Microgrid Operation Control Research Articles

Energy Management Strategy for Wind Solar Storage Microgrid Based on Improved Ant Lion Optimizer

The energy management of microgrids involves optimizing the capacity configuration, which significantly impacts the economic and stable operation of microgrids. This paper presents a control strategy for microgrid operation that effectively manages distributed power sources and energy storage to optimize capacity configuration. A mathematical optimization model for microgrid energy management is established considering minimum annual cost and optimal scale constraints. The traditional Ant Lion Optimizer (ALO) is improved by using dynamic weight coefficients and chaotic mapping to enhance the diversity of the population and improve the convergence of the algorithm. This can effectively avoid local optimal solutions and premature problems, and improve the convergence speed and search ability of the ALO algorithm. Based on this control strategy and improved ALO algorithm, simulations and tests were conducted using actual data from an independent microgrid, resulting in the optimal solution for the microgrid capacity allocation model. The case study results validate the practicality of the proposed microgrid operation control strategy as well as the superiority of the improved ant colony optimization algorithm.

Advanced Forecasting Methods of 5-Minute Power Generation in a PV System for Microgrid Operation Control

This paper concerns very-short-term (5-Minute) forecasting of photovoltaic power generation. Developing the methods useful for this type of forecast is the main aim of this study. We prepared a comprehensive study based on fragmentary time series, including 4 full days, of 5 min power generation. This problem is particularly important to microgrids’ operation control, i.e., for the proper operation of small energy micro-systems. The forecasting of power generation by renewable energy sources on a very-short-term horizon, including PV systems, is very important, especially in the island mode of microgrids’ operation. Inaccurate forecasts can lead to the improper operation of microgrids or increasing costs/decreasing profits for microgrid operators. This paper presents a short description of the performance of photovoltaic systems, particularly the main environmental parameters, and a very detailed statistical analysis of data collected from four sample time series of power generation in an existing PV system, which was located on the roof of a building. Different forecasting methods, which can be employed for this type of forecast, and the choice of proper input data in these methods were the subject of special attention in this paper. Ten various prognostic methods (including hybrid and team methods) were tested. A new, proprietary forecasting method—a hybrid method using three independent MLP-type neural networks—was a unique technique devised by the authors of this paper. The forecasts achieved with the use of various methods are presented and discussed in detail. Additionally, a qualitative analysis of the forecasts, achieved using different measures of quality, was performed. Some of the presented prognostic models are, in our opinion, promising tools for practical use, e.g., for operation control in low-voltage microgrids. The most favorable forecasting methods for various sets of input variables were indicated, and practical conclusions regarding the problem under study were formulated. Thanks to the analysis of the utility of different forecasting methods for four analyzed, separate time series, the reliability of conclusions related to the recommended methods was significantly increased.

Research on Control Strategy of Isolated DC Microgrid Based on SOC of Energy Storage System

With the rapid development of renewable energy technologies, islanded DC microgrids have received extensive attention in the field of distributed power generation due to their plug-and-play, flexible operation modes and convenient power conversion, and are likely to be one of the mainstream structures of microgrids in the future. The islanded DC microgrid contains multiple distributed power generation units. The battery energy storage system (BESS) is the main controlled unit used to smooth power fluctuations. The main parameter of concern is the state of charge (SOC). In order to maintain the stability of the microgrid, this paper takes the islanded DC microgrid as the research object and designs a control strategy based on the SOC of the BESS. Additionally, in the control strategy, the BESS’s energy balance control strategy and the microgrid’s operation control strategy are emphatically designed. The designed BESS control strategy adjusts the droop coefficient in real time according to the SOC of the battery energy storage unit (BESU), and controls the charge and discharge power of the BESU to achieve the SOC balance among the BESUs. The microgrid operation control strategy takes the energy storage system (ESS) as the main controlled unit to suppress power fluctuations, and distributes the power of distributed power sources according to the SOC of the BESS to achieve power balance in the microgrid, and control the DC bus voltage fluctuation deviation within 4.5%.

Forecasting of 10-Second Power Demand of Highly Variable Loads for Microgrid Operation Control

This paper addresses very short-term (10 s) forecasting of power demand of highly variable loads. The main purpose of this study is to develop methods useful for this type of forecast. We have completed a comprehensive study using two different time series, which are very difficult to access in practice, of 10 s power demand characterized by big dynamics of load changes. This is an emerging and promising forecasting research topic, yet to be more widely recognized in the forecasting research community. This problem is particularly important in microgrids, i.e., small energy micro-systems. Power demand forecasting, like forecasting of renewable power generation, is of key importance, especially in island mode operation of microgrids. This is due to the necessity of ensuring reliable power supplies to consumers. Inaccurate very short-term forecasts can cause improper operation of microgrids or increase costs/decrease profits in the electricity market. This paper presents a detailed statistical analysis of data for two sample low voltage loads characterized by large variability, which are located in a sewage treatment plant. The experience of the authors of this paper is that very short-term forecasting is very difficult for such loads. Special attention has been paid to different forecasting methods, which can be applied to this type of forecast, and to the selection of explanatory variables in these methods. Some of the ensemble models (eight selected models belonging to the following classes of methods: random forest regression, gradient boosted trees, weighted averaging ensemble, machine learning) proposed in the scope of choice of methods sets constituting the models set are unique models developed by the authors of this study. The obtained forecasts are presented and analyzed in detail. Moreover, qualitative analysis of the forecasts obtained has been carried out. We analyze various measures of forecasts quality. We think that some of the presented forecasting methods are promising for practical applications, i.e., for microgrid operation control, because of their accuracy and stability. The analysis of usefulness of various forecasting methods for two independent time series is an essential, very valuable element of the study carried out. Thanks to this, reliability of conclusions concerning the preferred methods has considerably increased.

Operational Cost Minimization of Grid Connected Microgrid System Using Fire Fly Technique

Present time, green energy sources interfacing to the utility grid by utilizing microgrid system is very vital to satisfy the ever increasing energy demand. Optimal operation of the microgrid system improved the generation from the distributed renewable energy sources at the lowest operational cost. Large amount of constraints and variables are associated with the microgrid economic operation problem. Thus, this problem is very complex and required efficient technique for handing the problem adequately. Therefore, this research utilized the efficient fire fly optimization technique for solving the formulated microgrid operation control problem. Fire fly algorithm is based on the behavior and nature of the fire flies. A microgrid system modelling which incorporated various distributed energy sources such as solar photo voltaic, wind turbine, micro turbine, fuel cell, diesel generator, electric vehicle technology, battery energy storage system and demands. Energy storage system is utilized in this research for supporting renewable energy sources’ integration in more reliable and qualitative way. Further, the electric vehicle technology i.e. battery electric vehicle, plug-in hybrid electric vehicle and fuel cell electric vehicle are utilized to support the microgrid and utility grid systems with respect to variable demands. Optimal operational cost minimization problem of the developed microgrid system is solved by fire fly algorithm and compared with the grey wolf optimization and particle swarm optimization techniques. By comparative analysis it is clear that the fire fly algorithm provides the minimum operational cost of microgrid system as compared to the GWO and PSO. MATLAB software is utilized to model the microgrid system and implementation of the optimization techniques.

A Microgrid Operation Control Strategy Based on Wide Area Information

Distributed Generator (DG) has many environmental benefits and potential values, but it is not controllable power for the large power grid, and brings many bad influences to the power grid, so that the power grid takes the way of isolation and restrictions that greatly limits the development of DG. In order to effectively solve the contradictions between DG and the power grid, the microgrid concept is putted forward. Microgrid is a small power system containing micro powers and local loads, which can operate with connecting to the power grid, or run in isolated island way with breaking away from the power grid. On the basis of analyzing the principle of DG, two control methods are established: PQ Control and V/f Control. And then, a microgrid operation control strategy based on wide area information is proposed. Using wide area information to get the following data: the switching power and the breaker state of the Point of Common Coupling (PCC); the output of DG; the local loads and so on. In the operation of isolated island, the control strategy controls and adjusts the DGs and loads quickly, makes the power balance, ensures that the voltage and frequency in the microgrid conforms to the standard, and ensures the important loads working steadily and reliably. Finally, the feasibility and effectiveness of the proposed control strategy are verified by matlab/simulink simulation.

Stability analysis of DC microgrid considering the action characteristics of relay protection

The stability of microgrid is the key issue of microgrid operation control. This paper focuses on the transient stability after the correct operation of relay protection. In this paper, 400V DC microgrid with photovoltaic and energy storage system is taken as the research object. Research on the fault characteristics of voltage and current after the system is subjected to short-circuit, it is proposed to introduce current differential protection. With bus voltage as the only indicator, whether the transient stability is improved after the protection system operates correctly. The DC microgrid is modeled and simulated based on MATLAB/Simulink to confirm the validity of the proposed statement. The simulation results show that the fault can be correctly located, accurately isolated and timely removed by the protection system after the short-circuit fault occurs, bus voltage is restored to maintain stable operation of the system.

A Review of Microgrid Development and Technology

The development, characteristics, types and key technologies of microgrid are summarized in this paper. This paper focuses on the operation control of microgrid, including the control method based on power electronics, energy management system and multi-agent technology. The article finally has made the forecast to the future development of the microgrid.

Control schemes for micro-grid application—A simulation and experimental approach for Electrical Engineering Project

The knowledge gain of micro-grid operation control schemes for micro-grid application is important for graduate and undergraduate students. In this paper, the issues on photovoltaic integrated to grid system and the control schemes are discussed from basics and the level of students’ understanding. Initially the basic photovoltaic modeling, maximum power point tracking techniques, and grid synchronization are presented. For grid synchronization, the mostly used synchronous reference frame-phase locked loop is considered here. For the understanding of the students, the control schemes are applied in three different cases with the help of MATLAB Simulink and the results are analyzed. The authors hope that the electrical engineering students may gain the knowledge about the effective use of solar energy and also grid synchronization technique for a reliable power supply to the critical loads in the topic control schemes on photovoltaic integrated grid system and proceed for their project or research work. The suggested scheme is duly simulated in MATLAB Simulink environment and also realized as a hardware prototype; the simulation and hardware results reveal that the suggested approach provides clear directions for a resilient operation of a micro-grid that embodies necessary renewable sources and storage elements.

The application of the CLONALG algorithm in the process of optimal operation control of hybrid AC/DC low voltage microgrid

The issue of optimal operation control of microgrids is a very important problem. As a result of changing weather conditions and the demand for the power of individual consumers, generation units and energy storage devices must constantly adjust their operation states. The optimization of the microgrid operation states can simultaneously provide the required level of power and energy and, for example, minimization of power losses or costs associated with the operation of this type of system. Among many available optimization methods, author of a paper decided to test the CLONALG algorithm, which is an implementation of artificial immune system. The article will presents the characteristics of selected CLONALG algorithm, and the description of the test microgrid together with the considered optimization criteria and constraints. The presentation and analysis of the obtained results from optimization calculations will be the main part of the paper. At the end of the paper observations and conclusion will be presented.

Study on operation control of microgrid based on improved droop control

In micro grid, the droop controlled micro power supply, the line impedance difference, the output voltage amplitude is not equal, and the microgrid complex structure and other factors will cause the reactive power of micro power output cannot achieve the same effect, so that reactive power circulation will appear between micro power supply. In order to solve this problem, an improved droop control strategy is proposed. That is to say, in traditional reactive droop control, line voltage drop and micro power access point voltage amplitude feedback are used as compensation amount for reactive droop control, which effectively tracks voltage change of microgrid and improves output voltage amplitude. The simulation model of microgrid is built in Matlab/Simulink. The simulation results show that the improved droop control can greatly improve the distribution precision of the reactive power sharing and improve the system stability of the microgrid.

Toward Optimal Day-Ahead Scheduling and Operation Control of Microgrids Under Uncertainty

In this paper, we present optimal day-ahead scheduling and control models for microgrids under uncertainty. The traditional deterministic mixed integer programming used in wholesale market fails to produce adequate results, especially when variations and risks are high. We develop stochastic programming optimization models with risk neutral and risk-averse options. We also characterize microgrids with their mean design capacity configuration and operational volatility. A dissimilarity measure determines the relative volatility between two microgrids. We demonstrate that risk-based decision-making in microgrids can significantly change the day-ahead scheduling and control outcomes, and capacity configuration and volatility measures are determining factors for microgrid risks and savings.

Research on Micro-Grid Operation Control Strategy

Micro-grid is to integrate a variety of distributed energy resources to weaken the adverse effects of decentralized distributed generation on a large grid, effective way to fully exploit the economic benefits of distributed generation.When large grid power quality appear, failure, power outages and other problems, micro-grid based on local information can be quickly switched to the state from the network, and under the jurisdiction of the load especially important to provide power to support the load, to avoid accidents.Therefore, micro-grid has become an important research focus and direction of development of distributed power generation field.The main thesis of the existing micro-grid operation control strategies to summarize, summarize, and control the operation of the micro-grid reference when choosing strategies.

Design and application of microgrid operation control system based on IEC 61850

We consider the microgrid operation control technology including design of microgrid operation control system, MG control device and control strategy. We pay much attention on microgrid operation control device which is core control device. In order to solve the contradiction of quick speed about microgrid operation mode shift and slow speed about the management system, three-layers control architecture based on IEC61850 is designed and adaptive control strategy is used on MG operation control system. The system has been applied in a distributed generation/energy storage power station. The actual operation shows that the system can be effectively and flexibly connected to distribution network.

Minimax Model Predictive Operation Control of Microgrids

Due to the steady growth of decentralised distributed generation, the operational management of small, local electricity networks (microgrids) is becoming an increasing challenge to meet: How to provide an operational control for microgrids with a high share of renewable energy sources (RES) that is robust to perturbations? In this paper we address an optimal control problem (OCP) that maintains all of the stated properties in the presence of an uncertain load and RES infeed in islanded operation. Assuming that the uncertainty is within a bounded region along a given load and RES trajectory prediction, the problem is posed as a worst-case hybrid OCP, where the RES output can be curtailed. We propose a minimax (MM) model predictive control (MPC) scheme that adjusts according to the present uncertainty and can be formulated as a mixed-integer linear program (MILP) and solved numerically online.

Design and Implementation of Microgrid SCADA Platform

Microgrid and traditional power system are different in terms of operation and control. SCADA reliability directly affects the operational control capacity of the microgrid. Based on the actual needs of the microgrid operation control and energy management, the author designed microgrid SCADA platform, including architecture, information exchange mechanism and data services, and then developed actual microgrid SCADA test platform. Through long-time test, the SCADA platform could achieve reliable microgrid operation and management.