Model predictive control of voltage profiles in MV networks with distributed generation

被引:36
作者
Farina, M. [1 ]
Guagardi, A. [2 ]
Mariani, F. [1 ]
Sandroni, C. [2 ]
Scattolini, R. [1 ]
机构
[1] Politecn Milan, Dipartimento Elettr Informaz & Bioingn, Milan, Italy
[2] RSE, Milan, Italy
关键词
Voltage control; Medium voltage network; Distributed generation; Model predictive control; Hierarchical control; PENETRATION; STABILITY; POWER;
D O I
10.1016/j.conengprac.2014.09.010
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The presence of distributed generators in Medium Voltage (MV) networks can produce local voltage increase, with inversion of power flows, and emergence of dangerous inverse currents. For this reason, the control of the voltage profile is becoming of paramount importance. However, the design of a dynamic controller is problematic due to the multivariable and large scale nature of the problem, and to the difficulty to derive a reliable model of the system. In this paper, we first identify a MIMO impulse response model of the system, through a suitable identification phase, where a detailed industrial reference simulator of the network is used. Then we propose and design an MPC-based algorithm for control of the network, used at the intermediate level of a three-layer hierarchical structure. At the upper level a static Optimal Power Flow (OPF) computes the required voltage profiles to be transmitted to the MPC level, while at the lower level local Automatic Voltage Regulators (AVR), one for each Distributed Generator (DG), track the reactive power reference values computed by MPC. The proposed method allows to cope with constraints on the voltage profiles and/or on the reactive power flows along the network. If these constraints cannot be satisfied by acting on the available DGs, the algorithm acts on the On-Load Tap Changing (OLTC) transformer. A radial rural network with two feeders, eight DGs, and thirty-one loads is used as case study. The model of the network is implemented in DIgSILENT PowerFactory (R), while the control algorithm runs in MATLAB (R). A number of simulation results is reported to witness the main characteristics and limitations of the proposed approach. (C) 2014 Elsevier Ltd. All rights reserved.
引用
收藏
页码:18 / 29
页数:12
相关论文
共 21 条
[1]   A Control Framework for the Smart Grid for Voltage Support Using Agent-Based Technologies [J].
Aquino-Lugo, Angel A. ;
Klump, Ray ;
Overbye, Thomas J. .
IEEE TRANSACTIONS ON SMART GRID, 2011, 2 (01) :173-180
[2]  
Biserica M., 2011, POWERTECH TRONDH JUN, P1
[3]  
Camacho E. F., 2007, MODEL PREDICTIVE CON
[4]  
Corsetti E., 2014, 14000645 RSE
[5]  
Gao C., 2010, P 45 INT C U POW ENG
[6]  
Grune L., IEEE T AUTOMATIC CON, V53, P2100
[7]  
Hojo M., 2009, P 20 C CIRED 2009 PR
[8]   A SURVEY OF THE OPTIMAL POWER FLOW LITERATURE [J].
HUNEAULT, M ;
GALIANA, FD .
IEEE TRANSACTIONS ON POWER SYSTEMS, 1991, 6 (02) :762-770
[9]   On the stability of receding horizon control with a general terminal cost [J].
Jadbabaie, A ;
Hauser, J .
IEEE TRANSACTIONS ON AUTOMATIC CONTROL, 2005, 50 (05) :674-678
[10]  
Kiprakis A. E., 2003, P CIRED BARC