Changes In Load Demand Research Articles

Optimum design and analysis of a dynamic energy management scheme for HESS in renewable power generation applications

A novel control strategy for a hybrid energy storage system (HESS) is outlined and examined in this paper. In the proposed system, the battery is utilized to stabilize the moderate changing of power surges, whereas supercapacitor is utilized to stabilize the rapidly changing of power surges. A two-loop proportional-integral controller is designed for the closed-loop operation of HESS. The source power and load power is not balanced because of the fluctuating conditions of photovoltaic (PV) power generation and load demand. This power imbalance causes fluctuations in direct current (DC) grid voltage. The DC bus voltage variations are mitigated using HESS, which is connected to DC grid through bi-directional DC–DC converter to enables the bidirectional power flow between energy storage devices and the DC bus. To enhance the life span and to reduce the current stress on the battery, the proposed method is employed with charge/discharge rate control feature. The proposed control procedure is realized in MATLAB/Simulink and the results are presented for different case studies. Experimental results are obtained for a two-input bi-directional converter at the sudden change in PV generation and load demand with the proposed controller. The proposed control strategy is effective for maintaining constant DC microgrid voltage under source and load fluctuations.

A complex filter-based adaptive integral grid synchronisation algorithm for a PV system

ABSTRACT The issues such as deterioration of power quality owing to nonlinear loads, sudden changes in load demand, switch to dynamic loads, the occurrence of fault at the load or grid side is addressed using proposed DQ frame Complex Filter-based Adaptive Integral Algorithm (DCFAIA). The objective of the proposed control algorithm is to maintain the frequency at the desired level irrespective of electrical disturbances and also to remove the DC offset present in the synchronising parameters due to nonlinear load, lower the harmonic content in the grid parameters and maintain the power factor unity by compensating the reactive power. The performance of the proposed algorithm is compared with that of conventional algorithms such as Improved Second-Order Generalised Integrator (ISOGI), Third Order Generalised Integrator (TOGI), Least Mean Fourth (LMF). From the comparative assessment, it is observed that the proposed algorithm exhibits superior performance in terms of precision, settling time, steady and transient errors.

Automatic Load Frequency Control of a Multi-Area Dynamic Interconnected Power System Using a Hybrid PSO-GSA-Tuned PID Controller

This paper proposes a new population-based hybrid particle swarm optimized-gravitational search algorithm (PSO-GSA) for tuning the parameters of the proportional-integral-derivative (PID) controller of a two-area interconnected dynamic power system with the presence of nonlinearities such as generator rate constraints (GRC) and governor dead-band (GDB). The tuning of controller parameters such as Kp, Ki, and Kd are obtained by minimizing the objective function formulated using the steady-state performance indices like Integral absolute error (IAE) of tie-line power and frequency deviation of interconnected system. To test the robustness of the propounded controller, the system is studied with system uncertainties, such as change in load demand, synchronizing power coefficient and inertia constant. The two-area interconnected power system (TAIPS) is modeled and simulated using Matlab/Simulink. The results exhibit that the steady-state and transient performance indices such as IAE, settling time, and control effort are impressively enhanced by an amount of 87.65%, 15.39%, and 91.17% in area-1 and 86.46%, 41.35%, and 91.04% in area-2, respectively, by the proposed method compared to other techniques presented. The minimum control effort of PSO-GSA-tuned PID controller depicts the robust performance of the controller compared to other non-meta-heuristic and meta-heuristic methods presented. The proffered method is also validated using the hardware-in-the-loop (HIL) real-time digital simulation to study the effectiveness of the controller.

Optimization of Power system with Automatic Voltage Regulator using Soft Computing Techniques

In an interconnected power system, if a load demand changes randomly, both frequency and tie line power varies. The main aim of automatic voltage controller is to minimize the transient variations in these variables and also to make sure that their steady state errors is zero. Many modern control techniques are used to implement a reliable controller. The objective of these control techniques is to produce and deliver power reliably by maintaining voltage within permissible range. When real power changes, system frequency gets affected while reactive power is dependent on variation in voltage value. That’s why real and reactive power is controlled separately. Our objective is here for to study and analyze the Genetic algorithms and their application to the problems of Function Optimization and System Identification. Since there are other methods traditionally adopted to obtain the optimum value of a function (which are usually derivative based), the project aims at establishing the superiority of Genetic Algorithms in optimizing complex, multivariable and multimodal function. The Genetic Algorithm is a popular optimization technique which is bio-inspired and is based on the concepts of natural genetics and natural selection theories proposed by Charles Darwin.

Event‐triggered consensus approach for distributed battery energy storage systems

Owing to the intermittency of the renewable generation and constantly changing load demand, the battery energy storage systems (BESSs) have become a required solution to future power systems. In this study, the BESS is modelled as an agent. The authors propose an event-trigger finite-time consensus approach to maintain the supply–demand balance and minimise the total power loss associated with charging/discharging inefficiency. The proposed consensus algorithm can guarantee all BESSs to converge to an optimal operation point in finite-time. A situation where the charging power of each individual BESS has a constraint is considered. Furthermore, event-triggered feedback is considered to reduce the frequency of agents’ communicating with their neighbours. The communication bandwidth and energy can be saved corresponding to the goal of economic requirement. Finally, some simulation cases are further presented to illustrate the effectiveness of the scheme.

Energy-Storage-Based Intelligent Frequency Control of Microgrid With Stochastic Model Uncertainties

With the increasing proportion of renewable power generations, the frequency control of microgrid becomes more challenging due to stochastic power generations and dynamic uncertainties. The energy storage system (ESS) is usually used in microgrid since it can provide flexible options to store or release power energy. In this paper, an intelligent control strategy completely based on the adaptive dynamic programming (ADP) is developed for the frequency stability, which is designed to adjust the power outputs of micro-turbine and ESS when photovoltaic (PV) power generation is connected into the microgrid. Further, considering the changes of PV power and load demand in a day, the full utilization of PV power and the recycling of energy storage are realized through the proposed regulation strategy. Numerical simulation results validate the energy-storage-based intelligent frequency control strategy for the microgird with stochastic model uncertainties, and comparative studies based on PID, LQR and fuzzy logic control illustrate the superiority of the proposed control strategy.

Placement of Distribution-Level Phasor Measurements for Topological Observability and Monitoring of Active Distribution Networks

This article presents a new method for the placement of distribution-level phasor measurement units (D-PMUs) in the active distribution networks (ADNs). The new objective function and constraints are proposed to ensure the minimization of capital cost as well the maximization of system observability, in the presence of distributed generations (DGs), zero injection buses (ZIBs), and tie-switches. The integer linear programming (ILP) is used to solve the framed objective function and the constraints. Furthermore, the accuracy of ADN state estimation (ADN-SE), in various system conditions, such as network reconfiguration, change in load demand, and measurement error degradation, is analyzed to check the impact of the proposed placement. The uncertainties caused by D-PMUs, DGs, and pseudomeasurements are considered well in ADN-SE using Monte Carlo simulations. The IEEE 69, 123, Indian 85, and UKGDS 95 bus distribution systems are used in the case studies.

An intelligent approach for dynamic load frequency control with hybrid energy storage system

ABSTRACTOne of the important factors to be considered in an electric power system is to maintain the frequency constant, so that power stations run satisfactorily in synchronise among the connected pool of power generation systems. The main purpose of load frequency control (LFC) is to reduce the frequency deviation and net interchange of power flow between electrical power generating units and for achieving steady-state error to be zero. This research paper proposes the way to improve the LFC by employing energy storage systems (battery energy storage systems and superconducting magnetic energy storage (SMES)) during change in load demand. The energy storage devices are acting quickly and they are effectively damp electro mechanical oscillations in a power system. Moreover, they provide storage capacity and the kinetic energy of the generator shares the sudden changes in power requirement. An integrated hybrid BES and SMES energy storage systems along with LFC minimise the deviation of frequency by contribution of additional power requirement. Investigating the performance of the LFC with storage system under step change of load (∆Pd) has been analysed by employing proportional-integral (PI) and fuzzy logic controller (FLC) for frequency regulation and load tracking. Even, the PI controller attains zero steady-state error in system frequency, it has unsatisfied dynamic (overshoots and settling time) performance followed by disturbances. The mismatch power in the power system makes frequency deviation followed by the change in load demand and electrical power generation and it is balanced by employing of an energy storage system with proper controller. The simulation results are illustrated that the performance of LFC system is enhanced by BES storage system which effectively reduces frequency deviation than SMES system. The comparative analysis has been made for LFC with BES, SMES and hybrid storage system employing FLC and PI controller design also. A significant improvement in the frequency profile has been obtained with FLC controller than PI controller followed by the step load changes.

Optimal Design of Load Frequency Control of Single Area System

In a single-area power system, if a load demand changes randomly, the frequency varies. The main aim of load frequency control (LFC) is to minimize the transient variations and to make sure that the steady state error is zero. Many modern and robust control techniques are used to implement an authentic controller. The objective of these control techniques is to produce and deliver power reliably by maintaining both frequency and voltage within the threshold range. As real power changes, system frequency gets affected and reactive power is dependent on variation in voltage level. Hence real power and reactive power are controlled separately. The role of automatic generation control (AGC) in power system operations under normal operating conditions is analysed. To study the reliability of various control techniques of LFC of the proposed system through simulation in MATLAB-Simulink.

Influence of a Step-Voltage Regulator on Synchronous DG Anti-Islanding Protection

The performance of anti-islanding frequency and voltage protections is strongly affected by the power imbalance between the islanded loads and distributed generators, which is altered by changes of load demand. Since the voltage-dependent loads change the demand as the voltage profile changes, automatic step-voltage regulator on the distribution grid can impact on the islanding detection performance. In this context, the main goal of this paper is to investigate the influence of the automatic step-voltage regulator on the performance of under/overfrequency and under/overvoltage protections applied for islanding detection of a synchronous distributed generator. The simulations were performed on the Alternative Transients Program. As this software does not have a model of a step-voltage regulator, a second contribution of this paper is to propose the full modeling of an on-load tap-changer of a voltage regulator using MODELS and controlled voltage and current sources, which was not observed in the literate so far. The behavior of the step-voltage regulator is validated by simulation. Then, the anti-islanding protection is analyzed, as different operational conditions are considered to simulate island events with constant impedance loads. The results have shown the performance of the protection scheme can be strongly affected by the steady-state voltage, and such issue should be considered to correctly adjust the anti-islanding protection.

Distributed, Bounded and Finite-Time Convergence Secondary Frequency Control in an Autonomous Microgrid

To accommodate the intermittent renewable generations and constantly changing load demands, a proper control approach with flexible convergence time is desirable for an autonomous microgrid. This paper proposes a distributed, bounded, and finite-time convergence secondary control for frequency restoration and accurate active power sharing in an autonomous microgrid. The control input is designed to be distributed and bounded. The finite-time convergence proof and convergence time upper bound are guaranteed by rigorous analysis. Moreover, an approximation method is proposed to achieve a less conservative convergence time upper-bound compared with that of the traditional method. The effectiveness of the proposed control algorithm is validated through simulations with a modified IEEE 5-bus system and extended to a modified IEEE 39-bus system for scalability analysis.

Introducing LQR-fuzzy for a dynamic multi area LFC-DR model

It is well known that Load Frequency Control (LFC) model plays a vital role in electric power system design and operation. In the literature, much research works has stated on the advantages and realization of DR (Demand Response), which has proved to be an important part of the future smart grid. In an interconnected power system, if a load demand changes randomly, both frequency and tie line power varies. LFC-DR model is tuned by standard controllers like PI, PD, PID controllers, as they have constant gains. Hence, they are incapable of acquiring desirable dynamic performance for an extensive variety of operating conditions and various load changes. This paper presents the idea of introducing a DR control loop in the traditional Multi area LFC model (called LFC -DR) using LQR- Fuzzy Logic Control. The effect of DR-CDL i.e. (Demand Response Communication Delay Latency) in the design is also considered and is linearized using Padé approximation. Simulation results shows that the addition of DR control loop with proposed controller guarantees stability of the overall closed-loop LFC-DR system which effectively improves the system dynamic performance and is superior over a classical controller at different operating scenarios.

Distributed, fixed‐time, and bounded control for secondary voltage and frequency restoration in islanded microgrids

Microgrid (MG) technology evolves as a promising solution to deal with the intermittent renewable generations and frequently changing load demand. This paper proposes a fully distributed and bounded secondary control algorithm with flexible convergence time for voltage and frequency restoration. It also enables accurate active power sharing for an islanded MG, compared with the well-known consensus-based distributed control approach. The proposed control scheme achieves accelerated fixed-time convergence. The upper bound on the convergence is established by using the Lyapunov stability theory. The bounded, distributed control approach restores the voltage and frequency in fixed-time while sharing the active power precisely. Further, the proposed controller is adaptive to the communication topology change and supports the plug and play feature of MG. Extensive simulations have been pursued using MATLAB/SimPowerSyetem toolbox considering frequent load perturbation and communication topology change. The obtained results are analysed to verify the performance of the proposed control algorithm. It is observed that the proposed bounded input controller converges faster than the conventional method.

Performance analysis of DC/DC bidirectional converter with sliding mode and pi controller

<span>A sliding mode controller for a non-isolated DC/DC, bidirectional converter is presented and comparative study with PI controller is done along with ISE analysis, in order to do performance analysis. The proposed system can be utilized in many applications such as electrical vehicle, distributed power generation or small grids. Second theorem of Lyapunov is utilized and stability of the closed loop system is mathematically proven. The adopted control strategy achieves effective output voltage regulation and good dynamic stability. Rejection of disturbance is also an inherent characteristic of this technique. Furthermore, it is illustrated that the system can successfully follow changes of load demand and compensates sudden disturbances in operating condition. The design is evaluated and verified using Matlab/Simulink. Results of Matlab simulation are provided to show the feasibility of the proposed system and effectiveness of control method. Simulation results show that this technique can provide a considerable edge over control techniques which are presently available (applied) over this type of converter.</span>

Frequency Separation Model Based on Infinite-Impulse Response Filter Applied To Hybrid Power Generation Intended For Residential Sector

This paper presents an optimal energy management system by means of frequency separation control, applied to an autonomous hybrid power generation intended for residential sector. Studied system is integrating photovoltaic and wind energy systems as main sources, and fuel cell stack as an auxiliary source. This residential hybrid power system is also including battery to support fast and large power demand fluctuation in order to preserve the fuel cell reliability and to enhance its lifetime. The models of the photovoltaic, wind, battery, fuel cell systems and the control strategy are carried out under MATLAB/SIMULINK. To display the performance of the studied energy management system, many scenarios are designed, in which the wind speed, the irradiance intensity and the load demand change over time. Simulation results illustrate the efficiency of the considered energy management system. The proposed strategy is validated experimentally in a lab-scale prototype. Experimental results are then presented to confirm the whole system performance and to verify the proposed controller efficiency.

PSS design for damping low‐frequency oscillations in a multi‐machine power system with penetration of renewable power generations

This study focused on the use of the non-dominated sorting genetic algorithm (NSGA-II) to achieve an optimal power system stabiliser (PSS) parameters for a given operating point with a renewable source of energy so as to increase the system damping and guarantee enough stability margin. The parameters tuning was formulated using an eigenvalue-based multi-objective function. In recent years, the changeability and fluctuation of the wind power injected into the network have led to new challenges in small signal stability (SSS). These wind speed change and load demand change perturbations take place routinely and cause the variation of the operating conditions. However, as the conventional PSS is conceived for a fixed operating point in order to obtain the linearised transfer function model, it cannot yield good results when the operating range is too wide. To this end, the adaptive neuro-fuzzy inference system was proposed to estimate the stabiliser parameters in real time after a learning phase. The nine-bus Western System Coordinating Council and the obtained simulations results were assessed using Matlab/Simulink package. The validity of the proposed methodology was checked through the PSS parameters evolution simulation for daily load forecast curves and monthly wind speed prediction curves.

Study of supercritical power plant integration with high temperature thermal energy storage for flexible operation

Abstract The paper presents the recent research in study of the strategies for the power plant flexible operation to serve the requirement of grid frequency control and load balance. The study aims to investigate whether it is feasible to bring the High Temperature Thermal Storage (HTTS) to the thermal power plant steam-water cycle, to identify the suitable thermal charge and discharge locations in the cycle and to test how the HTTS integration can help support grid operation via power plant dynamic mathematical modelling and simulation. The simulation software named SimuEngine is adopted and a 600 MW supercritical coal-fired power plant model is implemented onto the software platform. Three HTTS charging strategies and two HTTS discharging strategies are proposed and tested via the simulation platform. The simulation results show that it is feasible to extract steam from the steam turbine to charge the HTTS, and to discharge the stored thermal energy back to the power generation processes. With the integration of the HTTS charge and discharge processes, the power plant simulation model is also connected to a simplified GB (Great Britain) grid model. Then the study is extended to test the improved capability of the plant flexible operation in supporting the responses to the grid load demand changes. The simulation results demonstrate that the power plant with HTTS integration has faster dynamic responses to the load demand changes and, in turn, faster response to grid frequency services.

Set-theoretic detection of data corruption attacks on cyber physical power systems

This paper addresses a set-theoretic method for the detection of data corruption cyber-attacks on the load frequency control loop of a networked power system. The system consists of several interconnected control areas forming a power grid. Based on the overall discrete-time network dynamics, a convex and compact polyhedral robust invariant set is extracted and is used as a set-induced anomaly detector. If the state vector exits the invariant set, then an alarm will be activated, and the potential threat is considered disclosed. The attack scenario used to assess the efficiency of the proposed anomaly detector concerns corrupted frequency sensor measurements transmitted to the automatic generation control unit of a compromised control area. Simulation studies highlight the ability of a set-theoretic approach to disclose persistent and intermittent attack patterns even when they occur at the same time with changes in the power load demand.

Design and Operation of a Sensible Heat Peaking Unit for Small Modular Reactors

Approximately 19% of the electricity produced in the United States comes from nuclear power plants. Traditionally, nuclear power plants, as well as larger coal-fired plants, operate in a baseload manner at or near steady state for prolonged periods of time. Smaller, more maneuverable plants, such as gas-fired plants, are dispatched to match electricity supply and demand above the capacity of the baseload plants. However, air quality concerns and CO2 emission standards have made the burning of fossil fuels less desirable, despite the current low cost of natural gas. Wind and solar photovoltaic power generation are attractive options due to their lack of carbon footprint and falling capital costs. Yet, these renewable energy sources suffer from inherent intermittency. This inherent intermittency can strain electric grids, forcing carbon-based and nuclear sources of energy to operate in a load-follow mode. For nuclear reactors, load-follow operation can be undesirable due to the associated thermal and mechanical stresses placed on the fuel and other reactor components. Various methods of thermal energy storage (TES) can be coupled to nuclear (or renewable) power sources to help absorb grid variability caused by daily load demand changes and renewable intermittency. Our previous research has shown that coupling a sensible heat TES system to a small modular reactor allows the reactor to run at effectively nominal full power during periods of variable electric demand by bypassing steam to the TES system during periods of excess capacity. In this paper we demonstrate that this stored thermal energy can be recovered, allowing the TES system to act as a peaking unit during periods of high electric demand or used to produce steam for ancillary applications such as desalination. For both applications the reactor is capable of operating continuously at approximately 100% power.

Thermal Energy Storage Configurations for Small Modular Reactor Load Shedding

The increased penetration of intermittent renewable energy technologies such as wind and solar power can strain electric grids, forcing carbon-based and nuclear sources of energy to operate in a load-follow mode. For nuclear reactors, load-follow operation can be undesirable due to the associated thermal and mechanical stresses placed on the fuel and other reactor components. Various methods of thermal energy storage (TES) can be coupled to nuclear (or renewable) power sources to help absorb grid variability caused by daily load demand changes and renewable intermittency. Two TES techniques are investigated as candidate thermal reservoirs to be used in conjunction with a small modular reactor (SMR): a two-tank sensible heat storage system and a stratified chilled-water storage system. The goal when coupling the two systems to the SMR is to match turbine output and demand and bypass steam to the TES systems to maintain reactor power at approximately 100%. Simulations of integral pressurized water reactor dynamics are run in a high-fidelity FORTRAN model developed at North Carolina State University. Both TES systems are developed as callable FORTRAN subroutines to model the time-varying behavior associated with different configurations of these systems when connected to the SMR simulator. Simulation results reveal the sensible heat storage system is capable of meeting turbine demand and maintaining reactor power constant while providing enough steam to power four absorption chillers for chilled-water production and storage. The stored chilled water is used to supplement cooling loads of an adjacent facility.