Grid-connected Mode Research Articles

Energy management and SoC balancing of distributed batteries in AC microgrids using consensus tracking control

This paper proposes a consensus tracking control method for energy management and state-of-charge (SoC) balancing of energy storage batteries in the grid-connected mode of AC microgrids. By adding a target power term to the consensus average control law, taking into account battery energy storage system (BESS) with various SoCs and various capacities, the stability and robustness of the proposed consensus control approach are analytically validated. Simulations of a state–space battery model and a detailed dynamic model of batteries in grid-connected mode are constructed in a Matlab environment. A detailed study of weighting matrices of the control approach is presented, and their suitable range is identified. The results show that the proposed method could effectively balance SoC for batteries of equal and different capacities, allowing the battery with the higher capacity to charge and discharge more than the others at the same time while still maintaining the target power. Furthermore, the controller successfully prevented deep discharge or overcharging of the batteries by disconnecting them when they reached their SoC limitations and compensating for this disconnection by raising their target power to maintain the same load.

Intelligent learning approach for transition control and protection of solar PV integrated electric vehicle charging station

Recently, the control of distributed generations (DGs) with electric vehicles (EVs) parking lot charging systems has received much attention for supporting emergency local loads during grid outages. To achieve optimal transition control of grid-connected (GC) and standalone (SA) modes, an intelligent learning-based algorithm is implemented for optimal handling of the disturbance in the system by injecting a fault condition over certain cycles during a weak/strong grid operation. Here, a fuzzy Q-learning (FQL) based algorithm is implemented for detecting and monitoring the distributed grid condition during different scenarios and a seamless transitioning control in GC and SA modes of operation. In this context, the implementation of designed FQL algorithm enables dynamic adjustments of control signals in response to real-time uncertainties in two major applications (grid synchronization and islanding detection mode). The FQL algorithm focuses on real-time decision-making in response to sudden fault scenarios, addressing the problem under various modes of operation. To validate the proposed FQL controller accuracy, a real-time hardware-in-loop (HIL) simulation and their experimental validation is carried out of a 16kWp grid integrated PV sub-system with different load profiles. The performance evaluation of the FQL controller is investigated under linear and nonlinear local load scenarios.

Design of prototype for the short circuit protection of DC bus using Arduino Uno and DSP controller

Micro-grids (MGs) play a prominent role in the exchange of bulk power between loads and the central grid. MG can run in an islanding mode or grid-connected mode. When the central grid fails to provide power in such situations, MGs serves as power sources for critical facilities such as coordination facilities in railway stations and airports, transportation, university and research facilities. MGs use energy sources such as solar, wind, hydro, geothermal, and biomass to produce electricity along with rechargeable batteries, aircraft applications is continuously increasing. This leads to the development of DC MGs. A model of DC MG is located at the disaster management lab in the Department of Electrical and Electronics Engineering. The MG consists of step-downed and rectified DC power supply from conventional 230 V AC source, a PV array, wind, and a battery bank a source supplying power to a set of nine DC loads. Although DC MGs have many advantages compared to AC MGs, one of the challenges faced is the study of faults and protection of the DC MG. In this paper, a prototype for the existing system in the disaster management lab is designed in hardware and tested.

Analysis of a Grid-Tie Solar Power System for Efficient Transition between Grid-Connected Modes

Abstract: Solar Photo Voltaic (PV)-battery energy storage based micro-grid with a multifunctional Voltage Source Converter (VSC) is presented in this research paper. Whenever the grid fails, this system operates in SA mode automatically, thereby without causing any interruption in supplying the load. Similarly, it automatically shifts to the GC mode, when the grid is restored. The VSC functions in current control for GC mode, and it operates in voltage control for SA mode of operation. This system is capable of extracting the maximum power from the solar PV array irrespective it is operating in the GC mode or SA mode. It regulates the dc-link voltage to the maximum power point voltage of the PV array. If the absence of the battery is detected, then the control is automatically shifted to VSC for performing the extraction of the maximum power of the PV array

Grey Wolf Optimized Economic Load Dispatch Including Battery Storage In Microgrid

In last decades, grey wolf optimizer algorithm as a new meta-heuristic optimization technique plays major role in optimization of engineering problems such as load forecasting, controller parameter tuning and job scheduling. In this paper, grey wolf optimization (GWO) is used to optimize the microgrid system for effective dispatching of power to load with economic manner. The model of microgrid system components are developed and investigated in the MATLAB/Simulink platform. The vital objective of the proposed grey wolf algorithm is to minimize overall cost of the microgrid operation. The detailed investigation is carried out on power dispatch optimization and cost minimization for both modes, i.e. island and grid-connected modes of the microgrid system with considering the impact of running costs. From the analysis, the cost of the overall system is optimized effectively, and load sharing is done effectively by means of GWO.

Novel protection method for AC microgrids with multiple distributed generations using Unscented Kalman filter

Traditional protection methods were inadequate in multiple distributed generations (MDG) microgrids due to the bidirectional power flow/high fault current in the grid-connected (GC) mode, and reduced fault current in the islanded (ID) mode. Therefore, a reliable and robust protection method has become of paramount importance for such MDG-based microgrids. This article suggests an Unscented Kalman filter (UKF) to detect, classify, and locate faults in such MDG-based microgrids. Initially, the harmonic content is generated from the UKF-estimated current signal to compute the total harmonic RMS factor (THRF). Then the changes in the THRF of each phase are cross-checked to a pre-specified threshold level to distinguish the fault conditions. Furthermore, the cumulative covariance-dependent reactive energy (CCDRE) is computed from both the estimated state and covariance matrix of voltage and current signals provided by UKF. Finally, the directional trends in the CCDRE are used to identify the fault zone in the microgrids. The effectiveness of the proposed method is validated through ample simulations on CIGRE and IEC 61,850–7–420 microgrid test system via MATLAB® Simulink. The results illustrate that the presented strategy is robust in both the GC mode and the ID mode of operation in meshed and radial topologies with 99.9% accuracy.

Robust control for improving performance of grid-synchronized solar PV-BES-wind based microgrid

An integration of hybrid renewable energy systems (HRESs) to the grid results in power quality issues at the point of interconnection. This paper proposes an approach to investigate and mitigate power quality issues and uncertainties associated with integration of a HRES that includes a solar photovoltaic (PV) array, a wind generator, and battery energy storage (BES). The system functions in grid tied mode, standalone mode and seamless mode transition between these modes. Primary objective of proposed control approach is to ensure stable and reliable operation while mitigating effects of power quality issues. To achieve this objective, proposed control approach employs advanced control strategies, including generalized fourth order filter (GFOF) for grid tied mode and phase angle estimation. An off-grid mode uncertainty and disturbances are overcome by proportional resonant based control. GFOF addresses multiple power quality issues associated with grid-connected mode, including robust performance during voltage unbalance, harmonics suppression, DC offset removal, weak grid conditions, and evaluation of unit templates. GFOF extracts fundamental load currents and voltages for evaluation of reference grid currents and phase angle. This precisely estimates frequency and phase angle for seamless synchronization. It provides adaptive mode transition. Power quality of currents is enhanced in both islanded and grid-connected modes through utilization of GFOF control, ensuring that total harmonic distortions (THDs) of grid currents remain below 5% (simulated THD is 1.77% and experimental THD is 3.80%), as specified by the IEEE-1547and 519 standards. A comparative analysis has justified efficacy of control. Simulated and experimental results confirm effectiveness of proposed controllers in various scenarios, demonstrating their ability to provide a favourable solution for controlling unfavourable grid conditions with technical strength and precision.

Multi-objective based Hybrid Artificial Intelligence Controlled Parallel Inverter in Islanded and Grid Connected Operations

Background: The Integration of non-conventional energy systems (NCES), like solar, wind, etc., into the grid with power electronic devices is adapted to meet the demand. Parallel connection of inverters (PCI) is an efficient method to boost power handling capacity, reliability, and system efficiency. However, the main drawback is the unequal power sharing among the inverters while using the conventional droop control technique (CDC). In addition, the circulating currents (CC) flow between these PCI, leading to common mode voltage (CMV), current waveform distortion, and reduction in the system's overall performance. Objectives: This work consists of a photovoltaic system (PVS) and battery energy storage system (BES) as the distributed generation (DG) unit to voltage source inverter (VSI) 1 and 2. The multi- objectives of the suggested work are (a) the equal power/load sharing among two inverters, (b) effective minimization of CC and the CMV, (c) maintaining constant DC-link (DCL) voltage during different solar irradiation and constant temperature, and (d) the reduction in total harmonic distortion (THD) of load current. Methods: A novel approach related to the enhanced droop control (EDC) method with an adaptive neuro-fuzzy hybrid controller (ANFHC) was suggested here to overcome the above issues. The performance analysis of the suggested technique was done in the Matlab/ Simulink platform with islanded and grid-connected modes for different loads. Results: A comparative analysis with the available methods like the proportional integral controller (PIC) and sliding mode controller (SMC) was carried out to exhibit the viability of the developed control technique. Conclusion: This study focused on the operation and control of a PCI with ANFHC in islanded and grid-connected modes to address issues such as uniform power sharing and reduction of CC and CMV.

Performance Evaluation of Microgrid Management Function in KERI pilot plant

As usual, the microgrid operates in grid-connect mode, but, when a fault occurs in the upstream grid, it should disconnect and shift into islanded operation mode. In grid-connect mode, the controlling power flow at PCC is necessary management function rather than the frequency and voltage. However, the controlling the frequency and voltage is asked in islanded mode. To achieve these management goals appropriately, the cooperative control strategy among microsources is needed. This supervisory control action is executed at MMS. In this paper, the cooperative control strategy of microgrid components is presented and the management performance is evaluated by using microgrid pilot plant. The pilot plant consists of the PV, PV/Wind Hybrid system, BESS, diesel generators, and RLC loads, which are connected to 380V low voltage lines. The test results show that the proper control strategy can ensure stability of microgrid in islanded mode and maintain the power flow of PCC at desired value successfully.

Research on Grid-Connected Optimal Operation Mode between Renewable Energy Cluster and Shared Energy Storage on Power Supply Side

The renewable energy cluster can reduce the total power deviation of renewable energy stations and also bring cooperative benefits to renewable energy stations. Shared energy storage can assist in tracking the power generation plan of renewable energy and has advantages in the scale of investment, utilization rate, and other aspects. Therefore, this article proposes a study on the grid-connected optimal operation mode between renewable energy cluster and shared energy storage on the power supply side. Firstly, for the complementary characteristics blurring each member’s contribution to the cluster power deviation, an improved Shapley value method is used to build a rational mechanism for apportioning the cluster power deviation penalty. Secondly, based on the Nash negotiation model and allocation mechanism, the revenue model of the renewable energy cluster is constructed, and an improved particle swarm optimization algorithm is proposed to solve the cluster operation strategy. Then, based on the charge and discharge demand of renewable energy cluster, with the goal of maximizing the benefits of shared energy storage, capacity pricing is optimized, as well as capacity allocation and participation in the frequency control auxiliary service market. Finally, the solving process of grid-connected optimal operation mode is proposed, and the rationality of the grid-connected optimal operation strategy between renewable energy cluster and shared energy storage is verified by example analysis. The results indicate that renewable energy cluster and shared energy storage can effectively increase both benefits, and a win-win situation for all parties can be realized. On the one hand, the cooperation mode and allocation mechanism can effectively guarantee the benefit of each renewable energy station. On the other hand, shared energy storage is beneficial for assisting in tracking the power generation plan of renewable energy and reducing the renewable energy power curtailment situation. There also has residual capacity in the shared energy storage system; it can participate in the frequency control ancillary service market, which can improve the capacity utilization rate and benefit of shared energy storage.

Determination of Controllers Constraints for Frequency Stability in Islanded Microgrid

With large scale integration of micro-generation into low voltage grids, stability becomes an important issue for a Microgrid (MG). The unique nature of the MG requires that it becomes stable in both grid-connected and islanded modes. In grid-connected mode, the main grid guarantees the stability of MG but in islanded mode, the stability is related to all elements of the system and their control units. In this paper, the changes in droop coefficient influencing the frequency stability of the MG are investigated in islanded MG. The simulation results determine the new constraint for controllers in MG

Fault Analysis of Microgrid With Grid-Connected and Islanded mode Using IoT-Wavelet Approach

Now a days microgrid is one of the most widely used method in power network to reduce system losses as well as improve the reliability in the field of electrical systems. Integration of power projects typically involves adding new distributed energy sources with and without compensating devices to an existing power system network. It is essential to design new protection scheme due to changes in the topology and dynamic behavior of the system. Now fast fault detection algorithmic approaches are necessary to integrate different types of generating sources and loads under smart environment. The protection scheme must provide physical monitoring as well as parametrical with the help of new technologies. Internet-of-things(IoT) is one of the source to monitor electrical systems under various environmental conditions of the system. Wavelet (WT) basically investigates the fault transient signals of different frequency and divides the waveform into different approximate and detailed coefficient values, which provides the important knowledge about the classification and location of fault. The detection of faulty-line and the location of fault by implementation wavelet detailed coefficients of Bior1.5 mother wavelet. This proposed method provides fault analysis of IoT based protection of microgrid with Grid-connected and Islanded Mode Using Wavelet Approach under various types of faults.

Dynamic Power Control In Utility-Connected Microgrids: A Back To Back Converter Approach For Efficient Integration Of Solar And Wind Energy

This research directs the imperative need for robust power management and control in utility-connected microgrids featuring solar and wind energy sources. The suggested method employs back to back converters for precise control on the transfer of both active and reactive power between the microgrid and the utility. The new control strategy operates in two states, effectively sharing power among the utility and the microgrid. An innovative arrangement among DGs ensures seamless load sharing in both grid-connected (GCM) and islanded modes (IM). The back-to-back converters provide complete frequency isolation, protecting the microgrid from voltage or frequency fluctuations from the utility side. The study introduces synchronized relay-breaker operation during faults, along with disabling back to back converters, ensuring smooth resynchronization after fault clearance. System stability is confirmed under different load changes. The proposed control setup proves resilient to changes in grid-side voltage and frequency, ensuring a stable and reliable power-sharing mechanism under various operating conditions. Simulations conducted in MATLAB/SIMULINK validate the efficacy of the proposed control strategy, highlighting its ability to enhance the stability and reliability of utility-connected microgrids incorporating solar and wind energy sources. This study contributes to advancing sustainable energy solutions, advocating for resilient and eco-friendly power systems.Top of Form.

Design of a wind-PV system integrated with a hybrid energy storage system considering economic and reliability assessment

Hybrid energy systems (HESs) have garnered significant attention as a sustainable solution to meet the world's growing energy demands while minimizing environmental impact. Achieving cost-effective and resilient HES solutions requires considering economic and reliability factors for optimal design. This research delves into the optimization and design of a wind-PV system integrated with a hybrid energy storage system using the Multi-Objective African Vultures Optimization Algorithm (MOAVOA) in both standalone and grid-connected modes. A comprehensive case study is conducted in Tabuk, Saudi Arabia, focusing on a microgrid and incorporating wind speed, solar radiation, and load data. The effectiveness of MOAVOA is verified using the Non-Dominated Sorting Genetic Algorithm-II (NSGA-II) and Multi-Objective Particle Swarm Optimization (MOPSO) methods in achieving the Pareto front of optimal system designs. Then, the mean, entropy, and criteria importance using the inter-criteria correlation (CRITIC) methods are utilized to assign weights to each objective in the obtained Pareto front. Finally, the Technique for Order Preference by Similarity to the Ideal Solution (TOPSIS) method is employed to select the optimal system design from the Pareto front. The results underscore the significance of the optimization approach in assessing the cost, dependability, and ideal configurations of the system. Furthermore, they highlight the diverse outcomes produced by different optimization techniques. While the entropy method yields more cost-effective designs, the mean and CRITIC methods produce comparable results. However, the mean and CRITIC approaches exhibit higher levels of reliability. For instance, in the grid-connected mode, the entropy weighting method yields an optimal system design with a total cost of M$ 42.2 and a reliability index of 91.73 %, while using the mean method, the selected system configuration has a total cost of M$ 42.98 and a reliability index of 92.89 %. The study emphasizes the benefits of diversifying renewable resources by considering different scenarios involving wind and solar generation. For example, in the wind-PV grid-connected system, the total cost is 22.65 % less than in the PV-only grid-connected system with a higher system reliability. The findings provide valuable guidance for system designers in selecting optimal optimization techniques and promoting the integration of renewable energy sources in hybrid energy systems. By presenting a comprehensive framework that incorporates economic and reliability assessments through the utilization of MOAVOA, this study contributes to the field of HES design.

Unified dispatch of grid-connected and islanded microgrids

This work develops microgrid dispatch algorithms with a unified approach to model predictive control (MPC) to (a) operate in grid-connected mode to minimize total operational cost, (b) operate in islanded mode to maximize resilience during a utility outage, and (c) utilize weighting factors in the grid-connected objective function to preserve islanded capability (on-site fuel reserves, battery state of charge) to enhance resilience in the potential event of an unplanned grid outage. Resilience is defined using microgrid survivability (probability to serve 100% of critical load), autonomy (duration of time to serve 100% of critical load), and unserved energy (curtailed critical load) for a target of 7 days during a grid outage. The developed methods are applied to a military microgrid with 2,250 kW of diesel generation, 3,450 kW/13,800 kWh battery storage, and 16,479 kW of solar photovoltaics. Sensitivity analysis is conducted to determine the selection of weighting factors to have the best impact on three developed objectives: grid-connected economics, islanded resilience, and carbon intensity. Optimal weighting factors reduce operating costs by 0.1%, increase survivability by 3.9%, increase autonomy by 16.7%, reduce unserved energy by 94.1%, and increase carbon intensity by 2.5%.

The Frequency Regulation Strategy for Grid‐Forming Wind Turbine Generator and Energy Storage System Hybrid System in Grid‐Connected and Stand‐Alone Modes

This paper proposes a coordinated frequency regulation strategy for grid‐forming (GFM) type‐4 wind turbine (WT) and energy storage system (ESS) controlled by DC voltage synchronous control (DVSC), where the ESS consists of a battery array, enabling the power balance of WT and ESS hybrid system in both grid‐connected (GC) and stand‐alone (SA) modes. The newly developed GFM framework, i.e., DVSC, is adopted in both WT and ESS, which utilizes DC voltage dynamics for synchronization purposes. In this paper, the GC mode and SA mode are transferred by changing the status of the series‐connected switch, and it is necessary to meet the grid connection conditions when the system is transferred to the GC mode, namely, voltage, frequency, and phase sequence. For the GC mode, the inertia response from WT can be realized using the reserved energy of the DC capacitor, while the ESS serves to eliminate the steady‐state frequency deviation and reduce the DC voltage fluctuation of WT using the designed secondary frequency regulation scheme. For the SA mode, the proposed strategy can keep the power balance without external power sources. The small‐signal model of the WT and ESS hybrid system is derived. The stability analysis in both GC and SA modes is fully conducted utilizing the modal analysis method, where the impacts of control parameters on stability are assessed. The performance of the proposed strategy in a weak system is evaluated. Simulation studies are carried out under various power system contingencies to verify the effectiveness of the proposed strategy and validate the correctness of the theoretical analysis.

A hybrid butterfly algorithm in the optimal economic operation of microgrids.

With the increasing capacity of renewable energy generators, microgrid (MG) systems have experienced rapid development, and the optimal economic operation is one of the most important and challenging issues in the MG field. To reduce the overall generation cost of microgrids, a hybrid butterfly algorithm (HBOA) is proposed to address the optimal economic operation problem in MG systems. This algorithm uses adaptive switching thresholds to balance the global exploration capability and local exploitation capability of the algorithm. It introduces a diversity learning mechanism to enhance information exchange among populations to improve the algorithm's accuracy and proposes an elite-guided guidance strategy to accelerate the convergence speed of the algorithm. Numerical simulation experiments on 10 standard test functions validate that the HBOA algorithm has higher optimization accuracy and faster convergence speed. Simulation experiments are conducted on two operation modes of microgrids: Islanded and grid-connected, and compared with other algorithms. In islanded and grid-connected modes, HBOA can reduce operating costs by up to 11.7% and 17.7%, respectively. The experimental results confirm the applicability and superiority of the proposed algorithm for solving the optimal economic operation problem in microgrids.

A Comprehensive Evaluation of Renewable Energy Systems with a Backup to Provide a Part of Electrical Needs of a Hospital: A Case Study in Grid-connected Mode

A Comprehensive Evaluation of Renewable Energy Systems with a Backup to Provide a Part of Electrical Needs of a Hospital: A Case Study in Grid-connected Mode

Study on frequency stability control strategies for microgrid based on hybrid renewable energy

The dynamic nature of renewable energy sources, such as wind and photovoltaic power generation, significantly impacts the frequency stability of microgrid systems due to their pronounced intermittency, inherent randomness, and limited output support. Despite ongoing research, a comprehensive understanding of control measures to enhance microgrid frequency stability remains lacking. This paper addresses this gap by summarizing domestic and global advancements in control strategies for microgrid frequency stability. Specifically, it examines the operating states of microgrids and associated frequency stability issues and expounds various methods for maintaining frequency stability. The paper proposes innovative control measures to enhance frequency stability, including improvements in master-slave control, droop control, phase-locked loop, and virtual synchronous generator (VSG) techniques, particularly during transitions between islanded and grid-connected modes. The findings demonstrate the effectiveness of these enhanced control strategies in maintaining frequency stability, and the paper concludes by suggesting future research directions in this field.

Simultaneous Voltage and Current Harmonic Control of Grid-Forming Converters Considering Both Islanded and Grid-Connected Modes

Simultaneous Voltage and Current Harmonic Control of Grid-Forming Converters Considering Both Islanded and Grid-Connected Modes