Islanded Microgrid Research Articles

Energy Management of Islanded Micro-Grid with Uncertainties Using Nash Bargaining Solution

Abstract: With the increasing integration of solar PV and wind energy in island micro-grids (MGs), the intermittent nature of non-dispatchable sources and the unpredictability of load demands are unavoidable. As a result, maintaining high reliability and system stability becomes a significant challenge. Additionally, demand-side management technologies and energy storage are commonly implemented in island MGs to mitigate the negative effects of RESs. However, these solutions also introduce uncertainties. Moreover, RESs in MGs are highly susceptible to external environmental factors such as solar radiation, temperature fluctuations, and wind speed variations, making it difficult to ensure system stability, particularly in islanded mode. To address these uncertainties, this paper considers six participant sites and proposes a Cooperative Game Theory (CGT) based on Nash Bargaining Solution (NBC) for collaboration among the participants of MG under the condition of uncertainties introduced by each participant. First energy transaction among the MG participants is modeled. Secondly, CGT using NBS is applied to model the uncertainties in dispatchable and non-dispatchable energy resources of the participants. Moreover, using NBS, a cooperative operation model among MG participants is established, which is transformed into profit maximization in cooperation, ensuring fair profit distribution and improves economic outcomes. The simulation results show that cooperation among all participants leads to an increase in their benefit values. Additionally, the findings suggest that the proposed model demonstrates strong economic performance.

Multi-Timescale Dispatching Method for Industrial Microgrid Considering Electrolytic Aluminum Load Characteristics

In response to the challenges posed by the high proportion of photovoltaic (PV) in electrolytic aluminum (EA) industrial isolated microgrids, such as the low carbon economy problem and the dynamic dispatchability of EA and its combined heat and power (CHP) unit, a multi-timescale optimal dispatching method considering the dynamic temperature characteristics of an aluminum electrolytic cell is proposed for an EA isolated microgrid. Firstly, based on an electrothermal coupling model, the electrolyte dynamic temperature expression of aluminum electrolytic is derived, and the optimal dispatching method of an EA load considering the dynamic temperature characteristics of EA is proposed. Secondly, based on the carbon emission models of CHP units and EA loads, and with the optimization objective of maximizing the operating revenue of industrial isolated microgrids, a day-ahead-intraday multi-timescale optimal dispatching model considering the participation of EA loads in the demand response (DR) for isolated microgrids was established. Finally, numerical results for an industrial isolated microgrid have verified the effectiveness of the proposed method in improving the PV consumption rate and realizing low-carbon and economic operation of industrial islanded microgrids.

An Adaptive Droop and Feedforward Control Based Transient Power Sharing and Decoupling Method for Grid-Forming Inverters in Islanded Microgrids

An Adaptive Droop and Feedforward Control Based Transient Power Sharing and Decoupling Method for Grid-Forming Inverters in Islanded Microgrids

Coordinated control for distributed energy resources in Islanded microgrids with improved frequency regulation capability

Coordinated control for distributed energy resources in Islanded microgrids with improved frequency regulation capability

A Real-time Two-step Multi-objective Planning Framework for Resilience Improvement of Islanded Microgrids based on MPC

A Real-time Two-step Multi-objective Planning Framework for Resilience Improvement of Islanded Microgrids based on MPC

An efficient safety prediction and control strategy using fuzzy neural network architecture search in islanded microgrids

In islanded microgrids, voltage and frequency deviations are critical indicators of system safety. Effectively managing these deviations to achieve a dynamic balance between generation and consumption under load and power fluctuations is essential for maintaining stable system operation. This paper proposes a voltage-frequency control scheme based on an accelerated proportional-integral-derivative (PID) controller, with an adaptive neuro-fuzzy inference system (ANFIS) optimized via neural architecture search (NAS) as a preventive control strategy, tailored to the data distribution characteristics observed in microgrid applications. This approach leverages a hybrid differential evolution and particle swarm optimization (DEPSO) algorithm combined with a novel supernet weight sharing mechanism, enhancing the efficiency of ANFIS architecture search and reducing dependency on expert knowledge. Through dynamic evaluation and control, this method aims to improve the safety and stability of islanded microgrids under load and power disturbances. Simulation results demonstrate that the proposed method shows significant advantages in microgrid safety prediction and control, quickly restoring system stability and ensuring the secure operation of the microgrid in the face of load and power fluctuations.

Forward-thinking frequency management in islanded marine microgrid utilizing heterogeneous source of generation and nonlinear control assisted by energy storage integration

The increasing environmental challenges and global warming concerns have driven a shift towards renewable energy-based power generation, particularly in microgrids. However, marine microgrids face challenges in load-frequency regulation due to renewable energy intermittency, unpredictable load variations, and nonlinear system dynamics. Conventional control strategies often struggle with poor convergence, limited adaptability, and suboptimal frequency stabilization. Addressing these challenges requires an advanced control optimization technique for robust frequency regulation and system stability in dynamic marine environments. This study proposes a Chaotic Chimp-Mountain Gazelle Optimizer (CCMGO) for optimizing fractional-order proportional-integral-derivative (FOPID) controllers, enhancing load-frequency regulation in a multi-source marine microgrid. The system integrates wave energy, wind turbines, solar towers, and photovoltaic energy, along with controlled biogas turbines, micro hydro turbines, and bio-diesel engine generation. To improve frequency stability and grid flexibility, battery energy storage systems, ultra-capacitors, and electric vehicles are incorporated for dynamic compensation. The CCMGO algorithm combines the exploration strength of the mountain gazelle optimizer with solution diversity enhancements from chaotic mapping and chimp optimization algorithm, preventing premature convergence and improving control efficiency. The performance of CCMGO-optimized controllers (PID, PD–PID, FOPI–FOPID, and FOPID) is evaluated under various load conditions, including impulse, ramp, and stochastic disturbances, to test robustness and adaptability. Simulation results demonstrate that CCMGO-based FOPID controllers outperform conventional strategies, achieving lower frequency deviations, faster settling times, and enhanced transient response. These findings establish CCMGO–FOPID as a powerful tool for optimizing control performance in marine microgrids, ensuring greater resilience, stability, and energy efficiency.

Enhanced Power Sharing Control of an Islanded DC Microgrid with Unmatched Line Impedances

Nowadays, the rise of DC loads along with distributed energy resources (DERs) and energy storage systems (ESSs) have led to a growing interest in using direct current (DC) microgrid systems. Conventional droop control methods face significant limitations when applied to parallel-connected distributed generation (DG) units, particularly in achieving balanced power sharing and minimizing voltage deviations. To overcome this issue, an enhanced power sharing control method is proposed in this paper to address load sharing in parallel-connected DG units based DC microgrids, considering unmatched line impedance and load variation. The enhanced control method aims to achieve balanced load power sharing and voltage control through the use of a Luenberger observer to estimate the Point of Common Coupling (PCC) bus voltage and accordingly estimate the voltage deviation. The proposed method compensates for the effects of unmatched line impedances and dynamic load variations, enabling accurate power sharing and precise DC bus voltage regulation. Various scenarios are studied to evaluate the performance of the proposed method under different operating conditions including system and load parameters variations. Finally, the performance of the proposed control method was validated through real-time simulation using OPAL-RT target, and compared with conventional droop control approaches.

Advanced Voltage Stability Assessment in Renewable-Powered Islanded Microgrids Using Machine Learning Models

The assessment of voltage stability within a microgrid is essential to ensure that all buses in the system can maintain the required voltage levels. Recent research has focused on developing modern voltage stability estimation equipment rather than identifying optimal locations for integrating inverter-based resources (IBRs) within the network. This study analyzes and evaluates voltage stability in power systems with increasing levels of IBRs using modal analysis methodologies that consider active power (PV) and reactive power (QV). It examines the impact of load flow when integrating IBRs into the weakest-and strongest-load buses. Additionally, this study introduces a support vector machine (SVM) approach to assessing voltage stability in a microgrid. The results indicate that the proposed SVM approach achieved an optimal accuracy of 95.10%. Using the IEEE 14-bus scheme, the methodology demonstrated the effective and precise determination of the voltage stability category of the system. Furthermore, the analysis was conducted using the modified DES power system. The core contribution of this research lies in evaluating and identifying the locations that are the most and least favorable for integrating IBRs within the simplified DES power system network, utilizing modal analysis for both QV and solar photovoltaics (SPVs). The results of the load flow analysis suggest that integrating IBR is significantly more beneficial in the most substantial bus, as it minimally impacts other load buses assessed as the least reliable bus within the system.

A case study of optimal design and techno-economic analysis of an islanded AC microgrid

Microgrids (MGs) are essential in the distribution system by utilizing widely dispersed generation sources. Due to their economical and environmentally friendly attributes, Islanded AC MGs are commonly used to supply electricity to isolated locations independent of the primary grid. This study focuses on optimizing the configuration of an islanded AC MG to meet the electrical requirements of an international school in the New Administrative Capital, New Cairo, Egypt. Hybrid Optimization of Multiple Energy Resources (HOMER) software is employed to obtain the optimal size of the sources in the MG by minimizing the Levelized Cost of Energy (LCOE) and Total Net Present Cost (TNPC). According to the HOMER simulation results, a 200 kW PV system, a 180-kW wind turbine, a 50 kW FC, a 50 kW electrolyzer, a 50 kg hydrogen tank, a 180 kW DG, and a 686-kWh lead-acid battery form the optimal configuration of the islanded AC MG. The results reveal the contribution of each energy component to meeting the electricity demand, yielding an LCOE of $0.153/kWh and a TNPC of $1,775,300.00. The dynamic performance of the islanded microgrid is examined, introducing a Model Reference Adaptive Control based PI controller (MRAC-PI) to enhance transient response across all operational conditions. A comparative analysis is performed against traditional PI-PSO and PI-WOA controllers under load variations and changing weather conditions. The results indicate that the proposed control strategy effectively maintains system frequency and voltage amid various disturbances, improves dynamic performance, and achieves a balanced power generation and load demand. Additionally, the proposed controller demonstrates superior dynamic response, featuring reduced overshoot, undershoot, ITAE, and settling time compared to the others.

Integration of renewable energy generation and storage systems for emissions reduction in an islanded campus microgrid

Integration of renewable energy generation and storage systems for emissions reduction in an islanded campus microgrid

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

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

Dual-side virtual inertia control for stability enhancement in islanded AC-DC hybrid microgrids

Dual-side virtual inertia control for stability enhancement in islanded AC-DC hybrid microgrids

Multi-objective optimal dispatch of island microgrid considering a novel scheduling resource

Multi-objective optimal dispatch of island microgrid considering a novel scheduling resource

Optimal configuration of islanded microgrid capacity considering energy utilization and power supply reliability

Optimal configuration of islanded microgrid capacity considering energy utilization and power supply reliability

Time-domain protection scheme for inverter-dominated islanded microgrid using low-bandwidth communication channels

Time-domain protection scheme for inverter-dominated islanded microgrid using low-bandwidth communication channels

Accelerated secondary frequency regulation and active power sharing for islanded microgrids with external disturbances: A fully distributed approach

Accelerated secondary frequency regulation and active power sharing for islanded microgrids with external disturbances: A fully distributed approach

Enhanced Stability and Performance of Islanded DC Microgrid Systems Using Optimized Fractional Order Controller and Advanced Energy Management

ABSTRACTThe increasing demand for electrical power is placing heavy pressure on the power system transmission network. To reduce this burden and conversion losses, a distributed generation‐based DC microgrid system is favorable due to its flexibility and reliability. However, traditional control approaches for the power grid are impractical for islanded microgrids, making stability a primary concern. Using a conventional PI controller results in significant deviations in DC bus voltage and prolonged settling times. Additionally, conventional techniques fail to ensure adequate current sharing between the battery and supercapacitor, which are employed to control the DC bus voltage. To address these issues, this study proposes the use of an optimized fractional order PI (FOPI) controller and an efficient energy management algorithm. The FOPI controller regulates processes while meeting constraints, with the control rule generated from minimizing a cost function. A complete mathematical model of the DC microgrid is developed along with the proposed controller to facilitate detailed analyses. The developed energy management system (EMS) ensures energy balance within the microgrid with regulated DC bus voltage and state‐of‐charge (SoC) limits. Comparing the performance of the FOPI controller with that of the conventional PI controller reveals significant improvements: the DC bus voltage deviation is reduced by 63.63%, and the settling time is 16.67% faster during PV variation. During load variation, the maximum DC bus voltage deviation is 2.25 V, and the settling time is 202 ms, which are within acceptable ranges.

A Novel Management Approach for Optimal Operation of Hybrid AC-DC Microgrid in the Presence of Wind and Load Uncertainties

The optimal operation of a hybrid AC-DC microgrid is investigated in this study. The operation of an AC microgrid connected to the main grid and an islanded DC microgrid has been examined under three management approaches. In the first approach, two microgrids are not connected, and the DC microgrid is operated in the islanded mode. In the second and third approaches, AC and DC microgrids are connected. The main difference between these two approaches is the energy management framework. In the second approach, each microgrid has its own management system, while the third approach integrates both into a single energy management system to form an AC-DC microgrid that minimizes overall operational costs. The main goal of the proposed model is to minimize the operating costs of two microgrids over a 24 h period. The investigated AC microgrid includes a microturbine, wind turbine and diesel generator in order to supply the residential load profile, and the DC microgrid includes an energy storage system, fuel cell, wind turbine and solar panel in order to supply the commercial load profile. Simulations are performed first with a wind and load scenario in order to show and compare the optimal points of using the decision variables in three approaches. Finally, in order to prove the effectiveness of the proposed method in the presence of uncertainties, the cost distribution function for the three approaches is presented by means of Monte Carlo simulation. Applying the proposed model results in the following the cost reduction: 67.9% in the DC microgrid, 14.2% in the AC microgrid and 24.4% overall. This reduction is primarily attributed to the microgrid central energy management system, which decreases reliance on the main grid and instead utilizes alternative sources such as fuel cells. Comparing the first and third approaches, the fuel cell’s contribution to supplying microgrid loads increased by 29%, while the main grid’s participation decreased by 26%.

Exponential input‐to‐state stability of load frequency control system of island microgrid with time‐delay under aperiodic intermittent control

AbstractThis paper studies the exponential input‐to‐state stability (ISS) of the island microgrid system with time‐delay under aperiodic intermittent control. The event‐triggered intermittent control (ETIC) is designed to realize the exponential ISS of the system. Under the ETIC, the island microgrid is proved to achieve the exponential ISS. Based on state‐based control width (SCW), an ETIC‐SCW scheme is also proposed by improving the ETIC scheme. The effectiveness of the proposed ETIC scheme is verified by simulation results. It is shown that the designed ETIC, especially the ETIC‐SCW, can achieve not only the exponential ISS but also the lower minimum activation time rate than other control strategies including the time‐triggered intermittent control. Therefore, the island microgrid system with time‐delay may achieve a better balance between economy and stability.