Islanded Microgrid Research Articles

Enhancing voltage profile in islanded microgrids through hierarchical control strategies

This paper presents a novel approach aimed at enhancing the voltage profile of an islanded microgrid (MG) through the utilization of Phasor Measurement Units (PMUs) and a hierarchical control system for Distributed Generators (DGs). Recognizing the criticality of maintaining an optimal voltage profile for essential loads within an MG, we assume that PMUs are strategically placed across the MG based on existing placement methodologies to ensure the observability of load buses. The synchrophasor measurements captured by these PMUs are leveraged within an offline-designed tertiary control layer of the hierarchical framework, which in turn sets the voltage reference for the secondary control layer of DGs across the MG. This approach effectively enhances the voltage profile of vital load buses within the MG. The proposed hierarchical strategy encompasses primary, secondary, and tertiary levels of control, responsible for stabilizing voltage and frequency, computing power references, and managing power flow, respectively. PMU measurements play a crucial role in the secondary control level by continuously monitoring deviations. By ensuring the effective placement of PMUs, the proposed framework enables efficient control, leading to notable improvements in the voltage profile and power management. To evaluate the effectiveness of our approach, five test networks were used: 14-bus, 30-bus, 39-bus, 57-bus, and 118-bus test networks. Simulation results demonstrate an impressive over 80 % enhancement in the MG's voltage profile achieved by our proposed method. Additionally, our heuristic strategy efficiently assigns the closest load bus to each DG while aggregating equidistant bus deviations. Collectively, our research underscores the significant impact of PMU measurements and a well-structured hierarchical voltage control system in substantially improving the voltage profile of MGs.

Robust and fast control approach for islanded microgrid system and EV charging station applications

Robust and fast control approach for islanded microgrid system and EV charging station applications

Deep Reinforcement Learning for Load Frequency Control in Isolated Microgrids: A Knowledge Aggregation Approach with Emphasis on Power Symmetry and Balance

To address the issues of instability and inefficiency that the fluctuating and uncertain characteristics of renewable energy sources impose on low-carbon microgrids, this research introduces a novel Knowledge-Data-Driven Load Frequency Control (KDD-LFC) approach. This advanced strategy seamlessly combines pre-existing knowledge frameworks with the capabilities of deep learning neural networks, enabling the adaptive management and multi-faceted optimization of microgrid functionalities, with a keen emphasis on the symmetry and equilibrium of active power. Initially, the process involves the cultivation of foundational knowledge through established methodologies to augment the reservoir of experience. Following this, a Knowledge-Aggregation-based Proximal Policy Optimization (KA-PPO) technique is employed, which proficiently acquires an understanding of the microgrid’s state representations and operational tactics. This strategy meticulously navigates the delicate balance between the exploration of new strategies and the exploitation of known efficacies, ensuring the harmonization of frequency stability, precision in tracking, and the optimization of control expenditures through the strategic formulation of the reward function. The empirical validation of the KDD-LFC method’s effectiveness and its superiority are demonstrated via simulation tests conducted on the load frequency control (LFC) framework of the Sansha isolated island microgrid, which is under the administration of the China Southern Grid.

Load Frequency Control Strategy for Islanded Microgrid Based on SCQ(λ) Algorithm

In the evolving landscape of power grids, where green transportation and intermittent clean energy play a crucial role, ensuring the security and reliability of the urban network is of utmost importance. However, the increasing volatility associated with these new energy sources poses a challenge to the traditional control methods. The large-scale integration of new energy in microgrids often leads to frequency instability and deviation in control performance standards. Addressing these issues, this paper introduces the SCQ(λ) algorithm, which accurately estimates the system's state to enhance controller capabilities. To evaluate the effectiveness of the proposed SCQ(λ) algorithm, the authors employ a load frequency control model in our simulation. In this model, they introduce various load change disturbances, including sine waves, square waves, and step disturbances to simulate realistic scenarios encountered in power systems. Throughout the simulation, they observe a significant reduction in frequency deviation in the case of step perturbation, with the deviation value decreasing by 0.0096.

Cryptocurrency mining as a novel virtual energy storage system in islanded and grid-connected microgrids

Renewable electrical energy (such as: solar and wind energies) generation in microgrids (MGs), is gaining attention to reduce greenhouse gas emissions. Microgrid operators (MOs) aim to create self-sufficient, environmentally sustainable grids, increasing the capacity of renewable energy sources (RESs) by up to 100%. Despite of the benefits of this trend, challenges arise from non-controlled characteristics of these power generations and their seasonal variations, causing fluctuations and renewable energy curtailment. Although the technical solutions; such as: the demand response (DR) programs, and the conventional electrical energy storage systems (EESSs) can help, however those may face limitations in countries with high seasonal energy generation and consumption variations. This paper introduces cryptocurrency mining loads (CMLs) as innovative virtual energy storage systems (VESSs), named cryptocurrency energy storage systems (CESSs). It proposes a structure to store excess renewable energy in cryptocurrency units (CCUs) like Bitcoin (BTC). CESSs can be charged during off-peak intervals and, conversely, they discharge during high-demand periods to reduce the overall operational cost of MGs. Furthermore, it presents a new energy management system (EMS) formulation for the optimal operation of MGs in the presence of CESSs, providing an opportunity to generate additional electricity from RESs and to mitigate renewable energy curtailment. This paper explores the optimal operation conditions of both islanded and grid-connected MG with the proposed CESS. Utilizing a dataset from an island in Finland as a practical MG, its effectiveness is demonstrated through several case studies. The results of one case study in this paper demonstrate that the proposed CESS can decrease the operating cost of the MG by about 46.5%. Additionally, it is showed that by application of CESS the renewable energy curtailment is significantly reduced, and approached zero.

Analysis of Grid-Forming Inverter Controls for Grid-Connected and Islanded Microgrid Integration

Autonomous grid-forming (GFM) inverter testbeds with scalable platforms have attracted interest recently. In this study, a self-synchronized universal droop controller (SUDC) was adopted, tested, and scaled in a small network and a test feeder using a real-time simulation tool to operate microgrids without synchronous generators. We presented a novel GFM inverter control adoption to better understand the dynamic behavior of the inverters and their scalability, which can impact the distribution system (DS). This paper provides a steady-state and transient analysis of the GFM power inverter controller via simulation to better understand voltage and frequency stabilization and ensure that the critical electric loads are not affected during a prolonged power outage. The controllers of the GFM inverter are simulated in HYPERSIM to examine voltage and frequency fluctuations. This analysis includes assessing the black start capability for photovoltaic microgrids, both grid-connected and islanded, during transient fault conditions. The high photovoltaic PV penetration levels open exciting opportunities and challenges for the DS. The GFM inverter control demonstrated appropriate response times for synchronization, connection, and disconnection to the grid. The DS has become more resilient and independent of fossil fuels by increasing the penetration of inverter-based distributed energy resources (DERs).

Distributed Cooperative Control Strategy for Stable Voltage Restoration and Optimal Power Sharing in Islanded DC Microgrids

Conventionally, voltage regulation and economic dispatch in DC microgrid are performed at different time scales, which cannot keep the distributed generators (DGs) at the optimal operating point in real time. In this paper, a novel distributed cooperative control strategy is proposed to synchronously achieve stable bus voltage restoration and optimal power sharing in islanded DC microgrids. The proposed strategy breaks the constraints of hierarchical control strategies, and incorporates the objectives of voltage regulation and economic dispatch into a distributed cooperative control framework to eliminate average bus voltage deviation and minimize total power generation costs in real time. The stability of the proposed strategy is verified by eigenvalue analysis and steady-state analysis. Furthermore, the concept of “incremental cost (IC) margin” is introduced in cooperative control considering capacity constraints to avoid the converter output power violation and performance degradation. Finally, the MATLAB/Simulink simulation and StarSim HIL experimental results verify the effectiveness and robustness of the proposed strategy in an islanded DC microgrid under various testing scenarios.

Load frequency control in Island micro-grid with electric vehicles and renewable energy sources using modified fractional order PID controller

This paper presents a modified fractional-order proportional-integral-differential (MFOPID) controller for load frequency control in an Island microgrid based on an electric vehicle (EV) and renewable energy source. It tackles the intermittent energy sources and the dynamic of the load change with reduced speed and the quality of response generated on the microgrid. The MFOPID controller gains are well turned using a metaheuristic grasshopper optimization algorithm (GOA) technique to determine its robustness and optimal system performance. The controller gains are evaluated with three different searching agent populations. The proposed MFOPID with GOA improved system performance frequency by 19.485 Hz compared to 14.1151 Hz of the benchmark model. It takes 6.9068 s of the proposed model to settle compared to 16.6796 s of FOPID.

Power Sharing Enhancement Strategies for Parallel-Connected Voltage Source Inverters With Common dc and ac Buses in Islanded Microgrids: Two New Control Schemes

Power Sharing Enhancement Strategies for Parallel-Connected Voltage Source Inverters With Common dc and ac Buses in Islanded Microgrids: Two New Control Schemes

Source-Storage-Load Coordinated Master-Slave Control Strategy for Islanded Microgrid Considering Load Disturbance and Communication Interruption.

When there is a sudden load disturbance in an islanded microgrid, the peer-to-peer control model requires the energy resource to maintain a margin of generation, resulting in a relatively limited regulation range, that is, voltage/frequency sometimes requires additional control to maintain stability. A "source-storage-load" coordinated master-slave control strategy is proposed in this study to address the aforementioned issues. The system voltage and frequency will be stable as long as the output frequency and voltage of the master resource are stable. Furthermore, it can fully utilize the power supply capacity of resources to support the supply-demand balance. The following tasks are included in the proposed strategy: 1) to improve the operational security in the face of load disruption, a source-storage-load coordinated control method based on the "ramping speed" ratio is proposed, which can quickly restore the balance of supply and demand; 2) to improve the communication reliability in the face of interruption, a channel planning method is proposed, which can address the communication interruption problem by constructing an internal network among source-storage-load; and 3) to improve the mode switching stability of resources subjected to external disturbance, the external disturbance suppression and stability analysis involved in the regulation process are completed using sliding-mode control and small signal model methods. Related case studies are carried out to verify the effectiveness of the proposed strategies.

Remote Multinodal Voltage Unbalance Compensation in Islanded AC Microgrids

Remote Multinodal Voltage Unbalance Compensation in Islanded AC Microgrids

Impact and Integration of Electric vehicles on renewable energy based Microgrid: Frequency profile improvement by a-SCA optimized FO-Fuzzy PSS approach

The modelling of an electric vehicle along with its integration and impact over a renewable energy based microgrid topology is well addressed in this manuscript. The frequent charging and discharging of the electric vehicle makes an oscillation over grid frequency. The performance especially frequency of an islanded AC microgrid is also affected seriously under the actions of different uncertainties like load dynamics, wind fluctuation in wind plant, solar intensity variation of PV plant etc. In order to maintain standard frequency, this research work aims to regulate the net power generation of the system in response to total demand. To monitor net generation, this work has intended a fractional order fuzzy power system stabilizer (FO-Fuzzy PSS) control scheme in several dynamic situations. The proposed FO-Fuzzy PSS control scheme acts as most potential candidate to pertain stability in system frequency in above discussed disturbances. The controller gains are tuned optimally with suggesting an advanced- Sine Cosine Algorithm (a-SCA) under different conditions. The performance of the optimal FO- Fuzzy PSS controller is compared over standard fuzzy controller and PID controller in regard to frequency regulation of microgrid system. It is observed that proposed FO-Fuzzy PSS control scheme has the credential to reduce settling time of ΔF1 (area1 microgrid frequency) by 98.60% and 250.82% over fuzzy controller & PID controller correspondingly. Further, the dynamic optimal performance of the proposed a-SCA is compared over original SCA and PSO techniques to justify its superiority.

Distributed Learning-Based Secondary Control for Islanded DC Microgrids: A High-Order Fully Actuated System Approach

In this paper, a converter-based multi-bus DC microgrid (MG) in series is studied, in which the trade-off between voltage recovery and current equalization has been a hot topic of interest. To solve this problem, a distributed learning-based high-order fully actuated (DL-HOFA) secondary control is proposed in this paper, and the simple structure of this control technique facilitates its application in various modern DC MGs with different configurations. Before designing the secondary control protocol, this paper provides a comprehensive description of DC MGs in advance. In the suggested control strategy, the controller design is tightly related to the underlying physical characteristics of the MG, and this prominent feature represents a significant improvement in its adaptability. In addition, the DL-HOFA control obtains fast dynamic and accurate current sharing performance by virtue of the high-order fully actuated DC MG model. The effectiveness of the proposed control method is verified on a real photovoltaic- and battery-based hardware system with maximum power point tracking (MPPT) controller.

A Communication-Less Secondary Control Method for Parallel Grid-Forming Inverters in Islanded Microgrids Based on Mode Switching

A Communication-Less Secondary Control Method for Parallel Grid-Forming Inverters in Islanded Microgrids Based on Mode Switching

Optimized Unsymmetrical Per-Phase Droop for Soft Line Switching of Reconfigurable Unbalanced Inverter-Based Islanded Microgrid

Optimized Unsymmetrical Per-Phase Droop for Soft Line Switching of Reconfigurable Unbalanced Inverter-Based Islanded Microgrid

Deep neural networks based method to islanding detection for multi-sources microgrid

One of the significant issues in the field of microgrids is their islanding, where in many cases, the lack of awareness of microgrid islanding can lead to interference in the protective and control functions of the microgrid. Therefore, the accurate detection of microgrid islanding is of utmost importance. In this article, a method based on deep neural networks is presented. The proposed approach utilizes terminal parameters of microgrid resources, such as sequence current components, voltage, and other parameters, to detect islanding. Various operational states of the microgrid are simulated offline as standard test cases, and the parameters of each of them are recorded for later use. These data are then used to extract statistical features using discrete wavelet transform. Subsequently, the extracted features are fed into deep neural networks for training, and the training and evaluation results demonstrate an accuracy of over 99% for the proposed method in terms of precision and reliability. Furthermore, the accuracy of the proposed method is compared with some similar approaches for islanding detection.

Consensus-based secondary control for DC microgrids with communication delays via a networked predictive control strategy

In today’s cyber–physical microgrid systems, the consensus-based secondary control is generally utilized to settle the voltage deviation and rough current allocation issues at the primary control level. However, time delays follow inevitably the introduction of sparse communication networks, and most existing works adopt passive tolerance approaches. To actively alleviate the unavoidable delay effect in microgrids’ communication networks, a networked predictive control (NPC) strategy is proposed for an islanded DC microgrid subject to time delays in this paper. Firstly, the predictive approaches for both voltage and current are developed based on the cyber–physical microgrid model. Unlike the practice of passively tolerating time delays, the NPC strategy is proposed to actively compensate for the effect of communication delays by estimating real-time voltage and current values using the previously obtained prediction models. Moreover, to prove the generality of the developed method, the microgrid systems’ stability can be derived from the Schur stability of the closed-loop system, thus the DC microgrid can achieve voltage regulation and proportional current sharing simultaneously. Finally, the performance of our method against the time delay effect is validated by extensive experiments on an islanded 48-V DC microgrid system, in terms of its feasibility, delay tolerance ability, and robustness to load changes and communication faults. Experimental results demonstrate the effectiveness and superiority of the NPC strategy.

Reaction Curve-Assisted Rule-Based PID Control Design for Islanded Microgrid

In a renewable energy-based islanded microgrid system, frequency control is one of the major challenges. In general, frequency oscillations occur in islanded microgrids due to the stochastic nature of load and variable output power of distributed generating units (DGUs). In the presented research proposal, frequency oscillations are suppressed by implementing the proportional integral derivative (PID) controller-based control design strategy for an islanded microgrid. The modeling of the islanded microgrid is firstly presented in the form of a linearized transfer function. Further, the derived transfer function is approximated into its equivalent first-order plus dead time (FOPDT) form. The approximated FOPDT transfer function is obtained by employing the reaction curve method to calculate the parameters of the FOPDT transfer function. Furthermore, the desired frequency regulation is achieved for the manifested FOPDT transfer function by incorporating PID control design. For PID controller tuning, different rule-based methods are implemented. Additionally, comparative analysis is also performed to ensure the applicability of the comparatively better rule-based tuning method. The Wang–Chan–Juang (WCJ) method is found effective over other rule-based tuning methods. The efficacy of the WCJ method is proved in terms of transient response and frequency deviation. The tabulated data of tuning parameters, time domain specifications, and error indices along with responses are provided in support of the presented control strategy.

Strategic dispatch of electric buses for resilience enhancement of urban energy systems

The increasing frequency of the occurrence of high impact low probability (HILP) disruptive events has posed huge threats to the power system. Therefore, power system resilience improvement has drawn world-wide attention. Electric buses (EB) are equipped with a large capacity of batteries which could provide sufficient energy and capacity values to run islanded micro-grids (MG) for hours, with a particular focus on V2G, which will deliver system resilience during extreme operational conditions. In this paper, an innovative reciprocal transport-power system coordination scheme is proposed to simultaneously mitigate the adverse impacts on both systems. By using this economic incentive-free approach, EBs are endogenously motivated to provide resilience-oriented V2G service to the power system, while increasing the transport service survivability during HILP disruptive events. Additionally, a novel EB dispatch rescheduling method considering the trade-off of both the requirement of energy supply security and transport service fulfilment is proposed. By using this method, the essential load curtailment of local MGs can be further alleviated, while the impacts of reduced charging service on transport service can also be further mitigated. Through a series of case studies, we illustrate that EBs have significant potential to provide resilience enhancement to the urban energy system based on appropriate dispatch strategies. Meanwhile, the interests of the power system and the transport system can be well reconciled by using the proposed approach during HILP disruptive events.

Analysis and control of large-signal stability with storage in small scale islanded AC microgrids

The analysis of small-signal stability in AC microgrids has yielded numerous findings. However, investigating large-signal stability remains a major difficulty and has received limited attention in research. The article presents the establishment of a non-linear reduced-order model for small-scale AC microgrids with storage. The model considers the changes in converter structure that occur during large disturbances. Next, we will analyse the system’s stability under large-signal conditions and identify the underlying unstable mechanism. The impact of limitation links on system stability is significant, as they result in structural changes. The proposal of “virtual synchronous damping control” (VSD) aims to improve the stability of AC microgrids by addressing the issues caused by an unstable mechanism. The validation of the proposed analysis and control methods are demonstrated by examining relevant case studies in MATLAB/Simulink.