaches available in literature. The simulation results of this research show that DSA strategy is able to solve AGC problem and achieve less frequency and tie-line power flow deviations than those determined by other methods used in this paper.

Symbiotic organisms search algorithm for automatic generation control of interconnected power systems including wind farms

Automatic generation control (AGC) plays an important role in power systems, where it maintains the system frequency and tie-line power flow at their desired values. This study presents a novel symbiotic organisms search (SOS) algorithm in order to optimally design the proportional–integral–derivative (PID) controllers in the AGC of interconnected multiple-area power systems including wind farms uncertainty and system non-linearity. The PID controllers’ parameters define the design variables of the optimisation problem. The SOS algorithm is applied to different objective functions such as integral square error and integral absolute of error. The efficacy of the proposed controller is compared with other competing evolutionary algorithms-based proportional–integral or PID controller. The system performance is evaluated under different operating conditions such as different loading, variation of system parameters, and an addition of wind energy uncertainty. For obtaining realistic responses, real wind speed data that extracted from Zafarana location in Egypt is used in this study. The validity of the proposed controller is extensively confirmed using the simulation results. With the SOS-based PID controllers, the dynamic responses for the AGC of interconnected power systems, including wind farms uncertainty can be further enhanced.

Automatic Generation Control of Two Equal Areas with Traditional Controllers

Automatic generation control (AGC) is major issue in power system whose main purpose is to maintain the frequency and tie line power flow during normal period in an interconnected system. . Thus, It is the responsibility of the Power system engineers to ensure that adequate power is delivered to the load reliably and economically so that nominal condition will be re-established The main focus is to maintain the value of frequency in its prescribed limit. We use renewable source which are important as well as non renewable sources at the level of extinct. As renewable alone cannot reliable then we use interconnection of both for making the system reliable and more efficient.This research paper is devoted to explore the interconnection of the automatic generation control of hydro power system and wind system. The wind system is comprised with governor dead band, generation rate constraint and turbine dynamics where as the hydro system is comprised with generation rate constraint. The traditional PI controller does not have adequate control performance with the consideration of nonlinearities and turbine dynamics. To overcome this drawback, PID controllers helps in solving optimization problems by exploitation of random search. It will provide the system security also for maintain the frequency in prescribed limit with the help of simulation.

Amalgamated Firefly Algorithm with Migration Effect of Biogeography Based Optimization for Proportional Integral and Derivative Controller Parameters Optimization in Two Area Interconnected Power System

In this study, Firefly Algorithm and Amalgamated Firefly Algorithm with Migration Effect of Biogeography Based Optimization techniques are proposed to optimize the proportional, integral and derivative gains of PID controller in two equal areas Interconnected Power System for quenching the deviations of frequency and make the tie line power flow deviation to zero. The considered performance index for minimization is Integral of Time weighted Absolute value of Error. Two different operating conditions are taken. First operating condition is taken as, the occurrence of 5% step load perturbation in area 1 and 10% step load perturbation in area 2. Second operating condition is taken as, the occurrence of 15% step load perturbation in area 1 and 10% step load perturbation in area 2. Importance of this interconnected power system is to provide reliable and efficient power to consumers. For this reason, the responses are analyzed and discussed. Finally, it is concluded with the identification of better optimization technique which provides solution for supply of reliable and efficient power to consumers in an interconnected power system. From the response and analysis, amalgamated firefly algorithm with migration effect of biogeography based optimization gives better performance compared from firefly algorithm. Migration effect of biogeography based optimization technique improves the local search of firefly algorithm in the amalgamated performance.

Optimal AGC regulator for multi-area interconnected power systems with parallel AC/DC links

AbstractThe problem of simultaneous tuning of the automatic generation control (AGC) regulator’s gains of multi-area interconnected power system is carried out in this manuscript. Based on the types of area interconnections, a power system model consisting of reheat turbines is investigated by two test cases for the AGC study. In one of the test case AC link is used as area interconnection, whereas the parallel combination of AC/DC links is used as area interconnection in other test case. Each test case control area is consisting of plants with reheat thermal turbines. Genetic algorithm (GA) is used to globally optimize the gains of proportional integral-based AGC regulators with simultaneous optimization of frequency bias coefficient and tie-line power flows. The dynamic response curves are obtained for various system states with the implementation of designed GA-based AGC regulators considering 1% load perturbation in one of the areas. The conventional AGC regulators are also developed using the popular...

An Enhanced Droop Control Method for Accurate Load Sharing and Voltage Improvement of Isolated and Interconnected DC Microgrids

In this paper, a distributed local control scheme for dc microgrid is proposed along with the basic droop control. It eliminates the limitations of droop control when the distributed generators are geographically distributed, for which, the line resistances cannot be neglected. Effects of line inductance and constant power loading (CPL) are investigated by analyzing the voltage tracking transfer function for single source system. Stability of two sources single load microgrid with proposed controller is investigated. Simulated responses are presented for two sources single load microgrid (for the sake of simplicity) to depict the proper load sharing and voltage improvement capability of the proposed control method with the consideration of line resistances. However, this can be extended to multiple-source multiple-load configuration connected to the dc bus. A comparison of the result is presented to show the better performance of the proposed control scheme as compared to the conventional droop control and hierarchical secondary control. The interconnected operation of the microgrid is also investigated to show the applicability of the proposed control in the interconnected mode. A centralized controller in each area is used to make the tie-line power flow zero at steady state.

Simulation of the Two - Area Deregulated Power System using Particle Swarm Optimization

In the power system operation, the Load Frequency Control (LFC) is required for good quality reliable electric power supply. The main aim of the load frequency control is to maintain the frequency of each area and the tie-line power flow within the specified tolerance. This is achieved by adjusting the real power output of the generators for the corresponding changes in the load demand. Electric power industry is now an open market structure. This deregulated environment comprises of GENCOs, TRANSCOs and DISCOs, which are supervised by an Independent Service Operator (ISO). In this paper, the transaction between the GENCOs and DISCOs in the deregulated market structure based on the DISCO Participation Matrix (DPM) is designed and simulated. The Proportional-Integral (PI) controller is used to tune the LFC. In this tuning, an intelligent global Particle Swarm optimization (PSO) algorithm is used, which is a population based evolutionary algorithm. The dynamic response of the system is improved by minimizing the Integral Square Error (ISE). The response of the PSO tuned PI controller is compared with the response of the conventional PI controller for the system considered. It is found that, the response of the proposed PSO tuned PI controller is better than that of the conventional PI controller. The simulation is implemented in MATLAB-Simulink.

Microgrid operation optimization with regulation of grid tie-line power fluctuations and risk management

Summary This paper presents a novel multi-objective energy management method for a microgrid that includes renewable energy, diesel generators, battery storage, and various loads. The fluctuation of the grid tie-line power flow is regarded as one of the optimal objectives in order to decrease the power exchange between the microgrid and the main grid caused by intermittent and variable renewable resources. The uncertainty of renewable energy and loads is also considered in this paper. Stochastic optimization method is implemented for the output of renewable resources and controllable loads. Using the e-constrained and weighted sum method, the multi-objective operation optimization problem, which includes the minimum microgrid operation costs, fluctuations of the grid tie-line power, and the risk management, is converted to a single-objective mixed-integer linear optimization problem. The scheduling is achieved for controllable units such as diesel generators, batteries, controllable loads, and grid tie-line power under various weights. The main contribution of the study is to achieve the energy management for a microgrid with regulation of the grid tie-line power fluctuations and peak shaving. Copyright © 2016 John Wiley & Sons, Ltd.

Impact of phase shifting transformers on cross-border power flows in the Central and Eastern Europe region

Abstract Unscheduled power flows are a serious problem for the Central and Eastern Europe (CEE) region. One method of reducing these undesirable flows relies on the use of phase shifting transformers (PSTs). This paper presents how the installation of PSTs on the Polish-German and Czech-German borders affects cross-border power flows in the CEE region, as well as interactions between these devices. The essential parameters proposed for PSTs are based on the effects arising from the application of PSTs on the border between Poland and Germany. The results demonstrate that the use of PSTs in the CEE region can provide effective control of active power flows in tie-lines and significantly reduce unscheduled flows. However, the operation of these devices must be coordinated in order to achieve maximum controllability and to guarantee the secure operation of the interconnected systems.

Model Predictive Load-Frequency Control

A model predictive controller (MPC) for load frequency control (LFC) of an interconnected power system is investigated. The MPC is based on a simplified system model of the Nordic power system, and it takes into account limitations on tie-line power flow, generation capacity, and generation rate of change. The participation factors for each generator are optimization variables, and suggestions are made as to how one can ensure tie-line power transfer margins through slack-variables, and pricing information through the objective function. The solution of MPC for LFC is completed by including a Kalman filter for state estimation. The presented MPC is compared against a conventional LFC/AGC scheme with proportional integral (PI) controllers. Simulations show that the MPC gives better frequency response while using cheaper resources. This paper illustrates that MPC could be a realistic solution to some of the LFC problems power systems are facing today.

Model predictive load–frequency control taking into account imbalance uncertainty

Nonlinear model predictive control (NMPC) is investigated for load frequency control (LFC) of an interconnected power system which is exposed to increasing wind power penetration. The robustified NMPC (RNMPC) proposed here uses knowledge of the estimated worst-case deviation in wind-power production to make the NMPC more robust. The NMPC is based on a simplified system model that is updated using state- and parameter estimation by Kalman filters, and it takes into account limitations on among others tie-line power flow. Tests on a proxy of the Nordic power system show that the RNMPC is able to fulfill system constraints under worst-case deviations in wind-power production, where the nominal NMPC is not.

Reservoir based learning network for control of two-area power system with variable renewable generation

The penetration of renewable energy sources into the electric power system is rapidly increasing. Integrating variable renewable energy sources into the transmission grid introduces challenges in real time power system operation. This causes power and frequency fluctuations and raises stability concerns. In this paper, a 200MW photovoltaic (PV) plant is integrated into a two-area four-machine power system. In order to maintain the system frequency, a dynamic tie-line power flow control is implemented using predicted PV power as an input to the automatic generation controller in Area 1, which transfers power to Area 2 with PV generation. The prediction performances of two learning reservoir based networks, an echo state network (ESN) and an extreme learning machine (ELM), are investigated for day and night time operations. The experimental study is performed using actual weather data from Clemson, SC and a real time simulation of a utility-scale PV plant integrated power system. Phasor measurement units (PMUs) are used to provide input signals to automatic generation controllers in the two area power system. Typical tie-line power flow control results based on ESN and ELM models are presented to show the impact of predicting PV power in improved automatic generation control with variable generation. ESN and ELM models provide minimal tie-line power flow deviations from reference power flows during day and night time operations, respectively.

Automatic generation control of interconnected power system for robust decentralized random load disturbances using a novel quasi-oppositional harmony search algorithm

Abstract An effort is made in this paper to discuss the real-time problem of interconnected power system for resistance to random and rapid changes of small step load perturbation (SLP) in connection with automatic generation control (AGC). Rapid changes of loads, for a continuous period of time, always create problems in the benefits of optimum AGC performance. In view of this, a continuous nature of load profile is designed for its implementation in real-time application of AGC. In such case, the point of concern is to closely examine the frequency deviation and the behavior of tie-line power flow profiles within the control areas. To overcome these consequences, a novel quasi-oppositional harmony search (QOHS) algorithm based proportional–integral–derivative (PID) controller is proposed along with filtering technique. The test system under consideration is a three-area power system with two generating units (non-identical capacity) in each area having an appropriate generation rate constraint (GRC). Importance of considering the physical constraint (like GRC) is demonstrated by examining the closed loop performance of the studied power system model. The performance of the proposed QOHS algorithm is verified by comparing the obtained dynamic responses to those offered by the imperialist competitive algorithm for the same test system. In the final phase of investigation, the total load changes of all the three control areas are also considered for the purpose of analyzing the saturation and non-linearity effects of turbine. It may be apprehended from the simulation results that the proposed QOHS based PID controller is more efficient to minimize the effect of continuous SLP. The proposed QOHS algorithm shows the feasibility of the approach and is able to regain its steady-state operation for such load perturbation profiles.

Optimal Generation Control of Interconnected Power System Including DFIG-Based Wind Turbine

ABSTRACTThe impact of wind power with higher size of penetration becomes significant for frequency control problem due to its inconsistent nature and lack of frequency support from the wind turbine units. The frequency can be managed using enhanced control of inertia and droop characteristics. However, at very low and high speeds, the adjustment of pitch angle of wind turbine is necessary so that the aerodynamic power produced remains within the designed limits. This paper discloses the design of proportional integral (PI) control algorithm to adjust pitch angle of doubly fed induction generator (DFIG)-based wind turbine (WT) integrated with two-area-interconnected power system. Here, a heuristic gravitational search algorithm (GSA) is employed to optimize the gains of PI controllers used for pitch angle adjustment and governor speed control of wind turbine, frequency regulation, and tie-line power flow control. The influence of optimal gains by GSA is compared with genetic algorithm (GA) and ant colony optimization (ACO) approaches. Finally, the effectiveness of GSA-optimized controllers is demonstrated in terms of reduced settling time, overshoot, eigenvalues, and oscillations. The competency of proposed controller is also studied by considering the variation of wind power source from 10% to 40% in the power system and also the real-time physical constraints like generation rate, time delay, and governor deadband.

Stochastic multi‐objective tie‐line power flow and frequency control in market clearing of multi‐area electricity markets considering power system security

This study formulates a security-constrained multi-objective framework with unit commitment in multi-area electricity markets for day-ahead joint market-clearing. The dynamic and inertial characteristics of the power system are derived and incorporated into the market-clearing procedure in order to preserve power system security from the frequency viewpoint. In addition, two novel objective functions (tie-flow deviation index and Rocof index) besides the frequency-dependent social welfare and frequency excursion index have been defined to control the static frequency, rate of change of frequency (Rocof) and also the tie-line power flows, following the occurrence of a contingency. Comprehensive analysis tools for multi-area power systems and also pre- and post-contingency intervals are presented to verify the characteristics of the proposed model. The developed multi-objective programming is analysed through two case studies, a three-area system scheduled over 1 h and the IEEE two-area reliability test system over 24 h. It has been shown that the scheduling of energy and reserve services can be performed more effectively if the system frequency is considered in the market-clearing process. The proposed model can reconcile the need for reasonable total generation cost with concern for the independent system operator's responsibilities about the pre- and post-contingency tie-line power flow control and system security.

Identification of inter-area oscillations using wavelet transform and phasor measurement unit data

SUMMARY This paper presents a method for identification of the inter-area oscillations in power system by employing continuous wavelet transform (WT) with complex Morlet function. WT is implemented to decouple multi-component signals into the mono-component signals. The mono-component signals are represented as complex-valued signals. The corresponding parameters of oscillations such as the frequency and damping can be identified using the instantaneous amplitudes and phase angles of the complex-valued signals. The optimal values of Morlet parameters are obtained by minimization of the WT entropy. The performance of the proposed method is demonstrated by applying it to several simulated test cases and real power system data. The simulated test cases include a non-stationary test signal and two-area test system. The proposed method also implemented on measured data of Malin-Round Mountain tie-line power flow oscillation during 10 August 1996 event, and the results are compared with Prony method. Copyright © 2014 John Wiley & Sons, Ltd.

Neuro-Fuzzy Computational Technique to Control Load Frequency in Hydro-Thermal Interconnected Power System

In this research work, two areas hydro-thermal power system connected through tie-lines is considered. The perturbation of frequencies at the areas and resulting tie line power flows arise due to unpredictable load variations that cause mismatch between the generated and demanded powers. Due to rising and falling power demand, the real and reactive power balance is harmed; hence frequency and voltage get deviated from nominal value. This necessitates designing of an accurate and fast controller to maintain the system parameters at nominal value. The main purpose of system generation control is to balance the system generation against the load and losses so that the desired frequency and power interchange between neighboring systems are maintained. The intelligent controllers like fuzzy logic, artificial neural network (ANN) and hybrid fuzzy neural network approaches are used for automatic generation control for the two area interconnected power systems. Area 1 consists of thermal reheat power plant whereas area 2 consists of hydro power plant with electric governor. Performance evaluation is carried out by using intelligent (ANFIS, ANN and fuzzy) control and conventional PI and PID control approaches. To enhance the performance of controller sliding surface i.e. variable structure control is included. The model of interconnected power system has been developed with all five types of said controllers and simulated using MATLAB/SIMULINK package. The performance of the intelligent controllers has been compared with the conventional PI and PID controllers for the interconnected power system. A comparison of ANFIS, ANN, Fuzzy and PI, PID based approaches shows the superiority of proposed ANFIS over ANN, fuzzy and PI, PID. Thus the hybrid fuzzy neural network controller has better dynamic response i.e., quick in operation, reduced error magnitude and minimized frequency transients.