Multi-source Power System Research Articles

Application of Modified Biogeography Based Optimization in AGC of an Interconnected Multi-Unit Multi-Source AC-DC Linked Power System

An attempt has been made for the effective application of biogeography based optimization and its modified version to solve load frequency control (LFC) problem. Two-area interconnected multi-unit multi-source power system having thermal, hydro and gas power plant without and with AC-DC link is considered for study. Proportional-integral-derivative controller is used as secondary controller in LFC system and its gains are tuned by proposed algorithms through minimization of integral time absolute error based objective function. The results confirm the effectiveness of proposed algorithms after comparing results with other evolutionary algorithms like differential evolution (DE), teaching learning based optimization (TLBO) for the similar test system. The robustness of proposed algorithm is checked with different objective functions like integral square error, integral absolute error, integral time square error criterions and under different loading conditions. Critical analysis of results reveals that proposed method gives better performance than that obtained with DE, TLBO.

Applying fractional order PID to design TCSC-based damping controller in coordination with automatic generation control of interconnected multi-source power system

In this paper, fractional order proportional-integral-differential (FOPID) controller is employed in the design of thyristor controlled series capacitor (TCSC)-based damping controller in coordination with the secondary integral controller as automatic generation control (AGC) loop. In doing so, the contribution of the TCSC in tie-line power exchange is extracted mathematically for small load disturbance. Adjustable parameters of the proposed FOPID-based TCSC damping controller and the AGC loop are optimized concurrently via an improved particle swarm optimization (IPSO) algorithm which is reinforced by chaotic parameter and crossover operator to obtain a globally optimal solution. The powerful FOMCON toolbox is used along with MATLAB for handling fractional order modeling and control. An interconnected multi-source power system is simulated regarding the physical constraints of generation rate constraint (GRC) nonlinearity and governor dead band (GDB) effect. Simulation results using FOMCON toolbox demonstrate that the proposed FOPID-based TCSC damping controller achieves the greatest dynamic performance under different load perturbation patterns in comparison with phase lead-lag and classical PID-based TCSC damping controllers, all in coordination with the integral AGC. Moreover, sensitivity analyses are performed to show the robustness of the proposed controller under various uncertainty scenarios.

Load frequency control of a two-area multi-source power system using a tilt integral derivative controller

This paper introduces a tilt integral derivative controller as the supplementary controller for load frequency control of a two-area interconnected power system. The optimal value of parameters of the tilt integral derivative controller is evaluated using constrained nonlinear optimization by means of a performance index-based method. The proposed tilt integral derivative control offers superior properties such as simple parameter tuning and its performance does not compromise the occurrence of any parameter variations in the system. To verify these features of the controller, the test system is subjected to step load disturbance and parameter variations that ensure the robustness of the tilt integral derivative controller. Comparative analysis with previously published work indicates that the proposed tilt integral derivative controller gives better performance and holds the property of robustness. Simulations have been performed using Matlab®.

Modelling and coordinating multisource distributed power system models in service oriented architecture

Distributed power system models aim to combine multi-source sensor device data with power grid monitoring and control data to improve the model accuracy. A software platform is essential that coordinates multiple data sources and integrates with the data communication and computation infrastructure. In this paper, we present a service-oriented coordination platform that exposes parallel programs as services and data sources as ports. We model services and ports by extending classes of standard common information model (CIM) for energy management and distribution management. These services are then coordinated based on the typed ports in the context of domain specific power system models. We demonstrate this platform with a use case of deploying distributed state estimation on the IEEE 118 bus model. Our contribution is building a service-oriented platform that provides power engineers an integrated environment for composing distributed power system models, disseminating data and launching high performance computing jobs.

Effect of Wind Energy Participation in AGC of Interconnected Multisource Power Systems

This paper presents the investigations on the effect of wind energy system’s participation on dynamic stability margins available on AGC of interconnected power system. A two area power system model interconnected via EHVAC tie-line is considered for the study. Each of the areas is consisting of hybrid sources of power generation like; hydro, thermal, gas and wind power plants. Various participation factors for electrical energy received from wind power plants, along with the energy from thermal, gas and hydro plants, are considered for the investigations. Moreover, any reduction of generation from thermal power plant is supposed to be supplied by wind power plant for fuel saving and to reduce emissions to environment. The optimal AGC regulators are designed using full state vector feedback control theory. Following the achievement of optimal gains of AGC regulators, the system closed-loop system eigenvalues are obtained for various case studies. The investigations of the closed loop eigenvalues carried out reveal that all the closed-loop eigenvalues are lying in the negative half of s-plan for all case studies and thus ensure the closed-loop system stability. Also, closed-loop eigenvalues are found to be sensitive to reduction in thermal generation and subsequent increase in electrical energy from wind power plants. It is also observed that the computed complex eigenvalues have shown a considerable decrease in the magnitude of its imaginary part when reduction of thermal generation is met by wind power generation. The reduced magnitudes of imaginary parts of closed-loop eigenvalues result in cost effective controller realization and improvement in system stability. On the other hand, the replacing the deficit caused in the supply with wind energy has no undesirable emissions to environment.

Performance comparison of TCSC with TCPS and SSSC controllers in AGC of realistic interconnected multi-source power system

Abstract The primary goals of employing series flexible ac transmission system (FACTS) in automatic generation control (AGC) studies of interconnected power systems are mitigating area frequency and tie-line power oscillations. This paper compares dynamic performance of thyristor controlled series capacitor (TCSC) as damping controller with thyristor controlled phase shifter (TCPS) and static synchronous series compensator (SSSC) which are series FACTS damping controllers. Commonly used lead-lag controllers are used in structure of damping controllers. The effect of TCSC in tie-line power exchange is modeled mathematically based on the Taylor series expansion for small-signal load disturbance. The performance of the proposed TCSC controller in coordination with integral AGC is compared with cases of TCPS–AGC and SSSC–AGC. An improved particle swarm optimization (IPSO) algorithm and integral of time multiplied squared error (ITSE) performance index are used to design the damping controllers. A two-area power system having generations from reheat thermal, hydro, and gas units in each area is evaluated regarding nonlinearity effects of generation rate constraint (GRC) and governor dead band (GDB). The simulations results in MATLAB/SIMULINK environment show that the proposed TCSC–AGC yields superior performance than others in damping of area frequencies and tie-line oscillations. Furthermore, sensitivity analyses are performed to show greater robustness of TCSC–AGC.

Teaching learning based optimization algorithm for automatic generation control of power system using 2-DOF PID controller

Abstract In this paper, a novel Teaching Learning Based Optimization (TLBO) algorithm with 2-Degree Freedom of Proportional–Integral–Derivative (2-DOF PID) controller is proposed for Automatic Generation Control (AGC). Initially a widely used two area thermal system is considered and the gains of the PI/PID/2-DOF PID controller are optimized employing a TLBO algorithm. The supremacy of the proposed 2-DOF PID controller has been shown by comparing the results with recently published technique such as conventional ZN, GA, BFOA, DE and hBFOA-PSO based PI controllers for the same system. Additionally, the proposed approach is further extended to multi source power system such as thermal, hydro and gas power plant. The advantage of the proposed approach is demonstrated by comparing the results with some recently published approaches. Sensitivity analysis is performed which demonstrates the ability of the proposed approach to wide changes in system parameters. Finally the proposed approach is investigated under random load variation.

Load frequency control of interconnected power system using grey wolf optimization

In this article an attempt has been made to solve load frequency control (LFC) problem in an interconnected power system network equipped with classical PI/PID controller using grey wolf optimization (GWO) technique. Initially, proposed algorithm is used for two-area interconnected non-reheat thermal-thermal power system and then the study is extended to three other realistic power systems, viz. (i) two-area multi-units hydro-thermal, (ii) two-area multi-sources power system having thermal, hydro and gas power plants and (iii) three-unequal-area all thermal power system for better validation of the effectiveness of proposed algorithm. The generation rate constraint (GRC) of the steam turbine is included in the system modeling and dynamic stability of aforesaid systems is investigated in the presence of GRC. The controller gains are optimized by using GWO algorithm employing integral time multiplied absolute error (ITAE) based fitness function. Performance of the proposed GWO algorithm has been compared with comprehensive learning particle swarm optimization (CLPSO), ensemble of mutation and crossover strategies and parameters in differential evolution (EPSDE) and other similar meta-heuristic optimization techniques available in literature for similar test system. Moreover, to demonstrate the robustness of proposed GWO algorithm, sensitivity analysis is performed by varying the operating loading conditions and system parameters in the range of ±50%. Simulation results show that GWO has better tuning capability than CLPSO, EPSDE and other similar population-based optimization techniques.

Firefly algorithm optimized fuzzy PID controller for AGC of multi-area multi-source power systems with UPFC and SMES

In this paper, a Firefly Algorithm (FA) optimized fuzzy PID controller is proposed for Automatic Generation Control (AGC) of multi-area multi-source power system. Initially, a two area six units power system is used and the gains of the fuzzy PID controller are optimized employing FA optimization technique using an ITAE criterion. The superiority of the proposed FA optimized fuzzy PID controller has been demonstrated by comparing the results with some recently published approaches such as optimal control and Differential Evolution (DE) optimized PID controller for the identical interconnected power system. Then, physical constraints such as Time Delay (TD), reheat turbine and Generation Rate Constraint (GRC) are included in the system model and the superiority of FA is demonstrated by comparing the results over DE, Gravitational Search Algorithm (GSA) and Genetic Algorithm (GA) optimization techniques for the same interconnected power system. Additionally, a Unified Power Flow Controller (UPFC) is placed in the tie-line and Superconducting Magnetic Energy Storage (SMES) units are considered in both areas. Simulation results show that the system performances are improved significantly with the proposed UPFC and SMES units. Sensitivity analysis of the system is performed by varying the system parameters and operating load conditions from their nominal values. It is observed that the optimum gains of the proposed controller need not be reset even if the system is subjected to wide variation in loading condition and system parameters. Finally, the effectiveness of the proposed controller design is verified by considering different types of load patterns.

A novel hybrid LUS–TLBO optimized fuzzy-PID controller for load frequency control of multi-source power system

Abstract In this paper, a novel hybrid Local Unimodal Sampling (LUS) and Teaching Learning Based Optimization (TLBO) based fuzzy-PID controller is proposed for load frequency control (LFC) of a two-area interconnected multi-source power system with and without HVDC link. Each area of the multi-source power system consists of a reheat thermal, a hydro and a gas unit. Fuzzy-PID and conventional PID controllers are used to study the dynamic performance of the power system by applying a step load change of 0.01 pu in area1. The scaling factors of the fuzzy-PID controllers and the conventional PID controllers’ gains are optimized using the proposed hybrid LUS and TLBO (LUS–TLBO) algorithm. The supremacy of the proposed LUS–TLBO algorithm optimized fuzzy-PID controller is proved for both the power systems (with and without HVDC link) by comparing the results with that of recently published article based on Differential Evolution (DE) algorithm optimized conventional PID controller for the same power systems. Again the robustness of the proposed controller for power system with AC tie-line only is studied under parametric variation conditions by varying all the parameters from −50% to 50% of their nominal values in steps of 25%. Finally it is seen that LUS–TLBO optimized fuzzy-PID controller exhibit superior performance as compared to DE optimized fuzzy-PID controller and hybrid LUS–TLBO, TLBO, LUS & DE optimized conventional PID controller.

A hybrid DE–PS algorithm for load frequency control under deregulated power system with UPFC and RFB

Abstract In this paper, a Modified Integral Derivative (MID) controller is proposed for Load Frequency Control (LFC) of multi-area multi-source power system in deregulated environment. The multi-source power system is having different sources of power generation such as thermal, hydro, wind and diesel generating units considering boiler dynamics for thermal plants, Generation Rate Constraint (GRC) and Governor Dead Band (GDB) non-linearity. The superiority of proposed hybrid Differential Evolution and Pattern Search (hDE-PS) optimized MID controller over GA and DE techniques is demonstrated. Further, the effectiveness of proposed hDE-PS optimized MID controller over Integral (I) and Integral Derivative (ID) controller is verified. Then, to further improve the system performance, Unified Power Flow Controller (UPFC) is placed in the tie-line and Redox Flow Batteries (RFBs) are considered in the first area. The performance of proposed approach is evaluated at all possible power transactions that take place in a deregulated power market.

Lifetime estimation tool of lead–acid batteries for hybrid power sources design

Generally, battery lifespan depends on the number of cycles and depth of discharge (DOD). Nevertheless, in a renewable hybrid power system, charge and discharge cycles are random and not regular. Therefore, it is important to develop an aging model suitable to this case. Thus, in this paper, a pertinent way for aging lead–acid batteries connected to a stand-alone multi-source renewable system has been developed. It is based on the Rain Flow method for counting cycles and considers instantaneous DOD and average temperature. In fact, for each functioning year, a classification of the number of cycles according to the DOD is done. Then, based on these data, the battery degradation rate is estimated so that it is possible to draw conclusions about battery lifespan.The method has been successfully applied to a multi-source power system simulated dynamically under Matlab/Simulink. This last takes into account with good accuracy several inputs and elements such as sun irradiation, wind speed, load profile, photovoltaic generator, wind turbine, and diesel generator. Results show the influence of the DOD and the batteries nominal capacity on their lifespan. A mean of eight years’ life is detected. Finally, a reasonable over-sizing may favor battery longevity.

DE optimized fuzzy PID controller with derivative filter for LFC of multi source power system in deregulated environment

Abstract In this paper, Differential Evolution (DE) optimized fuzzy PID controller with derivative Filter (PIDF) is proposed for Load Frequency Control (LFC) of a deregulated power system with multi-source power generation and interconnected via parallel AC/DC transmission links. To get an accurate insight of the LFC problem, important physical constraints such as time delay and GRC are considered. The performance of proposed controller is evaluated at all possible power transactions that take place in a deregulated power market. The improvement in dynamic performance of the power system with DC link in parallel with AC tie-line is also assessed. Further, sensitivity analysis is performed by varying the system parameters and operating load conditions from their nominal values. It is observed from the simulation results that the optimum gains of the proposed controller need not be reset even if the system is subjected to wide variation in loading condition and system parameters.

Comparative performance analysis of teaching learning based optimization for automatic load frequency control of multi-source power systems

• Application of teaching learning based optimization to AGC problems. • PID controller gains have been optimized by teaching learning based optimization. • Dynamic performance is analyzed for single area system and multi area with HVDC link. • Dynamic performances of TLBO based PID controller are better than DE-PID controller. • Sensitivity analysis is done to load changes and different cost functions. This paper presents a new population based parameter free optimization algorithm as teaching learning based optimization (TLBO) and its application to automatic load frequency control (ALFC) of multi-source power system having thermal, hydro and gas power plants. The proposed method is based on the effect of the influence of teacher on the output of learners and the learners can enhance their knowledge by interactions among themselves in a class. In this extensive study, the algorithm is applied in multi area and multi-source realistic power system without and with DC link between two areas in order to tune the PID controller which is used for automatic generation control (AGC). The potential and effectiveness of the proposed algorithm is compared with that of differential evolution algorithm (DE) and optimal output feedback controller tuning performance for the same power systems. The dynamic performance of proposed controller is investigated by different cost functions like integral of absolute error (IAE), integral of squared error (ISE), integral of time weighted squared error (ITSE) and integral of time multiplied absolute error (ITAE) and the robustness of the optimized controller is verified by its response toward changing in load and system parameters. It is found that the dynamic performance of the proposed controller is better than that of recently published DE optimized controller and optimal output feedback controller and also the proposed system is more robust and stable to wide changes in system loading, parameters, size and locations of step load perturbation and different cost functions.

Effective oscillation damping of an interconnected multi-source power system with automatic generation control and TCSC

Abstract Stabilizing area frequency and tie-line power oscillations in interconnected power systems are main concerns that have received significant attention in automatic generation control (AGC) studies. This paper deals with modeling and simulation of thyristor controlled series capacitor (TCSC) based damping controller in coordination with AGC to damp the oscillations and thereby, improve the dynamic stability. The contribution of TCSC in tie-line power exchange is formulated analytically for small perturbation and a systematic method based on the Taylor series expansion is proposed for modeling of TCSC based damping controller. The integral gains of AGC and TCSC parameters are optimized simultaneously using an improved particle swarm optimization (IPSO) algorithm through minimizing integral of time multiplied squared error (ITSE) performance index. The performance of the proposed TCSC–AGC coordinated controller is compared with case of AGC alone. A two-area interconnected multi-source power system, including TCSC located in series with the tie-line, is studied considering nonlinearity effects of generation rate constraint (GRC) and governor dead band (GDB). Simulation results show that proposed controller shows greater performance in damping of the oscillations and enhancing the frequency stability. Furthermore, sensitivity analyses are carried out against system loading condition, parametric uncertainties, and different perturbation patterns to show the robustness of TCSC–AGC.

A novel hybrid DEPS optimized fuzzy PI/PID controller for load frequency control of multi-area interconnected power systems

In this paper, a novel hybrid Differential Evolution (DE) and Pattern Search (PS) optimized fuzzy PI/PID controller is proposed for Load Frequency Control (LFC) of multi-area power system. Initially a two-area non-reheat thermal system is considered and the optimum gains of the fuzzy PI/PID controller are optimized employing a hybrid DE and PS (hDEPS) optimization technique. The superiority of the proposed controller is demonstrated by comparing the results with some recently published modern heuristic optimization techniques such as DE, Bacteria Foraging Optimization Algorithm (BFOA), Genetic Algorithm (GA) and conventional Ziegler Nichols (ZN) based PI controllers for the same interconnected power system. Furthermore, robustness analysis is performed by varying the system parameters and operating load conditions from their nominal values. It is observed that the optimum gains of the proposed controller need not be reset even if the system is subjected to wide variation in loading condition and system parameters. Additionally, the proposed approach is further extended to multi-area multi-source power system with/without HVDC link and the gains of fuzzy PID controllers are optimized using hDEPS algorithm. The superiority of the proposed approach is shown by comparing the results with recently published DE optimized PID controller and conventional optimal output feedback controller for the same power systems. Finally, Reheat turbine, Generation Rate Constraint (GRC) and time delay are included in the system model to demonstrate the ability of the proposed approach to handle nonlinearity and physical constraints in the system model.

Load Frequency Control of Multi-Source Power System with Redox Flow Batteries: An Analysis

paper presents the Load frequency control (LFC) of a multi-source power system with Redox flow batteries (RFB). The power system comprises non-reheat thermal, hydro and gas generating units. RFB is integrated to the LFC system to improve the dynamic responses. The proportional plus integral (PI) controller is designed using the PSO technique. Dynamic responses are obtained by giving 1% step load perturbation (SLP) in the area. Further, to show the robustness of the controller, the dynamic responses are obtained by varying the SLP from 1% to 3%. Dynamic responses obtained in all the cases, satisfy the LFC requirements. PSO technique gives good convergence characteristics and promising computational results. General Terms Frequency deviation, Multi-source KeywordsParticle swarm Optimization, Load Frequency

Probabilistic Economic Emission Dispatch Optimization of Multi-sources Power System

The interest on renewable energy resources is growing and the study of different integration aspects of these resources becomes very important to overcome problems caused by their variability or uncertainty. This paper treats the economic environmental power dispatch as a probabilistic multiobjective problem. The operation cost and green house gas emission functions are considered as the sum of deterministic part and probabilistic one. First, the problem is solved based on expected values of generated wind power then, using the cumulative density function (CDF) of each renewable energy source (RES), the CDF of the required reserve to compensate the RESs variability in order to keep the power balance. Then, respecting to the reserve contribution of each thermal generator, the probabilistic part of the global generation cost as well as its CDF are developed. Finally, the proposed approach is applied to solve the active power dispatch problem of IEEE 30-bus test system in two cases with and without RESs. The simulation results show that this method allows to get the complete information about the cumulative distribution function of the actual global cost of the system operation.

Controller parameters tuning of differential evolution algorithm and its application to load frequency control of multi-source power system

This paper presents controller parameters tuning of Differential Evolution (DE) algorithm and its application to Load Frequency Control (LFC) of a multi-source power system having different sources of power generation like thermal, hydro and gas power plants. Initially, a single area multi-source power system with integral controllers for each unit is considered and DE technique is applied to obtain the controller parameters. Various mutation strategies of DE are compared and the control parameters of DE for best obtained strategy are tunned by executing multiple runs of algorithm for each parameter variation. The study is further extended to a multi-area multi-source power system and a HVDC link is also considered in parallel with existing AC tie line for the interconnection of two areas. The parameters of Integral (I), Proportional Integral (PI) and Proportional Integral Derivative (PID) are optimized employing tunned DE algorithm. The superiority of the proposed approach has been shown by comparing the results with recently published optimal output feedback controller for the same power systems. The comparison is done using various performance measures like overshoot, settling time and standard error criteria of frequency and tie-line power deviation following a step load perturbation (SLP). It is noticed that, the dynamic performance of proposed controller is better than optimal output feedback controller. Furthermore, it is also seen that the proposed system is robust and is not affected by change in the loading condition, system parameters and size of SLP.

Power flow Petri Net modelling for building integrated multi-source power system with smart grid interaction

This paper presents an energy management modelling of a multi-source power system composed of photovoltaic (PV) array, storage and power grid connection, and taking into account messages from smart grid. The designed system can supply a tertiary building at the same time as PV may produce energy. The control strategy aims to manage the power flow through the load with respect to its power demand and public grid constraints. The proposed energy management modelling is based on interpreted Petri Nets formalism. The system is tested using a simulation Stateflow model and responds within certain limits. The results show that this approach is valid and can be a solution for the future smart grid communication between buildings and public grid and may contribute to a better balance between production and consumption and future energy management.