Secondary Frequency and Voltage Control of Islanded Microgrids via Distributed Averaging

In this work we present new distributed controllers for secondary frequency and voltage control in islanded microgrids. Inspired by techniques from cooperative control, the proposed controllers use localized information and nearest-neighbor communication to collectively perform secondary control actions. The frequency controller rapidly regulates the microgrid frequency to its nominal value while maintaining active power sharing among the distributed generators. Tuning of the voltage controller provides a simple and intuitive trade-off between the conflicting goals of voltage regulation and reactive power sharing. Our designs require no knowledge of the microgrid topology, impedances or loads. The distributed architecture allows for flexibility and redundancy, and eliminates the need for a central microgrid controller. We provide a voltage stability analysis and present extensive experimental results validating our designs, verifying robust performance under communication failure and during plug-and-play operation.Comment: Accepted for publication in IEEE Transactions on Industrial Electronic

Deep Reinforcement Learning for Control of Microgrids: A Review

A microgrid is widely accepted as a prominent solution to enhance resilience and performance in distributed power systems. Microgrids are flexible for adding distributed energy resources in the ecosystem of the electrical networks. Control techniques are used to synchronize distributed energy resources (DERs) due to their turbulent nature. DERs including alternating current, direct current and hybrid load with storage systems have been used in microgrids quite frequently due to which controlling the flow of energy in microgrids have been complex task with traditional control approaches. Distributed as well central approach to apply control algorithms is well-known methods to regulate frequency and voltage in microgrids. Recently techniques based of artificial intelligence are being applied for the problems that arise in operation and control of latest generation microgrids and smart grids. Such techniques are categorized in machine learning and deep learning in broader terms. The objective of this research is to survey the latest strategies of control in microgrids using the deep reinforcement learning approach (DRL). Other techniques of artificial intelligence had already been reviewed extensively but the use of DRL has increased in the past couple of years. To bridge the gap for the researchers, this survey paper is being presented with a focus on only Microgrids control DRL techniques for voltage control and frequency regulation with distributed, cooperative and multi agent approaches are presented in this research

A Novel Distributed Secondary Coordination Control Approach for Islanded Microgrids

This paper develops a new distributed secondary cooperative control scheme to coordinate distributed generators (DGs) in islanded microgrids (MGs). A finite time frequency regulation strategy containing a consensus-based distributed active power regulator is presented, which can not only guarantee the active power sharing but also enable all DGs' frequencies to converge to the reference value within a finite time. This enables the frequency and voltage control designs to be separated. Then an observer-based distributed voltage regulator involving certain reactive power sharing constraints is proposed, which allows different set points for different DGs and, thus, accounts for the line impedance effects. The steady-state performance analysis shows that the voltage regulator can accurately address the issue of global voltage regulation and accurate reactive power sharing. Moreover, all the distributed controllers are equipped with bounded control inputs to suppress the transient overshoot, and they are implemented through sparse communication networks. The effectiveness of the control in case of load variation, plug-and-play capability, communication topology change, link failure, time delays, and data drop-out are verified by the simulation of an islanded MG in MATLAB/SimPowerSystems

A Novel Cooperative Controller for Inverters of Smart Hybrid AC/DC Microgrids

This paper presents a novel cooperative control technique concerning fully-distributed AC/DC microgrids. Distributed generation based on inverters has two types, i.e., Current Source Inverter (CSI), also referred to as PQ inverter, and Voltage Source Inverter (VSI). Both inverter forms have a two-layer coordination mechanism. This paper proposes a design method for the digital Proportional-Resonant (PR) controller that regulates the current inside an inverter. The inverters will improve the voltage quality of the microgrid while maintaining the average voltage of buses at the same desired level. There is comprehensive detail on the computations specific to resonant and proportional gains and digital resonance path coefficients. The paper includes a digital PR controller design and its analysis in the frequency domain. The analysis is based on the w-domain. The main contribution of this paper is the proposed method, which not only focuses on the transient response but also improves the steady-state response which smoothens the voltage; furthermore, all inverters are effectively involved to increase the capacity of the microgrid for better power management. The suggested cooperative control technique is used on an IEEE 14-bus system having fully distributed communication. The convincing outcomes indicate that the suggested control technique is an effectual means of regulating the microgrid’s voltage to obtain an evener and steady voltage profile. The microgrid comprises distributed resources and is used as the primary element to analyse power flow and quality indicators associated with a smart grid. Lastly, numerical simulation observations are utilised for substantiating the recommended algorithm

Design And Implementation Of Co-Operative Control Strategy For Hybrid AC/DC Microgrids

This thesis is mainly divided in two major sections: 1) Modelling and control of AC microgrid, DC microgrid, Hybrid AC/DC microgrid using distributed co-operative control, and 2) Development of a four bus laboratory prototype of an AC microgrid system. At first, a distributed cooperative control (DCC) for a DC microgrid considering the state-of-charge (SoC) of the batteries in a typical plug-in-electric-vehicle (PEV) is developed. In DC microgrids, this methodology is developed to assist the load sharing amongst the distributed generation units (DGs), according to their ratings with improved voltage regulation. Subsequently, a DCC based control algorithm for AC microgrid is also investigated to improve the performance of AC microgrid in terms of power sharing among the DGs, voltage regulation and frequency deviation. The results validate the advantages of the proposed methodology as compared to traditional droop control of AC microgrid. The DCC-based control methodology for AC microgrid and DC microgrid are further expanded to develop a DCC-based power management algorithm for hybrid AC/DC microgrid. The developed algorithm for hybrid microgrid controls the power flow through the interfacing converter (IC) between the AC and DC microgrids. This will facilitate the power sharing between the DGs according to their power ratings. Moreover, it enables the fixed scheduled power delivery at different operating conditions, while maintaining good voltage regulation and improved frequency profile. The second section provides a detailed explanation and step-by-step design and development of an AC/DC microgrid testbed. Controllers for the three-phase inverters are designed and tested on different generation units along with their corresponding inductor-capacitor-inductor (LCL) filters to eliminate the switching frequency harmonics. Electric power distribution line models are developed to form the microgrid network topology. Voltage and current sensors are placed in the proper positions to achieve a full visibility over the microgrid. A running average filter (RAF) based enhanced phase-locked-loop (EPLL) is designed and implemented to extract frequency and phase angle information. A PLL-based synchronizing scheme is also developed to synchronize the DGs to the microgrid. The developed laboratory prototype runs on dSpace platform for real time data acquisition, communication and controller implementation

A power consensus algorithm for DC microgrids

A novel power consensus algorithm for DC microgrids is proposed and analyzed. DC microgrids are networks composed of DC sources, loads, and interconnecting lines. They are represented by differential-algebraic equations connected over an undirected weighted graph that models the electrical circuit. A second graph represents the communication network over which the source nodes exchange information about the instantaneous powers, which is used to adjust the injected current accordingly. This give rise to a nonlinear consensus-like system of differential-algebraic equations that is analyzed via Lyapunov functions inspired by the physics of the system. We establish convergence to the set of equilibria consisting of weighted consensus power vectors as well as preservation of the weighted geometric mean of the source voltages. The results apply to networks with constant impedance, constant current and constant power loads.Comment: Abridged version submitted to the 20th IFAC World Congress, Toulouse, Franc

On the Robust Control and Optimization Strategies for Islanded Inverter-Based Microgrids

In recent years, the concept of Microgrids (MGs) has become more popular due to a significant integration of renewable energy sources (RESs) into electric power systems. Microgrids are small-scale power grids consisting of localized grouping of heterogeneous Distributed Generators (DGs), storage systems, and loads. MGs may operate either in autonomous islanded mode or connected to the main power system. Despite the significant benefits of increasing RESs, many new challenges raise in controlling MGs. Hence, a three layered hierarchical architecture consisting of three control loops closed on the DGs dynamics has been introduced for MGs. The inner loop is called Primary Control (PC), and it provides the references for the DG’s DC-AC power converters. In general, the PC is implemented in a decentralized way with the aim to establish, by means of a droop control term, the desired sharing of power among DGs while preserving the MG stability. Then, because of inverterbased DGs have no inertia, a Secondary Control (SC) layer is needed to compensate the frequency and voltage deviations introduced by the PC’s droop control terms. Finally, an operation control is designed to optimize the operation of the MGs by providing power setpoints to the lower control layers. This thesis is mainly devoted to the design of robust distributed secondary frequency and voltage restoration control strategies for AC MGs to avoid central controllers and complexity of communication networks. Different distributed strategies are proposed in this work: (i) Robust Adaptive Distributed SC with Communication delays (ii) Robust Optimal Distributed Voltage SC with Communication Delays and (iii) Distributed Finite-Time SC by Coupled Sliding-Mode Technique. In all three proposed approaches, the problem is addressed in a multi-agent fashion where the generator plays the role of cooperative agents communicating over a network and physically coupled through the power system. The first approach provides an exponentially converging voltage and frequency restoration rate in the presence of both, model uncertainties, and multiple time-varying delays in the DGs’s communications. This approach consist of two terms: 1) a decentralized Integral Sliding Mode Control (ISMC) aimed to enforce each agent (DG) to behaves as reference unperturbed dynamic; 2) an ad-hoc designed distributed protocol aimed to globally, exponentially, achieves the frequency and voltage restoration while fulfilling the power-sharing constraints in spite of the communication delays. The second approach extends the first one by including an optimization algorithm to find the optimal control gains and estimate the corresponding maximum delay tolerated by the controlled system. In the third approach, the problem of voltage and frequency restoration as well as active power sharing are solved in finite-time by exploiting delay-free communications among DGs and considering model uncertainties. In this approach, for DGs with no direct access to their reference values, a finite-time distributed sliding mode estimator is implemented for both secondary frequency and voltage schemes. The estimator determines local estimates of the global reference values of the voltage and frequency for DGs in a finite time and provides this information for the distributed SC schemes. This dissertation also proposes a novel certainty Model Predictive Control (MPC) approach for the operation of islanded MG with very high share of renewable energy sources. To this aim, the conversion losses of storage units are formulated by quadratic functions to reduce the error in storage units state of charge prediction