Optimal Cooperative Secondary Control for Islanded DC Microgrids via a Fully Actuated Approach

DC-DC converter-based multi-bus DC microgrids(MGs) in series have received much attention, where the conflict between voltage recovery and current balancing has been a hot topic. The lack of models that accurately portray the electrical characteristics of actual MGs while is controller design-friendly has kept the issue active. To this end, this paper establishes a large-signal model containing the comprehensive dynamical behavior of the DC MGs based on the theory of high-order fully actuated systems, and proposes distributed optimal control based on this. The proposed secondary control method can achieve the two goals of voltage recovery and current sharing for multi-bus DC MGs. Additionally, the simple structure of the proposed approach is similar to one based on droop control, which allows this control technique to be easily implemented in a variety of modern microgrids with different configurations. In contrast to existing studies, the process of controller design in this paper is closely tied to the actual dynamics of the MGs. It is a prominent feature that enables engineers to customize the performance metrics of the system. In addition, the analysis of the stability of the closed-loop DC microgrid system, as well as the optimality and consensus of current sharing are given. Finally, a scaled-down solar and battery-based microgrid prototype with maximum power point tracking controller is developed in the laboratory to experimentally test the efficacy of the proposed control method.

Enhancing microgrid renewable energy integration at SEKEM farm

This study explores the feasibility of implementing a hybrid microgrid system powered by renewable energy sources.Including solar photovoltaics,wind energy,and fuel cells to ensure a reliable and sustainable electricity supply for the SEKEM farm in WAHAT,Egypt.The study utilizes MATLAB/Simulink software to conduct simulations based on sun irradiation and wind speed data.Various control techniques,such as the proportional-integral(PI)controller,Fuzzy Logic Controller for PI tuning(fuzzy-PI),and neuro-fuzzy controllers,were evaluated to improve the performance of the microgrid.The results demonstrate that the Fuzzy-PI control strategy outperforms the alternative control systems,enhancing the overall dependability and long-term viability of energy provision.The hybrid system was integrated with a voltage source control(VSC)and fuzzy PI controller,which effectively addressed power fluctuations and improved the stability and reliability of the energy supply.Furthermore,it provides insightful information on how to design and implement a 100%renewable energy system,with the fuzzy PI controller emerging as a viable method of control that can guarantee the system’s resilience and outperform other approaches,such as the standalone PI controller and the neuro-fuzzy controller.

Optimal day-ahead scheduling strategy of microgrid considering regional pollution and potential load curtailment

With the frequent occurrence of global warming and extreme severe weather,the transition of energy to cleaner,and with lower carbon has gradually become a consensus.Microgrids can integrate multiple energy sources and consume renewable energy locally.The amount of pollutants emitted during the operation of the microgrids become an important issue to be considered.This study proposes an optimal day-ahead scheduling strategy of microgrid considering regional pollution and potential load curtailment.First,considering the operating characteristics of microgrids in islanded and grid-connected operation modes,this study proposes a regional pollution index(RPI)to quantify the impact of pollutants emitted from microgrid on the environment,and further proposes a penalty mechanism based on the RPI to reduce the microgrid’s utilization on non-clean power supplies.Second,considering the benefits of microgrid as the operating entity,utilizing a direct load control(DLC)enables microgrid to enhance power transfer capabilities to the grid under the penalty mechanism based on RPI.Finally,an optimal day-ahead scheduling strategy which considers both the load curtailment potential of curtailable loads and RPI is proposed,and the results show that the proposed optimal day-ahead scheduling strategy can effectively inspire the curtailment potential of curtailable loads in the microgrid,reducing pollutant emissions from the microgrid.

Adaptive VSG control of flywheel energy storage array for frequency support in microgrids

The application of virtual synchronous generator(VSG)control in flywheel energy storage systems(FESS)is an effective solution for addressing the challenges related to reduced inertia and inadequate power supply in microgrids.Considering the significant variations among individual units within a flywheel array and the poor frequency regulation performance under conventional control approaches,this paper proposes an adaptive VSG control strategy for a flywheel energy storage array(FESA).First,by leveraging the FESA model,a variable acceleration factor is integrated into the speed-balance control strategy to effectively achieve better state of charge(SOC)equalization across units.Furthermore,energy control with a dead zone is introduced to prevent SOC of the FESA from exceeding the limit.The dead zone parameter is designed based on the SOC warning intervals of the flywheel array to mitigate its impact on regular operation.In addition,VSG technology is applied for the grid-connected control of the FESA,and the damping characteristic of the VSG is decoupled from the primary frequency regulation through power differential feedback.This ensures optimal dynamic performance while reducing the need for frequent involvement in frequency regulation.Subsequently,a parameter design method is developed through a small-signal stability analysis.Consequently,considering the SOC of the FESA,an adaptive control strategy for the inertia damping and the P/ωdroop coefficient of the VSG control is proposed to optimize the grid support services of the FESA.Finally,the effectiveness of the proposed control methods is demonstrated through electromagnetic transient simulations using MATLAB/Simulink.

Research on the Stability Analysis Method of DC Microgrid Based on Bifurcation and Strobe Theory

During the operation of a DC microgrid,the nonlinearity and low damping characteristics of the DC bus make it prone to oscillatory instability.In this paper,we first establish a discrete nonlinear system dynamic model of a DC microgrid,study the effects of the converter sag coefficient,input voltage,and load resistance on the microgrid stability,and reveal the oscillation mechanism of a DC microgrid caused by a single source.Then,a DC microgrid stability analysis method based on the combination of bifurcation and strobe is used to analyze how the aforementioned parameters influence the oscillation characteristics of the system.Finally,the stability region of the system is obtained by the Jacobi matrix eigenvalue method.Grid simulation verifies the feasibility and effectiveness of the proposed method.

Flexible linear clock-based distributed self-triggered active power-sharing secondary control of AC microgrids

Traditional active power sharing in microgrids,achieved by the distributed average consensus,requires each controller to continuously trigger and communicate with each other,which is a wasteful use of the limited computation and communication resources of the secondary controller.To enhance the efficiency of secondary control,we developed a novel distributed self-triggered active power-sharing control strategy by introducing the signum function and a flexible linear clock.Unlike continuous communication–based controllers,the proposed self-triggered distributed controller prompts distributed generators to perform control actions and share information with their neighbors only at specific time instants monitored by the linear clock.Therefore,this approach results in a significant reduction in both the computation and communication requirements.Moreover,this design naturally avoids Zeno behavior.Furthermore,a modified triggering condition was established to achieve further reductions in computation and communication.The simulation results confirmed that the proposed control scheme achieves distributed active power sharing with very few controller triggers,thereby substantially enhancing the efficacy of secondary control in MGs.

A digital twin model-based approach to cost optimization of residential community microgrids

This paper presents a peer-to-peer community cost optimization approach based on a single-prosumer energy management system.Its objective is to optimize energy costs for prosumers in the community by enhancing the consumption efficiency.This study was conducted along two main axes.The first axis focuses on designing a digital twin for a residential community microgrid platform.This phase involves data collection,cleaning,exploration,and interpretation.Moreover,it includes replicating the functionality of the real platform and validating the results.The second axis involves the development of a novel approach that incorporates two distinct prosumer behaviors within the same community microgrid,while maintaining the concept of peer-to-peer energy trading.Prosumers without storage utilize their individual PV systems to fulfill their energy requirements and inject excess energy into a local microgrid.Meanwhile,a single prosumer with a storage system actively engages in energy exchange to maximize the community’s profit.This is achieved by optimizing battery usage using a cost optimization solution.The proposed solution is validated using the developed digital twin.

Optimal hydrogen-battery energy storage system operation in microgrid with zero-carbon emission

To meet the greenhouse gas reduction targets and address the uncertainty introduced by the surging penetration of stochastic renewable energy sources,energy storage systems are being deployed in microgrids.Relying solely on short-term uncertainty forecasts can result in substantial costs when making dispatch decisions for a storage system over an entire day.To mitigate this challenge,an adaptive robust optimization approach tailored for a hybrid hydrogen battery energy storage system(HBESS)operating within a microgrid is proposed,with a focus on efficient state-of-charge(SoC)planning to minimize microgrid expenses.The SoC ranges of the battery energy storage(BES)are determined in the day-ahead stage.Concurrently,the power generated by fuel cells and consumed by electrolysis device are optimized.This is followed by the intraday stage,where BES dispatch decisions are made within a predetermined SoC range to accommodate the uncertainties realized.To address this uncertainty and solve the adaptive optimization problem with integer recourse variables in the intraday stage,we proposed an outer-inner column-and-constraint generation algorithm(outer-inner-CCG).Numerical analyses underscored the high effectiveness and efficiency of the proposed adaptive robust operation model in making decisions for HBESS dispatch.

Exponential stabilization of linear systems with feedback optimization and its application to microgrids control

This paper proposes a feedback-optimization-based control method for linear time-invariant systems,which is aimed to exponentially stabilize the system and,meanwhile,drive the system output to an approximate solution of an optimization problem with convex set constraints and affine inequality constraints.To ensure the exponential stability of the closed-loop system,the original optimization problem is first reformulated into a counterpart that has only convex set constraints.It is shown that the optimal solution of the new optimization problem is an approximate optimal solution of the original problem.Then,based on this new optimization problem,the projected primal–dual gradient dynamics algorithm is used to design the controller.By using the singular perturbation method,sufficient conditions are provided to ensure the exponential stability of the closed-loop system.The proposed method is also applied to microgrid control.

Prediction and scheduling of multi-energy microgrid based on BiGRU self-attention mechanism and LQPSO

To predict renewable energy sources such as solar power in microgrids more accurately,a hybrid power prediction method is presented in this paper.First,the self-attention mechanism is introduced based on a bidirectional gated recurrent neural network(BiGRU)to explore the time-series characteristics of solar power output and consider the influence of different time nodes on the prediction results.Subsequently,an improved quantum particle swarm optimization(QPSO)algorithm is proposed to optimize the hyperparameters of the combined prediction model.The final proposed LQPSO-BiGRU-self-attention hybrid model can predict solar power more effectively.In addition,considering the coordinated utilization of various energy sources such as electricity,hydrogen,and renewable energy,a multi-objective optimization model that considers both economic and environmental costs was constructed.A two-stage adaptive multi-objective quantum particle swarm optimization algorithm aided by a Lévy flight,named MO-LQPSO,was proposed for the comprehensive optimal scheduling of a multi-energy microgrid system.This algorithm effectively balances the global and local search capabilities and enhances the solution of complex nonlinear problems.The effectiveness and superiority of the proposed scheme are verified through comparative simulations.

Heuristic-Based Optimal Load Frequency Control with Offsite Backup Controllers in Interconnected Microgrids

The primary factor contributing to frequency instability in microgrids is the inherent intermittency of renewable energy sources.This paper introduces novel dual-backup controllers utilizing advanced fractional order proportional integral derivative(FOPID)controllers to enhance frequency and tie-line power stability in microgrids amid increasing renewable energy integration.To improve load frequency control,the proposed controllers are applied to a two-area interconnectedmicrogrid system incorporating diverse energy sources,such as wind turbines,photovoltaic cells,diesel generators,and various storage technologies.A novelmeta-heuristic algorithm is adopted to select the optimal parameters of the proposed controllers.The efficacy of the advanced FOPID controllers is demonstrated through comparative analyses against traditional proportional integral derivative(PID)and FOPID controllers,showcasing superior performance inmanaging systemfluctuations.The optimization algorithm is also evaluated against other artificial intelligent methods for parameter optimization,affirming the proposed solution’s efficiency.The robustness of the intelligent controllers against system uncertainties is further validated under extensive power disturbances,proving their capability to maintain grid stability.The dual-controller configuration ensures redundancy,allowing them to operate as mutual backups,enhancing system reliability.This research underlines the importance of sophisticated control strategies for future-proofing microgrid operations against the backdrop of evolving energy landscapes.

DC microgrid stability control with constant power load:a review

The DC microgrid has the advantages of high energy conversion efficiency,high energy transmission density,no reactive power flow,and grid-connected synchronization.It is an essential component of the future intelligent power distribution system.Constant power load(CPL)will degrade the stability of the DC microgrid and cause system voltage oscillation due to its negative resistance characteristics.As a result,the stability of DC microgrids with CPL has become a problem.At present,the research on the stability of DC microgrid is mainly focused on unipolar DC microgrid,while the research on bipolar DC microgrid lacks systematic discussion.The stability of DC microgrid using CPL was studied first,and then the current stability criteria of DC microgrid were summarized,and its research trend was analyzed.On this basis,aiming at the stability problem caused by CPL,the existing control methods were summarized from the perspective of source converter output impedance and load converter input impedance,and the current control methods were outlined as active and passive control methods.Lastly,the research path of bipolar DC microgrid stability with CPL was prospected.

Frequency Regulation of Alternating Current Microgrid Based on Hierarchical Control Using Fuzzy Logic

An alternating current(AC)microgrid is a system that integrates renewable power,power converters,controllers and loads.Hierarchical control can manage the frequency of the microgrid to prevent imbalance and collapse of the system.The existing frequency control methods use traditional proportion integration(PI)controllers,which cannot adjust PI parameters in real-time to respond to the status changes of the system.Hierarchical control driven by fuzzy logic allows real-time adjustment of the PI parameters and the method used a two-layer control structure.The primary control used droop control to adjust power distribution,and fuzzy logic was used in the voltage loop of the primary control.The secondary control was added to make up for frequency deviation caused by droop control,and fuzzy logic was used in the secondary frequency control to deal with the dynamic change of frequency caused by the disturbances of loads.The proposed method was simulated in Matlab/Simulink.In the primary control,the proposed method reduced the total harmonic distortion(THD)of two cycles of the output voltage from 4.19%to 3.89%;in the secondary control,the proposed method reduced the frequency fluctuation of the system by about 0.03 Hz and 0.04 Hz when the load was increased and decreased,respectively.The results show that the proposed methods have a better effect on frequency maintenance and voltage control of the AC microgrid.

Automatic SOC Equalization Strategy of Energy Storage Units with DC Microgrid Bus Voltage Support

In this paper,an improved sag control strategy based on automatic SOC equalization is proposed to solve the problems of slow SOC equalization and excessive bus voltage fluctuation amplitude and offset caused by load and PV power variations in a stand-alone DC microgrid.The strategy includes primary and secondary control.Among them,the primary control suppresses the DC microgrid voltage fluctuation through the I and II section control,and the secondary control aims to correct the P-U curve of the energy storage system and the PV system,thus reducing the steady-state bus voltage excursion.The simulation results demonstrate that the proposed control strategy effectively achieves SOC balancing and enhances the immunity of bus voltage.The proposed strategy improves the voltage fluctuation suppression ability by approximately 39.4%and 43.1%under the PV power and load power fluctuation conditions,respectively.Furthermore,the steady-state deviation of the bus voltage,△U_(dc) is only 0.01–0.1 V,ensuring stable operation of the DC microgrid in fluctuating power environments.

Resilience-assuring hydrogen-powered microgrids

Green hydrogen has shown great potential to power microgrids as a primary source,whereas the resilient operation methodology under extreme events remains an open area.To fill this gap,this letter establishes an operational optimization strategy towards resilient hydrogen-powered microgrids.The frequency and voltage regulation characteristics of primary hydrogen sources under droop control and their electrical-chemical conversion process with nonlinear stack efficiency are accurately modeled by piecewise linear constraints.A resilience-oriented multi-time-slot stochastic optimization model is then formulated for an economic and robust operation under changing uncertainties.Test results show that the new formulation can leverage the primary hydrogen sources to achieve a resilience and safety-assured operation plan,supplying maximum critical loads while significantly reducing the frequency and voltage variations.

微网(Microgrid)的并网运行方式探讨

介绍了微网的产生背景和定义,分析了微网并网运行的意义,提出了微网并网连接的三种方式:直接交流连接、经电流源换流器(CSC)连接、经电压源换流器(VSC)的微网并网连接。对比三种并网方式的优缺点,得出利用电压源换流器VSC并网有优势。

基于自适应变异粒子群算法的风光储微网调度

为克服传统粒子群算法在求解时容易形成局部最优,求解精度低的不足,提出了一种基于自适应变异粒子群优化的微电网调度求解方法。惯性权重采用自适应正态分布递减,随着迭代次数的增加更新粒子位置的移动策略,并且在算法后期引入变异环节。为验证算法的有效性,文章与其他算法进行收敛性能对比,并对两种典型天气情况下的微网运行成本模型仿真求解,得到最优调度。算例结果表明,改进算法能够对粒子全局最优搜索优化,效果优于其他算法,可合理调配分布式电源出力时段,具有良好的可行性。

Distributed Virtual Inertia Based Control of Multiple Photovoltaic Systems in Autonomous Microgrid

The large inertia of a traditional power system slows down system's frequency response but also allows decent time for controlling the system.Since an autonomous renewable microgrid usually has much smaller inertia,the control system must be very fast and accurate to fight against the small inertia and uncertainties.To reduce the demanding requirements on control,this paper proposes to increase the inertia of photovoltaic(PV) system through inertia emulation.The inertia emulation is realized by controlling the charging/discharging of the direct current(DC)-link capacitor over a certain range and adjusting the PV generation when it is feasible and/or necessary.By well designing the inertia,the DC-link capacitor parameters and the control range,the negative impact of inertia emulation on energy efficiency can be reduced.The proposed algorithm can be integrated with distributed generation setting algorithms to improve dynamic performance and lower implementation requirements.Simulation studies demonstrate the effectiveness of the proposed solution.

Distributed Control of Multiple-Bus Microgrid With Paralleled Distributed Generators

A microgrid is hard to control due to its reduced inertia and increased uncertainties. To overcome the challenges of microgrid control, advanced controllers need to be developed.In this paper, a distributed, two-level, communication-economic control scheme is presented for multiple-bus microgrids with each bus having multiple distributed generators(DGs) connected in parallel. The control objective of the upper level is to calculate the voltage references for one-bus subsystems. The objectives of the lower control level are to make the subsystems' bus voltages track the voltage references and to enhance load current sharing accuracy among the local DGs. Firstly, a distributed consensusbased power sharing algorithm is introduced to determine the power generations of the subsystems. Secondly, a discrete-time droop equation is used to adjust subsystem frequencies for voltage reference calculations. Finally, a Lyapunov-based decentralized control algorithm is designed for bus voltage regulation and proportional load current sharing. Extensive simulation studies with microgrid models of different levels of detail are performed to demonstrate the merits of the proposed control scheme.

Reliability Assessment of Microgrid Using Sequential Monte Carlo Simulation

Sequential Monte Carlo simulation method is introduced to the reliability assessment of microgrid,and a Weibull distribution wind speed model is built to simulate the hourly wind speed of a specific site.Wind turbine generator model combined with a two-state reliability model is applied to Monte Carlo simulation method,and results show that the wind turbine reliability model works well with sequential Monte Carlo simulation.A two-state reliability model of micro gas turbine and a load model from IEEE reliability test system （IEEE RTS） are also introduced to the reliability evaluation of microgrid.Case studies show that Monte Carlo simulation method is flexible and efficient dealing with microgrid consisting of renewable resources with fluctuation characteristics.