This paper presents the latest comprehensive literature review of AC and DC microgrid (MG) systems in connection with distributed generation (DG) units using renewable energy sources (RESs), energy storage systems (ESS) and loads. A survey on the alternative DG units' configurations in the low voltage AC (LVAC) and DC (LVDC) distribution networks with several applications of microgrid systems in the viewpoint of the current and the future consumer equipments energy market is extensively discussed. Based on the economical, technical and environmental benefits of the renewable energy related DG units, a thorough comparison between the two types of microgrid systems is provided. The paper also investigates the feasibility, control and energy management strategies of the two microgrid systems relying on the most current research works. Finally, the generalized relay tripping currents are derived and the protection strategies in microgrid systems are addressed in detail. From this literature survey, it can be revealed that the AC and DC microgrid systems with multiconverter devices are intrinsically potential for the future energy systems to achieve reliability, efficiency and quality power supply.

AC-microgrids versus DC-microgrids with distributed energy resources: A review

Over the past few decades, many publications have been made in the area of Load frequency control (LFC) of interconnected power systems. Load frequency control is necessary to develop better control in order to achieve less effect on the frequency and tie line power deviations after a load perturbation. However, number of control strategies has been employed in the design of load frequency controllers in order to achieve a better dynamic response and the exact choice of the LFC controller in a particular case requires sufficient expertise because each controller has its own merits and demerits. Due to this, an appropriate review of load frequency control (LFC) mechanism is essential and a few attempts have been made in this concern. This paper presents a detailed survey on load frequency control (LFC) mechanism. The overall study explores the depth study issues related to LFC mechanism based on different sources of power system models. This paper focused on different control techniques of LFC, which also includes all the recent application of FACTS devices. This review reveals the investigation of soft computing based optimization technique and application of Energy Storage System (ESS) and HVDC-link in LFC. These studies also illustrates conventional power system, deregulated of power environment as well as distributed generation and micro grids. This paper is designed in order to highlight the major traits of Load forecasting and some critical case studies on LFC.

A comprehensive state of the art literature survey on LFC mechanism for power system

The applicability of fractional order (FO) automatic generation control (AGC) for power system frequency oscillation damping is investigated in this paper, employing distributed energy generation. The hybrid power system employs various autonomous generation systems like wind turbine, solar photovoltaic, diesel engine, fuel-cell, and aqua electrolyzer, along with other energy storage devices like the battery and flywheel. The controller is placed in a remote location while receiving and sending signals over an unreliable communication network with stochastic delay. The controller parameters are tuned using robust optimization techniques employing different variants of particle swarm optimization and are compared with the corresponding optimal solutions. An archival-based strategy is used for reducing the number of function evaluations for the robust optimization methods. The solutions obtained through the robust optimization are able to handle higher variation in the controller gains and orders without significant decrease in the system performance. This is desirable from the FO controller implementation point of view, as the design is able to accommodate variations in the system parameter, which may result due to the approximation of FO operators using different realization methods and order of accuracy. Also a comparison is made between the FO and the integer order controllers to highlight the merits and demerits of each scheme.

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Fractional Order AGC for Distributed Energy Resources Using Robust Optimization

In this study, an efficient load frequency controller (LFC) for standalone two-area hybrid microgrid system (HμGS) is addressed. Social-spider optimiser (SSO) is applied to fine tune the proposed proportional–integral–derivative (PID) controllers by generating their optimal settings. The integral time multiplied summation of absolute deviations and the gains of PID controllers define the fitness function and control variables, respectively. The performance of the proposed SSO-based method is demonstrated on an isolated HμGS complete with variety of energy storage systems under number of scenarios. The scenarios include load fluctuations, variations in wind speed, and sun irradiance employing real site measurements. In this study, photovoltaic generating arrays and wind turbine generators are not participating in system frequency regulations due the proposal of their maximum power tracking operation strategy. The signatures of time-domain dynamic responses and cropped numerical results ascertain that the proposed SSO-based LFC scheme is promising in diminuting the signal deviations and in short time. Further validations for cropped results produced by SSO are made compared with powerful optimisation tool such as genetic algorithm which signify the tuned PID gains.

Efficient frequency controllers for autonomous two-area hybrid microgrid system using social-spider optimiser

Determining optimal virtual inertia and frequency control parameters to preserve the frequency stability in islanded microgrids with high penetration of renewables

In this study an isolated microgrid comprising both controllable and uncontrollable sources, like solar, wind, diesel generator, fuel cell, aqua-electrolyser, hydrogen storage and battery is considered. To establish an efficient resource management strategy, a central controller takes the decisions based on the status of the loads and sources. The status is obtained with the help of multi-agent concept (treating each load and source as an agent) through internet using User Datagram Protocol/Internet Protocol (UDP/IP). The decisions are transmitted to the controllable sources to regulate their power output for damping of frequency excursion following a disturbance. A control strategy is adopted to regulate the power output from the battery only during transient, resulting in a floating battery scheme in steady state. This will reduce the ampere hour rating of the battery and can improve the damping of frequency excursion following each load disturbance. In a microgrid with generation rate constraint (GRC), tuning of controller parameters and frequency bias is a nonlinear optimisation problem. Hence, this study attempts to tune the controller parameters using an evolutionary technique named bacterial foraging optimisation (BFO). The tuned gains obtained utilising BFO method give satisfactory frequency excursion following a disturbance in the microgrid.

Design of controller and communication for frequency regulation of a smart microgrid

This paper deals with the load frequency control of a small scale microgrid consisting of wind, solar, diesel generator and fuel cell as power generating sources and battery, flywheel and aqua electrolyzer as energy storage elements. To improve the load frequency control, the controllers are properly tuned so as to reduce the mismatch between the real power generation and the load demand leading to minimum power and frequency deviations. A systematic approach to obtain frequency bias parameter followed by tuning the gains of Proportional, Integral and Derivative controller (PID) using Integral Square Time Error evaluation criterion (ITSE)and Ziegler Nichols method respectively is proposed. The simulation studies are carried out for different cases and it is found that the dynamic responses of the frequency and power of the microgrid is quite acceptable.

Ziegler-Nichols based controller parameters tuning for load frequency control in a microgrid

Development of “Q” and “R” matrices for designing a Linear Quadratic Regulator (LQR) is still a research challenge. The theory says they should belong to the group of positive definite matrices, so we need to find out the most suitable amongst them in order to obtain the desired response. In this paper biogeography based optimization (BBO) technique has been applied to come up with the best “Q” and “R” matrices such that the frequency excursion following a disturbance in a microgrid is minimized. As all the states in a practical system may not be measurable hence, we have used Kalman estimator to estimate them. These estimated states along with other measured states are used by the LQR to produce the desired control signal. The microgrid is made smarter by using the agent based scheme integrated with a master controller and a proper communication protocol. The simulation results show that the proposed approach improves the microgrid frequency response and also gives a new alternative method for frequency control of a smart microgrid.

Biogeography Based Optimal State Feedback Controller for Frequency Regulation of a Smart Microgrid

Microgrid is a small scale independent power system consisting of renewable energy sources: solar and wind power generation and backup by controllable sources: diesel generator, fuel cell, aqua electrolyzer and battery. In the microgrid, the ramp rate limit in power change in controllable sources has been implemented by means of generation rate constraint (GRC) and power frequency (P-f) droop characteristics (R) is also included for the parallel operation of generating sources participating in automatic generation control (AGC). These GRC and P-f droop make the system non linear and we have used artificial intelligence techniques (AI) like bacterial foraging optimization (BFO), particle swarm optimization (PSO), genetic algorithm (GA) to tune the important parameters simultaneously in AGC of microgrid. Simulation results show the superiority of BFO for optimal calculation of multiple parameters in microgrid over PSO, GA and classical methods.

Automatic generation control of microgrid using artificial intelligence techniques

This paper deals with the load frequency control of Distributed Generation Systems (DGS) consisting of Wind, Solar and Diesel Generator. The Diesel Generator is controlled either by P or PI or PID controller to inject regulated amount of real power to the power system based on its rating. As a result it regulates the mismatch between the real power generation and the load which will lead to a minimum power and frequency deviations. A systematic way of deciding frequency bias parameter along with tuning the gains of the Proportional, Integral and Derivative controller (PID) based on Ziegler-Nichols method and ITSE performance criterion is proposed. The simulation studies are carried out for different types of controllers, and disturbances and it is found that it regulates the frequency with less number of oscillations, minimum peak over shoot, and settling time in the case of PID controller.

G. Mallesham

Papers

Design of controller and communication for frequency regulation of a smart microgrid

Ziegler-Nichols based controller parameters tuning for load frequency control in a microgrid

Biogeography Based Optimal State Feedback Controller for Frequency Regulation of a Smart Microgrid

Automatic generation control of microgrid using artificial intelligence techniques

Maiden application of Ziegler-Nichols method to AGC of Distributed Generation System