Comparison of Hierarchical Control and Distributed Control for Microgrid

Feng, Xianyong; Shekhar, Aditya; Yang, Fang; Hebner, Robert E.; Bauer, Pavol

doi:10.1080/15325008.2017.1318982

Cited by 70 publications

(59 citation statements)

References 24 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…With the rapid development of micro-grid technologies in recent years, modern smart power grids, characterized by diversified energy types [1,2], an individualized energy supply [3,4], a multilayer control system [5,6], multi-type network structures [7,8], and flexible working modes [9,10] have gradually come into being. Since micro-grids have characteristics such as strong intermittency, low damping of output power, and high generation-demand sensitivity [11], the core goal of research on micro-grid control methods is to realize a stable, rapid, and reliable control system.…”

Section: Introductionmentioning

confidence: 99%

Research on Control Parameters for Voltage Source Inverter Output Controllers of Micro-Grids Based on the Fruit Fly Optimization Algorithm

2019

View full text Add to dashboard Cite

Due to the strong intermittency of micro-resources, the poor grid-tied power quality, and the high generation-demand sensitivity in micro-grids, research into the control methods of micro-grid systems has always been a notable issue in the field of micro-grids. The inverter is the core control equipment at the primary control level of the micro-grid, and the key factors affecting its output performance can be divided into three categories: control methods, hardware configuration, and control parameter design. Taking the classical active and reactive power (P-Q) control structure and the three-phase, two-stage inverter topology model as an example, this paper designs a parameter for offline tuning, and an online self-tuning optimization method for an inverter control system based on the fruit fly optimization algorithm (FOA). By simulating and comparing the inverter controllers with non-optimized parameters in the same object and environment, the designed parameter tuning method is verified. Specifically, it improves the dynamic response speed of the inverter controller, reduces the steady-state error and oscillation, and enhances the dynamic response performance of the controller. communications will seriously influence the control performance of the entire system [14]. In the field of control science, tuning and optimization of the controller parameters are often carried out to improve the performance of a complicated PI-based control system [15]. However, in the process of parameter tuning, the control objects of different parameters vary in their damping coefficients, which leads to different overshoots, oscillations, durations of rise, and durations of adjustment [16]. Therefore, it is of great significance to explore the application of parameter tuning methods of PI controllers in improving the performance of the underlying control system of a micro-grid [17]. Research on PI controller parameter tuning can be divided into two major categories: offline tuning [18,19] and online tuning [20,21]. In Al-Saedi's work [22], online optimization tuning is conducted for PI controller parameters of micro-grid inverters by the particle swarm optimization algorithm (PSO) and error performance index methods. However, as the update calculation process of an individual particle is relatively complex, the overall calculation time is long, which makes it more suitable for offline tuning [23,24]. Compared with PSO, the fruit fly optimization algorithm (FOA) [25] requires less in terms of the calculation process and a simpler structure, with the advantage of shorter calculation time for parameter tuning. Research works [26][27][28] have discussed the feasibility of optimizing PI controller parameter tuning in an industrial process by using FOA, and they have provided guidance for this paper. Appl. Sci. 2019, 9, 1327 2 of 24 control network communications will seriously influence the control performance of the entire system [14]. In the field of control science, tuning and optimization of the controller parameters are often carr...

show abstract

Section: Introductionmentioning

confidence: 99%

Research on Control Parameters for Voltage Source Inverter Output Controllers of Micro-Grids Based on the Fruit Fly Optimization Algorithm

2019

View full text Add to dashboard Cite

show abstract

“…This paper is the extension of authors' previous work in [7], which proposes a nonlinear distributed algorithm to optimize a multi-objective function using optimal reactive power generation control. [8] explores the advantages of distributed control over the prevailing hierarchical methods of control.…”

Section: Introductionmentioning

confidence: 99%

Effect of the approximation of voltage angle difference on the OPF algorithms in the power network

2019

View full text Add to dashboard Cite

In real-time applications involving power flow equations, measuring of voltage phase angle difference of the connected buses is essential. However, it needs special techniques to measure voltage angle difference, which may enlarge the computational burden of the working controller and hence, may make the control process slow. In this paper, authors investigate the approximation of angle difference to zero and its effects on the convergence speed and optimal solutions of a distributed algorithm. To test this approximation, a distributed nonlinear algorithm is proposed to optimize the multi-objective function which includes power loss, voltage deviation and cost of reactive power generation, by controlling the reactive power generations from distributed generators. Authors investigate the reasons which may outlaw making this approximation and finally, propose a condition to make such approximation. Importance of making this approximation in terms of fast convergence of the algorithms is also illustrated.Index Terms-voltage angles difference approximation, AC power flow, Reactive power control, power loss, voltage deviation.

show abstract

“…The battery bank charge power is given by the Equation (18) and the power absorbed by the BESS from the DC bus is represented by (19).…”

Section: Battery Management Algorithmmentioning

confidence: 99%

“…The power imbalance is a common scenario in MGs, being caused by the discontinuity in the energy generation or by the changes in the power demand. Nowadays, adequate strategies have been developed to manage the power dispatch in the MGs, which can be: centralized, decentralized or distributed [12][13][14][15][16][17][18][19][20][21].…”

Section: Introductionmentioning

confidence: 99%

Practical Analysis and Design of a Battery Management System for a Grid-Connected DC Microgrid for the Reduction of the Tariff Cost and Battery Life Maximization

et al. 2018

View full text Add to dashboard Cite

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.

show abstract

Comparison of Hierarchical Control and Distributed Control for Microgrid

Cited by 70 publications

References 24 publications

Research on Control Parameters for Voltage Source Inverter Output Controllers of Micro-Grids Based on the Fruit Fly Optimization Algorithm

Research on Control Parameters for Voltage Source Inverter Output Controllers of Micro-Grids Based on the Fruit Fly Optimization Algorithm

Effect of the approximation of voltage angle difference on the OPF algorithms in the power network

Practical Analysis and Design of a Battery Management System for a Grid-Connected DC Microgrid for the Reduction of the Tariff Cost and Battery Life Maximization

Contact Info

Product

Resources

About