Microgrid operation control strategy based on improved reactive power sag control

This paper summarizes the advantages of application of micro grid, analyzes the structure of microgrid, and discusses the factors, which are important to the stable operation of micro grid. The factors include the technology of power matching, harmonic suppression and the stability of electronic cascaded systems etc.

The hybrid microgrid with distributed power supply which includes wind turbine (WT), photovoltaic (PV) inverter and power converter system (PCS), not only could be connected to the power distribution network, but also can operate independently. It is realized switch from grid-connected mode to off-grid mode through the microgrid controller. Whether the microgrid can achieve smooth switching from grid-connected to off-grid has great influence on the safety and stability of the power grid. In order to accurately evaluate the influence of the microgrid switch to the distribution network, it is needed to research on the distributed source modeling technology, and establish an accurate microgrid model. In this paper, using a 400V voltage grade microgrid system with PV, WT and PCS as an example, model the internal equipment and the microgrid control system, and establish a microgrid model for simulation. At the meantime, it carries out the microgrid switch testing, and compare with the measured waveform to verify the accuracy of the model. It is confirmed the accuracy of the microgrid model by the contrast result.

CHP system with Energy saving, environmental protection, economic and other characteristics,have good prospects for the development and application value.This paper directe a micro grid system consisted by photovoltaic cells, wind turbines, fuel cells, microturbines, auxiliary boilers, thermal energy storage systems and batteries and heat load and electrical load.Considering various distributed power generation costs, environmental costs and micro-grid equipment maintenance costs,To meet the constraints of micro-grid operation, optimization of the different micro-grid distributed power and energy storage system power output, make the system's total operating costs are minimized.This paper analyzes the economic and environmental of micro-grid optimal operation characteristics, given a model of CHP micro-grid.For the cost of power generation and emissions of different weights, using bacterial foraging optimization(BFO) algorithm,through a numerical example verified the Correctness and effectiveness of mathematical model and optimization algorithm .

The economic benefit of microgrid is the key factor to realize environment-friendly power supply. With the wide application of new energy power generation, scholars have carried out a lot of research on microgrid models, but the existing models cannot reflect the important role of renewable energy in microgrid operation. Therefore, the author proposes a power generation and storage model based on renewable heat energy and microgrid. In order to minimize the cost and meet the requirements of CO2 emission limitation, the cost of power generation, storage and production in the microgrid is analyzed in detail. At the same time, the optimization method of renewable energy microgrid system operation is also studied. First of all, by analyzing the characteristics of the microgrid system, a mathematical model and simulation calculation system are established to help understand the microgrid system. Secondly, the author has carried out a separate study on the energy storage in the microgrid system, and listed the benefits and costs of the energy storage process. In the grid-connected state, the performance of each unit in the microgrid system is better, the system is more stable and safe, and the operating cost is reduced again..

Aiming at the inherent characteristics of traditional droop control of autonomous microgrid, which can cause the voltage amplitude and frequency deviation and the poor anti-disturbance capability of inner loop voltage control. A sliding mode control method based on second order generalized integral (SOGI) is proposed. Firstly, two phase orthogonal output voltage and current signals are reconstructed by the second order generalized integrator quadrature signals generators (SOGI-QSG) to realize independent control of active and reactive components. Then, in the reference voltage droop control loop, the second order generalized integral (SOGI-FLL) bus voltage frequency and amplitude estimation model based on frequency locked loop is used to improve the traditional droop control, so that the droop reference voltage is closer to the expected nominal value. Finally, a sliding mode voltage controller is designed for inner loop voltage control, so that the output voltage of inverter system can track its reference voltage quickly and accurately, and the robustness of the system can be enhanced. The experimental data shows that the method can ensure the stable output voltage, the output voltage total harmonic distortion is reduced, and has good dynamic response speed and has strong anti-interference of load.

Microgrid is a small power supply and distribution network, which connects multiple loads and multiple power units with energy storage systems together by power electronic converter interface. Because of the inherent intermittent and random characteristics of distributed generation units in microgrid, it is very important to study the structure and control mode of microgrid system. Firstly, this paper analyzes the structure and control modes of microgrid system under different operation modes, then proposes to optimize microgrid system, and analyzes the advantages and disadvantages of traditional centralized control and distributed control modes, which provides new ideas for the future development of distributed energy and microgrid system.

—This research paper focuses on decentralized control of an AC microgrid in standalone mode. The microgrid includes three solar PV arrays accompanied by three battery energy storage systems (BESS), utilizing renewable distributed energy resources (DERs). The connection between each DER system and the microgrid is established through a network-forming three-phase voltage source inverter (VSI). The microgrid’s operation is regulated using modified droop control, incorporating virtual impedance and feed-forward derivative in primary control, along with a phase-locked loop (PLL) system for inverter synchronization. A master-slave control configuration is employed between the VSIs to mitigate voltage amplitude and frequency deviations induced by primary control. These enhancements ensure smooth power distribution and maintain voltage amplitude and frequency within specified limits across different operational scenarios. Control operations are performed in a stationary frame ( frame) using Clarke’s transformation, and PR controllers regulate VSI’s output voltage and current. The research paper shows the effectiveness of controlled microgrid operations using MATLAB/Simulink software in various conditions including intermittent PV system behavior, load dynamics, and DER connection/disconnection challenges. Simulation results show that the proposed approach enhances stability and performance of the microgrid system, especially in managing power fluctuations and maintaining a constant frequency response.

Due to the rise in penetration of distributed energy resources (DERs) and energy storage systems (ESSs) into the microgrid (µG) system, the abrupt disconnections of DERs and ESSs might have an effect on the stability and dependability of the entire µG system. It is important to take into account the low-voltage ride-through (LVRT) capabilities to keep the µG system operating steadily. In order to quickly identify grid abnormalities and categorize islanding scenarios, this paper attempts to develop an islanding detection technique. The procedure involves generation of data samples corresponding to different grid abnormalities and training them with a machine learning based classifier. To achieve this process, a grid-connected (GC) three-phase µG system is simulated and compiled in Typhoon HIL application software to get distinct data sets for different grid fault conditions. Additionally, the data is trained using the multilayered perceptron neural network (MLPNN) classifier to create the islanding classification process. The trained classifier has 99.5% effectiveness and can classify data at a rate of about 170000 observations per second.

Optimal energy management of a PV-WTG-BSS-DG microgrid system

Aiming at the problems of promoting new energy consumption, reducing carbon emissions, load fluctuations, and multi-agent conflict of interests in the networked microgrid system, this article proposes a microgrid optimization operation strategy based on demand response and reward-penalty ladder-type carbon trading mechanism. First, in order to determine the electricity sales price of the system, an optimal scheduling model for microgrid operators is established, including gas cost, electricity profit for users, and surplus power supply network profit. Second, a demand response strategy on electricity price and low-carbon compensation incentives is proposed on the user side. The transaction model is embedded between microgrid operators and users into the master–slave game framework, and a multi-slave game collaborative optimization model is established with microgrid operators as leaders and users as followers. The existence and uniqueness of Stackelberg game are proved, and the differential evolution algorithm and CPLEX solver are used to solve the proposed model. Finally, an example of a microgrid system including three community users is provided to show the effectiveness of the proposed model and strategy.

Guest Editorial

Microgrid (MG) systems can either operate in on-grid or off-grid mode. The on-grid mode of microgrid operation can further be divided into active and passive mode. In active mode the grid both buys and sells power to the microgrid whereas in passive mode the grid acts as a backup and only sells power to the microgrid. In this study, the grid power commitment is sized optimally to incur the lowest MG system generating cost. The generation cost is reduced for three different scenarios of a low voltage microgrid (LV MG) system that comprises of battery energy storage (BES), renewable energy sources (RES), and fossil fuel generators while running in grid-connected mode. The load demand model is taken into account and distributed generator (DG) scheduling ideas are percolated for reducing the second level Microgrid system’s generating costs. The optimization tool for the study was a newly established hybrid swarm intelligence algorithm that has previously been utilized to solve a variety of power system optimization challenges. Numerical results show that there was 25% increase in generation cost when passive participation of grid was considered and 58% increase when fixed electricity pricing was considered.

Focusing on the electricity and thermal energy requirement of contemporary buildings, a joint operation of photovoltaic thermal (PV/T)‐based prosumers and a microturbine‐based combined heat and power system has been presented to analyse the economics of a grid‐connected microgrid (MG) system. The bidirectional flow of the electricity and heat model is considered and is optimally managed using a price‐based demand response (DR) scheme. Thermal storage is exploited to ward off the substantial amount of heat wastages that enhance the system's reliability during any disruption of microturbine. The objective functions of both the prosumer and MG operator (MGO) are formulated as a profit maximisation problem where they interact with each other on the basis of DR activity. To establish this strategic decision‐making process, the system is modelled as a Stackelberg equilibrium game, where MGO acts as a leader while PV/T prosumers act as a follower. The interaction or contribution of two players in a game is a problem of non‐linear optimisation, which is solved by the differential evolution algorithm. In the end, in a case study, it has been proved that the results are quite lucrative for the proposed model.

With a large number of distributed power sources connected to the distribution network, power supply reliability has always been one of the most concerned indicators for power supply companies. Fault mode and effect analysis (FMEA) can predict the impact of fault isolation and load switching diversity in active intelligent distribution networks. In this paper, a standardized model of reliability system evaluation is constructed by FEMA table, and the reliability index is solved by combining Monte Carlo analysis method. The simulation with IEEE-RBTS BUS6 as an example shows that the method can quantify the effect of distributed power supply on the reliability of active distribution network, which proves that the proposed method is effective and feasible to solve the index.

This study is focused on two areas: the design of a Battery Energy Storage System (BESS) for a grid-connected DC Microgrid and the power management of that microgrid. The power management is performed by a Microgrid Central Controller (MGCC). A Microgrid operator provides daily information to the MGCC about the photovoltaic generation profile, the load demand profile, and the real-time prices of the electricity in order to plan the power interchange between the BESS and the main grid, establishing the desired state of charge (SOC) of the batteries at any time. The main goals of the power management strategy under study are to minimize the cost of the electricity that is imported from the grid and to maximize battery life by means of an adequate charging procedure, which sets the charging rate as a function of the MG state. Experimental and simulation results in many realistic scenarios demonstrate that the proposed methodology achieves a proper power management of the DC microgrid.