Multi-source Power System Research Articles

Cascaded Centered Moving Average Filters for Energy Management in Multisource Power Systems with a Large Number of Devices

Hybrid systems constitute one of the solutions for supplying isolated applications. Such systems are classically based on clean energy sources. When the renewable energy sources have intermittent productions, they are associated with storage systems. This makes the system economically more interesting. Economically speaking, hybrid energy systems using multiple energy sources are often expensive and their cost must be optimized. This optimization can be done for the system sizing or for its energy management. However, optimizing one does not guarantee the optimization of the other. Indeed, previous studies optimize either the design and apply it with a simple energy management strategy, or the energy management with predetermined sizing supposed optimized, while minimizing the number of sources that contain the hybrid system. In this paper, an energy management and sizing algorithm, applicable to multisource systems, composed of a large number of sources, is proposed. The method is based on a modified centered moving average filters architecture for energy management, which permits one to consider and to automatically balance the forecasting errors in solar and load profiles. The energy management is then limited to a small number of parameters, which are the averaging horizon and weight coefficients. It is then possible to optimize, at the same time, the sizing and the energy management of such power systems. The proposed optimization criterion is based on a techno-economic approach, by considering acquisition and operation costs, as well as the ageing of the different devices. The main novelty of this approach is the use of energy management formulation that is able to manage an architecture with a high number of controlled devices. An original formulation of centered moving average filters also permits one to automatically balance the power bias due to forecasting errors on the renewable resources and the load profile. The method is applied to five devices, including photovoltaic panels, a fuel cell, two batteries with different technologies (Li-ion and lead-acid) and supercapacitors.

Small-signal stability analysis and frequency regulation strategy for photovoltaic sources in interconnected power system

This paper investigates the impact of high photovoltaic penetration on small signal stability of multi-source power system and proposes a new method which enables conventional PV system to improve the frequency response of the low inertia power system. The operating point of PV is linearized and shifted with respect to the change in grid frequency using a fuzzy interface system. A linearized multi-area model interconnected with tie-line comprises different generating sources is considered as a study case system. The system is extended to a more realistic network by incorporating the various system nonlinearities like generation rate constraint, governor dead band and area control error signal delay. To identify the effect of PV on system damping, eigenvalue analysis is carried out on the studies system. The proposed control scheme is found to be providing stabilizing power which may improve the frequency nadir and rate of change of frequency when the system is subjected to load change.

Robust Load Frequency Control Using Fractional-order TID-PD Approach Via Salp Swarm Algorithm

To preserve frequency and tie-line power flow within a tolerable range in modern intricate and renewable energy sources (RES) integrated power system, an intelligent, expert, and robust load frequency control (LFC) scheme is requisite. This paper proposes a new load frequency control (LFC) approach using a dual-stage controller composed of fractional-order tilted-integral-derivative (TID) and integer-order proportional-derivative (PD) controllers. The recently developed salp swarm algorithm has tuned the parameters of the controller. The proposed scheme exhibits robustness and fast disturbance rejection performance because the tilted-integral-derivative controller is structured in a fractional-order framework, and transient response is improved due to the proportional-derivative controller. The overall activity of the LFC has been further upgraded by incorporating the flexible AC transmission system (FACTS) device namely thyristor-controlled phase shifter (TCPS) unit and energy storage system called redox flow battery (RFB) units. The proposed control approach is applied to diverse types of multi-area multi-source power systems with thermal, hydro, and wind turbine units along with nonlinear functions namely generation rate constraint (GRC), governor dead band (GDB), and communication delay (CD). The simulation results yield improved frequency regulation activity with and without TCPS and RFB using the proposed control approach when compared with the recently developed LFC approaches. Sensitivity analysis also established the robustness of the proposed control approach.

Multi-objective optimization strategy of multi-sources power system operation based on fuzzy chance constraint programming and improved analytic hierarchy process

Nowadays, the valid development and full utilization of renewable energy sources such as wind power and solar energy are considered to be one of the most significant approaches to get rid of the energy dilemma and realize environmental governance. However, although there are more and more renewable power sources connected to power systems, the renewable energy has not been fully used yet. In this context, an optimization model for the regional power system with the pump storage power, wind, hydro, and thermal power is proposed to enhance the economy, environmental protection, energy-saving and stability of the power system. Besides, the fuzzy chance constraint programming and the improved analytic hierarchy process are used to deal with the uncertainty of the wind power and the load demand and the multi-objectives function, respectively. The case study not only verify the effectiveness of the proposed model but also shows that better comprehensive performance of the power system can be achieved through the proposed model when considering the effect of the pump storage power.

Load Frequency Control Using Hybrid Intelligent Optimization Technique for Multi-Source Power Systems

The automatic load frequency control for multi-area power systems has been a challenging task for power system engineers. The complexity of this task further increases with the incorporation of multiple sources of power generation. For multi-source power system, this paper presents a new heuristic-based hybrid optimization technique to achieve the objective of automatic load frequency control. In particular, the proposed optimization technique regulates the frequency deviation and the tie-line power in multi-source power system. The proposed optimization technique uses the main features of three different optimization techniques, namely, the Firefly Algorithm (FA), the Particle Swarm Optimization (PSO), and the Gravitational Search Algorithm (GSA). The proposed algorithm was used to tune the parameters of a Proportional Integral Derivative (PID) controller to achieve the automatic load frequency control of the multi-source power system. The integral time absolute error was used as the objective function. Moreover, the controller was also tuned to ensure that the tie-line power and the frequency of the multi-source power system were within the acceptable limits. A two-area power system was designed using MATLAB-Simulink tool, consisting of three types of power sources, viz., thermal power plant, hydro power plant, and gas-turbine power plant. The overall efficacy of the proposed algorithm was tested for two different case studies. In the first case study, both the areas were subjected to a load increment of 0.01 p.u. In the second case, the two areas were subjected to different load increments of 0.03 p.u and 0.02 p.u, respectively. Furthermore, the settling time and the peak overshoot were considered to measure the effect on the frequency deviation and on the tie-line response. For the first case study, the settling times for the frequency deviation in area-1, the frequency deviation in area-2, and the tie-line power flow were 8.5 s, 5.5 s, and 3.0 s, respectively. In comparison, these values were 8.7 s, 6.1 s, and 5.5 s, using PSO; 8.7 s, 7.2 s, and 6.5 s, using FA; and 9.0 s, 8.0 s, and 11.0 s using GSA. Similarly, for case study II, these values were: 5.5 s, 5.6 s, and 5.1 s, using the proposed algorithm; 6.2 s, 6.3 s, and 5.3 s, using PSO; 7.0 s, 6.5 s, and 10.0 s, using FA; and 8.5 s, 7.5 s, and 12.0 s, using GSA. Thus, the proposed algorithm performed better than the other techniques.

Load Frequency Control of Multi-interconnected Renewable Energy Plants Using Multi-Verse Optimizer

A reliable approach based on a multi-verse optimization algorithm (MVO) for designing load frequency control incorporated in multi-interconnected power system comprising wind power and photovoltaic (PV) plants is presented in this paper. It has been applied for optimizing the control parameters of the load frequency controller (LFC) of the multi-source power system (MSPS). The MSPS includes thermal, gas, and hydro power plants for energy generation. Moreover, the MSPS is integrated with renewable energy sources (RES). The MVO algorithm is applied to acquire the ideal parameters of the controller for controlling a single area and a multi-area MSPS integrated with RES. HVDC link is utilized in shunt with AC multi-areas interconnection tie line. The proposed scheme has achieved robust performance against the disturbance in loading conditions, variation of system parameters, and size of step load perturbation (SLP). Meanwhile, the simulation outcomes showed a good dynamic performance of the proposed controller.

Control of a Photovoltaic-battery grid-connected multi-source system under different operating conditions

This paper deals with the control of a grid-connected multi-source power system based on a photovoltaic (PV) array and a battery energy storage system (ESS), taking into account the variable and intermittent characteristics of the solar irradiation level and the ambient temperature in Morocco. The PV generator is connected via a dc-dc boost converter to a common dc bus which is connected through a bidirectional dc-dc converter to the battery ESS. The dc bus output is connected to the mains via a PWM dc-ac converter with an LCL filter. The control technique consists of three parts: the PV array is considered as the primary source and the boost converter is controlled locally to generate the maximum power extraction (MPPT), while the bidirectional dc-dc converter of the ESS battery is controlled to ensure the energy balance according to the power flow under different solar irradiation and temperature conditions. The PWM inverter is controlled to regulate the DC bus voltage and maintain the power factor at the unit. The system is implemented in Matlab/Simulink environment. The effectiveness of the control strategy is carried out by simulation results.

Dynamic Tuning of the Controller Parameters in a Two-Area Multi-Source Power System for Optimal Load Frequency Control Performance

Frequency control is becoming increasingly critical today due to the growing size and changing structure of complex interconnected power networks. Scaling up economic pressures for efficiency and reliability of the power system has necessitated a requirement for maintaining system frequency, and tie-line power flows as close as possible to scheduled values. High-frequency deviations may degrade load performance, damage equipment, resulting in overloading of transmission lines, which may interfere with system protection schemes, and, finally, may also result in an unstable condition of the power system. More so, Load Frequency Control ( LFC) plays a vital role in the modern power system as an auxiliary service to support power exchanges and, at the same time, to provide better conditions for the trading of electricity. Therefore, the tuning of the dynamic controller (i.e., net frequency and net power interchange errors) is a significant factor in achieving optimum LFC performance. Appropriate tuning of the controller parameters is required in order to achieve excellent control action. In view of this, this paper introduces the dynamic tuning of controller parameters in a two-area multi-source power system with an AC-DC parallel tie line for optimum load-frequency control performance. Matlab/Simulink software is used to realize the system simulation. System dynamic performance is observed for conventional PID tuning by the Ziegler Nichols method and the Kitamori method, fuzzy logic controllers, fuzzy-logic PID controllers, fuzzy PID controllers, and polar-Fuzzy controllers. Furthermore, the frequency and tie-line power response of the interconnected areas were compared based on the setting-time, peak-overshoot, and peak-undershoot. The simulation results show that the responses of the fuzzy-based controllers are faster than those of the classical controllers, resulting in minimized frequency and tie-line power deviations.

Frequency-constrained multi-source power system scheduling against N-1 contingency and renewable uncertainty

Security continues to be the most critical concern in power system operation, which is exceptionally important under low inertia and high uncertainty situations induced by an increasing penetration of renewable sources. This paper presents a transient frequency-constrained two-stage stochastic scheduling model to study the day-ahead operation of thermal-hydro-wind-demand response systems. Specifically, (i) limits on rate-of-change-of-frequency and maximum frequency derivation are introduced to provide sufficient governor reserve from multiple sources for guaranteeing dynamic frequency performance against N-1 contingency; (ii) The de-loaded mode of variable speed wind turbines is proposed for leveraging economics of system operation and security of dynamic frequency response; (iii) Virtual inertial constant of power systems with variable speed wind turbines is calculated to simulate performance of the virtual inertial control; (iv) Demand response is considered in the stochastic framework to mitigate the time delay of delivering virtual inertia. Multiple scenarios are generated via Monte Carlo method to simulate wind generation uncertainties. The proposed two-stage stochastic mixed-integer nonlinear programming model with binaries in both stages is solved via an improved generalized Benders decomposition, which takes about 40% less time than the standard generalized Benders decomposition. Several enhanced strategies are discussed to improve computational performance of the generalized Benders decomposition. Numerical simulations illustrate effectiveness of the proposed approach in coordinating multi-resource scheduling of power systems against N-1 contingencies and uncertainties with guaranteed frequency performance. Specifically, numerical results on the 6-bus system illustrate that: (i) The optimal wind generation penetration level of 40% could well balance the wind curtailments and the benefits of variable speed wind turbines for regulation provision; (ii) With 50% penetration of wind generation, doubling the capacity of demand response can reduce the amount of wind curtailment 50.42%, and decrease the transient frequency deviation to 0.25Hz.

Design and implementation of an interconnection and damping assignment–passivity-based control for grid-integrated hybrid renewable system with energy storage

This article introduces a unified Hamiltonian formulation for controlling grid-connected direct current microgrid via interconnection and damping assignment–passivity-based control. The direct current microgrid includes hydro–solar–wind hybrid renewable energy systems and battery/supercapacitor hybrid energy storage system. Hybrid renewable energy systems are integrated as a disturbed direct current source, while hybrid energy storage system is integrated via semi-active topology, where the battery is connected to the direct current bus through a bidirectional dc-to-dc converter. The proposed Hamiltonian approach allows us to design a control strategy for the bidirectional dc-to-dc converter and the grid-connected three-phase inverter to (1) reject power disturbances in the direct current bus via the supercapacitor and ensure smooth current in the battery as well as in the grid and (2) assign the system to a desired equilibrium after sharp changes. In the studied article, the stability of the system under the interconnection and damping assignment–passivity-based control controller is investigated. The interconnection and damping assignment–passivity-based control controller is compared with two conventional proportional–integral–based controllers through simulations under the MATLAB/Simulink environment. The main contributions in this article are the unified hybrid modelling for dc-to-dc power converter and grid-connected inverter using port-Hamiltonian approach, external disturbance rejection in the multi-source power system using interconnection and damping assignment–passivity-based control, and the assurance of global asymptotic stability of the closed-loop system.

Optimal Automatic Generation Control with Hydro, Thermal, Gas, and Wind Power Plants in 2-Area Interconnected Power System

This paper explores automatic generation control (AGC) of a more realistic 2-area multi-source power system comprising hydro, thermal, gas, and wind energy sources-based power plants in each control area. The wind power plants (WPPs) have been growing continuously worldwide due to their inherent feature of providing eco-friendly sustainable energy. But, operations of WPPs are associated with system stability problems due to lack of inertia. However, WPPs do not participate in the elimination of mismatch between generation and demand by AGC but disturbance can be injected by the WPPs due to the stochastic nature of wind energy. An optimal controller based on full state feedback control theory is designed to conduct the study. The system dynamic performance analysis is carried out for 1% step load disturbance in corresponding control areas. It is observed that the system dynamic graphs of deviation in area frequency and tie-line power are significantly improved with the implementation of optimal AGC controller compared to GA tuned classical controller. It has also been shown that the WPPs aid the increase in load disturbance when the input wind power reduces but it negates the effect of increase in load disturbance for increase in wind energy to the WPPs.

Generation‐based automatic generation control with multisources power system using bacterial foraging algorithm

AbstractThis article presents an application of bacterial foraging algorithm (BFA) for design and implementation of generation‐based PID structured automatic generation control (AGC) in a 2‐area multisources power system with hydro, thermal, and gas power plants incorporated in each area. Most of AGC studies carried out so far have considered the initial system loading to be equal to 50% of the area generation capacity. But, AGC controller parameters are uncertain due to stochastic nature of power demand of the end users. Hence, in this article, the design of AGC controller is proposed on the basis of generation schedule by incorporating changes in power system gain constant, power system time constant, frequency bias constant, and so on. The dynamic responses of power system with BFA tuned AGC controller are compared with the genetic algorithm tuned AGC controller. The parameters of the controllers are evaluated by using these techniques and investigations are carried out to find the best performance of the system. Therefore, it is desirable to find the parameters of the generation‐based controller depending upon the contribution of its constituent hydro, thermal, and gas energy sources in the total power generation.

Sliding Fuzzy Controller for Energy Management of Residential Load by Multi-sources Power System Using Wind PV and Battery

Sliding Fuzzy Controller for Energy Management of Residential Load by Multi-sources Power System Using Wind PV and Battery

Minimal Realized Power Systems for Load Frequency Control Using Optimal Theory Based PID Controller

The load-frequency control is a matter of interest in power system operation as it addresses the problem of controlling the system in response to the disturbances. A well-known solution to this problem is feedback stabilization through Linear Quadratic Regulator. The observability condition has to be satisfied for the implementation of LQR, but for certain cases of multi-source power systems this criteria fails. Also, to obtain the desired response, proper selection of the weighting matrices Q and R for LQR controller is inevitable. On a trial and error based choice of these matrices, the classical optimal controller may fail to achieve an optimum set point tracking, due to the absence of an integral control action. In this paper, a balanced reduction technique is proposed to obtain a minimal realization of the unobservable system, which makes the optimal control design possible for the control of change in frequency. Thus the paper also applies PID output feedback controller designed through LQR. The impact of reduction for minimal realization and the LQR based PID controller in the frequency stabilization of the considered systems are highlighted in this paper through pertinent cases.

Enhancing load frequency control of multi-area multi-sources power system including conventional and renewable energy units with nonlinearities

The foremost aims the Load Frequency Control (LFC) is to maintain the frequency at nominal value and minimize the unscheduled tie line power flow between different control areas. The penetration of renewable energy sources into the grid is a recent challenge to the power system operators due to their different modelling rather than conventional units. In this paper, enhancing load frequency control of multi-area multi-sources power system including renewable units system with nonlinearities is proposed using a new application of proportional–integral–derivative controller with proportional controller in the inner feedback loop, which is called as PID-P controller. To investigate the performance of the proposed controller, a thermal with reheater, hydro, wind and diesel power generation units with physical constraints such as governor dead band, generation rate constraint, time delay and boiler dynamics are considered. The proposed controller parameters are optimized using different heuristic optimization techniques such: Linearized Biogeography-Based Optimization technique, Biogeography-Based Optimization technique and Genetic Algorithm. The ability of the system to handle the large variation in load conditions, time delay, participation factors, and system parameters has been verified comprehensively.

Pathfinder algorithm optimized fractional order tilt-integral-derivative (FOTID) controller for automatic generation control of multi-source power system

This paper introduces a fractional order tilt-integral-derivative (FOTID) controller which is structurally analogous to fractional order proportional-integral-derivative controller in a power system for solving automatic generation control (AGC) problem. It is optimized by a recent metaheuristic optimizer called pathfinder algorithm (PFA). An interconnected two-area power system model comprising of multi-sources like thermal, hydro and gas generating units including physical constraints namely, governor dead band (GDB) and generation rate constraint (GRC) are taken into consideration for the study. The efficiency of the proposed controller for AGC is shown by comparing it with PFA optimized tilt-integral-derivative (TID) and proportional-integral-derivative (PID) controllers with integral of time multiplied absolute error (ITAE) taken as the objective function. Simulation study supports the claim that the proposed controller provides better dynamic responses as compared to the others. Sensitivity and robust analyses are done to demonstrate the effectiveness of the proposed PFA optimized FOTID controller to a wide variation in system parameters, at different step load and random load disturbances.

Effect of Electric Vehicle on Load Frequncy Control by Using SALP Swarm Algorithm Optimized FOPID

Now a days due to increasing participation of renewable sources in the production of energy there are more frequency fluctuations and this frequency instability is not possible to be controlled with load frequency control (LFC) alone. Meanwhile electric vehicles (EV) are gaining popularity to improve the frequency stability. In this paper multi area multi source power system with electrical vehicle by using Salp Swarm Algorithm (SSA) optimized Fractional order PID (FOPID) controller in the presence of EV is considered. The superiority of SSA is expressed by comparing with other algorithms like local unimodal sampling (LUS), differential algorithm (DE), teaching learning based algorithm (TLBO). Likewise FOPID controller is also compared with other controllers like I, PI, PID and the superiority of FOPID is demonstrated. The investigation reveal that SSA tuned FOPID controller provides the best dynamic performance for settling time and peak undershoot in deviation of frequency and deviation in the power of tie-line with EV.

Ant lion optimized hybrid intelligent PID-based sliding mode controller for frequency regulation of interconnected multi-area power systems

In this article, a novel hybrid intelligent Proportional Integral Derivative (PID)-based sliding mode controller (IPID-SMC) is proposed to solve the LFC problem for realistic interconnected multi-area power systems. The optimization task for best-regulating parameters of the suggested controller structure is fulfilled by the ant lion optimizer (ALO) technique. To assess the usefulness and practicability of the suggested ALO optimized IPID-SMC controller, three test systems – that is, four-area hybrid power system, two-area reheat thermal-photovoltaic system and two-area multi-sources power system – are employed. Different nonlinearities such as generation rate constraint (GRC) and governor dead band (GDB) as a provenance of physical constraints are taken into account in the model of the two-area multi-sources power systems to examine the ability of the proposed strategy for handling the practical challenges. The acceptability and novelty of the ALO-based IPID-SMC controller to solve the systems mentioned above are appraised in comparison with some recently reported approaches. The specifications of time-domain simulation disclose that the designed proposed controller provides a desirable level of performance and stability compared with other existing strategies. Furthermore, to check the robustness of the suggested technique, sensitivity analysis is fulfilled by varying the operating loading conditions and plant parameters within a particular tolerable range.

Deregulated Automatic Generation Control using Novel Opposition-based Interactive Search Algorithm Cascade Controller Including Distributed Generation and Electric Vehicle

This paper deals with the maiden application of opposition-based interactive search algorithm (OISA) for a multi-area, multi-source power system having thermal, hydro and gas generating units. For realistic approach, physical constraints like boiler dynamics (BD), governor dead band (GDB) and generation rate constraint (GRC) have been considered in the thermal system, while the effects of GRC and GDB are included in hydro and gas systems. Since modern power systems are focussing more towards renewable energy resources, for the purpose of analysis distributed generation (DG) and electric vehicle (EV) units are also incorporated in the system. A novel cascade combination of two-degree-of-freedom proportional–integral–derivative with a filter (PIDN) and fractional order integral–derivative (FOID) is used as the proposed controller for the system (2DOF-PIDN-FOID). The parameters of the proposed controller are optimised using the OISA algorithm. For analysis of the proposed system in deregulated environment, a step load perturbance (SLP) of 0.01 per unit is done in area-1. The effect of integration of distributed generation (DG) and electric vehicle (EV) on the system is analysed in both combined manner and separately. In both the cases, the system dynamics show marked improvement in comparison with previous cases. Analysis of system dynamics for various cases reveals the superiority of the proposed control scheme. Further, the superiority of the proposed algorithm is proven among other well-known evolutionary techniques like genetic algorithm (GA), particle swarm optimisation (PSO), interactive search algorithm (ISA) and whale optimisation algorithm (WOA) by comparison under same test conditions. Moreover, the robustness of the system is validated against system parameter variations. Finally, the superiority of the proposed control scheme is shown by comparison with published results in the literature under same test conditions.

Design of an Optimized Fractional High Order Differential Feedback Controller for Load Frequency Control of a Multi-Area Multi-Source Power System With Nonlinearity

Load frequency control (LFC) is one of the essential process in interconnected power systems. To provide high quality, reliable and stable electrical power, designed controller should perform satisfactorily, i.e. suppress area frequency and tie-line power deviations. Within this scope, in this study, a high order differential feedback controller (HODFC) and a developed fractional high order differential feedback controller (FHODFC) are proposed for LFC problem in multi-area power systems for the first time. The gains of the HODFC and FHODFC are optimally tuned by particle swarm optimization (PSO) algorithm aiming to minimize integral of time weighted absolute error (ITAE) performance index. The superiority of the developed FHODFC are verified by comparing reported controller structures in the recent state-of-the-art literature and HODFC for two identical non-reheat thermal power system and two-area multi-source power system consisting of gas, thermal and hydro generation units with/without consideration of HVDC link. To test the robustness of the designed controllers, varying system parameters and loading conditions are investigated. The governor dead band (GDB) and generation rate constraint (GRC) limitations are also considered for the system under study to examine non-linearity handling success of the proposed controllers. Performance results indicate that the developed FHODFC provides better dynamic response and robustness than other published techniques under nonlinearities, random load pattern, and variations in system parameters and loading conditions.