A Summary of Optimal Methods for the Planning of Stand-alone Microgrid System

This paper describes the characteristics and optimal methods for the planning of stand-alone microgrid system, in order to improve the power supply reliability, increase the coefficient of utilization of renewable energy and reduce the cost of investment and operation. Next, the problems in the optimal planning for a stand-alone microgrid system are summarized, including the unique operational control targets, the flexible combination approaches and the operation strategies of distributed generation energy supply system, and the special requirements of the reliability of power supply quality factor from the different users. And then, centering on the operational control and the advanced energy management strategy, the optimal mathematical models and the solving methods, the reliability assessment approaches and the improvement measures of a stand-alone microgrid system, an overview of the general situation of the recent research at home and abroad and the limitations of the study are summarized. Finally, several problems, existing in the optimal planning of stand-alone microgrid system, to be urgently solved, are put forward.

Optimal planning of stand-alone microgrids incorporating reliability

This paper proposes a new method for the planning of stand-alone microgrids.By means of clustering techniques,possible operating scenarios are obtained considering the daily patterns of wind and load profiles.Then,an approximate analytical model for reliability evaluation of battery energy storage system is developed in terms of the diverse scenarios,along with multistate models for wind energy system and diesel generating system.An optimal planning model is further illustrated based on the scenarios and the reliability models,with the objective of minimizing the present values of the costs occurring within the project lifetime,and with the constraints of system operation and reliability.Finally,a typical stand-alone microgrid is studied to verify the efficiency of the proposed method.

开发基于Matlab的Stand-Alone软件

Matlab语言是国际上使用最为广泛的科学与工程计算软件工具,但是由Matlab生成的代码不能脱离Matlab环境运行。如何令Matlab代码能够完全脱离Matlab环境独立运行,对于各专业人员借助Matlab语言快速开发出具备强大计算功能的专业应用软件具有重要的意义。本文在分析了Matlab软件的优缺点的基础上,给出了使包含Matlab代码的应用软件能够脱离Matlab环境运行的具体步骤和方法。

A Case Study to Determine Optimal Capacity of a Stand-Alone Wind/PV/Battery System

In this paper, a stand-alone hybrid microgrid consisting of wind turbines, photovoltaic (PV) arrays and storage battery banks is developed for use in Qinghai Province, China. With the help of Software Homer and Matlab, different variables such as annual average wind speed, annual average load demand, and annual capacity shortage are considered. The net present value is then used during an entire project lifetime for the optimization solution.

Jaya Learning-Based Optimization for Optimal Sizing of Stand-Alone Photovoltaic,Wind Turbine,and Battery Systems

Renewable energy sources(RESs)are considered to be reliable and green electric power generation sources.Photovoltaics(PVs)and wind turbines(WTs)are used to provide electricity in remote areas.Optimal sizing of hybrid RESs is a vital challenge in a stand-alone environment.The meta-heuristic algorithms proposed in the past are dependent on algorithm-specific parameters for achieving an optimal solution.This paper proposes a hybrid algorithm of Jaya and a teaching–learning-based optimization(TLBO)named the JLBO algorithm for the optimal unit sizing of a PV–WT–battery hybrid system to satisfy the consumer’s load at minimal total annual cost(TAC).The reliability of the system is considered by a maximum allowable loss of power supply probability(LPSPmax)concept.The results obtained from the JLBO algorithm are compared with the original Jaya,TLBO,and genetic algorithms.The JLBO results show superior performance in terms of TAC,and the PV–WT–battery hybrid system is found to be the most economical scenario.This system provides a cost-effective solution for all proposed LPSPmax values as compared with PV–battery and WT–battery systems.

Optimal Configuration for Design of Stand-Alone PV System

This paper presents a design for a stand-alone photovoltaic (PV) system to provide the required electricity for a single residential household in rural area in Jordan. The complete design steps for the suggested household loads are carried out. Site radiation data and the electrical load data of a typical household in the considered site are taken into account during the design steps. The reliability of the system is quantified by the loss of load probability. A computer program is developed to simulate the PV system behavior and to numerically find an optimal combination of PV array and battery bank for the design of stand-alone photovoltaic systems in terms of reliability and costs. The program calculates life cycle cost and annualized unit electrical cost. Simulations results showed that a value of loss of load probability LLP can be met by several combinations of PV array and battery storage. The method developed here uniquely determines the optimum configuration that meets the load demand with the minimum cost. The difference between the costs of these combinations is very large. The optimal unit electrical cost of 1 kWh for LLP = 0.049 is $0.293;while for LLP 0.0027 it is $0.402. The results of the study encouraged the use of the PV systems to electrify the remote sites in Jordan.

Stand-alone XLIF治疗退变性脊柱侧凸

目的评估Stand-alone XLIF(即不使用螺钉内固定的单纯极外侧入路椎间融合术)治疗退变性脊柱侧凸(DS)的临床疗效。方法回顾性分析南部战区总医院采用Stand-alone XLIF治疗的15例DS患者的临床资料,其中单节段8例、双节段4例、三节段1例、四节段2例,共27个节段。采用腰椎Oswestry功能障碍指数(ODI)、日本骨科学会(JOA)评分和腰腿痛视觉模拟量表(VAS)评分评估患者的临床疗效;测量术前和末次随访时腰椎冠状面Cobb角和椎间孔高度,观察随访期间植骨融合及并发症发生情况。结果随访时间1~9年,平均随访时间4.2年。末次随访时腰椎ODI、JOA评分和VAS评分均较术前改善(P<0.05),术前、末次随访腰椎冠状面Cobb角和椎间孔高度分别为(28.1±5.8)°、(11.7±3.6)°和(16.3±2.5)、(19.2±2.7)mm,手术前后比较,差异有统计学意义(P<0.05)。术后1年24个节段(89%)获植骨融合,3个节段植骨延迟愈合。术后4例出现腹胀,5例出现腹股沟区一过性麻木或疼痛。随访期间未有内固定松动、感染并发症发生。结论在合理选择适应证的前提下,Stand-alone XLIF具有微创、术后恢复快的优势,可有效治疗DS。

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.

Step-Loading Characteristics of Gas Engine Cogeneration System Using Doubly-Fed Induction Generator in Stand-Alone Operation

Application of a DFIG （doubly-fed induction generator）, which is one of adjustable speed generators, to a gas engine cogeneration system has been investigated. To operate during a blackout as an emergency power supply is one of important roles for the gas engine eogeneration system. In the case of conventional constant speed of synchronous generator, the amount of the allowed step load is limited to around 30% of the rated power. On the other hand, DFIG is expected to increase the amount of step load during the stand-alone operation. In this paper, it has been demonstrated that an increase in the gas engine speed resulted in an increase in the maximum amount of step load using experimental equipment with a real gas engine. It has been concluded that the proposed system can improve the performance of an emergency power supply at step-loading.

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.

Stand-Alone Wind Power System Operating with Different Storage Structures

This paper deals with control method related to a wind system operating in stand-alone applications. The stand-alone wind system is composed of three energy transfer subsystems： wind generator subsystem （wind turbine and electrical generator）, energy storage subsystem, respectively, specific local network subsystem （controlled loads）. This wind power system performs in the same time the maximization of wind energy conversion and the power balance between produced and required power. Three structures of the energy storage subsystem, based on buffer battery operation and/or capacitor voltage control, are discussed. The simulation results show that the proposed stand-alone wind power system ensures a good management of the local energy request. The design of the structures is analyzed in Matlab/Simulink environment, using PowerSim toolbox.

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.