Autonomous Microgrid Research Articles

Robust and Resilient Distributed Optimal Frequency Control for Microgrids Against Cyber Attacks

The optimal frequency control of autonomous microgrids (MGs), i.e., to achieve fast frequency recovery and dynamic power adjustment of the distributed generators in proportion to predefined participation factors, can be achieved in a fully distributed way based on the subgradient consensus protocol. However, such a distributively controlled MG is susceptible to different types of cyber attacks infiltrated from different locations. In this article, a robust and resilient distributed optimal frequency control scheme is proposed to address the threat of cyber attacks. It is facilitated by introducing an auxiliary networked system interconnecting with the original cooperative control system. On condition that the cyber attacks are within certain ranges, the robust design can maintain the functionalities by significantly attenuating the impact. Otherwise, the cyber attacks can be easily detected, and resilient reactions can be taken to mitigate their influences via isolation. Simulation results in a modified IEEE 34-bus MG validate the effectiveness of the proposed approach.

Direct-Quadrature Sequence Models for Energy-Function Based Transient Stability Analysis of Unbalanced Inverter-Based Microgrids

The reliability of supply in distribution networks can be improved by islanding (parts of) the network as autonomous microgrids in case of a contingency. Microgrids are commonly fed by inverter-based distributed energy resources, which causes transient stability challenges due to the lack of inertia and strongly coupled dynamics. The transient stability of inverter-based microgrids is conventionally analyzed by time-domain analysis. However, energy-function based transient stability analysis has advantages over time-domain analysis, as it provides a stability result for all initial conditions and allows uncertainty to be taken into account with the domain of attraction. Microgrids are generally unbalanced, however models for unbalanced energy-function based transient stability analysis are lacking in the literature. In this paper, coupled sequence components models of distributed energy resources and load devices in the dq reference frame are proposed, and experimentally validated with unbalanced voltage transients. The validated models are used for energy-function based transient stability analysis of an unbalanced inverter-based case study microgrid. Finally, the impact of unbalanced connection of devices on transient stability is analyzed. The results indicate that the proposed models accurately represent the behavior of physical devices and that the unbalanced connection of devices significantly impacts the transient stability of inverter-based microgrids.

Modified V-I droop based adaptive vector control scheme for demand side management in a stand-alone microgrid

The concept of conservative voltage reduction (CVR) is widely adopted in the distribution sector to curtail the load demand with the regulation of bus voltage to the lower value. The reduction of the peak demand and energy saving are the two key attributes furnished by implementing the CVR strategy. The voltage source inverter (VSI) based AC microgrid enables the integration of renewable energy sources (RES) to the AC network. Apart from facilitating the process of power generation, the VSI enabled renewable energy sources conducts the ancillary service such as demand side management (DSM) with the enforcement of CVR. The CVR’s applicability for demand side management considered to be prospective research for stand-alone microgrid. However, least exploration is being conducted in this direction for autonomous microgrid and hence, the paper is intended to investigate CVR’s performance on VSI enabled stand-alone microgrid. A 2-degree of freedom enabled adaptive vector control is being utilized to synchronize the frequency parameter of the microgrid network which utilizes the set parameter of static and transient droop gain function. A new approach is devised to compute the droop parameter for V-I droop which performs CVR action to realize demand side management. The proposed strategy utilizes the voltage reduction mechanism to establish voltage at the load side with the coordination of high and low bandwidth controller. The verification of the proposed work is established with 5 bus microgrid test system and further, three phases to ground fault condition is being put on the controller to test its adequacy. The simulation results are furnished through MATLAB/Simulink software.

Performance improvement of an islanded AC microgrid in presence of Plug-in Hybrid Electric vehicles, load and renewable generation uncertainties

In this paper, a performance improvement scheme for an autonomous AC microgrid in the presence of dispatchable and renewable units, and Plug-in Hybrid Electric vehicles has been proposed. In a standalone mode of operation, a droop-control strategy is implemented at the primary control level for a communication-free accurate power-sharing among multiple dispatchable generators. For a network that is neither highly reactive nor highly resistive, active and reactive powers are coupled to both voltage magnitudes and phase angles. A mixed-droop feature is incorporated at the primary control level for autonomous power-sharing among the units for such networks. The mixed-droop feature is considered in this paper. Further, stochastic models of load demands, renewable generation, and plug-in hybrid electric vehicle charging loads are considered. Objectives are to reduce the cost of operation and minimize the emission of greenhouse gases from generation activities. The bi-objective problem is solved in the fuzzy domain. Performance improvement is achieved in two steps, first, by choosing optimal static droop constants using the particle swarm optimization, and then a further performance improvement is achieved by network reconfiguration. The proposed algorithm is tested on a thirty-three bus autonomous microgrid and gives satisfactory results.

Renewable generation intermittence and economic dispatch control of autonomous microgrid with distributed sliding mode

This work addresses the Frequency Regulation (FR) and Economic Dispatch (ED) of autonomous Microgrid (MG) with distributed Renewable Energy Agents (REA). The MG possesses low inertia and lacks the natural synchronization capability requiring a fast-convergent control for FR and ED. Moreover, the nonlinear coupled dynamics of MG with unknown network parameter and network topology poses a critical control design challenge. The existing distributed control solutions; possess sluggish response against fluctuating power demand and system-disturbances, based on impractical assumptions and not applicable to generic network topologies. Moreover, the contemporary control schemes are unable to handle the renewable intermittence and fail to converge in presence of volatile production capacities of REA. A Distributed SMC based secondary control is proposed to fulfill the control requirements of MG. A novel decoupling technique is introduced that enables the application of control on generic network topologies with unknown network parameters. A constrained ED solution is derived for renewable agents possessing non-uniform and volatile production capacities and successfully achieved using the proposed control technique. The convergence of proposed control is proved using the Lyapunov Candidate function, while the performance is validated using IEEE 14 bus system and the results are compared with DAI control.

Distributed MPC for economic dispatch and intermittence control of renewable based autonomous microgrid

This work addresses secondary level control of Autonomous Microgrid composed of Distributed Renewable Energy Sources (DRES). The interconnection of DRES forms a nonlinear system with coupled dynamics, unknown network parameters, and network topologies. The challenging features of DRES, such as low inertia, large number, volatile production capacities, and geographically wide distribution pose critical control design challenges for Economic Dispatch (ED) and frequency regulation. Whereas the distributed control schemes proposed in contemporary research are too slow to provide ED in the presence of fluctuating power demand, based on impractical assumptions or too restrictive in terms of network topology to have practical significance. Moreover, the control schemes are unable to handle the intermittent and uncertain nature of DRES and lead to instability in the presence of volatile power production capacities. Considering the above, we propose Secondary Distributed Model Predictive Control that provides fast and robust convergence and avoids impractical assumptions. A unique decoupling technique enables the application of control to generic network topologies. A constrained ED solution is derived and successfully achieved in presence of volatile production capacities of DRES. The Lyapunov stability of control is proved through terminal constraints. The performance of the proposed control is validated using an IEEE 14-Bus System.

Hybrid Islanding Detection Method of Photovoltaic-Based Microgrid Using Reference Current Disturbance

This paper proposes a new hybrid islanding detection method for grid-connected photovoltaic system (GCPVS)-based microgrid. In the presented technique, the suspicious islanding event is initially recognized whilst the absolute deviation of the point of common coupling (PCC) voltage surpasses a threshold. After an intentional delay, a transient disturbance is injected into the voltage source inverter’s d-axis reference current to decline the active power output. As a result, the PCC voltage reduces in islanding operating mode whilst its variation is negligible in the grid presence. Therefore, the simultaneous drop of PCC voltage and active power output is used as an islanding detection criterion. The effectiveness of the proposed algorithm is investigated for various islanding and non-islanding scenarios for a practical distribution network with three GCPVSs. The simulation results in MATLAB/Simulink show successful islanding detection with a small non-detection zone within 300 ms without false tripping during non-islanding incidents. In addition to the precise and fast islanding classification, the presented scheme is realized inexpensively; its thresholds are determined self-standing, and its output power quality degradation is eminently small. Moreover, the active power output is restored to the nominal set after islanding recognition, enhancing the chance of GCPVS generation at its highest possible level in the autonomous microgrid.

Variable-Speed PICO Hydel Energy Storage With Synchronverter Control to Emulate Virtual Inertia in Autonomous Microgrids

Autonomous microgrids are potential alternative to grid connectivity for powering remote communities around the globe. A sustainable microgrid with renewables and energy storage having minimum operation and maintenance routines is the most sought option. Batteries are predominantly used to support the stochastic behavior of renewables in such microgrids. However, they are prone to frequent failure and require periodic maintenance, which demands an alternative. Thus, in this article, the renewable powered irrigation system in India was configured to form sustainable pico hydel energy storage (PHES). To enhance the inertia of the microgrid with static sources, virtual inertia capability was induced into PHES by modified synchronverter technology. First, the small-signal modeling approach was presented to derive the closed-loop transfer function of the system. Subsequently, the effect of control parameter variation on system stability and the interaction between the governor and the synchronverter was investigated using eigenvalue analysis. Next, the performance of synchronverter was compared with the established vector control through time-domain simulations in MATLAB/Simulink. The simulation results revealed that the proposed strategy improved the inertial response of PHES and outperformed vector control by reducing peak overshoot, settling time, and steady-state error.

Optimal Dump Load Allocations in High RBDG Penetrated Microgrid for Voltage and Frequency Regulation

The rising renewable penetrations has paved ways for the microgrids to operate independent of the conventional centrally located power plants. At low load hours, the microgrid operation is often disrupted due the excess power generations creating voltage (V) and frequency (f) regulation issues. The use of energy storage devices to absorb such excess generations would be infeasible due to their less usability, high cost and uneconomical trading. The offline planning of distributing dump loads (DLs) in the network can coordinate with the online control in maintaining V and f of the system. Thus, the present work provides an offline analysis to optimally allocate DLs in the power electronic (PE) interfaced DGs powered autonomous microgrid to minimize the V and f deviations at off-peak hours. The V and f deviations as per the droop characteristics of PE interfaced DGs have been taken into consideration in the load flow. The optimization problem is formulated and solved using heuristic techniques viz MWOA and NSGA-II. The weakly meshed standard test beds of IEEE 33 and 69 bus distribution systems have been used in the present work as autonomous microgrids.

Multi-Variable H∞ Control Approach for Voltage Ancillary Service in Autonomous Microgrids: Modelling, Design, and Sensitivity Analysis

This paper proposes a multi-variable robust control scheme for voltage regulation in a diesel-photovoltaic-supercapacitor hybrid power generation system operating in stand-alone mode. First, we study the influence of system parameters on the dynamic behavior of open-loop system measured outputs by means of a stability analysis method based on Monte Carlo simulation. Next, by applying $\mathcal {H}_{\infty }$ control theory, an $\mathcal {H}_{\infty }$ -based voltage controller is proposed to robustly force the voltage magnitude of a point of common coupling such as to satisfy design specifications. A cascaded two-level control architecture, where this controller acts as an upper control level and provides references to classical PI-based current tracking controllers placed on a lower level, is developed. A comprehensive methodology that casts the specific engineering demands of microgrid operation into an $\mathcal {H}_{\infty }$ control formalism is detailed. Effectiveness of the proposed voltage robust control strategy is validated via MATLAB®/Simulink® closed-loop time-domain simulations. Finally, we perform a sensitivity analysis of robust performance of the designed $\mathcal {H}_{\infty }$ controller in the presence of various load disturbances and model uncertainties through a series of closed-loop time-domain simulations carried out in MATLAB®/Simulink®.

Energy Analysis of A Hybrid Wind-Wave Solution For Remote Islands

The energy needs of most Aegean islands are covered by the operation of autonomous/local power stations (APS/LPS) using imported oil. The costly operation of the APS/LPS combined with the resulting environmental problems, set the issue of a sustainable and rational energy solution mainly for the remote islands, showing respect to the sensitive island ecosystems and the acceptance of local communities. In this context, high wind speeds as well as the remarkable wave potential of the Aegean Archipelagos could be the driving force for a sustainable energy supply solution for these islands by exploiting combined energy sources along with an appropriate energy storage system, comprising a modern hybrid renewable based station. Moreover, the exploitation of wave energy is one of the future priorities of the European Union (Blue Growth) in an effort to support the installation of wave energy converters, which are in the final stage of technological development. The proposed analysis examines the combined exploitation of the wave and wind potential for a representative medium sized island of the Aegean Archipelagos in order to cover its electrical needs. The results show that the installation of a hybrid power station contributes to a higher integration of renewable energy systems (RES) into an autonomous micro-grid and that the stochastic production of wind turbines can be counterbalanced due to the smoother (time-dependent) production of wave systems. In addition, the ability to store excess renewable energy enhances the energy supply security of an island micro-grid providing a clean energy solution for the remote Aegean island communities and thus reducing their oil dependence.

H∞ robustness for distributed control in autonomous microgrids considering cyber disturbances

H∞ robustness for distributed control in autonomous microgrids considering cyber disturbances

Increasing the Photovoltaic Hosting Capacity in Autonomous Grids and Microgrids via Enhanced Priority-List Schemes and Storage

European Union has seen a rapid increase in renewable energy sources during the last decade. The variability and uncertainty caused by the increased penetrations of renewable generation must be properly considered in day-ahead unit commitment to retain the stable operation of conventional power plants. In this work, we present an enhanced method to determine the hosting capacity of photovoltaic energy in an autonomous grid. Based on optimal unit commitment schedules derived from priority list-schemes, we examine the potential of increasing the hosting capacity performing annual simulations for different scenarios in the presence of electricity storage. According to the obtained results, the application of storage eliminates the reliability expenses of load shedding and spinning reserve deficits. Hence, the actual hosting capacity is appropriately retrieved based on the renewable generation curtailment during each case study. However, sustainable solutions are achieved at higher penetration levels, reaching a near of 20% with respect to photovoltaic systems. The proposed solution could be efficiently utilized to determine the photovoltaic hosting capacity of microgrids in islanded or interconnected mode.

LMSRE-Based Adaptive PI Controller for Enhancing the Performance of an Autonomous Operation of Microgrids

Microgrids take a large part in power networks thanks to their operational and economic benefits. This research introduces a novel implementation of an adaptive proportional plus integral (PI) controller to boost the autonomous microgrid operation efficiency. The least mean and square roots of the exponential algorithm are utilized in the adaptive PI control strategy. The multi-objective function for both sunflower optimization (SFO) and particle swarm optimization (PSO) algorithms is obtained by The Response Surface Methodology. The system is evaluated under different environments, which are stated as follows: 1) disconnect the system from the grid (islanding), 2) autonomous system exposure to load variability, and 3) autonomous system exposure to a symmetrical fault. The proposed practicality of the control plan is shown by the data of the simulation, which is extracted from PSCAD/EMTDC software. The strength of the suggested adaptive control is confirmed through matching its results with those obtained using the SFO and PSO based optimal PI controllers.

A Novel Frequency Control Scheme for Autonomous Microgrid Using Cooperative Application of Supercapacitor-Battery HESS, Photovoltaics, LED Lighting Loads and TCLs

The supercapacitor-battery hybrid energy storage system (SBHESS) has been commonly used to reduce the stress of fast power variations on the battery, and hence, prolong its lifetime. However, the utilization of the supercapacitor (SC) significantly increases the cost of energy storage system. Considering the potentials of the photovoltaic systems, the smart LED lighting loads and the thermostatically controlled loads in primary frequency control (PFC), three novel PFC schemes are proposed for each of them. They are enabled to cooperatively participate in the PFC of islanded MG alongside the SBHESS. Their cooperative application alongside the SBHESS decreases the participation share of the SC in the PFC and hence, reduces the size and the cost of the SC and its converter which consequently decreases the SBHESS cost. In this regard, the genetic algorithm is employed to tune the controller coefficients of the PFC schemes and the distributed generators to limit and minimize frequency deviations within an acceptable range, and also minimize the size of SC and its converter. The results show that the proposed cooperative application considerably decreases the size and the cost of the SC and its converter. This is while the SBHESS battery life is still extended the same as the case in which the SBHESS is used alone. As the frequency control results are similar with and without the proposed cooperative application and the imposed cost is much higher in the latter case, the proposed cooperative application increases the cost-effectiveness of the SBHESS.

Modelling of an innovative and autonomous micro-grid based on a biomass - solar PV hybrid power system

Micro-Combined heat and power (m-CHP) systems fuelled by renewables, such as residual biomasses, are today of great interest to produce energy in an efficient and green way. The aim of the present work is to develop a numerical model of a hybrid energy system including a biomass powered m-CHP unit based on gasification and coupled with solar photovoltaic (PV) modules and to an electrical storage device, able to provide energy to remote areas. Main advantages of the considered configuration are its ultra-low environmental impact and just its autonomous operation by local resources. The developed unsteady multiphysical model accounts for the main plant components, namely the syngas powered engine, the PV panels and the battery, as well for a dynamic use of the produced energy. Main features of the adopted schematization of the actual system rely on the proper description of syngas combustion, that takes into account the extreme difficulty of working with a non-conventional gas, and on a PID control that is considered for energy flow management to meet the electrical demand curve. The PV panel current is calculated through an ad-hoc function that reads, at any given time, actual solar irradiance data in the city of Naples, Italy, the battery voltage and the main parameters of the PV module. The battery, with a voltage of 48V and a capacity of 100kWh, is modelled as an equivalent circuit with its proper State of Charge (SoC) versus Open Circuit Voltage (OCV) curve. The voltage response to a current at a particular SoC and temperature are calculated. This dynamic modelling permits the optimal control of the whole system to meet the electrical and thermal user’s demand and also to better design any possible change in the storage or PV size to meet specific real uses of the produced energy.

Mitigation strategies for communication networks induced impairments in autonomous microgrids control: A review

<abstract> <p>The advancement in communication technology and the availability of intelligent electronic devices (IEDs) have impacted positively on the penetration of renewable energy sources (RES) into the main electricity grid. High penetration of RES also come along with greater demand for more effective control approaches, congestion management techniques, and microgrids optimal dispatch. Most of the secondary control methods of microgrid systems in the autonomous mode require communication links between the distributed generators (DGs) for sharing power information and data for control purposes. This article gives ample review on the communication induced impairments in islanded microgrids. In the review, attention is given to communication induced delay, data packet loss, and cyber-attack that degrades optimal operations of islanded microgrids. The review also considered impairments modelling, the impact of impairments on microgrids operation and management, and the control methods employed in mitigating some of their negative impacts. The paper revealed that innovative control solutions for impairment mitigation rather than the development of new high-speed communication infrastructure should be implemented for microgrid control. It was also pointed out that a sparse communication graph is the basis for communication topology design for distributed secondary control in the microgrid.</p> </abstract>

The Least Cost Design of 100% Solar Power Microgrids in Africa: The Sensitivity to Meteorological and Economic Drivers and the Possibility for Simple Sizing Rules

Autonomous micro-grids based on solar photovoltaic (PV) are one of the most promising solution to bring electricity access in many off-grid regions worldwide. Different storage/PV panel sizes can achieve the same level of service quality and an optimal design is typically identified by minimizing the levelized cost of electricity (LCOE). The cost optimization however relies on a number of economic hypothesis that come with large uncertainties. This work explores the robustness of the optimal sizing to variations of these hypotheses. Using SARAH2 irradiance data, we simulate the production of generic PV arrays for 200 locations in Africa. We then identify the configurations (storage, PV capacity) for which 95% of demand hours are satisfied. We then identify the configuration with the lowest LCOE for different PV/storage cost ratios. Our result show that the optimal configuration is highly dependent on the characteristics of the resource, and especially on its multi-scale co-variability with the electric demand. It is conversely relatively robust to changes in cost hypotheses. These results allow us to propose simple and robust sizing rules based on the characteristics of the solar resource and electrical demand that allow to guess the optimal configuration for different cost ratios with a good precision.

Power flow incorporating cost-based droop control strategies for ac autonomous microgrids

Several methods of power flow analysis for autonomous microgrids have been suggested; however, the implementation of these methods is challenging because of the lack of a swing bus and droop control characteristics. This paper puts forward an innovative technique for the load flow study of microgrids that autonomously operate according to droop control strategies incorporating cost rather than traditional droop schemes. This approach aims to extend the application of conventional power flow methodologies. In this approach, the incremental cost that is derivative of the fuel cost curve with respect to power output is embedded in droop schemes. The proposed approach deploys the iterative procedure to impose complex power that injects through the swing node to zero, which represents the autonomous operation of microgrids. Test results validate that this approach is exact and straightforward to implement; therefore, it can be highly beneficial for operating and planning microgrids

A survey on: Automation of micro grid and micro distributed generation

The demand and supply gap of energy is large and the people are pressured to bear increasing hours of load losing, unnecessary intake of energy makes subjects even worse. So, the importance and requirement for energy conservation is increased exponentially. This paper outlines a step towards the conservation of electricity in standard and electricity especially with the aid of employing efficient constructing system with automation and installation of renewable based Micro Distributed Generator (MDG). The Smart Grid (SG) is a technological transformation from conventional electric grid, electro-mechanically controlled system, to smart, intelligent, and electronically controlled system. There are about 20–30% losses present in the conventional electric grid due to substandard operations at generation, transmission and distribution side. MDG play important role to build an efficient and autonomous micro-grid. In this paper importance of microgrid and some renewable energy sources utilized in formation of microgrid are discussed.