A Novel Self Adaptive Modification Approach Based on Bat Algorithm for Optimal Management of Renewable MG

In the new competitive electricity market, the accurate operation management of Micro-Grid (MG) with various types of renewable power sources (RES) can be an effective approach to supply the electrical consumers more reliably and economically. In this regard, this paper proposes a novel solution methodology based on bat algorithm to solve the op- timal energy management of MG including several RESs with the back-up of Fuel Cell (FC), Wind Turbine (WT), Photovoltaics (PV), Micro Turbine (MT) as well as storage devices to meet the energy mismatch. The problem is formulated as a nonlinear constraint optimization problem to minimize the total cost of the grid and RESs, simultaneously. In addition, the problem considers the interactive effects of MG and utility in a 24 hour time interval which would in- crease the complexity of the problem from the optimization point of view more severely. The proposed optimization technique is consisted of a self adaptive modification method compromised of two modification methods based on bat algorithm to explore the total search space globally. The superiority of the proposed method over the other well-known algorithms is demonstrated through a typical renewable MG as the test system.

Autonomous Multi-Factor Energy Flows Controller (AmEFC): Enhancing Renewable Energy Management with Intelligent Control Systems Integration

The transition to sustainable energy systems is one of the defining challenges of our time, necessitating innovations in how we generate, distribute, and manage electrical power. Micro-grids, as localized energy hubs, have emerged as a promising solution to integrate renewable energy sources, ensure energy security, and improve system resilience. The Autonomous multi-factor Energy Flow Controller (AmEFC) introduced in this paper addresses this need by offering a scalable, adaptable, and resilient framework for energy management within an on-grid micro-grid context. The urgency for such a system is predicated on the increasing volatility and unpredictability in energy landscapes, including fluctuating renewable outputs and changing load demands. To tackle these challenges, the AmEFC prototype incorporates a novel hierarchical control structure that leverages Renewable Energy Sources (RES), such as photovoltaic systems, wind turbines, and hydro pumps, alongside a sophisticated Battery Management System (BMS). Its prime objective is to maintain an uninterrupted power supply to critical loads, efficiently balance energy surplus through hydraulic storage, and ensure robust interaction with the main grid. A comprehensive Simulink model is developed to validate the functionality of the AmEFC, simulating real-world conditions and dynamic interactions among the components. The model assesses the system’s reliability in consistently powering critical loads and its efficacy in managing surplus energy. The inclusion of advanced predictive algorithms enables the AmEFC to anticipate energy production and consumption trends, integrating weather forecasting and inter-controller communication to optimize energy flow within and across micro-grids. This study’s significance lies in its potential to facilitate the seamless incorporation of RES into existing power systems, thus propelling the energy sector towards a more sustainable, autonomous, and resilient future. The results underscore the potential of such a system to revolutionize energy management practices and highlight the importance of smart controller systems in the era of smart grids.

Distributed Economic MPC for Synergetic Regulation of the Voltage of an Island DC Micro-Grid

In this paper,distributed model predictive control(DMPC) for island DC micro-grids(MG) with wind/photovoltaic(PV)/battery power is proposed,which coordinates all distributed generations(DG) to stabilize the bus voltage together with the insurance of having computational efficiency under a real-time requirement.Based on the feedback of the bus voltage,the deviation of the current is dispatched to each DG according to cost over the prediction horizon.Moreover,to avoid the excessive fluctuation of the battery power,both the discharge-charge switching times and costs are considered in the model predictive control(MPC) optimization problems.A Lyapunov constraint with a time-varying steady-state is designed in each local MPC to guarantee the stabilization of the entire system.The voltage stabilization of the MG is achieved by this strategy with the cooperation of DGs.The numeric results of applying the proposed method to a MG of the Shanghai Power Supply Company shows the effectiveness of the distributed economic MPC.

Micro-Grid Planning with Aggregator’s Role in the Renewable Inclusive Prosumer Market

The paper proposes a model for a micro-grid architecture incorporating the role of aggregators and renewable sources on the prosumer side, working together to optimize configurations and operations. The final model takes the form of a mixed-integer linear programming model. This model is solved using the CPLEX solver via GAMS by having a consistent data set.

考虑可再生能源接入的微电网多目标优化配置研究

由于可再生能源和负荷需求的随机性会对微电网的稳定性造成冲击,因此对微电网的优化配置显得至关重要。文章将微电网的运营成本和投资成本相结合作为配置优化的多目标函数,以降低系统总成本和碳排放为目标,对微电网中的可再生能源数量进行优化配置。问题采用遗传算法(GA)对多目标函数进行优化,以得到最优的可再生能源配置数量。以1个典型的交直流混合微电网为例,对其各分布式电源的接入数量进行优化,结果表明优化配置后的微电网总成本和碳排放量得到了有效降低,验证了优化配置方法的有效性。

Control System Development and Test for the Operation of a Micro-Grid System—PART I

This paper presents design, analysis and simulation performance of an active power controller for stable and reliable operation of a micro-grid system. Power balance between generation and consumer is a critical issue for stable and reliable operation of the micro-grid systems. This issue becomes more critical when a micro-grid system contains stochastic nature distributed generations such as wind and solar because their output power changes non-uniformly. In order to achieve accurate and fast power balance in such a micro-grid system, power in the system has to be regulated continuously. Such an objective can be achieved using droop based alternating current control technique. Because the droop characteristic employed into the developed controller initiates determining the power deviation in the system which is continuously regulated by controlling the current flow into dump power resistors. The designed controller is simulated for the operation of a micro-grid system in stand-alone mode under various operating conditions. The simulated results show the ability of the developed controller for stable and reliable operation of the micro-grid that contains renewable sources. The experimental development of the micro-grid system and the testing of the developed active power controller are presented in PART II of this paper.

Intelligent Fuzzy Based High Gain Non-Isolated Converter for DC Micro-Grids

Renewable electricity options, such as fuel cells, solar photovoltaic,and batteries, are being integrated, which has made DC micro-grids famous.For DC micro-grid systems, a multi input interleaved non-isolated dc-dcconverter is suggested by the use of coupled inductor techniques. Since itcompensates for mismatches in photovoltaic devices and allows for separateand continuous power flow from these sources. The proposed converter hasthe benefits of high gain, a low ripple in the output voltage, minimal stressvoltage across the power semiconductor devices, a low ripple in inductorcurrent, high power density, and high efficiency. Soft-switching techniquesare used to realize that the reverse recovery issue of the diodes is moderated, the leakage energy is reused, and no new scheme is appropriated. Toreduce conduction losses, minimum voltage rating MOSFETs with a low ONresistance can be utilized. The converter can supply the required power fromthe load in the absence of one or two resources. Furthermore, due to the highgain of boosting voltage, the converter works in an Adaptive Neuro-FuzzyInference System (ANFIS). The operation principle, steady-state analysis ofthe proposed converter, is given and simulated utilizing MATLAB/Simulinksimulation software.

Trends and Overview Regarding the Involvement of Micro-Grids in Modern Power Systems

Customer satisfaction and participation in utility supply packages is the first and foremost factor in the success of any supplying agency whether wholesale or retail dealer. The paper presents the concept of major prospects of non- autonomous micro-grids installed in a certain locality. The article shows the basic background that is required for the installment of micro grid in a particular area and discusses the primary factors or pre-requisites that are required for the existence and operation of micro-grids. It elaborate the major profitable applications and benefits that developing and developed states get by using micro-grids in an area where utility grid is already functioning .It also explains the basic improvement in the quality of supply from micro grid after its installment. It also throws light on afterwards impact on society with this system, such impacts include reliability, tariff rates, economics etc. The article discusses micro-grids as the future of modern power systems. This paper shows significance of modernization by latest topologies in power systems and its effect that will come afterwards.

Control System Development and Test for the Operation of a Micro-Grid System—PART II

This paper presents experimental development and performance testing of an active power controller for stable and reliable operation of a micro-grid system. In order to achieve accurate and fast power balance in a micro-grid system that contains renewable energy sources, power in the system has to be regulated continuously. Such an objective can be achieved using droop based alternating current control technique. Because the droop characteristic employed into the developed controller initiates to determine the power deviation in the system which is continuously regulated by controlling the current flow into dump power resistors. The designed controller is tested and validated using a micro-grid prototype in the laboratory environment for stand-alone mode of operation under various operating conditions. The key development in the micro-grid prototype is the development of a wind turbine simulator. A dSPACE ds1104 DSP board is used to implement and interface the designed controller with the micro-grid system. The experimental investigation of the developed controller presents the significant capability to achieve continuous power balance in the micro-grid system, while it maintains stable and reliable operation of the system. Finally, the power quality of the isolated micro-grid system is presented and discussed under the operation of the developed controller.

Dynamic scheduling of market price-based combined heat–power-constrained renewable microgrid

In this paper,a market price-based combined heat–power dynamic dispatch model for a microgrid is presented.The microgrid comprises cogeneration units and wind and solar power-generation units.A battery and a heat storage tank are incorporated to optimally balance variations in heat-and-power load demands.The proposed model explores the impact of market prices of electricity,heat supply and load variability on the optimal schedule such that profit maximizes and emission,loss and waste heat are minimized.The Weibull probability distribution function is applied to characterize the uncertain renewable power variable in the model and to find the over-and under-scheduling costs.The problem is solved using an improved differential evolution algorithm in which a fuzzy membership module is appended to obtain a solution having the highest attainment for the selected multiple objectives.The results show that the proposed model can handle uncertain heat–power demand and price scenarios to produce feasible and optimal schedules with owner profits,heat utilization and renewable share varying between 10.55–115.97%,72.51–90.39%and 26.82–38.05%,respectively.

Economic benefit evaluation method for the micro-grid renewable energy system operation

The development of micro-grid renewable energy system in China has achieved rapid growth in recent years,and the micro-grid renewable energy system has been drawing more and more attention by its flexible operation.Due to the randomness,fluctuation,uncertainty of the wind and photovoltaic renewable generation,abundant flexibility is required to meet the needs of safe,reliable and independent operation of the micro-grid energy system.We need to connect large energy systems to accept outside assistance when the micro-grid renewable energy system is short of adjustment capability.Independent operation and network operation will affect the economic benefit of the micro-grid energy system,so it is practically meaningful to study on the economic benefit evaluation of the micro-grid renewable energy system.This paper proposes a micro-grid energy system operation simulation model about wind and photovoltaic generation,the uncertainty of which is tackled based on the scenario generation and extraction techniques.Based on the proposed indices,the economic benefit could be evaluated by simulating the micro-grid energy system operation.The proposed method is validated by a real micro-grid energy system.

Energy Management for a Residential Microgrid Using Wavelet Transform and Fuzzy Control Including a Vehicle-to-Grid System

This paper presents the design and implementation of an energy management system(EMS) with wavelet transform and fuzzy control for a residential micro-grid. The hybrid system in this paper consists of a wind turbine generator,photovoltaic(PV) panels,an electric vehicle(EV),and a super capacitor(SC),which is able to connect or disconnect to the main grid. The control strategy is responsible for compensating the difference between the generated power by the wind and solar generators and the demanded power by the loads. Wavelet transform decomposes the power difference into a smoothed component and a fast fluctuated component. The command approach used for fuzzy logic rules considers the state of charging(SOC) of EV,renewable production,and the load demand as parameters. Furthermore,the command rules are developed in order to ensure a reliable grid when taking into account the EV battery protection to decide the output power of the EV. The model of the hybrid system is developed in detail under Matlab/Simulink software environment.

考虑EV负荷的微电网多主体联合容量优化配置方法

随着可再生能源(RE)的快速发展与智能电网的不断进步,现代电力系统的能耗特性设计朝着更灵活、更经济的微电网(MG)快速转变,MG多主体综合能源的高度参与给系统的高效经济运行带来了挑战。针对MG多能交互的复杂容量配置现状,文中提出一种包含光伏(PV),风电(WT),柴油发电机(DG)和电池储能系统(BESS)的独立MG联合容量优化方法。建立PV、WT、DG、BESS和电动汽车(EV)充电负荷模型,考虑了EV充电负荷,以最小化成本、减少温室气体排放、减少弃能为目标进行容量配置,结果表明提出的PV-WT-BESS-DG组合结构不仅经济而且可靠性高,温室气体排放量小。研究结果可为MG容量优化配置提供有力支撑。

考虑需求响应的综合能源虚拟电厂多级管理模型

电力系统资产协同运行面临严峻挑战,微电网与虚拟电厂可解决一些实际问题。针对不确定性会增加运行成本问题,提出同时调度微电网和虚拟电厂能源的分层模型。该模型是一种虚拟发电厂和微电网同时调度的三阶段随机模型。考虑到可再生能源发电和负荷需求的不确定性,模型包含协调和不协调两种运行方式。另外,在调度模型中分析了相邻微电网之间进行功率交换的可能性,从而防止了不真实功率变化。通过算例验证电网协调运行可以降低负荷供应成本,同时分时定价机制可为微电网较提供较实时定价和尖峰定价更高的利润。

A Multi-Agent Framework for Operation of a Smart Grid

This paper presents the operation of a Multi-agent system (MAS) for the control of a smart grid. The proposed Multi-agent system consists of seven types of agents: Single Smart Grid Controller (SGC), Load Agents (LAGs), a Wind Turbine Agent (WTAG), Photo-Voltaic Agents (PVAGs), a Micro-Hydro Turbine Agent (MHTAG), Diesel Agents (DGAGs) and a Battery Agent (BAG). In a smart grid LAGs act as consumers or buyers, WTAG, PVAGs, MHTAG & DGAGs acts as producers or sellers and BAG act as producer/consumer or seller/buyer. The paper demonstrates the use of a Multi-agent system to control the smart grid in a simulated environment. In order to validate the performance of the proposed system, it has been applied to a simple model system with different time zone i.e. day time and night time and when power is available from the grid and when there is power shedding. Simulation results show that the proposed Multi-agent system can perform the operation of the smart grid efficiently.

Bi-Level Energy Management Model of Grid-Connected Microgrid Community

As the proportion of renewable energy power generation continues to increase,the number of grid-connected microgrids is gradually increasing,and geographically adjacent microgrids can be interconnected to form a Micro-Grid Community(MGC).In order to reduce the operation and maintenance costs of a single micro grid and reduce the adverse effects caused by unnecessary energy interaction between the micro grid and the main grid while improving the overall economic benefits of the micro grid community,this paper proposes a bi-level energy management model with the optimization goal of maximizing the social welfare of the micro grid community and minimizing the total electricity cost of a single micro grid.The lower-level model optimizes the output of each equipment unit in the system and the exchange power between the system and the external grid with the goal of minimizing the operating cost of each microgrid.The upper-level model optimizes the goal ofmaximizing the socialwelfare of themicrogrid.Taking amicrogrid community with four microgrids as an example,the simulation analysis shows that the proposed optimization model is beneficial to reduce the operating cost of a single microgrid,improve the overall revenue of the microgrid community,and reduce the power interaction pressure on the main grid.

Demand and Response in Smart Grids for Modern Power System

Micro-grid plays a vital role in fulfilling the increasing demand by using distributed renewable energy resources. Demand and response technique can be broadly classified under the setup DR deployed (e.g. ISO’s/RTO’s). Demand response program can be implemented to improve power system quality, reliability and increasing demand. In modern power industry, strategic player can take more benefit from more emphasized DR study in terms of social benefit (uninterrupted power supply to consumers) and economy. This paper proposes the distributed micro-grid control and implemented control setup implemented demand response algorithm, which provides better power system reliability. This paper presents contingencies control demand and response for micro-grid. The main advantage of implementation of demand and response algorithms in Micro-grids provides reliable power supplies to consumers. The proposed micro-grid TCP/IP setup provides a chance to respond the contingencies to recover the shed to active condition. Micro-grid controller implements demand and response algorithm reasonable for managing the demand of the load and intelligent load scheme in case of blackout.

μPMU-based smart adaptive protection scheme for microgrids

The concepts of microgrids(MGs)and smart grid represent the recent targeted revolution towards fully smart electrical network integrated with high penetration of renewable energy sources(RESs).The protection system of MGs becomes a challenge due to variable characteristics of its currents,bidirectional power flow and output power fluctuations of RES,causing selectivity and sensitivity issues for conventional protective devices(PDs)with fixed setting.In this paper,a smart protection scheme(SPS)is proposed using micro-phasor measurement units(μPMUs)to obtain the continuous rapid synchronized phasor measurement data.And it is communicated with a microgrid central controller(MGCC)through highly reliable communication architecture to carry out online smart adaptive protection scheme.Fault index coefficients and abnormality coefficients are calculated for each feeder to detect the fault location and the abnormality case.Detailed modeling of an MG including 10-bus connected distribution system with integrated distributed generation(DG)is simulated using ETAP software.The proposed protection algorithm is modeled and evaluated using MATLAB software.The proposed fault detector and abnormality detector can enable quick and accurate fault identification and isolation.

Flexible Stochastic Scheduling of Microgrids with Islanding Operations Complemented by Optimal Offering Strategies

This paper presents a stochastic framework for optimal scheduling of microgrids(MGs)considering unscheduled islanding events,initiated by disturbances in the main grid.This scheduling approach considers different uncertainties and determines the day-ahead schedule of the resources considering emergency operations.The proposed strategy attempts to effectively manage demand and supply side resources to mitigate the effects of uncertainties in both normal and emergency operations.The prevailing uncertainties associated with renewable power generations,demand and electricity prices as well as uncertainties of islanding duration are addressed in the presented framework.The objective is to maximize the expected profit of the operator over the scheduling horizon,while restricting the risk of mandatory load shedding imposed by uncertain parameters within an acceptable level.According to the proposed strategy,an efficient probabilistic index is obtained from generation reserve margin(GRM)in islanded mode,and applied to create a proper offering price signal to coordinate responsive loads with renewable generations providing more reliable operations.The effectiveness of the proposed strategy in terms of economy and reliability is investigated via a comparison with other methods.Extensive numerical results illustrate that the proposed offering price strategy can improve the MG’s operation from both reliability and economic aspects.